Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

PubMed Central

Nogueira, Waldo; Schurzig, Daniel; Büchner, Andreas; Penninger, Richard T.; Würfel, Waldemar

2016-01-01

Cochlear Implants (CIs) are medical implantable devices that can restore the sense of hearing in people with profound hearing loss. Clinical trials assessing speech intelligibility in CI users have found large intersubject variability. One possibility to explain the variability is the individual differences in the interface created between electrodes of the CI and the auditory nerve. In order to understand the variability, models of the voltage distribution of the electrically stimulated cochlea may be useful. With this purpose in mind, we developed a parametric model that can be adapted to each CI user based on landmarks from individual cone beam computed tomography (CBCT) scans of the cochlea before and after implantation. The conductivity values of each cochlea compartment as well as the weighting factors of different grounding modes have also been parameterized. Simulations were performed modeling the cochlea and electrode positions of 12 CI users. Three models were compared with different levels of detail: a homogeneous model (HM), a non-patient-specific model (NPSM), and a patient-specific model (PSM). The model simulations were compared with voltage distribution measurements obtained from the backward telemetry of the 12 CI users. Results show that the PSM produces the lowest error when predicting individual voltage distributions. Given a patient-specific geometry and electrode positions, we show an example on how to optimize the parameters of the model and how to couple it to an auditory nerve model. The model here presented may help to understand speech performance variability and support the development of new sound coding strategies for CIs. PMID:27933290

Proceedings of the Symposium on Psychology in the Department of Defense (12th) Held in Colorado Springs, Colorado on 18-20 April 1990

DTIC Science & Technology

1990-04-01

structure or level of performance. To the extant this increased motivation result in greater...application users and not power users, they will quickly abandon the use of these models in favor of those that require less of a data entry burden, even if... behavior in Individuals is best measured by convergence over time of the value structures of the individual and those of a model group (e.g., tu•ity

Social relevance: toward understanding the impact of the individual in an information cascade

NASA Astrophysics Data System (ADS)

Hall, Robert T.; White, Joshua S.; Fields, Jeremy

2016-05-01

Information Cascades (IC) through a social network occur due to the decision of users to disseminate content. We define this decision process as User Diffusion (UD). IC models typically describe an information cascade by treating a user as a node within a social graph, where a node's reception of an idea is represented by some activation state. The probability of activation then becomes a function of a node's connectedness to other activated nodes as well as, potentially, the history of activation attempts. We enrich this Coarse-Grained User Diffusion (CGUD) model by applying actor type logics to the nodes of the graph. The resulting Fine-Grained User Diffusion (FGUD) model utilizes prior research in actor typing to generate a predictive model regarding the future influence a user will have on an Information Cascade. Furthermore, we introduce a measure of Information Resonance that is used to aid in predictions regarding user behavior.

Dynamic User Modeling within a Game-Based ITS

ERIC Educational Resources Information Center

Snow, Erica L.

2015-01-01

Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…

EPPRD: An Efficient Privacy-Preserving Power Requirement and Distribution Aggregation Scheme for a Smart Grid.

PubMed

Zhang, Lei; Zhang, Jing

2017-08-07

A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users' private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes.

A Randomized Response Model For Privacy Preserving Smart Metering.

PubMed

Wang, Shuang; Cui, Lijuan; Que, Jialan; Choi, Dae-Hyun; Jiang, Xiaoqian; Cheng, Samuel; Xie, Le

2012-09-01

The adoption of smart meters may bring new privacy concerns to the general public. Given the fact that metering data of individual homes/factories is accumulated every 15 minutes, it is possible to infer the pattern of electricity consumption of individual users. In order to protect the privacy of users in a completely de-centralized setting (i.e., individuals do not communicate with one another), we propose a novel protocol, which allows individual meters to report the true electricity consumption reading with a pre-determinted probability. Load serving entities (LSE) can reconstruct the total electricity consumption of a region or a district through inference algorithm, but their ability of identifying individual users' energy consumption pattern is significantly reduced. Using simulated data, we verify the feasibility of the proposed method and demonstrate performance advantages over existing approaches.

A Driving Behaviour Model of Electrical Wheelchair Users

PubMed Central

Hamam, Y.; Djouani, K.; Daachi, B.; Steyn, N.

2016-01-01

In spite of the presence of powered wheelchairs, some of the users still experience steering challenges and manoeuvring difficulties that limit their capacity of navigating effectively. For such users, steering support and assistive systems may be very necessary. To appreciate the assistance, there is need that the assistive control is adaptable to the user's steering behaviour. This paper contributes to wheelchair steering improvement by modelling the steering behaviour of powered wheelchair users, for integration into the control system. More precisely, the modelling is based on the improved Directed Potential Field (DPF) method for trajectory planning. The method has facilitated the formulation of a simple behaviour model that is also linear in parameters. To obtain the steering data for parameter identification, seven individuals participated in driving the wheelchair in different virtual worlds on the augmented platform. The obtained data facilitated the estimation of user parameters, using the ordinary least square method, with satisfactory regression analysis results. PMID:27148362

Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use.

PubMed

Harlé, Katia M; Stewart, Jennifer L; Zhang, Shunan; Tapert, Susan F; Yu, Angela J; Paulus, Martin P

2015-11-01

Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Thermal Profiling of Residential Energy Use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albert, A; Rajagopal, R

This work describes a methodology for informing targeted demand-response (DR) and marketing programs that focus on the temperature-sensitive part of residential electricity demand. Our methodology uses data that is becoming readily available at utility companies-hourly energy consumption readings collected from "smart" electricity meters, as well as hourly temperature readings. To decompose individual consumption into a thermal-sensitive part and a base load (non-thermally-sensitive), we propose a model of temperature response that is based on thermal regimes, i.e., unobserved decisions of consumers to use their heating or cooling appliances. We use this model to extract useful benchmarks that compose thermal profiles ofmore » individual users, i.e., terse characterizations of the statistics of these users' temperature-sensitive consumption. We present example profiles generated using our model on real consumers, and show its performance on a large sample of residential users. This knowledge may, in turn, inform the DR program by allowing scarce operational and marketing budgets to be spent on the right users-those whose influencing will yield highest energy reductions-at the right time. We show that such segmentation and targeting of users may offer savings exceeding 100% of a random strategy.« less

Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes

PubMed Central

Fernández-Llatas, Carlos; Benedi, José-Miguel; García-Gómez, Juan M.; Traver, Vicente

2013-01-01

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection. PMID:24225907

Young macaques (Macaca fascicularis) preferentially bias attention towards closer, older, and better tool users.

PubMed

Tan, Amanda W Y; Hemelrijk, Charlotte K; Malaivijitnond, Suchinda; Gumert, Michael D

2018-05-12

Examining how animals direct social learning during skill acquisition under natural conditions, generates data for examining hypotheses regarding how transmission biases influence cultural change in animal populations. We studied a population of macaques on Koram Island, Thailand, and examined model-based biases during interactions by unskilled individuals with tool-using group members. We first compared the prevalence of interactions (watching, obtaining food, object exploration) and proximity to tool users during interactions, in developing individuals (infants, juveniles) versus mature non-learners (adolescents, adults), to provide evidence that developing individuals are actively seeking information about tool use from social partners. All infants and juveniles, but only 49% of mature individuals carried out interacted with tool users. Macaques predominantly obtained food by scrounging or stealing, suggesting maximizing scrounging opportunities motivates interactions with tool users. However, while interactions by adults was limited to obtaining food, young macaques and particularly infants also watched tool users and explored objects, indicating additional interest in tool use itself. We then ran matrix correlations to identify interaction biases, and what attributes of tool users influenced these. Biases correlated with social affiliation, but macaques also preferentially targeted tool users that potentially increase scrounging and learning opportunities. Results suggest that social structure may constrain social learning, but the motivation to bias interactions towards tool users to maximize feeding opportunities may also socially modulate learning by facilitating close proximity to better tool users, and further interest in tool-use actions and materials, especially during development.

Determinants of Presence in 3D Virtual Worlds: A Structural Equation Modelling Analysis

ERIC Educational Resources Information Center

Chow, Meyrick

2016-01-01

There is a growing body of evidence that feeling present in virtual environments contributes to effective learning. Presence is a psychological state of the user; hence, it is generally agreed that individual differences in user characteristics can lead to different experiences of presence. Despite the fact that user characteristics can play a…

Adaptive Hypermedia Educational System Based on XML Technologies.

ERIC Educational Resources Information Center

Baek, Yeongtae; Wang, Changjong; Lee, Sehoon

This paper proposes an adaptive hypermedia educational system using XML technologies, such as XML, XSL, XSLT, and XLink. Adaptive systems are capable of altering the presentation of the content of the hypermedia on the basis of a dynamic understanding of the individual user. The user profile can be collected in a user model, while the knowledge…

Measuring User-Created Content: Implications for the ICT Access and Use by Households and Individuals Surveys. OECD Digital Economy Papers, No. 139

ERIC Educational Resources Information Center

van Beuzekom, Brigitte

2008-01-01

This paper reviews recent measurement work on User-Created Content (UCC) undertaken in OECD countries. It shows that UCC is emerging as a significant area of economic and social activity worthy of consideration for official measurement and discusses the implications for the OECD Model Survey on ICT Access and Use by Households and Individuals.…

Competitive Cyber-Insurance and Internet Security

NASA Astrophysics Data System (ADS)

Shetty, Nikhil; Schwartz, Galina; Felegyhazi, Mark; Walrand, Jean

This paper investigates how competitive cyber-insurers affect network security and welfare of the networked society. In our model, a user's probability to incur damage (from being attacked) depends on both his security and the network security, with the latter taken by individual users as given. First, we consider cyberinsurers who cannot observe (and thus, affect) individual user security. This asymmetric information causes moral hazard. Then, for most parameters, no equilibrium exists: the insurance market is missing. Even if an equilibrium exists, the insurance contract covers only a minor fraction of the damage; network security worsens relative to the no-insurance equilibrium. Second, we consider insurers with perfect information about their users' security. Here, user security is perfectly enforceable (zero cost); each insurance contract stipulates the required user security. The unique equilibrium contract covers the entire user damage. Still, for most parameters, network security worsens relative to the no-insurance equilibrium. Although cyber-insurance improves user welfare, in general, competitive cyber-insurers fail to improve network security.

MOAB: a spatially explicit, individual-based expert system for creating animal foraging models

USGS Publications Warehouse

Carter, J.; Finn, John T.

1999-01-01

We describe the development, structure, and corroboration process of a simulation model of animal behavior (MOAB). MOAB can create spatially explicit, individual-based animal foraging models. Users can create or replicate heterogeneous landscape patterns, and place resources and individual animals of a goven species on that landscape to simultaneously simulate the foraging behavior of multiple species. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. MOAB can be used to explore hypotheses concerning the influence of landscape patttern on animal movement and foraging behavior. A red fox (Vulpes vulpes L.) foraging and nest predation model was created to test MOAB's capabilities. Foxes were simulated for 30-day periods using both expert system and random movement rules. Home range size, territory formation and other available simulation studies. A striped skunk (Mephitis mephitis L.) model also was developed. The expert system model proved superior to stochastic in respect to territory formation, general movement patterns and home range size.

A Grammar-based Approach for Modeling User Interactions and Generating Suggestions During the Data Exploration Process.

PubMed

Dabek, Filip; Caban, Jesus J

2017-01-01

Despite the recent popularity of visual analytics focusing on big data, little is known about how to support users that use visualization techniques to explore multi-dimensional datasets and accomplish specific tasks. Our lack of models that can assist end-users during the data exploration process has made it challenging to learn from the user's interactive and analytical process. The ability to model how a user interacts with a specific visualization technique and what difficulties they face are paramount in supporting individuals with discovering new patterns within their complex datasets. This paper introduces the notion of visualization systems understanding and modeling user interactions with the intent of guiding a user through a task thereby enhancing visual data exploration. The challenges faced and the necessary future steps to take are discussed; and to provide a working example, a grammar-based model is presented that can learn from user interactions, determine the common patterns among a number of subjects using a K-Reversible algorithm, build a set of rules, and apply those rules in the form of suggestions to new users with the goal of guiding them along their visual analytic process. A formal evaluation study with 300 subjects was performed showing that our grammar-based model is effective at capturing the interactive process followed by users and that further research in this area has the potential to positively impact how users interact with a visualization system.

An Analysis of Contraceptive Discontinuation among Female, Reversible Method Users in Urban Honduras

PubMed Central

Barden-O’Fallon, Janine; Speizer, Ilene S.; Cálix, Javier; Rodriguez, Francisco

2013-01-01

A panel study examining the effects of individual characteristics, side effects experienced, and service quality on contraceptive discontinuation was undertaken in four urban areas of Honduras. Data were collected from October 2006 to December 2007. The baseline population included 800 women aged 15–44 who were new or continuing users of the injectable, IUD, or oral contraceptive pill. A total of 671 women (84%) were re-interviewed after one year. Life tables and Cox proportional hazards models are used to present discontinuation rates and factors associated with contraceptive discontinuation. Among new users, discontinuation of the baseline method at 12 months was high (45%); especially for users of the injectable (50%). In the hazards model, service quality had little effect on discontinuation, while individual characteristics and the experience of specific side effects showed significant effects. The results suggest that programs should emphasize continuous contraceptive coverage rather than continuous use of a particular method. PMID:21500697

Groundwars Version 5.0. User’s Guide

DTIC Science & Technology

1992-08-01

model, Monte Carlo, land duel , heterogeneous forces, TANKWARS, target acquisition, combat survivability 19. ABSTRACT (Continue on reverse if necessary...land duel between two heterogeneous forces. The model simuJ.ates individual weapon systems and employs Monte Carlo probability theory as its primary...is a weapon systems effectiveness model which provides the results of a land duel between two forces. The model simulates individual weapon systems

MobRISK: a model for assessing the exposure of road users to flash flood events

NASA Astrophysics Data System (ADS)

Shabou, Saif; Ruin, Isabelle; Lutoff, Céline; Debionne, Samuel; Anquetin, Sandrine; Creutin, Jean-Dominique; Beaufils, Xavier

2017-09-01

Recent flash flood impact studies highlight that road networks are often disrupted due to adverse weather and flash flood events. Road users are thus particularly exposed to road flooding during their daily mobility. Previous exposure studies, however, do not take into consideration population mobility. Recent advances in transportation research provide an appropriate framework for simulating individual travel-activity patterns using an activity-based approach. These activity-based mobility models enable the prediction of the sequence of activities performed by individuals and locating them with a high spatial-temporal resolution. This paper describes the development of the MobRISK microsimulation system: a model for assessing the exposure of road users to extreme hydrometeorological events. MobRISK aims at providing an accurate spatiotemporal exposure assessment by integrating travel-activity behaviors and mobility adaptation with respect to weather disruptions. The model is applied in a flash-flood-prone area in southern France to assess motorists' exposure to the September 2002 flash flood event. The results show that risk of flooding mainly occurs in principal road links with considerable traffic load. However, a lag time between the timing of the road submersion and persons crossing these roads contributes to reducing the potential vehicle-related fatal accidents. It is also found that sociodemographic variables have a significant effect on individual exposure. Thus, the proposed model demonstrates the benefits of considering spatiotemporal dynamics of population exposure to flash floods and presents an important improvement in exposure assessment methods. Such improved characterization of road user exposures can present valuable information for flood risk management services.

EPPRD: An Efficient Privacy-Preserving Power Requirement and Distribution Aggregation Scheme for a Smart Grid

PubMed Central

Zhang, Lei; Zhang, Jing

2017-01-01

A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users’ private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes. PMID:28783122

DIRT: The Dust InfraRed Toolbox

NASA Astrophysics Data System (ADS)

Pound, M. W.; Wolfire, M. G.; Mundy, L. G.; Teuben, P. J.; Lord, S.

We present DIRT, a Java applet geared toward modeling a variety of processes in envelopes of young and evolved stars. Users can automatically and efficiently search grids of pre-calculated models to fit their data. A large set of physical parameters and dust types are included in the model database, which contains over 500,000 models. The computing cluster for the database is described in the accompanying paper by Teuben et al. (2000). A typical user query will return about 50-100 models, which the user can then interactively filter as a function of 8 model parameters (e.g., extinction, size, flux, luminosity). A flexible, multi-dimensional plotter (Figure 1) allows users to view the models, rotate them, tag specific parameters with color or symbol size, and probe individual model points. For any given model, auxiliary plots such as dust grain properties, radial intensity profiles, and the flux as a function of wavelength and beamsize can be viewed. The user can fit observed data to several models simultaneously and see the results of the fit; the best fit is automatically selected for plotting. The URL for this project is http://dustem.astro.umd.edu.

Exploring the Complex Pattern of Information Spreading in Online Blog Communities

PubMed Central

Pei, Sen; Muchnik, Lev; Tang, Shaoting; Zheng, Zhiming; Makse, Hernán A.

2015-01-01

Information spreading in online social communities has attracted tremendous attention due to its utmost practical values in applications. Despite that several individual-level diffusion data have been investigated, we still lack the detailed understanding of the spreading pattern of information. Here, by comparing information flows and social links in a blog community, we find that the diffusion processes are induced by three different spreading mechanisms: social spreading, self-promotion and broadcast. Although numerous previous studies have employed epidemic spreading models to simulate information diffusion, we observe that such models fail to reproduce the realistic diffusion pattern. In respect to users behaviors, strikingly, we find that most users would stick to one specific diffusion mechanism. Moreover, our observations indicate that the social spreading is not only crucial for the structure of diffusion trees, but also capable of inducing more subsequent individuals to acquire the information. Our findings suggest new directions for modeling of information diffusion in social systems, and could inform design of efficient propagation strategies based on users behaviors. PMID:25985081

Exploring the complex pattern of information spreading in online blog communities.

PubMed

Pei, Sen; Muchnik, Lev; Tang, Shaoting; Zheng, Zhiming; Makse, Hernán A

2015-01-01

Information spreading in online social communities has attracted tremendous attention due to its utmost practical values in applications. Despite that several individual-level diffusion data have been investigated, we still lack the detailed understanding of the spreading pattern of information. Here, by comparing information flows and social links in a blog community, we find that the diffusion processes are induced by three different spreading mechanisms: social spreading, self-promotion and broadcast. Although numerous previous studies have employed epidemic spreading models to simulate information diffusion, we observe that such models fail to reproduce the realistic diffusion pattern. In respect to users behaviors, strikingly, we find that most users would stick to one specific diffusion mechanism. Moreover, our observations indicate that the social spreading is not only crucial for the structure of diffusion trees, but also capable of inducing more subsequent individuals to acquire the information. Our findings suggest new directions for modeling of information diffusion in social systems, and could inform design of efficient propagation strategies based on users behaviors.

Aggregation Trade Offs in Family Based Recommendations

NASA Astrophysics Data System (ADS)

Berkovsky, Shlomo; Freyne, Jill; Coombe, Mac

Personalized information access tools are frequently based on collaborative filtering recommendation algorithms. Collaborative filtering recommender systems typically suffer from a data sparsity problem, where systems do not have sufficient user data to generate accurate and reliable predictions. Prior research suggested using group-based user data in the collaborative filtering recommendation process to generate group-based predictions and partially resolve the sparsity problem. Although group recommendations are less accurate than personalized recommendations, they are more accurate than general non-personalized recommendations, which are the natural fall back when personalized recommendations cannot be generated. In this work we present initial results of a study that exploits the browsing logs of real families of users gathered in an eHealth portal. The browsing logs allowed us to experimentally compare the accuracy of two group-based recommendation strategies: aggregated group models and aggregated predictions. Our results showed that aggregating individual models into group models resulted in more accurate predictions than aggregating individual predictions into group predictions.

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model

PubMed Central

Guan, Li; Hao, Bibo; Cheng, Qijin; Yip, Paul SF

2015-01-01

Background Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. Objective The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. Methods There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric “Screening Efficiency” that were adopted to evaluate model effectiveness. Results Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%. Conclusions Individuals in China with high suicide probability are recognizable by profile and text-based information from microblogs. Although there is still much space to improve the performance of classification models in the future, this study may shed light on preliminary screening of risky individuals via machine learning algorithms, which can work side-by-side with expert scrutiny to increase efficiency in large-scale-surveillance of suicide probability from online social media. PMID:26543921

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model.

PubMed

Guan, Li; Hao, Bibo; Cheng, Qijin; Yip, Paul Sf; Zhu, Tingshao

2015-01-01

Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric "Screening Efficiency" that were adopted to evaluate model effectiveness. Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%. Individuals in China with high suicide probability are recognizable by profile and text-based information from microblogs. Although there is still much space to improve the performance of classification models in the future, this study may shed light on preliminary screening of risky individuals via machine learning algorithms, which can work side-by-side with expert scrutiny to increase efficiency in large-scale-surveillance of suicide probability from online social media.

Designing visual displays and system models for safe reactor operations based on the user`s perspective of the system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown-VanHoozer, S.A.

Most designers are not schooled in the area of human-interaction psychology and therefore tend to rely on the traditional ergonomic aspects of human factors when designing complex human-interactive workstations related to reactor operations. They do not take into account the differences in user information processing behavior and how these behaviors may affect individual and team performance when accessing visual displays or utilizing system models in process and control room areas. Unfortunately, by ignoring the importance of the integration of the user interface at the information process level, the result can be sub-optimization and inherently error- and failure-prone systems. Therefore, tomore » minimize or eliminate failures in human-interactive systems, it is essential that the designers understand how each user`s processing characteristics affects how the user gathers information, and how the user communicates the information to the designer and other users. A different type of approach in achieving this understanding is Neuro Linguistic Programming (NLP). The material presented in this paper is based on two studies involving the design of visual displays, NLP, and the user`s perspective model of a reactor system. The studies involve the methodology known as NLP, and its use in expanding design choices from the user`s ``model of the world,`` in the areas of virtual reality, workstation design, team structure, decision and learning style patterns, safety operations, pattern recognition, and much, much more.« less

Individual differences in the behavioral effects of nicotine: A review of the preclinical animal literature

PubMed Central

Falco, Adriana M.; Bevins, Rick A.

2015-01-01

Not everyone who tries tobacco or other nicotine-containing products becomes a long-term user. Certain traits or factors that are differentially present in these individuals must be able to help health care providers and researchers determine who is more likely to become chronic users of nicotine-containing products. Some of these factors, particularly sensation-seeking/novelty, impulsivity, and anxiety, lend themselves to the creation of animal models of reactivity to nicotine. These models of reactivity to nicotine can improve the translational aspects of preclinical animal research on nicotine-induced behaviors and treatments in order to help reduce negative outcomes in human populations. The goal of this review is to evaluate the current status of animal models of individual differences that serve to predict the later behavioral effects of nicotine. The limited utility and inconsistency of existing novelty models is considered, as well as the promise of impulsivity and anxiety models in preclinical animal populations. Finally, other models that could be employed to extend the benefit of the current research are examined. PMID:26410616

ASSIST user manual

NASA Technical Reports Server (NTRS)

Johnson, Sally C.; Boerschlein, David P.

1995-01-01

Semi-Markov models can be used to analyze the reliability of virtually any fault-tolerant system. However, the process of delineating all the states and transitions in a complex system model can be devastatingly tedious and error prone. The Abstract Semi-Markov Specification Interface to the SURE Tool (ASSIST) computer program allows the user to describe the semi-Markov model in a high-level language. Instead of listing the individual model states, the user specifies the rules governing the behavior of the system, and these are used to generate the model automatically. A few statements in the abstract language can describe a very large, complex model. Because no assumptions are made about the system being modeled, ASSIST can be used to generate models describing the behavior of any system. The ASSIST program and its input language are described and illustrated by examples.

Cognitive Modeling of Individual Variation in Reference Production and Comprehension

PubMed Central

Hendriks, Petra

2016-01-01

A challenge for most theoretical and computational accounts of linguistic reference is the observation that language users vary considerably in their referential choices. Part of the variation observed among and within language users and across tasks may be explained from variation in the cognitive resources available to speakers and listeners. This paper presents a computational model of reference production and comprehension developed within the cognitive architecture ACT-R. Through simulations with this ACT-R model, it is investigated how cognitive constraints interact with linguistic constraints and features of the linguistic discourse in speakers’ production and listeners’ comprehension of referring expressions in specific tasks, and how this interaction may give rise to variation in referential choice. The ACT-R model of reference explains and predicts variation among language users in their referential choices as a result of individual and task-related differences in processing speed and working memory capacity. Because of limitations in their cognitive capacities, speakers sometimes underspecify or overspecify their referring expressions, and listeners sometimes choose incorrect referents or are overly liberal in their interpretation of referring expressions. PMID:27092101

An Inter-Personal Information Sharing Model Based on Personalized Recommendations

NASA Astrophysics Data System (ADS)

Kamei, Koji; Funakoshi, Kaname; Akahani, Jun-Ichi; Satoh, Tetsuji

In this paper, we propose an inter-personal information sharing model among individuals based on personalized recommendations. In the proposed model, we define an information resource as shared between people when both of them consider it important --- not merely when they both possess it. In other words, the model defines the importance of information resources based on personalized recommendations from identifiable acquaintances. The proposed method is based on a collaborative filtering system that focuses on evaluations from identifiable acquaintances. It utilizes both user evaluations for documents and their contents. In other words, each user profile is represented as a matrix of credibility to the other users' evaluations on each domain of interests. We extended the content-based collaborative filtering method to distinguish other users to whom the documents should be recommended. We also applied a concept-based vector space model to represent the domain of interests instead of the previous method which represented them by a term-based vector space model. We introduce a personalized concept-base compiled from each user's information repository to improve the information retrieval in the user's environment. Furthermore, the concept-spaces change from user to user since they reflect the personalities of the users. Because of different concept-spaces, the similarity between a document and a user's interest varies for each user. As a result, a user receives recommendations from other users who have different view points, achieving inter-personal information sharing based on personalized recommendations. This paper also describes an experimental simulation of our information sharing model. In our laboratory, five participants accumulated a personal repository of e-mails and web pages from which they built their own concept-base. Then we estimated the user profiles according to personalized concept-bases and sets of documents which others evaluated. We simulated inter-personal recommendation based on the user profiles and evaluated the performance of the recommendation method by comparing the recommended documents to the result of the content-based collaborative filtering.

GeneOnEarth: fitting genetic PC plots on the globe.

PubMed

Torres-Sánchez, Sergio; Medina-Medina, Nuria; Gignoux, Chris; Abad-Grau, María M; González-Burchard, Esteban

2013-01-01

Principal component (PC) plots have become widely used to summarize genetic variation of individuals in a sample. The similarity between genetic distance in PC plots and geographical distance has shown to be quite impressive. However, in most situations, individual ancestral origins are not precisely known or they are heterogeneously distributed; hence, they are hardly linked to a geographical area. We have developed GeneOnEarth, a user-friendly web-based tool to help geneticists to understand whether a linear isolation-by-distance model may apply to a genetic data set; thus, genetic distances among a set of individuals resemble geographical distances among their origins. Its main goal is to allow users to first apply a by-view Procrustes method to visually learn whether this model holds. To do that, the user can choose the exact geographical area from an on line 2D or 3D world map by using, respectively, Google Maps or Google Earth, and rotate, flip, and resize the images. GeneOnEarth can also compute the optimal rotation angle using Procrustes analysis and assess statistical evidence of similarity when a different rotation angle has been chosen by the user. An online version of GeneOnEarth is available for testing and using purposes at http://bios.ugr.es/GeneOnEarth.

Tailored motivational message generation: A model and practical framework for real-time physical activity coaching.

PubMed

Op den Akker, Harm; Cabrita, Miriam; Op den Akker, Rieks; Jones, Valerie M; Hermens, Hermie J

2015-06-01

This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models. Copyright © 2015 Elsevier Inc. All rights reserved.

Individual psychological therapy in an acute inpatient setting: Service user and psychologist perspectives.

PubMed

Small, Catherine; Pistrang, Nancy; Huddy, Vyv; Williams, Claire

2018-01-18

The acute inpatient setting poses potential challenges to delivering one-to-one psychological therapy; however, there is little research on the experiences of both receiving and delivering therapies in this environment. This qualitative study aimed to explore service users' and psychologists' experiences of undertaking individual therapy in acute inpatient units. It focused on the relationship between service users and psychologists, what service users found helpful or unhelpful, and how psychologists attempted to overcome any challenges in delivering therapy. The study used a qualitative, interview-based design. Eight service users and the six psychologists they worked with were recruited from four acute inpatient wards. They participated in individual semi-structured interviews eliciting their perspectives on the therapy. Service users' and psychologists' transcripts were analysed together using Braun and Clarke's (2006, Qualitative Research in Psychology, 3, 77) method of thematic analysis. The accounts highlighted the importance of forming a 'human' relationship - particularly within the context of the inpatient environment - as a basis for therapeutic work. Psychological therapy provided valued opportunities for meaning-making. To overcome the challenges of acute mental health crisis and environmental constraints, psychologists needed to work flexibly and creatively; the therapeutic work also extended to the wider context of the inpatient unit, in efforts to promote a shared understanding of service users' difficulties. Therapeutic relationships between service users and clinicians need to be promoted more broadly within acute inpatient care. Psychological formulation can help both service users and ward staff in understanding crisis and working collaboratively. Practice-based evidence is needed to demonstrate the effectiveness of adapted psychological therapy models. Developing 'human' relationships at all levels of acute inpatient care continues to be an important challenge for clinical practice. Due to the distress of individuals and the constraints of the acute inpatient environment, psychologists need to be flexible and adaptable in delivering individual therapy. Making meaning and psychological formulation can give service users a sense of hope and empowerment, and can contribute to a shared understanding within the ward team of service users' difficulties. © 2018 The British Psychological Society.

User Manual for SAHM package for VisTrails

USGS Publications Warehouse

Talbert, C.B.; Talbert, M.K.

2012-01-01

The Software for Assisted Habitat I\\•1odeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre-and post-processing steps and modeling options incorporated in the construction of a species distribution model. The four main advantages to using the combined VisTrail: SAHM package for species distribution modeling are: 1. formalization and tractable recording of the entire modeling process 2. easier collaboration through a common modeling framework 3. a user-friendly graphical interface to manage file input, model runs, and output 4. extensibility to incorporate future and additional modeling routines and tools. This user manual provides detailed information on each module within the SAHM package, their input, output, common connections, optional arguments, and default settings. This information can also be accessed for individual modules by right clicking on the documentation button for any module in VisTrail or by right clicking on any input or output for a module and selecting view documentation. This user manual is intended to accompany the user guide which provides detailed instructions on how to install the SAHM package within VisTrails and then presents information on the use of the package.

Software Helps Retrieve Information Relevant to the User

NASA Technical Reports Server (NTRS)

Mathe, Natalie; Chen, James

2003-01-01

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Quantitative Agent Based Model of User Behavior in an Internet Discussion Forum

PubMed Central

Sobkowicz, Pawel

2013-01-01

The paper presents an agent based simulation of opinion evolution, based on a nonlinear emotion/information/opinion (E/I/O) individual dynamics, to an actual Internet discussion forum. The goal is to reproduce the results of two-year long observations and analyses of the user communication behavior and of the expressed opinions and emotions, via simulations using an agent based model. The model allowed to derive various characteristics of the forum, including the distribution of user activity and popularity (outdegree and indegree), the distribution of length of dialogs between the participants, their political sympathies and the emotional content and purpose of the comments. The parameters used in the model have intuitive meanings, and can be translated into psychological observables. PMID:24324606

Emotional persistence in online chatting communities

NASA Astrophysics Data System (ADS)

Garas, Antonios; Garcia, David; Skowron, Marcin; Schweitzer, Frank

2012-05-01

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional ``tone'' of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.

Emotional persistence in online chatting communities

PubMed Central

Garas, Antonios; Garcia, David; Skowron, Marcin; Schweitzer, Frank

2012-01-01

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional “tone” of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication. PMID:22577512

Predicting future protection of respirator users: Statistical approaches and practical implications.

PubMed

Hu, Chengcheng; Harber, Philip; Su, Jing

2016-01-01

The purpose of this article is to describe a statistical approach for predicting a respirator user's fit factor in the future based upon results from initial tests. A statistical prediction model was developed based upon joint distribution of multiple fit factor measurements over time obtained from linear mixed effect models. The model accounts for within-subject correlation as well as short-term (within one day) and longer-term variability. As an example of applying this approach, model parameters were estimated from a research study in which volunteers were trained by three different modalities to use one of two types of respirators. They underwent two quantitative fit tests at the initial session and two on the same day approximately six months later. The fitted models demonstrated correlation and gave the estimated distribution of future fit test results conditional on past results for an individual worker. This approach can be applied to establishing a criterion value for passing an initial fit test to provide reasonable likelihood that a worker will be adequately protected in the future; and to optimizing the repeat fit factor test intervals individually for each user for cost-effective testing.

An enhanced archive facilitating climate impacts analysis

USGS Publications Warehouse

Maurer, E.P.; Brekke, L.; Pruitt, T.; Thrasher, B.; Long, J.; Duffy, P.; Dettinger, M.; Cayan, D.; Arnold, J.

2014-01-01

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrologi- cal variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_ cmip_projections).

Model-Driven Development of Interactive Multimedia Applications with MML

NASA Astrophysics Data System (ADS)

Pleuss, Andreas; Hussmann, Heinrich

There is an increasing demand for high-quality interactive applications which combine complex application logic with a sophisticated user interface, making use of individual media objects like graphics, animations, 3D graphics, audio or video. Their development is still challenging as it requires the integration of software design, user interface design, and media design.

Achieving recommended daily physical activity levels through commuting by public transportation: unpacking individual and contextual influences.

PubMed

Wasfi, Rania A; Ross, Nancy A; El-Geneidy, Ahmed M

2013-09-01

This paper estimates the amount of daily walking associated with using public transportation in a large metropolitan area and examines individual and contextual characteristics associated with walking distances. Total walking distance to and from transit was calculated from a travel diary survey for 6913 individuals. Multilevel regression modelling was used to examine the underlying factors associated with walking to public transportation. The physical activity benefits of public transportation varied along gender and socio-economic lines. Recommended minutes of daily physical activity can be achieved for public transportation users, especially train users living in affluent suburbs. Copyright © 2013 Elsevier Ltd. All rights reserved.

[A new model fo the evaluation of measurements of the neurocranium].

PubMed

Seidler, H; Wilfing, H; Weber, G; Traindl-Prohazka, M; zur Nedden, D; Platzer, W

1993-12-01

A simple and user-friendly model for trigonometric description of the neurocranium based on newly defined points of measurement is presented. This model not only provides individual description, but also allows for an evaluation of developmental and phylogenetic aspects.

Opinion formation on social media: An empirical approach

NASA Astrophysics Data System (ADS)

Xiong, Fei; Liu, Yun

2014-03-01

Opinion exchange models aim to describe the process of public opinion formation, seeking to uncover the intrinsic mechanism in social systems; however, the model results are seldom empirically justified using large-scale actual data. Online social media provide an abundance of data on opinion interaction, but the question of whether opinion models are suitable for characterizing opinion formation on social media still requires exploration. We collect a large amount of user interaction information from an actual social network, i.e., Twitter, and analyze the dynamic sentiments of users about different topics to investigate realistic opinion evolution. We find two nontrivial results from these data. First, public opinion often evolves to an ordered state in which one opinion predominates, but not to complete consensus. Second, agents are reluctant to change their opinions, and the distribution of the number of individual opinion changes follows a power law. Then, we suggest a model in which agents take external actions to express their internal opinions according to their activity. Conversely, individual actions can influence the activity and opinions of neighbors. The probability that an agent changes its opinion depends nonlinearly on the fraction of opponents who have taken an action. Simulation results show user action patterns and the evolution of public opinion in the model coincide with the empirical data. For different nonlinear parameters, the system may approach different regimes. A large decay in individual activity slows down the dynamics, but causes more ordering in the system.

User Guide for VISION 3.4.7 (Verifiable Fuel Cycle Simulation) Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacob J. Jacobson; Robert F. Jeffers; Gretchen E. Matthern

2011-07-01

The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters and options; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an R&D work in progress and may contain errors and omissions. It is based upon numerous assumptions. This model is intended to assist in evaluating 'what if' scenarios and in comparing fuel, reactor, and fuel processing alternatives at a systems level. The model is not intended as amore » tool for process flow and design modeling of specific facilities nor for tracking individual units of fuel or other material through the system. The model is intended to examine the interactions among the components of a fuel system as a function of time varying system parameters; this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., 'reactor types' not individual reactors and 'separation types' not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, and depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation or disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. You must use Powersim Studio 8 or better. We have tested VISION with the Studio 8 Expert, Executive, and Education versions. The Expert and Education versions work with the number of reactor types of 3 or less. For more reactor types, the Executive version is currently required. The input files are Excel2003 format (xls). The output files are macro-enabled Excel2007 format (xlsm). VISION 3.4 was designed with more flexibility than previous versions, which were structured for only three reactor types - LWRs that can use only uranium oxide (UOX) fuel, LWRs that can use multiple fuel types (LWR MF), and fast reactors. One could not have, for example, two types of fast reactors concurrently. The new version allows 10 reactor types and any user-defined uranium-plutonium fuel is allowed. (Thorium-based fuels can be input but several features of the model would not work.) The user identifies (by year) the primary fuel to be used for each reactor type. The user can identify for each primary fuel a contingent fuel to use if the primary fuel is not available, e.g., a reactor designated as using mixed oxide fuel (MOX) would have UOX as the contingent fuel. Another example is that a fast reactor using recycled transuranic (TRU) material can be designated as either having or not having appropriately enriched uranium oxide as a contingent fuel. Because of the need to study evolution in recycling and separation strategies, the user can now select the recycling strategy and separation technology, by year.« less

Classification of Twitter Users Who Tweet About E-Cigarettes

PubMed Central

Miano, Thomas; Chew, Robert; Eggers, Matthew; Nonnemaker, James

2017-01-01

Background Despite concerns about their health risks, e‑cigarettes have gained popularity in recent years. Concurrent with the recent increase in e‑cigarette use, social media sites such as Twitter have become a common platform for sharing information about e-cigarettes and to promote marketing of e‑cigarettes. Monitoring the trends in e‑cigarette–related social media activity requires timely assessment of the content of posts and the types of users generating the content. However, little is known about the diversity of the types of users responsible for generating e‑cigarette–related content on Twitter. Objective The aim of this study was to demonstrate a novel methodology for automatically classifying Twitter users who tweet about e‑cigarette–related topics into distinct categories. Methods We collected approximately 11.5 million e‑cigarette–related tweets posted between November 2014 and October 2016 and obtained a random sample of Twitter users who tweeted about e‑cigarettes. Trained human coders examined the handles’ profiles and manually categorized each as one of the following user types: individual (n=2168), vaper enthusiast (n=334), informed agency (n=622), marketer (n=752), and spammer (n=1021). Next, the Twitter metadata as well as a sample of tweets for each labeled user were gathered, and features that reflect users’ metadata and tweeting behavior were analyzed. Finally, multiple machine learning algorithms were tested to identify a model with the best performance in classifying user types. Results Using a classification model that included metadata and features associated with tweeting behavior, we were able to predict with relatively high accuracy five different types of Twitter users that tweet about e‑cigarettes (average F1 score=83.3%). Accuracy varied by user type, with F1 scores of individuals, informed agencies, marketers, spammers, and vaper enthusiasts being 91.1%, 84.4%, 81.2%, 79.5%, and 47.1%, respectively. Vaper enthusiasts were the most challenging user type to predict accurately and were commonly misclassified as marketers. The inclusion of additional tweet-derived features that capture tweeting behavior was found to significantly improve the model performance—an overall F1 score gain of 10.6%—beyond metadata features alone. Conclusions This study provides a method for classifying five different types of users who tweet about e‑cigarettes. Our model achieved high levels of classification performance for most groups, and examining the tweeting behavior was critical in improving the model performance. Results can help identify groups engaged in conversations about e‑cigarettes online to help inform public health surveillance, education, and regulatory efforts. PMID:28951381

Designing Interactive Learning Systems.

ERIC Educational Resources Information Center

Barker, Philip

1990-01-01

Describes multimedia, computer-based interactive learning systems that support various forms of individualized study. Highlights include design models; user interfaces; design guidelines; media utilization paradigms, including hypermedia and learner-controlled models; metaphors and myths; authoring tools; optical media; workstations; four case…

Examining the Moderating Effect of Individual-Level Cultural Values on Users' Acceptance of E-Learning in Developing Countries: A Structural Equation Modeling of an Extended Technology Acceptance Model

ERIC Educational Resources Information Center

Tarhini, Ali; Hone, Kate; Liu, Xiaohui; Tarhini, Takwa

2017-01-01

In this study, we examine the effects of individual-level culture on the adoption and acceptance of e-learning tools by students in Lebanon using a theoretical framework based on the Technology Acceptance Model (TAM). To overcome possible limitations of using TAM in developing countries, we extend TAM to include "subjective norms" (SN)…

Algorithm research for user trajectory matching across social media networks based on paragraph2vec

NASA Astrophysics Data System (ADS)

Xu, Qian; Chen, Hongchang; Zhi, Hongxin; Wang, Yanchuan

2018-04-01

Identifying users across different social media networks (SMN) is to link accounts of the same user that belong to the same individual across SMNs. The problem is fundamental and important, and its results can benefit many applications such as cross SMN user modeling and recommendation. With the development of GPS technology and mobile communication, more and more social networks provide location services. This provides a new opportunity for cross SMN user identification. In this paper, we solve cross SMN user identification problem in an unsupervised manner by utilizing user trajectory data in SMNs. A paragraph2vec based algorithm is proposed in which location sequence feature of user trajectory is captured in temporal and spatial dimensions. Our experimental results validate the effectiveness and efficiency of our algorithm.

Using Article Photocopy Data in Bibliographic Models for Journal Collection Management.

ERIC Educational Resources Information Center

Cooper, Michael D.; McGregor, George F.

1994-01-01

Describes a method of cost-per-use analysis for individual journal articles to facilitate journal selection, deselection, and retention decisions. Conducted in a biotechnology library, the study was based on 491 users who requested more than 48,000 article photocopies over 3 years. Information on user behavior and journal use patterns is provided.…

Shuttle/TDRSS modelling and link simulation study

NASA Technical Reports Server (NTRS)

Braun, W. R.; Mckenzie, T. M.; Biederman, L.; Lindsey, W. C.

1979-01-01

A Shuttle/TDRSS S-band and Ku-band link simulation package called LinCsim was developed for the evaluation of link performance for specific Shuttle signal designs. The link models were described in detail and the transmitter distortion parameters or user constraints were carefully defined. The overall link degradation (excluding hardware degradations) relative to an ideal BPSK channel were given for various sets of user constraint values. The performance sensitivity to each individual user constraint was then illustrated. The effect of excessive Spacelab clock jitter on the return link BER performance was also investigated as was the problem of subcarrier recovery for the K-band Shuttle return link signal.

Personalized Vehicle Energy Efficiency & Range Predictor/MyGreenCar

DOE Office of Scientific and Technical Information (OSTI.GOV)

SAXENA, SAMVEG

MyGreenCar provides users with the ability to predict the range capabilities, fuel economy, and operating costs for any vehicle for their individual driving patterns. Users launce the MyGreeCar mobile app on their smartphones to collect their driving patterns over any duration (e.g. serval days, weeks, months, etc) using a phones's locational capabilities. Using vehicle powertrain models for any user-specified vehicle type, MyGreenCar, calculates the component-level energy and power interactions for the chosen vehicle to predict several important quantities, including: 1. For Evs: Alleviating range anxiety 2. Comparing fuel economy, operating costs, and payback time across models and types.

Semantic Visualization of Wireless Sensor Networks for Elderly Monitoring

NASA Astrophysics Data System (ADS)

Stocklöw, Carsten; Kamieth, Felix

In the area of Ambient Intelligence, Wireless Sensor Networks are commonly used for user monitoring purposes like health monitoring and user localization. Existing work on visualization of wireless sensor networks focuses mainly on displaying individual nodes and logical, graph-based topologies. This way, the relation to the real-world deployment is lost. This paper presents a novel approach for visualization of wireless sensor networks and interaction with complex services on the nodes. The environment is realized as a 3D model, and multiple nodes, that are worn by a single individual, are grouped together to allow an intuitive interface for end users. We describe application examples and show that our approach allows easier access to network information and functionality by comparing it with existing solutions.

AdaBoost-based on-line signature verifier

NASA Astrophysics Data System (ADS)

Hongo, Yasunori; Muramatsu, Daigo; Matsumoto, Takashi

2005-03-01

Authentication of individuals is rapidly becoming an important issue. The authors previously proposed a Pen-input online signature verification algorithm. The algorithm considers a writer"s signature as a trajectory of pen position, pen pressure, pen azimuth, and pen altitude that evolve over time, so that it is dynamic and biometric. Many algorithms have been proposed and reported to achieve accuracy for on-line signature verification, but setting the threshold value for these algorithms is a problem. In this paper, we introduce a user-generic model generated by AdaBoost, which resolves this problem. When user- specific models (one model for each user) are used for signature verification problems, we need to generate the models using only genuine signatures. Forged signatures are not available because imposters do not give forged signatures for training in advance. However, we can make use of another's forged signature in addition to the genuine signatures for learning by introducing a user generic model. And Adaboost is a well-known classification algorithm, making final decisions depending on the sign of the output value. Therefore, it is not necessary to set the threshold value. A preliminary experiment is performed on a database consisting of data from 50 individuals. This set consists of western-alphabet-based signatures provide by a European research group. In this experiment, our algorithm gives an FRR of 1.88% and an FAR of 1.60%. Since no fine-tuning was done, this preliminary result looks very promising.

Upper extremity prosthesis user perspectives on unmet needs and innovative technology.

PubMed

Benz, Heather L; Jia Yao; Rose, Laura; Olgac, Okan; Kreutz, Karen; Saha, Anindita; Civillico, Eugene F

2016-08-01

The needs of individuals with upper limb amputation and congenital limb difference are not being fully met by current prostheses, as evidenced by prosthesis rejection, non-wear, and user reports of pain and challenging activities. Emerging technologies such as dexterous sensorized robotic limbs, osseointegrated prostheses, implantable EMG electrodes, and electrical stimulation for sensory feedback have the potential to address unmet needs, but pose additional risks. We plan to assess upper limb prosthesis user needs and perspectives on these new benefits and risks using an extensive quantitative survey. In preparation for this survey, we report here on qualitative interviews with seven individuals with upper limb amputation or congenital limb difference. Unstructured text was mined using topic modeling and the results compared with identified themes. A more complete understanding of how novel technologies could address real user concerns will inform implementation of new technologies and regulatory decision-making.

Upper Extremity Prosthesis User Perspectives on Unmet Needs and Innovative Technology

PubMed Central

Benz, Heather L.; Yao, Jia; Rose, Laura; Olgac, Okan; Kreutz, Karen; Saha, Anindita; Civillico, Eugene F.

2017-01-01

The needs of individuals with upper limb amputation and congenital limb difference are not being fully met by current prostheses, as evidenced by prosthesis rejection, non-wear, and user reports of pain and challenging activities. Emerging technologies such as dexterous sensorized robotic limbs, osseointegrated prostheses, implantable EMG electrodes, and electrical stimulation for sensory feedback have the potential to address unmet needs, but pose additional risks. We plan to assess upper limb prosthesis user needs and perspectives on these new benefits and risks using an extensive quantitative survey. In preparation for this survey, we report here on qualitative interviews with seven individuals with upper limb amputation or congenital limb difference. Unstructured text was mined using topic modeling and the results compared with identified themes. A more complete understanding of how novel technologies could address real user concerns will inform implementation of new technologies and regulatory decision-making. PMID:28268333

A power information user (PIU) model to promote information integration in Tennessee's public health community.

PubMed

Sathe, Nila A; Lee, Patricia; Giuse, Nunzia Bettinsoli

2004-10-01

Observation and immersion in the user community are critical factors in designing and implementing informatics solutions; such practices ensure relevant interventions and promote user acceptance. Libraries can adapt these strategies to developing instruction and outreach. While needs assessment is typically a core facet of library instruction, sustained, iterative assessment underlying the development of user-centered instruction is key to integrating resource use into the workflow. This paper describes the Eskind Biomedical Library's (EBL's) recent work with the Tennessee public health community to articulate a training model centered around developing power information users (PIUs). PIUs are community-based individuals with an advanced understanding of information seeking and resource use and are committed to championing information integration. As model development was informed by observation of PIU workflow and information needs, it also allowed for informal testing of the applicability of assessment via domain immersion in library outreach. Though the number of PIUs involved in the project was small, evaluation indicated that the model was useful for promoting information use in PIU workgroups and that the concept of domain immersion was relevant to library-related projects. Moreover, EBL continues to employ principles of domain understanding inherent in the PIU model to develop further interventions for the public health community and library users.

The impact of SOA for achieving healthcare interoperability. An empirical investigation based on a hypothetical adoption.

PubMed

Daskalakis, S; Mantas, J

2009-01-01

The evaluation of a service-oriented prototype implementation for healthcare interoperability. A prototype framework was developed, aiming to exploit the use of service-oriented architecture (SOA) concepts for achieving healthcare interoperability and to move towards a virtual patient record (VPR) paradigm. The prototype implementation was evaluated for its hypothetical adoption. The evaluation strategy was based on the initial proposition of the DeLone and McLean model of information systems (IS) success [1], as modeled by Iivari [2]. A set of SOA and VPR characteristics were empirically encapsulated within the dimensions of IS success model, combined with measures from previous research works. The data gathered was analyzed using partial least squares (PLS). The results highlighted that system quality is a partial predictor of system use but not of user satisfaction. On the contrary, information quality proved to be a significant predictor of user satisfaction and partially a strong significant predictor of system use. Moreover, system use did not prove to be a significant predictor of individual impact whereas the bi-directional relation between use and user satisfaction did not confirm. Additionally, user satisfaction was found to be a strong significant predictor of individual impact. Finally, individual impact proved to be a strong significant predictor of organizational impact. The empirical study attempted to obtain hypothetical, but still useful beliefs and perceptions regarding the SOA prototype implementation. The deduced observations can form the basis for further investigation regarding the adaptability of SOA implementations with VPR characteristics in the healthcare domain.

Individually adapted imagery improves brain-computer interface performance in end-users with disability.

PubMed

Scherer, Reinhold; Faller, Josef; Friedrich, Elisabeth V C; Opisso, Eloy; Costa, Ursula; Kübler, Andrea; Müller-Putz, Gernot R

2015-01-01

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - binary classification performance of about 75%. Performance in users with central nervous system (CNS) tissue damage is typically lower. User training generally enhances reliability of EEG pattern generation and thus also robustness of pattern recognition. In this study, we investigated the impact of mental tasks on binary classification performance in BCI users with central nervous system (CNS) tissue damage such as persons with stroke or spinal cord injury (SCI). Motor imagery (MI), that is the kinesthetic imagination of movement (e.g. squeezing a rubber ball with the right hand), is the "gold standard" and mainly used to modulate EEG patterns. Based on our recent results in able-bodied users, we hypothesized that pair-wise combination of "brain-teaser" (e.g. mental subtraction and mental word association) and "dynamic imagery" (e.g. hand and feet MI) tasks significantly increases classification performance of induced EEG patterns in the selected end-user group. Within-day (How stable is the classification within a day?) and between-day (How well does a model trained on day one perform on unseen data of day two?) analysis of variability of mental task pair classification in nine individuals confirmed the hypothesis. We found that the use of the classical MI task pair hand vs. feed leads to significantly lower classification accuracy - in average up to 15% less - in most users with stroke or SCI. User-specific selection of task pairs was again essential to enhance performance. We expect that the gained evidence will significantly contribute to make imagery-based BCI technology become accessible to a larger population of users including individuals with special needs due to CNS damage.

Individually Adapted Imagery Improves Brain-Computer Interface Performance in End-Users with Disability

PubMed Central

Scherer, Reinhold; Faller, Josef; Friedrich, Elisabeth V. C.; Opisso, Eloy; Costa, Ursula; Kübler, Andrea; Müller-Putz, Gernot R.

2015-01-01

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - binary classification performance of about 75%. Performance in users with central nervous system (CNS) tissue damage is typically lower. User training generally enhances reliability of EEG pattern generation and thus also robustness of pattern recognition. In this study, we investigated the impact of mental tasks on binary classification performance in BCI users with central nervous system (CNS) tissue damage such as persons with stroke or spinal cord injury (SCI). Motor imagery (MI), that is the kinesthetic imagination of movement (e.g. squeezing a rubber ball with the right hand), is the "gold standard" and mainly used to modulate EEG patterns. Based on our recent results in able-bodied users, we hypothesized that pair-wise combination of "brain-teaser" (e.g. mental subtraction and mental word association) and "dynamic imagery" (e.g. hand and feet MI) tasks significantly increases classification performance of induced EEG patterns in the selected end-user group. Within-day (How stable is the classification within a day?) and between-day (How well does a model trained on day one perform on unseen data of day two?) analysis of variability of mental task pair classification in nine individuals confirmed the hypothesis. We found that the use of the classical MI task pair hand vs. feed leads to significantly lower classification accuracy - in average up to 15% less - in most users with stroke or SCI. User-specific selection of task pairs was again essential to enhance performance. We expect that the gained evidence will significantly contribute to make imagery-based BCI technology become accessible to a larger population of users including individuals with special needs due to CNS damage. PMID:25992718

[Assessing user satisfaction, an objective for quality of care].

PubMed

Séné-Bourgeois, Martine; Mathieu-Chakroun, Isabelle; Margat, Aurore

The assessment of user satisfaction constitutes a key indicator of the quality of care. It can be envisaged either as part of an internal strategy which favours the improvement of practices, an external strategy whose focus is more commercial and/or an exploratory strategy to develop care models. User satisfaction is expressed in particular through complaint letters and discharge questionnaires. These regulated schemes enable quality to be approached on an individual and collective level. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

SmartG: Spontaneous Malaysian Augmented Reality Tourist Guide

NASA Astrophysics Data System (ADS)

Kasinathan, Vinothini; Mustapha, Aida; Subramaniam, Tanabalan

2016-11-01

In effort to attract higher tourist expenditure along with higher tourist arrivals, this paper proposes a travel application called the SmartG, acronym for Spontaneous Malaysian Augmented Reality Tourist Guide, which operates by making recommendations to user based on the travel objective and individual budget constraints. The applications relies on augmented reality technology, whereby a three dimensional model is presented to the user based on input from real world environment. User testing returned a favorable feedback on the concept of using augmented reality in promoting Malaysian tourism.

The SmartH2O project: a platform supporting residential water management through smart meters and data intensive modeling

NASA Astrophysics Data System (ADS)

Cominola, A.; Nanda, R.; Giuliani, M.; Piga, D.; Castelletti, A.; Rizzoli, A. E.; Maziotis, A.; Garrone, P.; Harou, J. J.

2014-12-01

Designing effective urban water demand management strategies at the household level does require a deep understanding of the determinants of users' consumption. Low resolution data on residential water consumption, as traditionally metered, can only be used to model consumers' behavior at an aggregate level whereas end uses breakdown and the motivations and individual attitudes of consumers are hidden. The recent advent of smart meters allows gathering high frequency consumption data that can be used both to provide instantaneous information to water utilities on the state of the network and continuously inform the users on their consumption and savings. Smart metered data also allow for the characterization of water end uses: this information, coupled with users' psychographic variables, constitutes the knowledge basis for developing individual and multi users models, through which water utilities can test the impact of different management strategies. SmartH2O is an EU funded project which aims at creating an ICT platform able to (i) capture and store quasi real time, high resolution residential water usage data measured with smart meters, (ii) infer the main determinants of residential water end uses and build customers' behavioral models and (iii) predict how the customer behavior can be influenced by various water demand management strategies, spanning from dynamic water pricing schemes to social awareness campaigns. The project exploits a social computing approach for raising users' awareness about water consumption and pursuing water savings in the residential sector. In this work, we first present the SmartH2O platform and data collection, storage and analysis components. We then introduce some preliminary models and results on total water consumption disaggregation into end uses and single user behaviors using innovative fully automated algorithms and overcoming the need of invasive metering campaigns at the fixture level.

A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

PubMed

Pan, Shaoming; Chong, Yanwen; Zhang, Hang; Tan, Xicheng

2017-01-01

A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client's requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users' access behaviors and all tiles' relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users' access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods.

GRAPHICAL USER INTERFACE WITH APPLICATIONS IN SUSCEPTIBLE-INFECTIOUS-SUSCEPTIBLE MODELS.

PubMed

Ilea, M; Turnea, M; Arotăriţei, D; Rotariu, Mariana; Popescu, Marilena

2015-01-01

Practical significance of understanding the dynamics and evolution of infectious diseases increases continuously in contemporary world. The mathematical study of the dynamics of infectious diseases has a long history. By incorporating statistical methods and computer-based simulations in dynamic epidemiological models, it could be possible for modeling methods and theoretical analyses to be more realistic and reliable, allowing a more detailed understanding of the rules governing epidemic spreading. To provide the basis for a disease transmission, the population of a region is often divided into various compartments, and the model governing their relation is called the compartmental model. To present all of the information available, a graphical user interface provides icons and visual indicators. The graphical interface shown in this paper is performed using the MATLAB software ver. 7.6.0. MATLAB software offers a wide range of techniques by which data can be displayed graphically. The process of data viewing involves a series of operations. To achieve it, I had to make three separate files, one for defining the mathematical model and two for the interface itself. Considering a fixed population, it is observed that the number of susceptible individuals diminishes along with an increase in the number of infectious individuals so that in about ten days the number of individuals infected and susceptible, respectively, has the same value. If the epidemic is not controlled, it will continue for an indefinite period of time. By changing the global parameters specific of the SIS model, a more rapid increase of infectious individuals is noted. Using the graphical user interface shown in this paper helps achieving a much easier interaction with the computer, simplifying the structure of complex instructions by using icons and menus, and, in particular, programs and files are much easier to organize. Some numerical simulations have been presented to illustrate theoretical analysis.

Individual and Network Interventions With Injection Drug Users in 5 Ukraine Cities

PubMed Central

Lehman, Wayne E. K.; Latkin, Carl A.; Dvoryak, Sergey; Brewster, John T.; Royer, Mark S.; Sinitsyna, Larisa

2011-01-01

Objectives. We evaluated the effects of an individual intervention versus a network intervention on HIV-related injection and sexual risk behaviors among street-recruited opiate injection drug users in 5 Ukraine cities. Methods. Between 2004 and 2006, 722 opiate injection drug users were recruited to participate in interventions that were either individually based or based on a social network model in which peer educators intervened with their network members. Audio computer-assisted self-interview techniques were used to interview participants at baseline and follow-up. Results. Multiple logistic analyses controlling for baseline injection and sexual risks revealed that both peer educators and network members in the network intervention reduced injection-related risk behaviors significantly more than did those in the individually based intervention and that peer educators increased condom use significantly more than did those in the individual intervention. Individual intervention participants, however, showed significantly greater improvements than did network members with respect to reductions in sexual risk behaviors. Conclusions. Social network interventions may be more effective than individually based interventions in changing injection risk behaviors among both peer educators and network members. The effectiveness of network interventions in changing sexual risk behaviors is less clear, probably owing to network composition and inhibitions regarding discussing sexual risk behaviors. PMID:20395584

Classification of Twitter Users Who Tweet About E-Cigarettes.

PubMed

Kim, Annice; Miano, Thomas; Chew, Robert; Eggers, Matthew; Nonnemaker, James

2017-09-26

Despite concerns about their health risks, e‑cigarettes have gained popularity in recent years. Concurrent with the recent increase in e‑cigarette use, social media sites such as Twitter have become a common platform for sharing information about e-cigarettes and to promote marketing of e‑cigarettes. Monitoring the trends in e‑cigarette-related social media activity requires timely assessment of the content of posts and the types of users generating the content. However, little is known about the diversity of the types of users responsible for generating e‑cigarette-related content on Twitter. The aim of this study was to demonstrate a novel methodology for automatically classifying Twitter users who tweet about e‑cigarette-related topics into distinct categories. We collected approximately 11.5 million e‑cigarette-related tweets posted between November 2014 and October 2016 and obtained a random sample of Twitter users who tweeted about e‑cigarettes. Trained human coders examined the handles' profiles and manually categorized each as one of the following user types: individual (n=2168), vaper enthusiast (n=334), informed agency (n=622), marketer (n=752), and spammer (n=1021). Next, the Twitter metadata as well as a sample of tweets for each labeled user were gathered, and features that reflect users' metadata and tweeting behavior were analyzed. Finally, multiple machine learning algorithms were tested to identify a model with the best performance in classifying user types. Using a classification model that included metadata and features associated with tweeting behavior, we were able to predict with relatively high accuracy five different types of Twitter users that tweet about e‑cigarettes (average F 1 score=83.3%). Accuracy varied by user type, with F 1 scores of individuals, informed agencies, marketers, spammers, and vaper enthusiasts being 91.1%, 84.4%, 81.2%, 79.5%, and 47.1%, respectively. Vaper enthusiasts were the most challenging user type to predict accurately and were commonly misclassified as marketers. The inclusion of additional tweet-derived features that capture tweeting behavior was found to significantly improve the model performance-an overall F 1 score gain of 10.6%-beyond metadata features alone. This study provides a method for classifying five different types of users who tweet about e‑cigarettes. Our model achieved high levels of classification performance for most groups, and examining the tweeting behavior was critical in improving the model performance. Results can help identify groups engaged in conversations about e‑cigarettes online to help inform public health surveillance, education, and regulatory efforts. ©Annice Kim, Thomas Miano, Robert Chew, Matthew Eggers, James Nonnemaker. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 26.09.2017.

Versatile clinical information system design for emergency departments.

PubMed

Amouh, Teh; Gemo, Monica; Macq, Benoît; Vanderdonckt, Jean; El Gariani, Abdul Wahed; Reynaert, Marc S; Stamatakis, Lambert; Thys, Frédéric

2005-06-01

Compared to other hospital units, the emergency department presents some distinguishing characteristics of its own. Emergency health-care delivery is a collaborative process involving the contribution of several individuals who accomplish their tasks while working autonomously under pressure and sometimes with limited resources. Effective computerization of the emergency department information system presents a real challenge due to the complexity of the scenario. Current computerized support suffers from several problems, including inadequate data models, clumsy user interfaces, and poor integration with other clinical information systems. To tackle such complexity, we propose an approach combining three points of view, namely the transactions (in and out of the department), the (mono and multi) user interfaces and data management. Unlike current systems, we pay particular attention to the user-friendliness and versatility of our system. This means that intuitive user interfaces have been conceived and specific software modeling methodologies have been applied to provide our system with the flexibility and adaptability necessary for the individual and group coordinated tasks. Our approach has been implemented by prototyping a web-based, multiplatform, multiuser, and versatile clinical information system built upon multitier software architecture, using the Java programming language.

User-Adapted Recommendation of Content on Mobile Devices Using Bayesian Networks

NASA Astrophysics Data System (ADS)

Iwasaki, Hirotoshi; Mizuno, Nobuhiro; Hara, Kousuke; Motomura, Yoichi

Mobile devices, such as cellular phones and car navigation systems, are essential to daily life. People acquire necessary information and preferred content over communication networks anywhere, anytime. However, usability issues arise from the simplicity of user interfaces themselves. Thus, a recommendation of content that is adapted to a user's preference and situation will help the user select content. In this paper, we describe a method to realize such a system using Bayesian networks. This user-adapted mobile system is based on a user model that provides recommendation of content (i.e., restaurants, shops, and music that are suitable to the user and situation) and that learns incrementally based on accumulated usage history data. However, sufficient samples are not always guaranteed, since a user model would require combined dependency among users, situations, and contents. Therefore, we propose the LK method for modeling, which complements incomplete and insufficient samples using knowledge data, and CPT incremental learning for adaptation based on a small number of samples. In order to evaluate the methods proposed, we applied them to restaurant recommendations made on car navigation systems. The evaluation results confirmed that our model based on the LK method can be expected to provide better generalization performance than that of the conventional method. Furthermore, our system would require much less operation than current car navigation systems from the beginning of use. Our evaluation results also indicate that learning a user's individual preference through CPT incremental learning would be beneficial to many users, even with only a few samples. As a result, we have developed the technology of a system that becomes more adapted to a user the more it is used.

Enhancing Transparency and Control When Drawing Data-Driven Inferences About Individuals.

PubMed

Chen, Daizhuo; Fraiberger, Samuel P; Moakler, Robert; Provost, Foster

2017-09-01

Recent studies show the remarkable power of fine-grained information disclosed by users on social network sites to infer users' personal characteristics via predictive modeling. Similar fine-grained data are being used successfully in other commercial applications. In response, attention is turning increasingly to the transparency that organizations provide to users as to what inferences are drawn and why, as well as to what sort of control users can be given over inferences that are drawn about them. In this article, we focus on inferences about personal characteristics based on information disclosed by users' online actions. As a use case, we explore personal inferences that are made possible from "Likes" on Facebook. We first present a means for providing transparency into the information responsible for inferences drawn by data-driven models. We then introduce the "cloaking device"-a mechanism for users to inhibit the use of particular pieces of information in inference. Using these analytical tools we ask two main questions: (1) How much information must users cloak to significantly affect inferences about their personal traits? We find that usually users must cloak only a small portion of their actions to inhibit inference. We also find that, encouragingly, false-positive inferences are significantly easier to cloak than true-positive inferences. (2) Can firms change their modeling behavior to make cloaking more difficult? The answer is a definitive yes. We demonstrate a simple modeling change that requires users to cloak substantially more information to affect the inferences drawn. The upshot is that organizations can provide transparency and control even into complicated, predictive model-driven inferences, but they also can make control easier or harder for their users.

Enhancing Transparency and Control When Drawing Data-Driven Inferences About Individuals

PubMed Central

Chen, Daizhuo; Fraiberger, Samuel P.; Moakler, Robert; Provost, Foster

2017-01-01

Abstract Recent studies show the remarkable power of fine-grained information disclosed by users on social network sites to infer users' personal characteristics via predictive modeling. Similar fine-grained data are being used successfully in other commercial applications. In response, attention is turning increasingly to the transparency that organizations provide to users as to what inferences are drawn and why, as well as to what sort of control users can be given over inferences that are drawn about them. In this article, we focus on inferences about personal characteristics based on information disclosed by users' online actions. As a use case, we explore personal inferences that are made possible from “Likes” on Facebook. We first present a means for providing transparency into the information responsible for inferences drawn by data-driven models. We then introduce the “cloaking device”—a mechanism for users to inhibit the use of particular pieces of information in inference. Using these analytical tools we ask two main questions: (1) How much information must users cloak to significantly affect inferences about their personal traits? We find that usually users must cloak only a small portion of their actions to inhibit inference. We also find that, encouragingly, false-positive inferences are significantly easier to cloak than true-positive inferences. (2) Can firms change their modeling behavior to make cloaking more difficult? The answer is a definitive yes. We demonstrate a simple modeling change that requires users to cloak substantially more information to affect the inferences drawn. The upshot is that organizations can provide transparency and control even into complicated, predictive model-driven inferences, but they also can make control easier or harder for their users. PMID:28933942

Visual Basic, Excel-based fish population modeling tool - The pallid sturgeon example

USGS Publications Warehouse

Moran, Edward H.; Wildhaber, Mark L.; Green, Nicholas S.; Albers, Janice L.

2016-02-10

The model presented in this report is a spreadsheet-based model using Visual Basic for Applications within Microsoft Excel (http://dx.doi.org/10.5066/F7057D0Z) prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service. It uses the same model structure and, initially, parameters as used by Wildhaber and others (2015) for pallid sturgeon. The difference between the model structure used for this report and that used by Wildhaber and others (2015) is that variance is not partitioned. For the model of this report, all variance is applied at the iteration and time-step levels of the model. Wildhaber and others (2015) partition variance into parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level and temporal variance (uncertainty caused by random environmental fluctuations with time) applied at the time-step level. They included implicit individual variance (uncertainty caused by differences between individuals) within the time-step level.The interface developed for the model of this report is designed to allow the user the flexibility to change population model structure and parameter values and uncertainty separately for every component of the model. This flexibility makes the modeling tool potentially applicable to any fish species; however, the flexibility inherent in this modeling tool makes it possible for the user to obtain spurious outputs. The value and reliability of the model outputs are only as good as the model inputs. Using this modeling tool with improper or inaccurate parameter values, or for species for which the structure of the model is inappropriate, could lead to untenable management decisions. By facilitating fish population modeling, this modeling tool allows the user to evaluate a range of management options and implications. The goal of this modeling tool is to be a user-friendly modeling tool for developing fish population models useful to natural resource managers to inform their decision-making processes; however, as with all population models, caution is needed, and a full understanding of the limitations of a model and the veracity of user-supplied parameters should always be considered when using such model output in the management of any species.

Exploring User Acceptance of FOSS: The Role of the Age of the Users

NASA Astrophysics Data System (ADS)

Gallego, M. Dolores; Bueno, Salvador

Free and open source software (FOSS) movement essentially arises like answer to the evolution occurred in the market from the software, characterized by the closing of the source code. Furthermore, some FOSS characteristics, such as (1) the advance of this movement and (2) the attractiveness that contributes the voluntary and cooperative work, have increased the interest of the users towards free software. Traditionally, research in FOSS has focused on identifying individual personal motives for participating in the development of a FOSS project, analyzing specific FOSS solutions, or the FOSS movement itself. Nevertheless, the advantages of the FOSS for users and the effect of the demographic dimensions on user acceptance for FOSS have been two research topics with little attention. Specifically, this paper's aim is to focus on the influence of the userś age with FOSS the FOSS acceptance. Based on the literature, userś age is an essential demographic dimension for explaining the Information Systems acceptance. With this purpose, the authors have developed a research model based on the Technological Acceptance Model (TAM).

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

Technology Acceptance Model for Wireless Internet.

ERIC Educational Resources Information Center

Lu, June; Yu, Chun-Sheng; Liu, Chang; Yao, James E.

2003-01-01

Develops a technology acceptance model (TAM) for wireless Internet via mobile devices (WIMD) and proposes that constructs, such as individual differences, technology complexity, facilitating conditions, social influences, and wireless trust environment determine user-perceived short and long-term usefulness, and ease of using WIMD. Twelve…

A Chemical Properties Simulator to Support Integrated Environmental Modeling

EPA Science Inventory

Users of Integrated Environmental Modeling (IEM) systems are responsible for defining individual chemicals and their properties, a process that is time-consuming at best and overwhelming at worst, especially for new chemicals with new structures. A software tool is needed to allo...

3-dimensional orthodontics visualization system with dental study models and orthopantomograms

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ong, S. H.; Foong, K. W. C.; Dhar, T.

2005-04-01

The aim of this study is to develop a system that provides 3-dimensional visualization of orthodontic treatments. Dental plaster models and corresponding orthopantomogram (dental panoramic tomogram) are first digitized and fed into the system. A semi-auto segmentation technique is applied to the plaster models to detect the dental arches, tooth interstices and gum margins, which are used to extract individual crown models. 3-dimensional representation of roots, generated by deforming generic tooth models with orthopantomogram using radial basis functions, is attached to corresponding crowns to enable visualization of complete teeth. An optional algorithm to close the gaps between deformed roots and actual crowns by using multi-quadratic radial basis functions is also presented, which is capable of generating smooth mesh representation of complete 3-dimensional teeth. User interface is carefully designed to achieve a flexible system with as much user friendliness as possible. Manual calibration and correction is possible throughout the data processing steps to compensate occasional misbehaviors of automatic procedures. By allowing the users to move and re-arrange individual teeth (with their roots) on a full dentition, this orthodontic visualization system provides an easy and accurate way of simulation and planning of orthodontic treatment. Its capability of presenting 3-dimensional root information with only study models and orthopantomogram is especially useful for patients who do not undergo CT scanning, which is not a routine procedure in most orthodontic cases.

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Language workbench user interfaces for data analysis

PubMed Central

Benson, Victoria M.

2015-01-01

Biological data analysis is frequently performed with command line software. While this practice provides considerable flexibility for computationally savy individuals, such as investigators trained in bioinformatics, this also creates a barrier to the widespread use of data analysis software by investigators trained as biologists and/or clinicians. Workflow systems such as Galaxy and Taverna have been developed to try and provide generic user interfaces that can wrap command line analysis software. These solutions are useful for problems that can be solved with workflows, and that do not require specialized user interfaces. However, some types of analyses can benefit from custom user interfaces. For instance, developing biomarker models from high-throughput data is a type of analysis that can be expressed more succinctly with specialized user interfaces. Here, we show how Language Workbench (LW) technology can be used to model the biomarker development and validation process. We developed a language that models the concepts of Dataset, Endpoint, Feature Selection Method and Classifier. These high-level language concepts map directly to abstractions that analysts who develop biomarker models are familiar with. We found that user interfaces developed in the Meta-Programming System (MPS) LW provide convenient means to configure a biomarker development project, to train models and view the validation statistics. We discuss several advantages of developing user interfaces for data analysis with a LW, including increased interface consistency, portability and extension by language composition. The language developed during this experiment is distributed as an MPS plugin (available at http://campagnelab.org/software/bdval-for-mps/). PMID:25755929

A Novel Recommendation System to Match College Events and Groups to Students

NASA Astrophysics Data System (ADS)

Qazanfari, K.; Youssef, A.; Keane, K.; Nelson, J.

2017-10-01

With the recent increase in data online, discovering meaningful opportunities can be time-consuming and complicated for many individuals. To overcome this data overload challenge, we present a novel text-content-based recommender system as a valuable tool to predict user interests. To that end, we develop a specific procedure to create user models and item feature-vectors, where items are described in free text. The user model is generated by soliciting from a user a few keywords and expanding those keywords into a list of weighted near-synonyms. The item feature-vectors are generated from the textual descriptions of the items, using modified tf-idf values of the users’ keywords and their near-synonyms. Once the users are modeled and the items are abstracted into feature vectors, the system returns the maximum-similarity items as recommendations to that user. Our experimental evaluation shows that our method of creating the user models and item feature-vectors resulted in higher precision and accuracy in comparison to well-known feature-vector-generating methods like Glove and Word2Vec. It also shows that stemming and the use of a modified version of tf-idf increase the accuracy and precision by 2% and 3%, respectively, compared to non-stemming and the standard tf-idf definition. Moreover, the evaluation results show that updating the user model from usage histories improves the precision and accuracy of the system. This recommender system has been developed as part of the Agnes application, which runs on iOS and Android platforms and is accessible through the Agnes website.

A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China.

PubMed

Qi, Chang; Kelly, Brian C; Liao, Yanhui; He, Haoyu; Luo, Tao; Deng, Huiqiong; Liu, Tieqiao; Hao, Wei; Wang, Jichuan

2015-03-01

Although evidence exists for distinct barriers to drug abuse treatment (BDATs), investigations of their inter-relationships and the effect of individual characteristics on the barrier factors have been sparse, especially in China. A Multiple Indicators Multiple Causes (MIMIC) model is applied for this target. A sample of 262 drug users were recruited from three drug rehabilitation centers in Hunan Province, China. We applied a MIMIC approach to investigate the effect of gender, age, marital status, education, primary substance use, duration of primary drug use, and drug treatment experience on the internal barrier factors: absence of problem (AP), negative social support (NSS), fear of treatment (FT), and privacy concerns (PC). Drug users of various characteristics were found to report different internal barrier factors. Younger participants were more likely to report NSS (-0.19, p=0.038) and PC (-0.31, p<0.001). Compared to other drug users, ice users were more likely to report AP (0.44, p<0.001) and NSS (0.25, p=0.010). Drug treatment experiences related to AP (0.20, p=0.012). In addition, differential item functioning (DIF) occurred in three items when participant from groups with different duration of drug use, ice use, or marital status. Individual characteristics had significant effects on internal barriers to drug treatment. On this basis, BDAT perceived by different individuals could be assessed before tactics were utilized to successfully remove perceived barriers to drug treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Observing Consistency in Online Communication Patterns for User Re-Identification.

PubMed

Adeyemi, Ikuesan Richard; Razak, Shukor Abd; Salleh, Mazleena; Venter, Hein S

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Prediction of user preference over shared-control paradigms for a robotic wheelchair.

PubMed

Erdogan, Ahmetcan; Argall, Brenna D

2017-07-01

The design of intelligent powered wheelchairs has traditionally focused heavily on providing effective and efficient navigation assistance. Significantly less attention has been given to the end-user's preference between different assistance paradigms. It is possible to include these subjective evaluations in the design process, for example by soliciting feedback in post-experiment questionnaires. However, constantly querying the user for feedback during real-world operation is not practical. In this paper, we present a model that correlates objective performance metrics and subjective evaluations of autonomous wheelchair control paradigms. Using off-the-shelf machine learning techniques, we show that it is possible to build a model that can predict the most preferred shared-control method from task execution metrics such as effort, safety, performance and utilization. We further characterize the relative contributions of each of these metrics to the individual choice of most preferred assistance paradigm. Our evaluation includes Spinal Cord Injured (SCI) and uninjured subject groups. The results show that our proposed correlation model enables the continuous tracking of user preference and offers the possibility of autonomy that is customized to each user.

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

NASA Astrophysics Data System (ADS)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

Effects of a recovery management intervention on Chinese heroin users' community recovery through the mediation effect of enhanced service utilization

PubMed Central

Wu, F.; Fu, L.M.; Hser, Y.H.

2015-01-01

Background This study investigates whether a recovery management intervention (RMI) can improve the utilization of community drug treatment and wraparound services among heroin users in China and subsequently lead to positive recovery outcomes. Methods Secondary analysis was conducted drawing data from a randomized controlled trial; 100 heroin users with no severe mental health problems were recruited in two Shanghai districts (Hongkou and Yangpu) upon their release from compulsory rehabilitation facilities. A latent variable modeling approach was utilized to test whether the RMI influences heroin users' perceived motivation and readiness for treatment, enhances treatment and wraparound service participation, and, in turn, predicts better recovery outcomes. Results Enrollment in drug treatment and other social service utilization increased significantly as a result of RMI rather than an individual drug user's motivation and readiness for treatment. Increased service utilization thus led to more positive individual recovery outcomes. In addition to this mediation effect through service utilization, the RMI also improved participants' community recovery directly. Conclusions Findings suggest that better drug treatment enrollment, community service utilization and recovery outcomes can be potentially achieved among heroin users in China with carefully designed case management interventions. PMID:24990956

Performance & Emotion--A Study on Adaptive E-Learning Based on Visual/Verbal Learning Styles

ERIC Educational Resources Information Center

Beckmann, Jennifer; Bertel, Sven; Zander, Steffi

2015-01-01

Adaptive e-Learning systems are able to adjust to a user's learning needs, usually by user modeling or tracking progress. Such learner-adaptive behavior has rapidly become a hot topic for e-Learning, furthered in part by the recent rapid increase in the use of MOOCs (Massive Open Online Courses). A lack of general, individual, and situational data…

User acceptance of mobile health services from users' perspectives: The role of self-efficacy and response-efficacy in technology acceptance.

PubMed

Zhang, Xiaofei; Han, Xiaocui; Dang, Yuanyuan; Meng, Fanbo; Guo, Xitong; Lin, Jiayue

2017-03-01

With the swift emergence of electronic medical information, the global popularity of mobile health (mHealth) services continues to increase steadily. This study aims to investigate the efficacy factors that directly or indirectly influence individuals' acceptance of mHealth services. Based on the technology acceptance model, this research incorporates efficacy factors into the acceptance decision process. A research model was proposed involving the direct and indirect effects of self-efficacy and response-efficacy on acceptance intention, along with their moderating effects. The model and hypotheses were validated using data collected from a field survey of 650 potential service users. The results reveal that: (1) self-efficacy and response-efficacy are both positively associated with perceived ease of use; and (2) self-efficacy and response-efficacy moderate the impact of perceived usefulness toward adoption intention. Self-efficacy and response-efficacy both play an important role in individuals' acceptance of mHealth services, which not only affect their perceived ease of use of mHealth services, but also positively moderate the effects of perceived usefulness on adoption intention. Our findings serve to provide recommendations that are specifically customized for mHealth service providers and their marketers.

Individual-Based Modeling of Tuberculosis in a User-Friendly Interface: Understanding the Epidemiological Role of Population Heterogeneity in a City

PubMed Central

Prats, Clara; Montañola-Sales, Cristina; Gilabert-Navarro, Joan F.; Valls, Joaquim; Casanovas-Garcia, Josep; Vilaplana, Cristina; Cardona, Pere-Joan; López, Daniel

2016-01-01

For millennia tuberculosis (TB) has shown a successful strategy to survive, making it one of the world’s deadliest infectious diseases. This resilient behavior is based not only on remaining hidden in most of the infected population, but also by showing slow evolution in most sick people. The course of the disease within a population is highly related to its heterogeneity. Thus, classic epidemiological approaches with a top-down perspective have not succeeded in understanding its dynamics. In the past decade a few individual-based models were built, but most of them preserved a top-down view that makes it difficult to study a heterogeneous population. We propose an individual-based model developed with a bottom-up approach to studying the dynamics of pulmonary TB in a certain population, considered constant. Individuals may belong to the following classes: healthy, infected, sick, under treatment, and treated with a probability of relapse. Several variables and parameters account for their age, origin (native or immigrant), immunodeficiency, diabetes, and other risk factors (smoking and alcoholism). The time within each infection state is controlled, and sick individuals may show a cavitated disease or not that conditions infectiousness. It was implemented in NetLogo because it allows non-modelers to perform virtual experiments with a user-friendly interface. The simulation was conducted with data from Ciutat Vella, a district of Barcelona with an incidence of 67 TB cases per 100,000 inhabitants in 2013. Several virtual experiments were performed to relate the disease dynamics with the structure of the infected subpopulation (e.g., the distribution of infected times). Moreover, the short-term effect of health control policies on modifying that structure was studied. Results show that the characteristics of the population are crucial for the local epidemiology of TB. The developed user-friendly tool is ready to test control strategies of disease in any city in the short-term. PMID:26793189

Individual-Based Modeling of Tuberculosis in a User-Friendly Interface: Understanding the Epidemiological Role of Population Heterogeneity in a City.

PubMed

Prats, Clara; Montañola-Sales, Cristina; Gilabert-Navarro, Joan F; Valls, Joaquim; Casanovas-Garcia, Josep; Vilaplana, Cristina; Cardona, Pere-Joan; López, Daniel

2015-01-01

For millennia tuberculosis (TB) has shown a successful strategy to survive, making it one of the world's deadliest infectious diseases. This resilient behavior is based not only on remaining hidden in most of the infected population, but also by showing slow evolution in most sick people. The course of the disease within a population is highly related to its heterogeneity. Thus, classic epidemiological approaches with a top-down perspective have not succeeded in understanding its dynamics. In the past decade a few individual-based models were built, but most of them preserved a top-down view that makes it difficult to study a heterogeneous population. We propose an individual-based model developed with a bottom-up approach to studying the dynamics of pulmonary TB in a certain population, considered constant. Individuals may belong to the following classes: healthy, infected, sick, under treatment, and treated with a probability of relapse. Several variables and parameters account for their age, origin (native or immigrant), immunodeficiency, diabetes, and other risk factors (smoking and alcoholism). The time within each infection state is controlled, and sick individuals may show a cavitated disease or not that conditions infectiousness. It was implemented in NetLogo because it allows non-modelers to perform virtual experiments with a user-friendly interface. The simulation was conducted with data from Ciutat Vella, a district of Barcelona with an incidence of 67 TB cases per 100,000 inhabitants in 2013. Several virtual experiments were performed to relate the disease dynamics with the structure of the infected subpopulation (e.g., the distribution of infected times). Moreover, the short-term effect of health control policies on modifying that structure was studied. Results show that the characteristics of the population are crucial for the local epidemiology of TB. The developed user-friendly tool is ready to test control strategies of disease in any city in the short-term.

Building A Community Focused Data and Modeling Collaborative platform with Hardware Virtualization Technology

NASA Astrophysics Data System (ADS)

Michaelis, A.; Wang, W.; Melton, F. S.; Votava, P.; Milesi, C.; Hashimoto, H.; Nemani, R. R.; Hiatt, S. H.

2009-12-01

As the length and diversity of the global earth observation data records grow, modeling and analyses of biospheric conditions increasingly requires multiple terabytes of data from a diversity of models and sensors. With network bandwidth beginning to flatten, transmission of these data from centralized data archives presents an increasing challenge, and costs associated with local storage and management of data and compute resources are often significant for individual research and application development efforts. Sharing community valued intermediary data sets, results and codes from individual efforts with others that are not in direct funded collaboration can also be a challenge with respect to time, cost and expertise. We purpose a modeling, data and knowledge center that houses NASA satellite data, climate data and ancillary data where a focused community may come together to share modeling and analysis codes, scientific results, knowledge and expertise on a centralized platform, named Ecosystem Modeling Center (EMC). With the recent development of new technologies for secure hardware virtualization, an opportunity exists to create specific modeling, analysis and compute environments that are customizable, “archiveable” and transferable. Allowing users to instantiate such environments on large compute infrastructures that are directly connected to large data archives may significantly reduce costs and time associated with scientific efforts by alleviating users from redundantly retrieving and integrating data sets and building modeling analysis codes. The EMC platform also provides the possibility for users receiving indirect assistance from expertise through prefabricated compute environments, potentially reducing study “ramp up” times.

Estimating the contribution of a service delivery organisation to the national modern contraceptive prevalence rate: Marie Stopes International's Impact 2 model

PubMed Central

2013-01-01

Background Individual family planning service delivery organisations currently rely on service provision data and couple-years of protection as health impact measures. Due to the substitution effect and the continuation of users of long-term methods, these metrics cannot estimate an organisation's contribution to the national modern contraceptive prevalence rate (CPR), the standard metric for measuring family planning programme impacts. Increasing CPR is essential for addressing the unmet need for family planning, a recognized global health priority. Current health impact estimation models cannot isolate the impact of an organisation in these efforts. Marie Stopes International designed the Impact 2 model to measure an organisation's contribution to increases in national CPR, as well as resulting health and demographic impacts. This paper aims to describe the methodology for modelling increasing national-level CPR as well as to discuss its benefits and limitations. Methods Impact 2 converts service provision data into estimates of the number of family planning users, accounting for continuation among users of long-term methods and addressing the challenges of converting commodity distribution data of short-term methods into user numbers. These estimates, combined with the client profile and data on the organisation's previous year's CPR contribution, enable Impact 2 to estimate which clients maintain an organisation's baseline contribution, which ones fulfil population growth offsets, and ultimately, which ones increase CPR. Results Illustrative results from Marie Stopes Madagascar show how Impact 2 can be used to estimate an organisation's contribution to national changes in the CPR. Conclusions Impact 2 is a useful tool for service delivery organisations to move beyond cruder output measures to a better understanding of their role in meeting the global unmet need for family planning. By considering health impact from the perspective of an individual organisation, Impact 2 addresses gaps not met by other models for family planning service outcomes. Further, the model helps organisations improve service delivery by demonstrating that increases in the national CPR are not simply about expanding user numbers; rather, the type of user (e.g. adopters, provider changers) must be considered. Impact 2 can be downloaded at http://www.mariestopes.org/impact-2. PMID:23902699

EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model

PubMed Central

2014-01-01

Background This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. Results An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. Conclusions The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues. PMID:24708668

EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model.

PubMed

Menegaldo, Luciano Luporini; de Oliveira, Liliam Fernandes; Minato, Kin K

2014-04-04

This paper describes the "EMG Driven Force Estimator (EMGD-FE)", a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. An example of the application's functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

Understanding the Effects of Users' Behaviors on Effectiveness of Different Exogenous Regulatory Common Pool Resource Management Institutions

NASA Astrophysics Data System (ADS)

Madani, K.; Dinar, A.

2013-12-01

Tragedy of the commons is generally recognized as one of the possible destinies for common pool resources (CPRs). To avoid the tragedy of the commons and prolonging the life of CPRs, users may show different behavioral characteristics and use different rationales for CPR planning and management. Furthermore, regulators may adopt different strategies for sustainable management of CPRs. The effectiveness of different regulatory exogenous management institutions cannot be evaluated through conventional CPR models since they assume that either users base their behavior on individual rationality and adopt a selfish behavior (Nash behavior), or that the users seek the system's optimal solution without giving priority to their own interests. Therefore, conventional models fail to reliably predict the outcome of CPR problems in which parties may have a range of behavioral characteristics, putting them somewhere in between the two types of behaviors traditionally considered. This work examines the effectiveness of different regulatory exogenous CPR management institutions through a user-based model (as opposed to a system-based model). The new modeling framework allows for consideration of sensitivity of the results to different behavioral characteristics of interacting CPR users. The suggested modeling approach is applied to a benchmark groundwater management problem. Results indicate that some well-known exogenous management institutions (e.g. taxing) are ineffective in sustainable management of CPRs in most cases. Bankruptcy-based management can be helpful, but determination of the fair level of cutbacks remains challenging under this type of institution. Furthermore, some bankruptcy rules such as the Constrained Equal Award (CEA) method are more beneficial to wealthier users, failing to establish social justice. Quota-based and CPR status-based management perform as the most promising and robust regulatory exogenous institutions in prolonging the CPR's life and increasing the long-term benefits to its users.

A social network-informed latent class analysis of patterns of substance use, sexual behavior, and mental health: Social Network Study III, Winnipeg, Manitoba, Canada.

PubMed

Hopfer, Suellen; Tan, Xianming; Wylie, John L

2014-05-01

We assessed whether a meaningful set of latent risk profiles could be identified in an inner-city population through individual and network characteristics of substance use, sexual behaviors, and mental health status. Data came from 600 participants in Social Network Study III, conducted in 2009 in Winnipeg, Manitoba, Canada. We used latent class analysis (LCA) to identify risk profiles and, with covariates, to identify predictors of class. A 4-class model of risk profiles fit the data best: (1) solitary users reported polydrug use at the individual level, but low probabilities of substance use or concurrent sexual partners with network members; (2) social-all-substance users reported polydrug use at the individual and network levels; (3) social-noninjection drug users reported less likelihood of injection drug and solvent use; (4) low-risk users reported low probabilities across substances. Unstable housing, preadolescent substance use, age, and hepatitis C status predicted risk profiles. Incorporation of social network variables into LCA can distinguish important subgroups with varying patterns of risk behaviors that can lead to sexually transmitted and bloodborne infections.

Interactive computation of coverage regions for indoor wireless communication

NASA Astrophysics Data System (ADS)

Abbott, A. Lynn; Bhat, Nitin; Rappaport, Theodore S.

1995-12-01

This paper describes a system which assists in the strategic placement of rf base stations within buildings. Known as the site modeling tool (SMT), this system allows the user to display graphical floor plans and to select base station transceiver parameters, including location and orientation, interactively. The system then computes and highlights estimated coverage regions for each transceiver, enabling the user to assess the total coverage within the building. For single-floor operation, the user can choose between distance-dependent and partition- dependent path-loss models. Similar path-loss models are also available for the case of multiple floors. This paper describes the method used by the system to estimate coverage for both directional and omnidirectional antennas. The site modeling tool is intended to be simple to use by individuals who are not experts at wireless communication system design, and is expected to be very useful in the specification of indoor wireless systems.

LANDFILL GAS EMISSIONS MODEL (LANDGEM) VERSION 3.02 USER'S GUIDE

EPA Science Inventory

The Landfill Gas Emissions Model (LandGEM) is an automated estimation tool with a Microsoft Excel interface that can be used to estimate emission rates for total landfill gas, methane, carbon dioxide, nonmethane organic compounds, and individual air pollutants from municipal soli...

A Chemical Properties Simulator to Support Integrated Environmental Modeling (proceeding)

EPA Science Inventory

Users of Integrated Environmental Modeling (IEM) systems are responsible for defining individual chemicals and their properties, a process that is time-consuming at best and overwhelming at worst, especially for new chemicals with new structures. A software tool is needed to allo...

Microcomputers, Model Rockets, and Race Cars.

ERIC Educational Resources Information Center

Mirus, Edward A., Jr.

1985-01-01

The industrial education orientation program at Wisconsin School for the Deaf (WSD) presents problem-solving situations to all seventh- and eighth-grade hearing-impaired students. WSD developed user-friendly microcomputer software to guide students individually through complex computations involving model race cars and rockets while freeing…

A Guide to Computer Simulations of Three Adaptive Instructional Models for the Advanced Instructional System Phases II and III. Final Report.

ERIC Educational Resources Information Center

Hansen, Duncan N.; And Others

Computer simulations of three individualized adaptive instructional models (AIM) were undertaken to determine if these models function as prescribed in Air Force technical training programs. In addition, the project sought to develop a user's guide for effective understanding of adaptive models during field implementation. Successful simulations…

JEDI Transmission Line Model | Jobs and Economic Development Impact Models

Science.gov Websites

, reasonable default values are provided. Individual projects may vary and when possible, project specific data Line Model rel. TL12.23.16. JEDI Transmission Line Model User Reference Guide Using MS Excel 2007 When ;High." Set the level to "Medium" or "Low" and then re-open the JEDI worksheet

A User’s Guide for the Software Technology Economic Impact Model

DTIC Science & Technology

1991-10-01

Copy 16 oft22 oples U AD-A248 023 \\\\1\\\\\\i\\~\\1\\1\\\\1\\1\\11\\\\\\l~ IDA DOCUMENT D-971 E Tt USER’S GUIDE FOR THE SOFTWARE TECHNOLOGY ECONOMIC IMPACT MODEL I... studied , and they are released by the President of IDA. Group Reports Group Reports record the findings and results of IDA established working groups and...the senior individuals responsible for the project and others as selected by IDA to ensure their high quality and relevance to the problems studied

Evaluating the success of an emergency response medical information system.

PubMed

Petter, Stacie; Fruhling, Ann

2011-07-01

STATPack™ is an information system used to aid in the diagnosis of pathogens in hospitals and state public health laboratories. STATPack™ is used as a communication and telemedicine diagnosis tool during emergencies. This paper explores the success of this emergency response medical information system (ERMIS) using a well-known framework of information systems success developed by DeLone and McLean. Using an online survey, the entire population of STATPack™ users evaluated the success of the information system by considering system quality, information quality, system use, intention to use, user satisfaction, individual impact, and organizational impact. The results indicate that the overall quality of this ERMIS (i.e., system quality, information quality, and service quality) has a positive impact on both user satisfaction and intention to use the system. However, given the nature of ERMIS, overall quality does not necessarily predict use of the system. Moreover, the user's satisfaction with the information system positively affected the intention to use the system. User satisfaction, intention to use, and system use had a positive influence on the system's impact on the individual. Finally, the organizational impacts of the system were positively influenced by use of the system and the system's individual impact on the user. The results of the study demonstrate how to evaluate the success of an ERMIS as well as introduce potential changes in how one applies the DeLone and McLean success model in an emergency response medical information system context. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Regional Atmospheric Transport Code for Hanford Emission Tracking (RATCHET). Hanford Environmental Dose Reconstruction Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramsdell, J.V. Jr.; Simonen, C.A.; Burk, K.W.

1994-02-01

The purpose of the Hanford Environmental Dose Reconstruction (HEDR) Project is to estimate radiation doses that individuals may have received from operations at the Hanford Site since 1944. This report deals specifically with the atmospheric transport model, Regional Atmospheric Transport Code for Hanford Emission Tracking (RATCHET). RATCHET is a major rework of the MESOILT2 model used in the first phase of the HEDR Project; only the bookkeeping framework escaped major changes. Changes to the code include (1) significant changes in the representation of atmospheric processes and (2) incorporation of Monte Carlo methods for representing uncertainty in input data, model parameters,more » and coefficients. To a large extent, the revisions to the model are based on recommendations of a peer working group that met in March 1991. Technical bases for other portions of the atmospheric transport model are addressed in two other documents. This report has three major sections: a description of the model, a user`s guide, and a programmer`s guide. These sections discuss RATCHET from three different perspectives. The first provides a technical description of the code with emphasis on details such as the representation of the model domain, the data required by the model, and the equations used to make the model calculations. The technical description is followed by a user`s guide to the model with emphasis on running the code. The user`s guide contains information about the model input and output. The third section is a programmer`s guide to the code. It discusses the hardware and software required to run the code. The programmer`s guide also discusses program structure and each of the program elements.« less

Evaluation of a Physiologically Based Pharmacokinetic (PBPK) Model Used to Develop Health Protective Levels for Trichloroethylene

DTIC Science & Technology

2017-02-28

is the response variable resulting from an input parameter value of θ+. EPA (2011) used a variation of this equation to calculate their...EPA (2011) used both individual and grouped data. While individual data are preferred as it maintains any intra-individual variation , it is often...grouped data, the user would, ideally, account for the loss of intra-individual variation in some manner; however, there is not a commonly accepted

Equivalent ZF precoding scheme for downlink indoor MU-MIMO VLC systems

NASA Astrophysics Data System (ADS)

Fan, YangYu; Zhao, Qiong; Kang, BoChao; Deng, LiJun

2018-01-01

In indoor visible light communication (VLC) systems, the channels of photo detectors (PDs) at one user are highly correlated, which determines the choice of spatial diversity model for individual users. In a spatial diversity model, the signals received by PDs belonging to one user carry the same information, and can be combined directly. Based on the above, we propose an equivalent zero-forcing (ZF) precoding scheme for multiple-user multiple-input single-output (MU-MIMO) VLC systems by transforming an indoor MU-MIMO VLC system into an indoor multiple-user multiple-input single-output (MU-MISO) VLC system through simply processing. The power constraints of light emitting diodes (LEDs) are also taken into account. Comprehensive computer simulations in three scenarios indicate that our scheme can not only reduce the computational complexity, but also guarantee the system performance. Furthermore, the proposed scheme does not require noise information in the calculating of the precoding weights, and has no restrictions on the numbers of APs and PDs.

Modeling users' activity on Twitter networks: validation of Dunbar's number

NASA Astrophysics Data System (ADS)

Goncalves, Bruno; Perra, Nicola; Vespignani, Alessandro

2012-02-01

Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100-200 stable relationships. Thus, the ``economy of attention'' is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior.

NUNOA: a computer simulator of individuals, families, and extended families of the high-altitude Quechua

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brandt, C.C.; Weinstein, D.A.; Shugart, H.H.

1980-10-01

The Quechua Indians of the Peruvian Andes are an example of a human population which has developed special cultural adaptations to deal with hypocaloric stress imposed by a harsh environment. A highly detailed human ecosystem model, NUNOA, which simulates the yearly energy balance of individuals, families, and extended families in a hypothetical farming and herding Quechua community of the high Andes was developed. Unlike most population models which use sets of differential equations in which individuals are aggregated into groups, this model considers the response of each individual to a stochastic environment. The model calculates the yearly energy demand formore » each family based on caloric requirements of its members. For each family, the model simulates the cultivation of seven different crops and the impact of precipitation, temperature, and disease on yield. Herding, slaughter, and market sales of three different animal species are also simulated. Any energy production in excess of the family's energy demand is placed into extended family storage for possible redistribution. A family failing to meet their annual energy demand may slaughter additional herd animals, temporarily migrate from the community, or borrow food from the extended family storage. The energy balance is used in determining births, deaths, marriages, and resource sharing in the Indian community. In addition, the model maintains a record of each individual's ancestry as well as seven genetic traits for use in tracing lineage and gene flow. The model user has the opportunity to investigate the effect of changes in marriage patterns, resource sharing patterns, or subsistence activities on the ability of the human population to survive in the harsh Andean environment. In addition, the user may investigate the impact of external technology on the Indian culture.« less

AXAOTHER XL -- A spreadsheet for determining doses for incidents caused by tornadoes or high-velocity straight winds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simpkins, A.A.

1996-09-01

AXAOTHER XL is an Excel Spreadsheet used to determine dose to the maximally exposed offsite individual during high-velocity straight winds or tornado conditions. Both individual and population doses may be considered. Potential exposure pathways are inhalation and plume shine. For high-velocity straight winds the spreadsheet has the capability to determine the downwind relative air concentration, however for the tornado conditions, the user must enter the relative air concentration. Theoretical models are discussed and hand calculations are performed to ensure proper application of methodologies. A section has also been included that contains user instructions for the spreadsheet.

Development and usability testing of a web-based decision support for users and health professionals in psychiatric services.

PubMed

Grim, Katarina; Rosenberg, David; Svedberg, Petra; Schön, Ulla-Karin

2017-09-01

Shared decision making (SMD) related to treatment and rehabilitation is considered a central component in recovery-oriented practice. Although decision aids are regarded as an essential component for successfully implementing SDM, these aids are often lacking within psychiatric services. The aim of this study was to use a participatory design to facilitate the development of a user-generated, web-based decision aid for individuals receiving psychiatric services. The results of this effort as well as the lessons learned during the development and usability processes are reported. The participatory design included 4 iterative cycles of development. Various qualitative methods for data collection were used with potential end users participating as informants in focus group and individual interviews and as usability and pilot testers. Interviewing and testing identified usability problems that then led to refinements and making the subsequent prototypes increasingly user-friendly and relevant. In each phase of the process, feedback from potential end-users provided guidance in developing the formation of the web-based decision aid that strengthens the position of users by integrating access to information regarding alternative supports, interactivity between staff and users, and user preferences as a continual focus in the tool. This web-based decision aid has the potential to strengthen service users' experience of self-efficacy and control as well as provide staff access to user knowledge and preferences. Studies employing participatory models focusing on usability have potential to significantly contribute to the development and implementation of tools that reflect user perspectives. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Smart Meter Driven Segmentation: What Your Consumption Says About You

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albert, A; Rajagopal, R

With the rollout of smart metering infrastructure at scale, demand-response (DR) programs may now be tailored based on users' consumption patterns as mined from sensed data. For issuing DR events it is key to understand the inter-temporal consumption dynamics as to appropriately segment the user population. We propose to infer occupancy states from consumption time series data using a hidden Markov model framework. Occupancy is characterized in this model by 1) magnitude, 2) duration, and 3) variability. We show that users may be grouped according to their consumption patterns into groups that exhibit qualitatively different dynamics that may be exploitedmore » for program enrollment purposes. We investigate empirically the information that residential energy consumers' temporal energy demand patterns characterized by these three dimensions may convey about their demographic, household, and appliance stock characteristics. Our analysis shows that temporal patterns in the user's consumption data can predict with good accuracy certain user characteristics. We use this framework to argue that there is a large degree of individual predictability in user consumption at a population level.« less

iCARE

Cancer.gov

The iCARE R Package allows researchers to quickly build models for absolute risk, and apply them to estimate an individual's risk of developing disease during a specifed time interval, based on a set of user defined input parameters.

Medical homes versus individual practice in primary care: impact on health care expenditures.

PubMed

Perelman, Julian; Roch, Isabelle; Heymans, Isabelle; Moureaux, Catherine; Lagasse, Raphael; Annemans, Lieven; Closon, Marie-Christine

2013-08-01

The medical home (MH) model has prompted increasing attention given its potential to improve quality of care while reducing health expenditures. We compare overall and specific health care expenditures in Belgium, from the third-party payer perspective (compulsory social insurance), between patients treated at individual practices (IP) and at MHs. We compare the sociodemographic profile of MH and IP users. This is a retrospective study using public insurance claims data. Generalized linear models estimate the impact on health expenditures of being treated at a MH versus IP, controlling for individual, and area-based sociodemographic characteristics. The choice of primary care setting is modeled using logistic regressions. A random sample of 43,678 persons followed during the year 2004. Third-party payer expenditures for primary care, secondary care consultations, pharmaceuticals, laboratory tests, acute and long-term inpatient care. Overall third-party payer expenditures do not differ significantly between MH and IP users (€+27). Third-party payer primary care expenditures are higher for MH than for IP users (€+129), but this difference is offset by lower expenditures for secondary care consultations (€-11), drugs (€-40), laboratory tests (€-5) and acute and long-term inpatient care (€-53). MHs attract younger and more underprivileged populations. MHs induce a shift in expenditures from secondary care, drugs, and laboratory tests to primary care, while treating a less economically favored population. Combined with positive results regarding quality, MH structures are a promising way to tackle the challenges of primary care.

Information system success model for customer relationship management system in health promotion centers.

PubMed

Choi, Wona; Rho, Mi Jung; Park, Jiyun; Kim, Kwang-Jum; Kwon, Young Dae; Choi, In Young

2013-06-01

Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. THE EVALUATION AREAS OF THE CRM SYSTEM INCLUDES THREE AREAS: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems.

Information System Success Model for Customer Relationship Management System in Health Promotion Centers

PubMed Central

Choi, Wona; Rho, Mi Jung; Park, Jiyun; Kim, Kwang-Jum; Kwon, Young Dae

2013-01-01

Objectives Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. Methods The evaluation areas of the CRM system includes three areas: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. Results Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. Conclusions This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems. PMID:23882416

Adaptive rehabilitation gaming system: on-line individualization of stroke rehabilitation.

PubMed

Nirme, Jens; Duff, Armin; Verschure, Paul F M J

2011-01-01

The effects of stroke differ considerably in degree and symptoms for different patients. It has been shown that specific, individualized and varied therapy favors recovery. The Rehabilitation Gaming System (RGS) is a Virtual Reality (VR) based rehabilitation system designed following these principles. We have developed two algorithms to control the level of task difficulty that a user of the RGS is exposed to, as well as providing controlled variation in the therapy. In this paper, we compare the two algorithms by running numerical simulations and a study with healthy subjects. We show that both algorithms allow for individualization of the challenge level of the task. Further, the results reveal that the algorithm that iteratively learns a user model for each subject also allows a high variation of the task.

A user-oriented and computerized model for estimating vehicle ride quality

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Barker, L. M.

1984-01-01

A simplified empirical model and computer program for estimating passenger ride comfort within air and surface transportation systems are described. The model is based on subjective ratings from more than 3000 persons who were exposed to controlled combinations of noise and vibration in the passenger ride quality apparatus. This model has the capability of transforming individual elements of a vehicle's noise and vibration environment into subjective discomfort units and then combining the subjective units to produce a single discomfort index typifying passenger acceptance of the environment. The computational procedures required to obtain discomfort estimates are discussed, and a user oriented ride comfort computer program is described. Examples illustrating application of the simplified model to helicopter and automobile ride environments are presented.

IASM: Individualized activity space modeler

NASA Astrophysics Data System (ADS)

Hasanzadeh, Kamyar

2018-01-01

Researchers from various disciplines have long been interested in analyzing and describing human mobility patterns. Activity space (AS), defined as an area encapsulating daily human mobility and activities, has been at the center of this interest. However, given the applied nature of research in this field and the complexity that advanced geographical modeling can pose to its users, the proposed models remain simplistic and inaccurate in many cases. Individualized Activity Space Modeler (IASM) is a geographic information system (GIS) toolbox, written in Python programming language using ESRI's Arcpy module, comprising four tools aiming to facilitate the use of advanced activity space models in empirical research. IASM provides individual-based and context-sensitive tools to estimate home range distances, delineate activity spaces, and model place exposures using individualized geographical data. In this paper, we describe the design and functionality of IASM, and provide an example of how it performs on a spatial dataset collected through an online map-based survey.

Loneliness and Shyness in Adolescent Problematic Internet Users: The Role of Social Anxiety

ERIC Educational Resources Information Center

Huan, Vivien S.; Ang, Rebecca P.; Chye, Stefanie

2014-01-01

Background: Davis' ("Comput Hum Behav" 17:187-195, 2001) cognitive-behavioral model of problematic Internet use (PIU) proposed and theorized that certain psychopathological characteristics present within an individual, predispose him to PIU. Objective: This study extended Davis' model in hypothesizing that social anxiety mediates in a…

Multilevel Evaluation Systems Project. Final Report.

ERIC Educational Resources Information Center

Herman, Joan L.

Several studies were conducted in 1987 by the Multilevel Evaluation Systems Project, which focuses on developing a model for a multi-purpose, multi-user evaluation system to facilitate educational decision making and evaluation. The project model emphasizes on-going integrated assessment of individuals, classes, and programs using a variety of…

End users transforming experiences into formal information and process models for personalised health interventions.

PubMed

Lindgren, Helena; Lundin-Olsson, Lillemor; Pohl, Petra; Sandlund, Marlene

2014-01-01

Five physiotherapists organised a user-centric design process of a knowledge-based support system for promoting exercise and preventing falls. The process integrated focus group studies with 17 older adults and prototyping. The transformation of informal medical and rehabilitation expertise and older adults' experiences into formal information and process models during the development was studied. As tool they used ACKTUS, a development platform for knowledge-based applications. The process became agile and incremental, partly due to the diversity of expectations and preferences among both older adults and physiotherapists, and the participatory approach to design and development. In addition, there was a need to develop the knowledge content alongside with the formal models and their presentations, which allowed the participants to test hands-on and evaluate the ideas, content and design. The resulting application is modular, extendable, flexible and adaptable to the individual end user. Moreover, the physiotherapists are able to modify the information and process models, and in this way further develop the application. The main constraint was found to be the lack of support for the initial phase of concept modelling, which lead to a redesigned user interface and functionality of ACKTUS.

CDFISH: an individual-based, spatially-explicit, landscape genetics simulator for aquatic species in complex riverscapes

USGS Publications Warehouse

Erin L. Landguth,; Muhlfeld, Clint C.; Luikart, Gordon

2012-01-01

We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k-allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.

Modeling the heterogeneity of human dynamics based on the measurements of influential users in Sina Microblog

NASA Astrophysics Data System (ADS)

Wang, Chenxu; Guan, Xiaohong; Qin, Tao; Yang, Tao

2015-06-01

Online social network has become an indispensable communication tool in the information age. The development of microblog also provides us a great opportunity to study human dynamics that play a crucial role in the design of efficient communication systems. In this paper we study the characteristics of the tweeting behavior based on the data collected from Sina Microblog. The user activity level is measured to characterize how often a user posts a tweet. We find that the user activity level follows a bimodal distribution. That is, the microblog users tend to be either active or inactive. The inter-tweeting time distribution is then measured at both the aggregate and individual levels. We find that the inter-tweeting time follows a piecewise power law distribution of two tails. Furthermore, the exponents of the two tails have different correlations with the user activity level. These findings demonstrate that the dynamics of the tweeting behavior are heterogeneous in different time scales. We then develop a dynamic model co-driven by the memory and the interest mechanism to characterize the heterogeneity. The numerical simulations validate the model and verify that the short time interval tweeting behavior is driven by the memory mechanism while the long time interval behavior by the interest mechanism.

Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case

PubMed Central

Li, Guowei; Thabane, Lehana; Delate, Thomas; Witt, Daniel M.; Levine, Mitchell A. H.; Cheng, Ji; Holbrook, Anne

2016-01-01

Objectives To construct and validate a prediction model for individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both) in patients with atrial fibrillation (AF) with and without warfarin therapy. Methods Using the Kaiser Permanente Colorado databases, we included patients newly diagnosed with AF between January 1, 2005 and December 31, 2012 for model construction and validation. The primary outcome was a prediction model of composite of stroke or major bleeding using polytomous logistic regression (PLR) modelling. The secondary outcome was a prediction model of all-cause mortality using the Cox regression modelling. Results We included 9074 patients with 4537 and 4537 warfarin users and non-users, respectively. In the derivation cohort (n = 4632), there were 136 strokes (2.94%), 280 major bleedings (6.04%) and 1194 deaths (25.78%) occurred. In the prediction models, warfarin use was not significantly associated with risk of stroke, but increased the risk of major bleeding and decreased the risk of death. Both the PLR and Cox models were robust, internally and externally validated, and with acceptable model performances. Conclusions In this study, we introduce a new methodology for predicting individual combined benefit and harm outcomes associated with warfarin therapy for patients with AF. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches as a patient-physician aid for shared decision-making PMID:27513986

User's Guide for Mixed-Size Sediment Transport Model for Networks of One-Dimensional Open Channels

USGS Publications Warehouse

Bennett, James P.

2001-01-01

This user's guide describes a mathematical model for predicting the transport of mixed sizes of sediment by flow in networks of one-dimensional open channels. The simulation package is useful for general sediment routing problems, prediction of erosion and deposition following dam removal, and scour in channels at road embankment crossings or other artificial structures. The model treats input hydrographs as stepwise steady-state, and the flow computation algorithm automatically switches between sub- and supercritical flow as dictated by channel geometry and discharge. A variety of boundary conditions including weirs and rating curves may be applied both external and internal to the flow network. The model may be used to compute flow around islands and through multiple openings in embankments, but the network must be 'simple' in the sense that the flow directions in all channels can be specified before simulation commences. The location and shape of channel banks are user specified, and all bedelevation changes take place between these banks and above a user-specified bedrock elevation. Computation of sediment-transport emphasizes the sand-size range (0.0625-2.0 millimeter) but the user may select any desired range of particle diameters including silt and finer (<0.0625 millimeter). As part of data input, the user may set the original bed-sediment composition of any number of layers of known thickness. The model computes the time evolution of total transport and the size composition of bed- and suspended-load sand through any cross section of interest. It also tracks bed -surface elevation and size composition. The model is written in the FORTRAN programming language for implementation on personal computers using the WINDOWS operating system and, along with certain graphical output display capability, is accessed from a graphical user interface (GUI). The GUI provides a framework for selecting input files and parameters of a number of components of the sediment-transport process. There are no restrictions in the use of the model as to numbers of channels, channel junctions, cross sections per channel, or points defining the cross sections. Following completion of the simulation computations, the GUI accommodates display of longitudinal plots of either bed elevation and size composition, or of transport rate and size composition of the various components, for individual channels and selected times during the simulation period. For individual cross sections, the GUI also allows display of time series of transport rate and size composition of the various components and of bed elevation and size composition.

An assisted navigation training framework based on judgment theory using sparse and discrete human-machine interfaces.

PubMed

Lopes, Ana C; Nunes, Urbano

2009-01-01

This paper aims to present a new framework to train people with severe motor disabilities steering an assisted mobile robot (AMR), such as a powered wheelchair. Users with high level of motor disabilities are not able to use standard HMIs, which provide a continuous command signal (e. g. standard joystick). For this reason HMIs providing a small set of simple commands, which are sparse and discrete in time must be used (e. g. scanning interface, or brain computer interface), making very difficult to steer the AMR. In this sense, the assisted navigation training framework (ANTF) is designed to train users driving the AMR, in indoor structured environments, using this type of HMIs. Additionally it provides user characterization on steering the robot, which will later be used to adapt the AMR navigation system to human competence steering the AMR. A rule-based lens (RBL) model is used to characterize users on driving the AMR. Individual judgment performance choosing the best manoeuvres is modeled using a genetic-based policy capturing (GBPC) technique characterized to infer non-compensatory judgment strategies from human decision data. Three user models, at three different learning stages, using the RBL paradigm, are presented.

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. PMID:27918593

VISION User Guide - VISION (Verifiable Fuel Cycle Simulation) Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacob J. Jacobson; Robert F. Jeffers; Gretchen E. Matthern

2009-08-01

The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an R&D work in progress and may contain errors and omissions. It is based upon numerous assumptions. This model is intended to assist in evaluating “what if” scenarios and in comparing fuel, reactor, and fuel processing alternatives at a systems level for U.S. nuclear power. The model is not intendedmore » as a tool for process flow and design modeling of specific facilities nor for tracking individual units of fuel or other material through the system. The model is intended to examine the interactions among the components of a fuel system as a function of time varying system parameters; this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., “reactor types” not individual reactors and “separation types” not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, and depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation of disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. Note that recovered uranium is itself often partitioned: some RU flows with recycled transuranic elements, some flows with wastes, and the rest is designated RU. RU comes out of storage if needed to correct the U/TRU ratio in new recycled fuel. Neither RU nor DU are designated as wastes. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. We use Microsoft Excel 2003 and have not tested VISION with Microsoft Excel 2007. The VISION team uses both Powersim Studio 2005 and 2009 and it should work with either.« less

User-driven health care: answering multidimensional information needs in individual patients utilizing post-EBM approaches: an operational model.

PubMed

Biswas, Rakesh; Maniam, Jayanthy; Lee, Edwin Wen Huo; Gopal, Premalatha; Umakanth, Shashikiran; Dahiya, Sumit; Ahmed, Sayeed

2008-10-01

The hypothesis in the conceptual model was that a user-driven innovation in presently available information and communication technology infrastructure would be able to meet patient and health professional users information needs and help them attain better health outcomes. An operational model was created to plan a trial on a sample diabetic population utilizing a randomized control trial design, assigning one randomly selected group of diabetics to receive electronic information intervention and analyse if it would improve their health outcomes in comparison with a matched diabetic population who would only receive regular medical intervention. Diabetes was chosen for this particular trial, as it is a major chronic illness in Malaysia as elsewhere in the world. It is in essence a position paper for how the study concept should be organized to stimulate wider discussion prior to beginning the study.

Controlling user access to electronic resources without password

DOEpatents

Smith, Fred Hewitt

2017-08-22

Described herein are devices and techniques for remotely controlling user access to a restricted computer resource. The process includes obtaining an image from a communication device of a user. An individual and a landmark are identified within the image. Determinations are made that the individual is the user and that the landmark is a predetermined landmark. Access to a restricted computing resource is granted based on the determining that the individual is the user and that the landmark is the predetermined landmark. Other embodiments are disclosed.

A 5-year follow-up study of users of benzodiazepine: starting with diazepam versus oxazepam.

PubMed

Tvete, Ingunn Fride; Bjørner, Trine; Skomedal, Tor

2016-04-01

Drug dependency may develop during long-term benzodiazepine use, indicated, for example, by dose escalation. The first benzodiazepine chosen may affect the risk of dose escalation. To detect possible differences in benzodiazepine use between new users of diazepam and oxazepam over time. This 5-year prescription database study included 19 747 new benzodiazepine users, inhabitants of Norway, aged 30-60 years, with first redemption for diazepam or oxazepam. Individuals starting on diazepam versus oxazepam were analysed by logistic regression with sex, age, other drug redemptions, prescriber's specialty, household income, education level, type of work, and vocational rehabilitation support as background variables. Time to reach a daily average intake of ≥1 defined daily doses (DDD) over a 3-month period was analysed using a Cox proportional hazard regression model. New users of oxazepam had a higher risk for dose escalation compared with new users of diazepam. This was true even when accounting for differences in sociodemographic status and previous drug use (hazard ratio [HR] 1.33, 95% confidence interval = 1.17 to 1.51). Most doctors prescribed, according to recommendations, oxazepam to individuals they may have regarded as prone to and at risk of dependency. However, these individuals were at higher risk for dose escalation even when accounting for differences in sociodemographic status and previous drug use. Differences between the two user groups could be explained by different preferences for starting drug, DDD for oxazepam being possibly too low, and some unaccounted differences in illness. © British Journal of General Practice 2016.

Play-Personas: Behaviours and Belief Systems in User-Centred Game Design

NASA Astrophysics Data System (ADS)

Canossa, Alessandro; Drachen, Anders

Game designers attempt to ignite affective, emotional responses from players via engineering game designs to incite definite user experiences. Theories of emotion state that definite emotional responses are individual, and caused by the individual interaction sequence or history. Engendering desired emotions in the audience of traditional audiovisual media is a considerable challenge; however it is potentially even more difficult to achieve the same goal for the audience of interactive entertainment, because a substantial degree of control rests in the hand of the end user rather than the designer. This paper presents a possible solution to the challenge of integrating the user in the design of interactive entertainment such as computer games by employing the "persona" framework introduced by Alan Cooper. This approach is already in use in interaction design. The method can be improved by complementing the traditional narrative description of personas with quantitative, data-oriented models of predicted patterns of user behaviour for a specific computer game Additionally, persona constructs can be applied both as design-oriented metaphors during the development of games, and as analytical lenses to existing games, e.g. for evaluation of patterns of player behaviour.

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

PubMed

Soysal, Ergin; Wang, Jingqi; Jiang, Min; Wu, Yonghui; Pakhomov, Serguei; Liu, Hongfang; Xu, Hua

2017-11-24

Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The TENCompetence Infrastructure: A Learning Network Implementation

NASA Astrophysics Data System (ADS)

Vogten, Hubert; Martens, Harrie; Lemmers, Ruud

The TENCompetence project developed a first release of a Learning Network infrastructure to support individuals, groups and organisations in professional competence development. This infrastructure Learning Network infrastructure was released as open source to the community thereby allowing users and organisations to use and contribute to this development as they see fit. The infrastructure consists of client applications providing the user experience and server components that provide the services to these clients. These services implement the domain model (Koper 2006) by provisioning the entities of the domain model (see also Sect. 18.4) and henceforth will be referenced as domain entity services.

Measuring mobile patient safety information system success: an empirical study.

PubMed

Jen, Wen-Yuan; Chao, Chia-Cheng

2008-10-01

The Health Risk Reminders and Surveillance (HRRS) system was designed to deliver critical abnormal test results of severely ill patients from Laboratory, Radiology, and Pathology departments to physicians within 5 min using cell phone text messages. This paper explores the success of the HRRS system. This study employed an augmented version of the DeLone and McLean IS success model. Seven variables (system quality, information quality, system use, user satisfaction, mobile healthcare anxiety, impact on the individual and impact on the organization) were used to evaluate the success of the HRRS system. The interrelationships between the seven variables were hypothesized and the hypotheses were empirically tested. The results indicate that the information quality of the HRRS system is positively associated with both system use and user satisfaction. In addition, system use is positively associated with user satisfaction, which is also positively associated with mobile healthcare anxiety. Moreover, results indicate that impact on the individual is positively associated with both user satisfaction and mobile healthcare anxiety. Finally, the impact of the organization is positively associated with impact on the individual. The results of the study provide an expanded understanding of the factors that contribute to mobile patient safety information system (IS) success. Implications of the relationship between system use and physician mobile healthcare anxiety are discussed.

Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number

PubMed Central

Gonçalves, Bruno; Perra, Nicola; Vespignani, Alessandro

2011-01-01

Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100–200 stable relationships. Thus, the ‘economy of attention’ is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior. PMID:21826200

Service user involvement in mental health system strengthening in a rural African setting: qualitative study.

PubMed

Abayneh, Sisay; Lempp, Heidi; Alem, Atalay; Alemayehu, Daniel; Eshetu, Tigist; Lund, Crick; Semrau, Maya; Thornicroft, Graham; Hanlon, Charlotte

2017-05-18

It is essential to involve service users in efforts to expand access to mental health care in integrated primary care settings in low- and middle-income countries (LMICs). However, there is little evidence from LMICs to guide this process. The aim of this study was to explore barriers to, and facilitators of, service user/caregiver involvement in rural Ethiopia to inform the development of a scalable approach. Thirty nine semi-structured interviews were carried out with purposively selected mental health service users (n = 13), caregivers (n = 10), heads of primary care facilities (n = 8) and policy makers/planners/service developers (n = 8). The interviews were audio-recorded and transcribed in Amharic, and translated into English. Thematic analysis was applied. All groups of participants supported service user and caregiver involvement in mental health system strengthening. Potential benefits were identified as (i) improved appropriateness and quality of services, and (ii) greater protection against mistreatment and promotion of respect for service users. However, hardly any respondents had prior experience of service user involvement. Stigma was considered to be a pervasive barrier, operating within the health system, the local community and individuals. Competing priorities of service users included the need to obtain adequate individual care and to work for survival. Low recognition of the potential contribution of service users seemed linked to limited empowerment and mobilization of service users. Potential health system facilitators included a culture of community oversight of primary care services. All groups of respondents identified a need for awareness-raising and training to equip service users, caregivers, service providers and local community for involvement. Empowerment at the level of individual service users (information about mental health conditions, care and rights) and the group level (for advocacy and representation) were considered essential, alongside improved, accessible mental health care and livelihood interventions. As Ethiopia increases access to mental health care, a fundamental barrier to service user involvement is beginning to be addressed. Our study identified further barriers that need to be tackled, including a supportive political climate, and receptiveness amongst stakeholders. The findings will inform the development of a model of service user involvement, which will be piloted and evaluated.

An Analysis of Internet Addiction Levels of Individuals according to Various Variables

ERIC Educational Resources Information Center

Sahin, Cengiz

2011-01-01

The concept of internet addiction refers to the excessive use of internet which in turn causes various problems in individual, social and professional aspects. The aim of this study was to determine internet addiction levels of internet users from all age groups. The study used survey model. Study group of the study consisted of a total of 596…

Cannabis use and symptom severity in individuals at ultra high risk for psychosis: a meta-analysis.

PubMed

Carney, R; Cotter, J; Firth, J; Bradshaw, T; Yung, A R

2017-07-01

We aimed to assess whether individuals at ultra high risk (UHR) for psychosis have higher rates of cannabis use and cannabis use disorders (CUDs) than non-UHR individuals and determine whether UHR cannabis users have more severe psychotic experiences than non-users. We conducted a meta-analysis of studies reporting cannabis use in the UHR group and/or positive or negative symptoms among UHR cannabis users and non-users. Logit event rates were calculated for cannabis use, in addition to odds ratios to assess the difference between UHR and controls. Severity of clinical symptoms in UHR cannabis users and non-users was compared using Hedges' g. Thirty unique studies were included (UHR n = 4205, controls n = 667) containing data from cross-sectional and longitudinal studies, and randomised control trials. UHR individuals have high rates of current (26.7%) and lifetime (52.8%) cannabis use, and CUDs (12.8%). Lifetime use and CUDs were significantly higher than controls (lifetime OR: 2.09; CUD OR: 5.49). UHR cannabis users had higher rates of unusual thought content and suspiciousness than non-users. Ultra high risk individuals have high rates of cannabis use and CUDs, and cannabis users had more severe positive symptoms. Targeting substance use during the UHR phase may have significant benefits to an individual's long-term outcome. © 2017 The Authors Acta Psychiatrica Scandinavica Published by John Wiley & Sons Ltd.

The user's guide to STEMS (Stand and Tree Evaluation and Modeling System).

Treesearch

David M. Belcher

1981-01-01

Presents the structure of STEMS, a computer program for projecting growth of individual trees within the Lake States Region, and discusses its input, processing, major subsystems, and output. Includes an example projection.

Design Support System for Coloring Illustrations by Using the Colors Preferred by a User as Determined from the Hue Patterns of Illustrations Prepared by that User

NASA Astrophysics Data System (ADS)

Fukai, Hironobu; Mitsukura, Yasue

We propose a new design support system that can color illustrations according to a person's color preferences that are determined on the basis of the color patterns of illustrations prepared by that person. Recently, many design tools for promoting free design have been developed. However, preferences for various colors differ depending on individual personality. Therefore, a system that can automatically color various designs on the basis of human preference is required. In this study, we propose an automatic modeling system that can be used to model illustrations. To verify the effectiveness of the proposed system, we simulate a coloring design experiment to determine the color patterns preferred by some subjects by using various design data. By using the design data, we determine each subjects preferred color pattern, and send feedback on these individual color patterns to the proposed system.

Redefining the bureaucratic encounter between service providers and service users: evidence from the Norwegian HUSK projects.

PubMed

Carnochan, Sarah; Austin, Michael J

2015-01-01

The HUSK projects, involving collaboration between service users, providers, educators, and researchers, coincided with the reorganization of national government services (NAV). The NAV reorganization brought together employment services, social insurance, and municipal social service benefits, and called for a service model where users would be empowered to influence the provision of services. In this analysis of the HUSK cases the authors focus on the relationship between the service user and the service provider, identifying themes in two broad domains: concepts of the individual that included the service user and the service provider and concepts of the relationship that included power, role, activity, interaction, and communication. Within each theme, the analysis highlights the transition from a traditional or historical state to a new or desired state and draws upon some of the classic literature that frames the encounters between service users and providers.

Vulnerability- and Diversity-Aware Anonymization of Personally Identifiable Information for Improving User Privacy and Utility of Publishing Data.

PubMed

Majeed, Abdul; Ullah, Farman; Lee, Sungchang

2017-05-08

Personally identifiable information (PII) affects individual privacy because PII combinations may yield unique identifications in published data. User PII such as age, race, gender, and zip code contain private information that may assist an adversary in determining the user to whom such information relates. Each item of user PII reveals identity differently, and some types of PII are highly identity vulnerable. More vulnerable types of PII enable unique identification more easily, and their presence in published data increases privacy risks. Existing privacy models treat all types of PII equally from an identity revelation point of view, and they mainly focus on hiding user PII in a crowd of other users. Ignoring the identity vulnerability of each type of PII during anonymization is not an effective method of protecting user privacy in a fine-grained manner. This paper proposes a new anonymization scheme that considers the identity vulnerability of PII to effectively protect user privacy. Data generalization is performed adaptively based on the identity vulnerability of PII as well as diversity to anonymize data. This adaptive generalization effectively enables anonymous data, which protects user identity and private information disclosures while maximizing the utility of data for performing analyses and building classification models. Additionally, the proposed scheme has low computational overheads. The simulation results show the effectiveness of the scheme and verify the aforementioned claims.

Vulnerability- and Diversity-Aware Anonymization of Personally Identifiable Information for Improving User Privacy and Utility of Publishing Data

PubMed Central

Majeed, Abdul; Ullah, Farman; Lee, Sungchang

2017-01-01

Personally identifiable information (PII) affects individual privacy because PII combinations may yield unique identifications in published data. User PII such as age, race, gender, and zip code contain private information that may assist an adversary in determining the user to whom such information relates. Each item of user PII reveals identity differently, and some types of PII are highly identity vulnerable. More vulnerable types of PII enable unique identification more easily, and their presence in published data increases privacy risks. Existing privacy models treat all types of PII equally from an identity revelation point of view, and they mainly focus on hiding user PII in a crowd of other users. Ignoring the identity vulnerability of each type of PII during anonymization is not an effective method of protecting user privacy in a fine-grained manner. This paper proposes a new anonymization scheme that considers the identity vulnerability of PII to effectively protect user privacy. Data generalization is performed adaptively based on the identity vulnerability of PII as well as diversity to anonymize data. This adaptive generalization effectively enables anonymous data, which protects user identity and private information disclosures while maximizing the utility of data for performing analyses and building classification models. Additionally, the proposed scheme has low computational overheads. The simulation results show the effectiveness of the scheme and verify the aforementioned claims. PMID:28481298

Web-based collaboration in individual care planning challenges the user and the provider roles – toward a power transition in caring relationships

PubMed Central

Bjerkan, Jorunn; Vatne, Solfrid; Hollingen, Anne

2014-01-01

Background and objective The Individual Care Plan (ICP) was introduced in Norway to meet new statutory requirements for user participation in health care planning, incorporating multidisciplinary and cross-sector collaboration. A web-based solution (electronic ICP [e-ICP]) was used to support the planning and documentation. The aim of this study was to investigate how web-based collaboration challenged user and professional roles. Methods Data were obtained from 15 semistructured interviews with users and eight with care professionals, and from two focus-group interviews with eight care professionals in total. The data were analyzed using systematic text condensation in a stepwise analysis model. Results Users and care professionals took either a proactive or a reluctant role in e-ICP collaboration. Where both user and care professionals were proactive, the pairing helped to ensure that the planning worked well; so did pairings of proactive care professionals and reluctant users. Proactive users paired with reluctant care professionals also made care planning work, thanks to the availability of information and the users’ own capacity or willingness to conduct the planning. Where both parties were reluctant, no planning activities occurred. Conclusion Use of the e-ICP challenged the user–professional relationship. In some cases, a power transition took place in the care process, which led to patient empowerment. This knowledge might be used to develop a new understanding of how role function can be challenged when users and care professionals have equal access to health care documentation and planning tools. PMID:25525367

Improving access to competitive employment for service users in forensic psychiatric units

PubMed Central

Beck, Charlotte; Wernham, Connie

2014-01-01

Employment has been proven to be an effective recovery tool and therapeutic intervention for those with severe and enduring mental health conditions. Aside from monetary reward, employment is a means of structuring time and provides a sense of worth and achievement, which enhances self-esteem and confidence. A social identity is developed through employment, encouraging social support and increasing social networks. Securing employment can bring about improved quality of life and positive change in one's social circumstances; therefore it can reduce symptoms associated with mental illness and potentially prevent re-offending, as the individual develops a sense of independence, self-efficacy, and value. Barriers to employment exist for forensic mental health service users and therefore it is imperative that employment needs are addressed at the earliest possible stage in recovery. An evaluation of employment activities across two forensic mental health units revealed a lack of appropriate employment opportunities for service users, and those roles available were not implemented in line with recommended best practice. In response to this issue several enterprises were established to offer opportunities for service users to engage in meaningful employment and develop skills that a future employer would value. Each enterprise responds to a business need within the units to ensure sustainability of services. The enterprises are essentially micro-businesses with social objectives whose surpluses are reinvested for the purpose of increasing opportunities for service users. The enterprises are underpinned by the philosophy of the Individual Placement and Support (IPS) model; empirical evidence suggests that the IPS model is the most effective intervention, based on the ‘place then train’ philosophy. The model recommends a focus upon rapid job search to achieve competitive employment for those who want to work; opportunities sourced should be consistent with individual preference and benefits counselling offered. Support should be time unlimited and integrated with mental health treatment. A person-centred and strengths-based approach is also adopted to support people to build on their strengths, establish goals, and encourage motivation. PMID:26734271

Individual Characteristics of Adolescent Methamphetamine Users in Relation to Self-Reported Trouble with the Police

ERIC Educational Resources Information Center

Gassman, Ruth; Nowicke, Carole E.; Jun, Mi Kung

2010-01-01

Survey responses by nonexperimental drug users in grades 6-12 were examined to determine whether MA users and nonusers with shared individual characteristics experience differential rates of police trouble, and whether specific factors place some users at greater risk than others. Findings showed that police trouble is pronounced for MA users,…

Healthcare costs and utilization associated with high-risk prescription opioid use: a retrospective cohort study.

PubMed

Chang, Hsien-Yen; Kharrazi, Hadi; Bodycombe, Dave; Weiner, Jonathan P; Alexander, G Caleb

2018-05-16

Previous studies on high-risk opioid use have only focused on patients diagnosed with an opioid disorder. This study evaluates the impact of various high-risk prescription opioid use groups on healthcare costs and utilization. This is a retrospective cohort study using QuintilesIMS health plan claims with independent variables from 2012 and outcomes from 2013. We included a population-based sample of 191,405 non-elderly adults with known sex, one or more opioid prescriptions, and continuous enrollment in 2012 and 2013. Three high-risk opioid use groups were identified in 2012 as (1) persons with 100+ morphine milligram equivalents per day for 90+ consecutive days (chronic users); (2) persons with 30+ days of concomitant opioid and benzodiazepine use (concomitant users); and (3) individuals diagnosed with an opioid use disorder. The length of time that a person had been characterized as a high-risk user was measured. Three healthcare costs (total, medical, and pharmacy costs) and four binary utilization indicators (the top 5% total cost users, the top 5% pharmacy cost users, any hospitalization, and any emergency department visit) derived from 2013 were outcomes. We applied a generalized linear model (GLM) with a log-link function and gamma distribution for costs while logistic regression was employed for utilization indicators. We also adopted propensity score weighting to control for the baseline differences between high-risk and non-high-risk opioid users. Of individuals with one or more opioid prescription, 1.45% were chronic users, 4.81% were concomitant users, and 0.94% were diagnosed as having an opioid use disorder. After adjustment and propensity score weighting, chronic users had statistically significant higher prospective total (40%), medical (3%), and pharmacy (172%) costs. The increases in total, medical, and pharmacy costs associated with concomitant users were 13%, 7%, and 41%, and 28%, 21% and 63% for users with a diagnosed opioid use disorder. Both total and pharmacy costs increased with the length of time characterized as high-risk users, with the increase being statistically significant. Only concomitant users were associated with a higher odds of hospitalization or emergency department use. Individuals with high-risk prescription opioid use have significantly higher healthcare costs and utilization than their counterparts, especially those with chronic high-dose opioid use.

Identifying Frequent Users of an Urban Emergency Medical Service Using Descriptive Statistics and Regression Analyses.

PubMed

Norman, Chenelle; Mello, Michael; Choi, Bryan

2016-01-01

This retrospective cohort study provides a descriptive analysis of a population that frequently uses an urban emergency medical service (EMS) and identifies factors that contribute to use among all frequent users. For purposes of this study we divided frequent users into the following groups: low- frequent users (4 EMS transports in 2012), medium-frequent users (5 to 6 EMS transports in 2012), high-frequent users (7 to 10 EMS transports in 2012) and super-frequent users (11 or more EMS transports in 2012). Overall, we identified 539 individuals as frequent users. For all groups of EMS frequent users (i.e. low, medium, high and super) one or more hospital admissions, receiving a referral for follow-up care upon discharge, and having no insurance were found to be statistically significant with frequent EMS use (P<0.05). Within the diagnostic categories, 41.61% of super-frequent users had a diagnosis of "primarily substance abuse/misuse" and among low-frequent users a majority, 53.33%, were identified as having a "reoccurring (medical) diagnosis." Lastly, relative risk ratios for the highest group of users, super-frequent users, were 3.34 (95% CI [1.90-5.87]) for obtaining at least one referral for follow-up care, 13.67 (95% CI [5.60-33.34]) for having four or more hospital admissions and 5.95 (95% CI [1.80-19.63]) for having a diagnoses of primarily substance abuse/misuse. Findings from this study demonstrate that among low- and medium-frequent users a majority of patients are using EMS for reoccurring medical conditions. This could potentially be avoided with better care management. In addition, this study adds to the current literature that illustrates a strong correlation between substance abuse/misuse and high/super-frequent EMS use. For the subgroup analysis among individuals 65 years of age and older, we did not find any of the independent variables included in our model to be statistically significant with frequent EMS use.

Evaluation of a primary care adult mental health service: Year 2

PubMed Central

2013-01-01

Aims This study aimed to examine the effectiveness of a primary care adult mental health service operating within a stepped care model of service delivery. Methods Supervised by a principal psychologist manager, psychology graduate practitioners provided one-to-one brief cognitive behavioural therapy (CBT) to service users. The Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) was used to assess service user treatment outcomes. Satisfaction questionnaires were administered to service users and referring general practitioners (GPs). Results A total of 43 individuals attended for an initial appointment, of whom 19 (44.2%) completed brief CBT treatment. Of the 13 service users who were in the clinical range pre-treatment, 11 (84.6%) achieved clinical and reliably significant improvement. Of the six service users who were in the non-clinical range pre-treatment, three (50%) achieved reliably significant improvement. Both service users and GPs indicated high levels of satisfaction with the service, although service accessibility was highlighted as needing improvement. Conclusion The service was effective in treating mild to moderate mental health problems in primary care. Stricter adherence to a stepped care model through the provision of low-intensity, high-throughput interventions would be desirable for future service provision. PMID:24381655

WLCG scale testing during CMS data challenges

NASA Astrophysics Data System (ADS)

Gutsche, O.; Hajdu, C.

2008-07-01

The CMS computing model to process and analyze LHC collision data follows a data-location driven approach and is using the WLCG infrastructure to provide access to GRID resources. As a preparation for data taking, CMS tests its computing model during dedicated data challenges. An important part of the challenges is the test of the user analysis which poses a special challenge for the infrastructure with its random distributed access patterns. The CMS Remote Analysis Builder (CRAB) handles all interactions with the WLCG infrastructure transparently for the user. During the 2006 challenge, CMS set its goal to test the infrastructure at a scale of 50,000 user jobs per day using CRAB. Both direct submissions by individual users and automated submissions by robots were used to achieve this goal. A report will be given about the outcome of the user analysis part of the challenge using both the EGEE and OSG parts of the WLCG. In particular, the difference in submission between both GRID middlewares (resource broker vs. direct submission) will be discussed. In the end, an outlook for the 2007 data challenge is given.

Bringing Chatbots into education: Towards Natural Language Negotiation of Open Learner Models

NASA Astrophysics Data System (ADS)

Kerlyl, Alice; Hall, Phil; Bull, Susan

There is an extensive body of work on Intelligent Tutoring Systems: computer environments for education, teaching and training that adapt to the needs of the individual learner. Work on personalisation and adaptivity has included research into allowing the student user to enhance the system's adaptivity by improving the accuracy of the underlying learner model. Open Learner Modelling, where the system's model of the user's knowledge is revealed to the user, has been proposed to support student reflection on their learning. Increased accuracy of the learner model can be obtained by the student and system jointly negotiating the learner model. We present the initial investigations into a system to allow people to negotiate the model of their understanding of a topic in natural language. This paper discusses the development and capabilities of both conversational agents (or chatbots) and Intelligent Tutoring Systems, in particular Open Learner Modelling. We describe a Wizard-of-Oz experiment to investigate the feasibility of using a chatbot to support negotiation, and conclude that a fusion of the two fields can lead to developing negotiation techniques for chatbots and the enhancement of the Open Learner Model. This technology, if successful, could have widespread application in schools, universities and other training scenarios.

Structural diversity effect on hashtag adoption in Twitter

NASA Astrophysics Data System (ADS)

Zhang, Aihua; Zheng, Mingxing; Pang, Bowen

2018-03-01

With online social network developing rapidly these years, user' behavior in online social network has attracted a lot of attentions to it. In this paper, we study Twitter user's behavior of hashtag adoption from the perspective of social contagion and focus on "structure diversity" effect on individual's behavior in Twitter. We achieve data through Twitter's API by crawling and build a users' network to carry on empirical research. The Girvan-Newman (G-N) algorithm is used to analyze the structural diversity of user's ego network, and Logistic regression model is adopted to examine the hypothesis. The findings of our empirical study indicate that user' behavior in online social network is indeed influenced by his friends and his decision is significantly affected by the number of groups that these friends belong to, which we call structural diversity.

Cognitive Styles and Virtual Environments.

ERIC Educational Resources Information Center

Ford, Nigel

2000-01-01

Discussion of navigation through virtual information environments focuses on the need for robust user models that take into account individual differences. Considers Pask's information processing styles and strategies; deep (transformational) and surface (reproductive) learning; field dependence/independence; divergent/convergent thinking;…

Context-based user grouping for multi-casting in heterogeneous radio networks

NASA Astrophysics Data System (ADS)

Mannweiler, C.; Klein, A.; Schneider, J.; Schotten, H. D.

2011-08-01

Along with the rise of sophisticated smartphones and smart spaces, the availability of both static and dynamic context information has steadily been increasing in recent years. Due to the popularity of social networks, these data are complemented by profile information about individual users. Making use of this information by classifying users in wireless networks enables targeted content and advertisement delivery as well as optimizing network resources, in particular bandwidth utilization, by facilitating group-based multi-casting. In this paper, we present the design and implementation of a web service for advanced user classification based on user, network, and environmental context information. The service employs simple and advanced clustering algorithms for forming classes of users. Available service functionalities include group formation, context-aware adaptation, and deletion as well as the exposure of group characteristics. Moreover, the results of a performance evaluation, where the service has been integrated in a simulator modeling user behavior in heterogeneous wireless systems, are presented.

HOMER® Micropower Optimization Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lilienthal, P.

2005-01-01

NREL has developed the HOMER micropower optimization model. The model can analyze all of the available small power technologies individually and in hybrid configurations to identify least-cost solutions to energy requirements. This capability is valuable to a diverse set of energy professionals and applications. NREL has actively supported its growing user base and developed training programs around the model. These activities are helping to grow the global market for solar technologies.

Predicting Smartphone Operating System from Personality and Individual Differences.

PubMed

Shaw, Heather; Ellis, David A; Kendrick, Libby-Rae; Ziegler, Fenja; Wiseman, Richard

2016-12-01

Android and iPhone devices account for over 90 percent of all smartphones sold worldwide. Despite being very similar in functionality, current discourse and marketing campaigns suggest that key individual differences exist between users of these two devices; however, this has never been investigated empirically. This is surprising, as smartphones continue to gain momentum across a variety of research disciplines. In this article, we consider if individual differences exist between these two distinct groups. In comparison to Android users, we found that iPhone owners are more likely to be female, younger, and increasingly concerned about their smartphone being viewed as a status object. Key differences in personality were also observed with iPhone users displaying lower levels of Honesty-Humility and higher levels of emotionality. Following this analysis, we were also able to build and test a model that predicted smartphone ownership at above chance level based on these individual differences. In line with extended self-theory, the type of smartphone owned provides some valuable information about its owner. These findings have implications for the increasing use of smartphones within research particularly for those working within Computational Social Science and PsychoInformatics, where data are typically collected from devices and applications running a single smartphone operating system.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

PubMed

Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

2014-07-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology

PubMed Central

Deodhar, Suruchi; Bisset, Keith R.; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V.

2014-01-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity. PMID:25530914

Risk of lung cancer associated with domestic use of coal in Xuanwei, China: retrospective cohort study

PubMed Central

Chapman, Robert S; Silverman, Debra T; He, Xinghzhou; Hu, Wei; Vermeulen, Roel; Ning, Bofu; Fraumeni, Joseph F; Rothman, Nathaniel; Lan, Qing

2012-01-01

Objective To estimate the risk of lung cancer associated with the use of different types of coal for household cooking and heating. Setting Xuanwei County, Yunnan Province, China. Design Retrospective cohort study (follow-up 1976-96) comparing mortality from lung cancer between lifelong users of “smoky coal” (bituminous) and “smokeless coal” (anthracite). Participants 27 310 individuals using smoky coal and 9962 individuals using smokeless coal during their entire life. Main outcome measures Primary outcomes were absolute and relative risk of death from lung cancer among users of different types of coal. Unadjusted survival analysis was used to estimate the absolute risk of lung cancer, while Cox regression models compared mortality hazards for lung cancer between smoky and smokeless coal users. Results Lung cancer mortality was substantially higher among users of smoky coal than users of smokeless coal. The absolute risks of lung cancer death before 70 years of age for men and women using smoky coal were 18% and 20%, respectively, compared with less than 0.5% among smokeless coal users of both sexes. Lung cancer alone accounted for about 40% of all deaths before age 60 among individuals using smoky coal. Compared with smokeless coal, use of smoky coal was associated with an increased risk of lung cancer death (for men, hazard ratio 36 (95% confidence interval 20 to 65); for women, 99 (37 to 266)). Conclusions In Xuanwei, the domestic use of smoky coal is associated with a substantial increase in the absolute lifetime risk of developing lung cancer and is likely to represent one of the strongest effects of environmental pollution reported for cancer risk. Use of less carcinogenic types of coal could translate to a substantial reduction of lung cancer risk. PMID:22936785

A Comparison of Opioid and Nonopioid Substance Users in Residential Treatment for Co-Occurring Substance Use and Mental Disorders.

PubMed

Bride, Brian E; Macmaster, Samuel A; Morse, Siobhan A; Watson, Cayce M; Choi, Sam; Seiters, John

2016-01-01

The past decade has seen a marked increase in the illicit use of opioids, as well as a doubling of the percentage of individuals seeking treatment for opioid use disorders. However, little is known about the differences between opioid users and nonopioid users in residential treatment. Further, no studies have been published that compare opioid users and nonopioid users in treatment for co-occurring substance use and mental disorders. To address this gap, this study examined differences between opioid and nonopioid substance users in residential treatment for co-occurring disorders. Data was drawn from 1,972 individuals treated between 2009 and 2011 at one of three private residential treatment centers that provide integrated treatment for co-occurring substance use and mental disorders. Data was collected at program intake, and 1- and 6-month postdischarge using the Addiction Severity Index and the University of Rhode Island Change Assessment. To examine within-group changes in substance use, addiction severity, and mental health across time, linear mixed-model analyses were conducted with facility, year, age, gender, and race included as covariates. The authors found more similarities than differences between the two groups on baseline characteristics, treatment motivation, length of stay, and outcomes on measures of substance use, addiction severity, and mental health. The results demonstrate that though opioid users entered treatment with higher levels of substance use-related impairment, they were just as successful in treatment outcomes as their non-opioid-using peers.

Barriers and facilitators of disclosures of domestic violence by mental health service users: qualitative study.

PubMed

Rose, Diana; Trevillion, Kylee; Woodall, Anna; Morgan, Craig; Feder, Gene; Howard, Louise

2011-03-01

Mental health service users are at high risk of domestic violence but this is often not detected by mental health services. To explore the facilitators and barriers to disclosure of domestic violence from a service user and professional perspective. A qualitative study in a socioeconomically deprived south London borough, UK, with 18 mental health service users and 20 mental health professionals. Purposive sampling of community mental health service users and mental healthcare professionals was used to recruit participants for individual interviews. Thematic analysis was used to determine dominant and subthemes. These were transformed into conceptual maps with accompanying illustrative quotations. Service users described barriers to disclosure of domestic violence to professionals including: fear of the consequences, including fear of Social Services involvement and consequent child protection proceedings, fear that disclosure would not be believed, and fear that disclosure would lead to further violence; the hidden nature of the violence; actions of the perpetrator; and feelings of shame. The main themes for professionals concerned role boundaries, competency and confidence. Service users and professionals reported that the medical diagnostic and treatment model with its emphasis on symptoms could act as a barrier to enquiry and disclosure. Both groups reported that enquiry and disclosure were facilitated by a supportive and trusting relationship between the individual and professional. Mental health services are not currently conducive to the disclosure of domestic violence. Training of professionals in how to address domestic violence to increase their confidence and expertise is recommended.

Effects of a recovery management intervention on Chinese heroin users' community recovery through the mediation effect of enhanced service utilization.

PubMed

Wu, F; Fu, L M; Hser, Y H

2015-09-01

This study investigates whether a recovery management intervention (RMI) can improve the utilization of community drug treatment and wraparound services among heroin users in China and subsequently lead to positive recovery outcomes. Secondary analysis was conducted drawing data from a randomized controlled trial; 100 heroin users with no severe mental health problems were recruited in two Shanghai districts (Hongkou and Yangpu) upon their release from compulsory rehabilitation facilities. A latent variable modeling approach was utilized to test whether the RMI influences heroin users' perceived motivation and readiness for treatment, enhances treatment and wraparound service participation, and, in turn, predicts better recovery outcomes. Enrollment in drug treatment and other social service utilization increased significantly as a result of RMI rather than an individual drug user's motivation and readiness for treatment. Increased service utilization thus led to more positive individual recovery outcomes. In addition to this mediation effect through service utilization, the RMI also improved participants' community recovery directly. Findings suggest that better drug treatment enrollment, community service utilization and recovery outcomes can be potentially achieved among heroin users in China with carefully designed case management interventions. © The Author 2014. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Measuring Emotional Contagion in Social Media.

PubMed

Ferrara, Emilio; Yang, Zeyao

2015-01-01

Social media are used as main discussion channels by millions of individuals every day. The content individuals produce in daily social-media-based micro-communications, and the emotions therein expressed, may impact the emotional states of others. A recent experiment performed on Facebook hypothesized that emotions spread online, even in absence of non-verbal cues typical of in-person interactions, and that individuals are more likely to adopt positive or negative emotions if these are over-expressed in their social network. Experiments of this type, however, raise ethical concerns, as they require massive-scale content manipulation with unknown consequences for the individuals therein involved. Here, we study the dynamics of emotional contagion using a random sample of Twitter users, whose activity (and the stimuli they were exposed to) was observed during a week of September 2014. Rather than manipulating content, we devise a null model that discounts some confounding factors (including the effect of emotional contagion). We measure the emotional valence of content the users are exposed to before posting their own tweets. We determine that on average a negative post follows an over-exposure to 4.34% more negative content than baseline, while positive posts occur after an average over-exposure to 4.50% more positive contents. We highlight the presence of a linear relationship between the average emotional valence of the stimuli users are exposed to, and that of the responses they produce. We also identify two different classes of individuals: highly and scarcely susceptible to emotional contagion. Highly susceptible users are significantly less inclined to adopt negative emotions than the scarcely susceptible ones, but equally likely to adopt positive emotions. In general, the likelihood of adopting positive emotions is much greater than that of negative emotions.

An unsupervised machine learning model for discovering latent infectious diseases using social media data.

PubMed

Lim, Sunghoon; Tucker, Conrad S; Kumara, Soundar

2017-02-01

The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a communicable disease that has not yet been formalized by national public health institutes and explicitly communicated to the general public. Most existing approaches to modeling infectious-disease-related knowledge discovery through social media networks are top-down approaches that are based on already known information, such as the names of diseases and their symptoms. In existing top-down approaches, necessary but unknown information, such as disease names and symptoms, is mostly unidentified in social media data until national public health institutes have formalized that disease. Most of the formalizing processes for latent infectious diseases are time consuming. Therefore, this study presents a bottom-up approach for latent infectious disease discovery in a given location without prior information, such as disease names and related symptoms. Social media messages with user and temporal information are extracted during the data preprocessing stage. An unsupervised sentiment analysis model is then presented. Users' expressions about symptoms, body parts, and pain locations are also identified from social media data. Then, symptom weighting vectors for each individual and time period are created, based on their sentiment and social media expressions. Finally, latent-infectious-disease-related information is retrieved from individuals' symptom weighting vectors. Twitter data from August 2012 to May 2013 are used to validate this study. Real electronic medical records for 104 individuals, who were diagnosed with influenza in the same period, are used to serve as ground truth validation. The results are promising, with the highest precision, recall, and F 1 score values of 0.773, 0.680, and 0.724, respectively. This work uses individuals' social media messages to identify latent infectious diseases, without prior information, quicker than when the disease(s) is formalized by national public health institutes. In particular, the unsupervised machine learning model using user, textual, and temporal information in social media data, along with sentiment analysis, identifies latent infectious diseases in a given location. Copyright © 2016 Elsevier Inc. All rights reserved.

Rule-based interface generation on mobile devices for structured documentation.

PubMed

Kock, Ann-Kristin; Andersen, Björn; Handels, Heinz; Ingenerf, Josef

2014-01-01

In many software systems to date, interactive graphical user interfaces (GUIs) are represented implicitly in the source code, together with the application logic. Hence, the re-use, development, and modification of these interfaces is often very laborious. Flexible adjustments of GUIs for various platforms and devices as well as individual user preferences are furthermore difficult to realize. These problems motivate a software-based separation of content and GUI models on the one hand, and application logic on the other. In this project, a software solution for structured reporting on mobile devices is developed. Clinical content archetypes developed in a previous project serve as the content model while the Android SDK provides the GUI model. The necessary bindings between the models are specified using the Jess Rule Language.

A model of user engagement in medical device development.

PubMed

Grocott, Patricia; Weir, Heather; Ram, Mala Bridgelal

2007-01-01

The purpose of this paper is to address three topical themes: user involvement in health services research; determining the value of new medical technologies in patient care pathways, furthering knowledge related to quality in health and social care; and knowledge exchange between manufacturers, health service supply chain networks and device users. The model is being validated in a case study in progress. The latter is a "proving ground" study for a translational research company. Medical devices play a pivotal role in the management of chronic diseases, across all care settings. Failure to engage users in device development inevitably affects the quality of clinical outcomes. A model of user engagement is presented, turning unmet needs for medical devices into viable commercial propositions. A case study investigating the perceptions of individuals with Epidermolysis Bullosa (EB), their lay and professional carers into unmet needs. EB is an inherited condition affecting the skin and mucosal linings that leads to blistering and wounds. Qualitative data are being collected to generate understanding of unmet needs and wound care products. These needs are being translated into new design concepts and prototypes. Prototypes will be evaluated in an n = 1 experimental design, generating quantitative outcomes data. There are generalisations from the case study, and the model outlined. New products for managing EB wounds can logically benefit other groups. The model is transferable to other clinical problems, which can benefit from research and technological advances that are integral to clinical needs and care.

Characteristics of Innovators Adopting a National Personal Health Record in Portugal: Cross-Sectional Study

PubMed Central

Rodolfo, Inês; Pereira, Ana Marta; de Sá, Armando Brito

2017-01-01

Background Personal health records (PHRs) are increasingly being deployed worldwide, but their rates of adoption by patients vary widely across countries and health systems. Five main categories of adopters are usually considered when evaluating the diffusion of innovations: innovators, early adopters, early majority, late majority, and laggards. Objective We aimed to evaluate adoption of the Portuguese PHR 3 months after its release, as well as characterize the individuals who registered and used the system during that period (the innovators). Methods We conducted a cross-sectional study. Users and nonusers were defined based on their input, or not, of health-related information into the PHR. Users of the PHR were compared with nonusers regarding demographic and clinical variables. Users were further characterized according to their intensity of information input: single input (one single piece of health-related information recorded) and multiple inputs. Multivariate logistic regression was used to model the probability of being in the multiple inputs group. ArcGis (ESRI, Redlands, CA, USA) was used to create maps of the proportion of PHR registrations by region and district. Results The number of registered individuals was 109,619 (66,408/109,619, 60.58% women; mean age: 44.7 years, standard deviation [SD] 18.1 years). The highest proportion of registrations was observed for those aged between 30 and 39 years (25,810/109,619, 23.55%). Furthermore, 16.88% (18,504/109,619) of registered individuals were considered users and 83.12% (91,115/109,619) nonusers. Among PHR users, 32.18% (5955/18,504) engaged in single input and 67.82% (12,549/18,504) in multiple inputs. Younger individuals and male users had higher odds of engaging in multiple inputs (odds ratio for male individuals 1.32, CI 1.19-1.48). Geographic analysis revealed higher proportions of PHR adoption in urban centers when compared with rural noncoastal districts. Conclusions Approximately 1% of the country’s population registered during the first 3 months of the Portuguese PHR. Registered individuals were more frequently female aged between 30 and 39 years. There is evidence of a geographic gap in the adoption of the Portuguese PHR, with higher proportions of adopters in urban centers than in rural noncoastal districts. PMID:29021125

Simulation and experimental studies of operators` decision styles and crew composition while using an ecological and traditional user interface for the control room of a nuclear power plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meshkati, N.; Buller, B.J.; Azadeh, M.A.

1995-04-01

The goal of this research is threefold: (1) use of the Skill-, Rule-, and Knowledge-based levels of cognitive control -- the SRK framework -- to develop an integrated information processing conceptual framework (for integration of workstation, job, and team design); (2) to evaluate the user interface component of this framework -- the Ecological display; and (3) to analyze the effect of operators` individual information processing behavior and decision styles on handling plant disturbances plus their performance on, and preference for, Traditional and Ecological user interfaces. A series of studies were conducted. In Part I, a computer simulation model and amore » mathematical model were developed. In Part II, an experiment was designed and conducted at the EBR-II plant of the Argonne National Laboratory-West in Idaho Falls, Idaho. It is concluded that: the integrated SRK-based information processing model for control room operations is superior to the conventional rule-based model; operators` individual decision styles and the combination of their styles play a significant role in effective handling of nuclear power plant disturbances; use of the Ecological interface results in significantly more accurate event diagnosis and recall of various plant parameters, faster response to plant transients, and higher ratings of subject preference; and operators` decision styles affect on both their performance and preference for the Ecological interface.« less

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

PubMed

Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.

Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month

PubMed Central

2013-01-01

Background One in eight women will develop breast cancer in her lifetime. The best-known awareness event is breast cancer awareness month (BCAM). BCAM month outreach efforts have been associated with increased media coverage, screening mammography and online information searching. Traditional mass media coverage has been enhanced by social media. However, there is a dearth of literature about how social media is used during awareness-related events. The purpose of this research was to understand how Twitter is being used during BCAM. Methods This was a cross-sectional, descriptive study. We collected breast cancer- related tweets from 26 September - 12 November 2012, using Twitter’s application programming interface. We classified Twitter users into organizations, individuals, and celebrities; each tweet was classified as an original or a retweet, and inclusion of a mention, meaning a reference to another Twitter user with @username. Statistical methods included ANOVA and chi square. For content analysis, we used computational linguistics techniques, specifically the MALLET implementation of the unsupervised topic modeling algorithm Latent Dirichlet Allocation. Results There were 1,351,823 tweets by 797,827 unique users. Tweets spiked dramatically the first few days then tapered off. There was an average of 1.69 tweets per user. The majority of users were individuals. Nearly all of the tweets were original. Organizations and celebrities posted more often than individuals. On average celebrities made far more impressions; they were also retweeted more often and their tweets were more likely to include mentions. Individuals were more likely to direct a tweet to a specific person. Organizations and celebrities emphasized fundraisers, early detection, and diagnoses while individuals tweeted about wearing pink. Conclusions Tweeting about breast cancer was a singular event. The majority of tweets did not promote any specific preventive behavior. Twitter is being used mostly as a one-way communication tool. To expand the reach of the message and maximize the potential for word-of-mouth marketing using Twitter, organizations need a strategic communications plan to ensure on-going social media conversations. Organizations may consider collaborating with individuals and celebrities in these conversations. Social media communication strategies that emphasize fundraising for breast cancer research seem particularly appropriate. PMID:24168075

Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month.

PubMed

Thackeray, Rosemary; Burton, Scott H; Giraud-Carrier, Christophe; Rollins, Stephen; Draper, Catherine R

2013-10-29

One in eight women will develop breast cancer in her lifetime. The best-known awareness event is breast cancer awareness month (BCAM). BCAM month outreach efforts have been associated with increased media coverage, screening mammography and online information searching. Traditional mass media coverage has been enhanced by social media. However, there is a dearth of literature about how social media is used during awareness-related events. The purpose of this research was to understand how Twitter is being used during BCAM. This was a cross-sectional, descriptive study. We collected breast cancer- related tweets from 26 September - 12 November 2012, using Twitter's application programming interface. We classified Twitter users into organizations, individuals, and celebrities; each tweet was classified as an original or a retweet, and inclusion of a mention, meaning a reference to another Twitter user with @username. Statistical methods included ANOVA and chi square. For content analysis, we used computational linguistics techniques, specifically the MALLET implementation of the unsupervised topic modeling algorithm Latent Dirichlet Allocation. There were 1,351,823 tweets by 797,827 unique users. Tweets spiked dramatically the first few days then tapered off. There was an average of 1.69 tweets per user. The majority of users were individuals. Nearly all of the tweets were original. Organizations and celebrities posted more often than individuals. On average celebrities made far more impressions; they were also retweeted more often and their tweets were more likely to include mentions. Individuals were more likely to direct a tweet to a specific person. Organizations and celebrities emphasized fundraisers, early detection, and diagnoses while individuals tweeted about wearing pink. Tweeting about breast cancer was a singular event. The majority of tweets did not promote any specific preventive behavior. Twitter is being used mostly as a one-way communication tool. To expand the reach of the message and maximize the potential for word-of-mouth marketing using Twitter, organizations need a strategic communications plan to ensure on-going social media conversations. Organizations may consider collaborating with individuals and celebrities in these conversations. Social media communication strategies that emphasize fundraising for breast cancer research seem particularly appropriate.

Overall Preference of Running Shoes Can Be Predicted by Suitable Perception Factors Using a Multiple Regression Model.

PubMed

Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah

2017-05-01

This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.

A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems

PubMed Central

Pan, Shaoming; Chong, Yanwen; Zhang, Hang; Tan, Xicheng

2017-01-01

A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client’s requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users’ access behaviors and all tiles’ relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users’ access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods. PMID:28085937

ModelArchiver—A program for facilitating the creation of groundwater model archives

USGS Publications Warehouse

Winston, Richard B.

2018-03-01

ModelArchiver is a program designed to facilitate the creation of groundwater model archives that meet the requirements of the U.S. Geological Survey (USGS) policy (Office of Groundwater Technical Memorandum 2016.02, https://water.usgs.gov/admin/memo/GW/gw2016.02.pdf, https://water.usgs.gov/ogw/policy/gw-model/). ModelArchiver version 1.0 leads the user step-by-step through the process of creating a USGS groundwater model archive. The user specifies the contents of each of the subdirectories within the archive and provides descriptions of the archive contents. Descriptions of some files can be specified automatically using file extensions. Descriptions also can be specified individually. Those descriptions are added to a readme.txt file provided by the user. ModelArchiver moves the content of the archive to the archive folder and compresses some folders into .zip files.As part of the archive, the modeler must create a metadata file describing the archive. The program has a built-in metadata editor and provides links to websites that can aid in creation of the metadata. The built-in metadata editor is also available as a stand-alone program named FgdcMetaEditor version 1.0, which also is described in this report. ModelArchiver updates the metadata file provided by the user with descriptions of the files in the archive. An optional archive list file generated automatically by ModelMuse can streamline the creation of archives by identifying input files, output files, model programs, and ancillary files for inclusion in the archive.

Comparison of sensory, physiological, personality, and cultural attributes in regular spicy food users and non-users.

PubMed

Ludy, Mary-Jon; Mattes, Richard D

2012-02-01

Some individuals savor spicy foods, while others avoid them. Reasons underlying this range of hedonic responses are unknown. The purpose of this study was to explore the basis for individual differences in preference for spicy foods. Regular spicy food users (n=13) and non-users (n=12) were characterized for selected sensory, physiological, personality, and cultural attributes. Individual differences between users and non-users were primarily related to sensory and cultural attributes (i.e., a higher proportion of users reported consuming spicy foods since childhood and users rated spicy foods as more palatable and were better able to discriminate this burn than non-users). Users and non-users exhibited comparable responsiveness to noxious pressure pain, oral tactile sensitivity, and auditory sensitivity, varying only in responsiveness to oral thermal heat (i.e., users were more sensitive to increases than non-users). Studied personality traits did not vary between users and non-users. These findings suggest that prior experience, rather than physiological adaptation or personality differences, may best predict preference for spicy foods. These findings are of public health interest, given that spicy food consumption is reported to confer weight management and food safety benefits. Copyright © 2011 Elsevier Ltd. All rights reserved.

Requirements Modeling with the Aspect-oriented User Requirements Notation (AoURN): A Case Study

NASA Astrophysics Data System (ADS)

Mussbacher, Gunter; Amyot, Daniel; Araújo, João; Moreira, Ana

The User Requirements Notation (URN) is a recent ITU-T standard that supports requirements engineering activities. The Aspect-oriented URN (AoURN) adds aspect-oriented concepts to URN, creating a unified framework that allows for scenario-based, goal-oriented, and aspect-oriented modeling. AoURN is applied to the car crash crisis management system (CCCMS), modeling its functional and non-functional requirements (NFRs). AoURN generally models all use cases, NFRs, and stakeholders as individual concerns and provides general guidelines for concern identification. AoURN handles interactions between concerns, capturing their dependencies and conflicts as well as the resolutions. We present a qualitative comparison of aspect-oriented techniques for scenario-based and goal-oriented requirements engineering. An evaluation carried out based on the metrics adapted from literature and a task-based evaluation suggest that AoURN models are more scalable than URN models and exhibit better modularity, reusability, and maintainability.

ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership.

PubMed

Wu, Hongchen; Wang, Xinjun

2016-01-01

The rapid growth of social network data has given rise to high security awareness among users, especially when they exchange and share their personal information. However, because users have different feelings about sharing their information, they are often puzzled about who their partners for exchanging information can be and what information they can share. Is it possible to assist users in forming a partnership network in which they can exchange and share information with little worry? We propose a modified information sharing behavior prediction (ISBP) model that can help in understanding the underlying rules by which users share their information with partners in light of three common aspects: what types of items users are likely to share, what characteristics of users make them likely to share information, and what features of users' sharing behavior are easy to predict. This model is applied with machine learning techniques in WEKA to predict users' decisions pertaining to information sharing behavior and form them into trustable partnership networks by learning their features. In the experiment section, by using two real-life datasets consisting of citizens' sharing behavior, we identify the effect of highly sensitive requests on sharing behavior adjacent to individual variables: the younger participants' partners are more difficult to predict than those of the older participants, whereas the partners of people who are not computer majors are easier to predict than those of people who are computer majors. Based on these findings, we believe that it is necessary and feasible to offer users personalized suggestions on information sharing decisions, and this is pioneering work that could benefit college researchers focusing on user-centric strategies and website owners who want to collect more user information without raising their privacy awareness or losing their trustworthiness.

Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

PubMed Central

Kim, Seungjoo

2014-01-01

There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information. PMID:25374943

Trust-based access control model from sociological approach in dynamic online social network environment.

PubMed

Baek, Seungsoo; Kim, Seungjoo

2014-01-01

There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information.

An SSH key management system: easing the pain of managing key/user/account associations

NASA Astrophysics Data System (ADS)

Arkhipkin, D.; Betts, W.; Lauret, J.; Shiryaev, A.

2008-07-01

Cyber security requirements for secure access to computing facilities often call for access controls via gatekeepers and the use of two-factor authentication. Using SSH keys to satisfy the two factor authentication requirement has introduced a potentially challenging task of managing the keys and their associations with individual users and user accounts. Approaches for a facility with the simple model of one remote user corresponding to one local user would not work at facilities that require a many-to-many mapping between users and accounts on multiple systems. We will present an SSH key management system we developed, tested and deployed to address the many-to-many dilemma in the environment of the STAR experiment. We will explain its use in an online computing context and explain how it makes possible the management and tracing of group account access spread over many sub-system components (data acquisition, slow controls, trigger, detector instrumentation, etc.) without the use of shared passwords for remote logins.

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

PubMed Central

Hopkins, John B.; Ferguson, Jake M.

2012-01-01

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs. PMID:22235246

Identification and impact of discoverers in online social systems

PubMed Central

Medo, Matúš; Mariani, Manuel S.; Zeng, An; Zhang, Yi-Cheng

2016-01-01

Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by being repeatedly and persistently among the first to collect the items that later become hugely popular. Since these users effectively discover future hits, we refer them as discoverers. We use the proposed framework to demonstrate that discoverers are present in a wide range of real systems. Once identified, discoverers can be used to predict the future success of new items. We finally introduce a simple network model which reproduces the discovery patterns observed in the real data. Our results open the door to quantitative study of detailed temporal patterns in social systems. PMID:27687588

Identification and impact of discoverers in online social systems

NASA Astrophysics Data System (ADS)

Medo, Matúš; Mariani, Manuel S.; Zeng, An; Zhang, Yi-Cheng

2016-09-01

Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by being repeatedly and persistently among the first to collect the items that later become hugely popular. Since these users effectively discover future hits, we refer them as discoverers. We use the proposed framework to demonstrate that discoverers are present in a wide range of real systems. Once identified, discoverers can be used to predict the future success of new items. We finally introduce a simple network model which reproduces the discovery patterns observed in the real data. Our results open the door to quantitative study of detailed temporal patterns in social systems.

Identification and impact of discoverers in online social systems.

PubMed

Medo, Matúš; Mariani, Manuel S; Zeng, An; Zhang, Yi-Cheng

2016-09-30

Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by being repeatedly and persistently among the first to collect the items that later become hugely popular. Since these users effectively discover future hits, we refer them as discoverers. We use the proposed framework to demonstrate that discoverers are present in a wide range of real systems. Once identified, discoverers can be used to predict the future success of new items. We finally introduce a simple network model which reproduces the discovery patterns observed in the real data. Our results open the door to quantitative study of detailed temporal patterns in social systems.

User perspectives on the usability of a regional health information exchange

PubMed Central

Ho, Yun-Xian; Cala, Cather Marie; Blakemore, Dana; Chen, Qingxia; Frisse, Mark E; Johnson, Kevin B

2011-01-01

Objective We assessed the usability of a health information exchange (HIE) in a densely populated metropolitan region. This grant-funded HIE had been deployed rapidly to address the imminent needs of the patient population and the need to draw wider participation from regional entities. Design We conducted a cross-sectional survey of individuals given access to the HIE at participating organizations and examined some of the usability and usage factors related to the technology acceptance model. Measurements We probed user perceptions using the Questionnaire for User Interaction Satisfaction, an author-generated Trust scale, and user characteristic questions (eg, age, weekly system usage time). Results Overall, users viewed the system favorably (ratings for all usability items were greater than neutral (one-sample Wilcoxon test, p<0.0014, Bonferroni-corrected for 35 tests). System usage was regressed on usability, trust, and demographic and user characteristic factors. Three usability factors were positively predictive of system usage: overall reactions (p<0 0.01), learning (p<0.05), and system functionality (p<0.01). Although trust is an important component in collaborative relationships, we did not find that user trust of other participating healthcare entities was significantly predictive of usage. An analysis of respondents' comments revealed ways to improve the HIE. Conclusion We used a rapid deployment model to develop an HIE and found that perceptions of system usability were positive. We also found that system usage was predicted well by some aspects of usability. Results from this study suggest that a rapid development approach may serve as a viable model for developing usable HIEs serving communities with limited resources. PMID:21622933

Preference heterogeneity in a count data model of demand for off-highway vehicle recreation

Treesearch

Thomas P Holmes; Jeffrey E Englin

2010-01-01

This paper examines heterogeneity in the preferences for OHV recreation by applying the random parameters Poisson model to a data set of off-highway vehicle (OHV) users at four National Forest sites in North Carolina. The analysis develops estimates of individual consumer surplus and finds that estimates are systematically affected by the random parameter specification...

Depression as Measured by the Beck Depression Inventory-II among Injecting Drug Users

ERIC Educational Resources Information Center

Johnson, Mark E.; Neal, David B.; Brems, Christiane; Fisher, Dennis G.

2006-01-01

This study conducts a confirmatory factor analysis of the Beck Depression Inventory-II (BDI-II) with a sample of 598 individuals who reported recent injecting drug use. Findings indicate that out of four models tested, the best model for this sample is a three-factor solution (somatic, affective, and cognitive) previously reported by Buckley,…

The GRASP 3: Graphical Reliability Analysis Simulation Program. Version 3: A users' manual and modelling guide

NASA Technical Reports Server (NTRS)

Phillips, D. T.; Manseur, B.; Foster, J. W.

1982-01-01

Alternate definitions of system failure create complex analysis for which analytic solutions are available only for simple, special cases. The GRASP methodology is a computer simulation approach for solving all classes of problems in which both failure and repair events are modeled according to the probability laws of the individual components of the system.

Predicting use of case management support services for adolescents and adults living in community following brain injury: A longitudinal Canadian database study with implications for life care planning.

PubMed

Baptiste, B; Dawson, D R; Streiner, D

2015-01-01

To determine factors associated with case management (CM) service use in people with traumatic brain injury (TBI), using a published model for service use. A retrospective cohort, with nested case-control design. Correlational and logistic regression analyses of questionnaires from a longitudinal community data base. Questionnaires of 203 users of CM services and 273 non-users, complete for all outcome and predictor variables. Individuals with TBI, 15 years of age and older. Out of a dataset of 1,960 questionnaires, 476 met the inclusion criteria. Eight predictor variables and one outcome variable (use or non-use of the service). Predictor variables considered the framework of the Behaviour Model of Health Service Use (BMHSU); specifically, pre-disposing, need and enabling factor groups as these relate to health service use and access. Analyses revealed significant differences between users and non-users of CM services. In particular, users were significantly younger than non-users as the older the person the less likely to use the service. Also, users had less education and more severe activity limitations and lower community integration. Persons living alone are less likely to use case management. Funding groups also significantly impact users. This study advances an empirical understanding of equity of access to health services usage in the practice of CM for persons living with TBI as a fairly new area of research, and considers direct relevance to Life Care Planning (LCP). Many life care planers are CM and the genesis of LCP is CM. The findings relate to health service use and access, rather than health outcomes. These findings may assist with development of a modified model for prediction of use to advance future cost of care predictions.

Service user experiences of specialist mental health supported accommodation: A systematic review of qualitative studies and narrative synthesis.

PubMed

Krotofil, Joanna; McPherson, Peter; Killaspy, Helen

2018-04-02

Specialist supported accommodation services have become a key component of most community-based mental healthcare systems. While mental health policies highlight the importance of service user involvement in service development and care planning, there are no comprehensive literature reviews synthesising services users' perspectives on, or experiences of, supported accommodation services. This systematic review was undertaken to fill this gap. We searched electronic databases (January 2015, updated June 2017), conducted hand searches and used forward-backward snowballing to identify 13,678 papers. We inspected the full-text of 110 papers and included 50 of these in the final review. Data extraction and quality assessments were conducted. We used narrative synthesis to develop a conceptual model of service users' experiences that included structural, process, relational and contextual factors, such as the characteristics of the service, relationships with staff and other service users, the intensity and nature of support, the physical environment, and social and community integration. The review highlights the complex interplay of individual, service-level and community factors in shaping the lived experience of service users and their impact on personal identity and recovery. Our approach addressed some of the widely reported limitations of the quantitative research in this field, providing a conceptual model relevant to service user experiences across supported accommodation service types, population groups and countries. © 2018 John Wiley & Sons Ltd.

A psychotechnological review on eye-tracking systems: towards user experience.

PubMed

Mele, Maria Laura; Federici, Stefano

2012-07-01

The aim of the present work is to show a critical review of the international literature on eye-tracking technologies by focusing on those features that characterize them as 'psychotechnologies'. A critical literature review was conducted through the main psychology, engineering, and computer sciences databases by following specific inclusion and exclusion criteria. A total of 46 matches from 1998 to 2010 were selected for content analysis. Results have been divided into four broad thematic areas. We found that, although there is a growing attention to end-users, most of the studies reviewed in this work are far from being considered as adopting holistic human-computer interaction models that include both individual differences and needs of users. User is often considered only as a measurement object of the functioning of the technological system and not as a real alter-ego of the intrasystemic interaction. In order to fully benefit from the communicative functions of gaze, the research on eye-tracking must emphasize user experience. Eye-tracking systems would become an effective assistive technology for integration, adaptation and neutralization of the environmental barrier only when a holistic model can be applied for both design processes and assessment of the functional components of the interaction.

Reducing the Complexity of an Agent-Based Local Heroin Market Model

PubMed Central

Heard, Daniel; Bobashev, Georgiy V.; Morris, Robert J.

2014-01-01

This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed. PMID:25025132

Learning about individuals' health from aggregate data.

PubMed

Colbaugh, Rich; Glass, Kristin

2017-07-01

There is growing awareness that user-generated social media content contains valuable health-related information and is more convenient to collect than typical health data. For example, Twitter has been employed to predict aggregate-level outcomes, such as regional rates of diabetes and child poverty, and to identify individual cases of depression and food poisoning. Models which make aggregate-level inferences can be induced from aggregate data, and consequently are straightforward to build. In contrast, learning models that produce individual-level (IL) predictions, which are more informative, usually requires a large number of difficult-to-acquire labeled IL examples. This paper presents a new machine learning method which achieves the best of both worlds, enabling IL models to be learned from aggregate labels. The algorithm makes predictions by combining unsupervised feature extraction, aggregate-based modeling, and optimal integration of aggregate-level and IL information. Two case studies illustrate how to learn health-relevant IL prediction models using only aggregate labels, and show that these models perform as well as state-of-the-art models trained on hundreds or thousands of labeled individuals.

How does personality matter? An investigation of the impact of extraversion on individuals' SNS use.

PubMed

Deng, Shengli; Liu, Yong; Li, Hongxiu; Hu, Feng

2013-08-01

The fast proliferation of social networking sites (SNS) offers Internet users new possibilities for developing and maintaining their social network. Despite a growing interest in SNS, less research attention has been paid to SNS usage from the perspective of personality, that is, the Big Five personality traits. This study develops a model to elucidate how extraversion, an important dimension of personality, affects the perceptions of SNS users and their continuance intention. The research model is empirically tested with answers gained from 221 usable questionnaires. The results indicate that extraversion positively affects perceived satisfaction, supplementary entertainment, and critical mass directly, and indirectly influences both playfulness and SNS continuance intention.

Toward a user-driven approach to radiology software solutions: putting the wag back in the dog.

PubMed

Morgan, Matthew; Mates, Jonathan; Chang, Paul

2006-09-01

The relationship between healthcare providers and the software industry is evolving. In many cases, industry's traditional, market-driven model is failing to meet the increasingly sophisticated and appropriately individualized needs of providers. Advances in both technology infrastructure and development methodologies have set the stage for the transition from a vendor-driven to a more user-driven process of solution engineering. To make this transition, providers must take an active role in the development process and vendors must provide flexible frameworks on which to build. Only then can the provider/vendor relationship mature from a purchaser/supplier to a codesigner/partner model, where true insight and innovation can occur.

Estimating net drawdown resulting from episodic withdrawals at six well fields in the coastal plain physiographic province of Virginia

USGS Publications Warehouse

Focazio, M.J.; Speiran, G.K.

1993-01-01

The groundwater-flow system of the Virginia Coastal Plain consists of areally extensive and interconnected aquifers. Large, regionally coalescing cones of depression that are caused by large withdrawals of water are found in these aquifers. Local groundwater systems are affected by regional pumping, because of the interactions within the system of aquifers. Accordingly, these local systems are affected by regional groundwater flow and by spatial and temporal differences in withdrawals by various users. A geographic- information system was used to refine a regional groundwater-flow model around selected withdrawal centers. A method was developed in which drawdown maps that were simulated by the regional groundwater-flow model and the principle of superposition could be used to estimate drawdown at local sites. The method was applied to create drawdown maps in the Brightseat/Upper Potomac Aquifer for periods of 3, 6, 9, and 12 months for Chesapeake, Newport News, Norfolk, Portsmouth, Suffolk, and Virginia Beach, Virginia. Withdrawal rates were supplied by the individual localities and remained constant for each simulation period. This provides an efficient method by which the individual local groundwater users can determine the amount of drawdown produced by their wells in a groundwater system that is a water source for multiple users and that is affected by regional-flow systems.

Finding user personal interests by tweet-mining using advanced machine learning algorithm in R

NASA Astrophysics Data System (ADS)

Krithika, L. B.; Roy, P.; Asha Jerlin, M.

2017-11-01

The social-media plays a key role in every individual’s life by anyone’s personal views about their liking-ness/disliking-ness. This methodology is a sharp departure from the traditional techniques of inferring interests of a user from the tweets that he/she posts or receives. It is showed that the topics of interest inferred by the proposed methodology are far superior than the topics extracted by state-of-the-art techniques such as using topic models (Labelled LDA) on tweets. Based upon the proposed methodology, a system has been built, “Who is interested in what”, which can infer the interests of millions of Twitter users. A novel mechanism is proposed to infer topics of interest of individual users in the twitter social network. It has been observed that in twitter, a user generally follows experts on various topics of his/her interest in order to acquire information on those topics. A methodology based on social annotations is used to first deduce the topical expertise of popular twitter users and then transitively infer the interests of the users who follow them.

Empathic design: Research strategies.

PubMed

Thomas, Joyce; McDonagh, Deana

2013-01-01

This paper explores the role of empathy within new product development from the perspective of human-centred design. The authors have developed a range of empathic design tools and strategies that help to identify authentic human needs.For products and services to be effective, they need to satisfy both functional and emotional needs of individuals. In addition, the individual user needs to feel that the product and/or service has been designed 'just for them', otherwise they may misuse, underuse or abandon the product/service. This becomes critical with a product such as a Zimmer frame (walker), when it fails to resonate with the patient due to any stigma the patient may perceive, and thus remains unused.When training young designers to consider the wider community (people unlike themselves) during the design process, it has proven extremely valuable to take them outside their comfort zones, by seeking to develop empathy with the end user for whom they are designing. Empathic modelling offers designers the opportunity to develop greater insight and understanding, in order to support more effective design outcomes. Sensitising designers to the different ways that individuals complete daily tasks has helped to diminish the gap between themselves and others (e.g. people with disabilities).The authors intend for this paper to resonate with health care providers. Human-centred design can help to refocus the designer, by placing the individual end user's needs at the heart of their decision-making.

A simple generative model of collective online behavior.

PubMed

Gleeson, James P; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A; Reed-Tsochas, Felix

2014-07-22

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates--even when using purely observational data without experimental design--that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior.

A simple generative model of collective online behavior

PubMed Central

Gleeson, James P.; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A.; Reed-Tsochas, Felix

2014-01-01

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates—even when using purely observational data without experimental design—that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior. PMID:25002470

Gated Auditory Speech Perception in Elderly Hearing Aid Users and Elderly Normal-Hearing Individuals: Effects of Hearing Impairment and Cognitive Capacity

PubMed Central

Lidestam, Björn; Hällgren, Mathias; Rönnberg, Jerker

2014-01-01

This study compared elderly hearing aid (EHA) users and elderly normal-hearing (ENH) individuals on identification of auditory speech stimuli (consonants, words, and final word in sentences) that were different when considering their linguistic properties. We measured the accuracy with which the target speech stimuli were identified, as well as the isolation points (IPs: the shortest duration, from onset, required to correctly identify the speech target). The relationships between working memory capacity, the IPs, and speech accuracy were also measured. Twenty-four EHA users (with mild to moderate hearing impairment) and 24 ENH individuals participated in the present study. Despite the use of their regular hearing aids, the EHA users had delayed IPs and were less accurate in identifying consonants and words compared with the ENH individuals. The EHA users also had delayed IPs for final word identification in sentences with lower predictability; however, no significant between-group difference in accuracy was observed. Finally, there were no significant between-group differences in terms of IPs or accuracy for final word identification in highly predictable sentences. Our results also showed that, among EHA users, greater working memory capacity was associated with earlier IPs and improved accuracy in consonant and word identification. Together, our findings demonstrate that the gated speech perception ability of EHA users was not at the level of ENH individuals, in terms of IPs and accuracy. In addition, gated speech perception was more cognitively demanding for EHA users than for ENH individuals in the absence of semantic context. PMID:25085610

Calling patterns in human communication dynamics

PubMed Central

Jiang, Zhi-Qiang; Xie, Wen-Jie; Li, Ming-Xia; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2013-01-01

Modern technologies not only provide a variety of communication modes (e.g., texting, cell phone conversation, and online instant messaging), but also detailed electronic traces of these communications between individuals. These electronic traces indicate that the interactions occur in temporal bursts. Here, we study intercall duration of communications of the 100,000 most active cell phone users of a Chinese mobile phone operator. We confirm that the intercall durations follow a power-law distribution with an exponential cutoff at the population level but find differences when focusing on individual users. We apply statistical tests at the individual level and find that the intercall durations follow a power-law distribution for only 3,460 individuals (3.46%). The intercall durations for the majority (73.34%) follow a Weibull distribution. We quantify individual users using three measures: out-degree, percentage of outgoing calls, and communication diversity. We find that the cell phone users with a power-law duration distribution fall into three anomalous clusters: robot-based callers, telecom fraud, and telephone sales. This information is of interest to both academics and practitioners, mobile telecom operators in particular. In contrast, the individual users with a Weibull duration distribution form the fourth cluster of ordinary cell phone users. We also discover more information about the calling patterns of these four clusters (e.g., the probability that a user will call the cr-th most contact and the probability distribution of burst sizes). Our findings may enable a more detailed analysis of the huge body of data contained in the logs of massive users. PMID:23319645

Calling patterns in human communication dynamics.

PubMed

Jiang, Zhi-Qiang; Xie, Wen-Jie; Li, Ming-Xia; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene

2013-01-29

Modern technologies not only provide a variety of communication modes (e.g., texting, cell phone conversation, and online instant messaging), but also detailed electronic traces of these communications between individuals. These electronic traces indicate that the interactions occur in temporal bursts. Here, we study intercall duration of communications of the 100,000 most active cell phone users of a Chinese mobile phone operator. We confirm that the intercall durations follow a power-law distribution with an exponential cutoff at the population level but find differences when focusing on individual users. We apply statistical tests at the individual level and find that the intercall durations follow a power-law distribution for only 3,460 individuals (3.46%). The intercall durations for the majority (73.34%) follow a Weibull distribution. We quantify individual users using three measures: out-degree, percentage of outgoing calls, and communication diversity. We find that the cell phone users with a power-law duration distribution fall into three anomalous clusters: robot-based callers, telecom fraud, and telephone sales. This information is of interest to both academics and practitioners, mobile telecom operators in particular. In contrast, the individual users with a Weibull duration distribution form the fourth cluster of ordinary cell phone users. We also discover more information about the calling patterns of these four clusters (e.g., the probability that a user will call the c(r)-th most contact and the probability distribution of burst sizes). Our findings may enable a more detailed analysis of the huge body of data contained in the logs of massive users.

Model evaluation using a community benchmarking system for land surface models

NASA Astrophysics Data System (ADS)

Mu, M.; Hoffman, F. M.; Lawrence, D. M.; Riley, W. J.; Keppel-Aleks, G.; Kluzek, E. B.; Koven, C. D.; Randerson, J. T.

2014-12-01

Evaluation of atmosphere, ocean, sea ice, and land surface models is an important step in identifying deficiencies in Earth system models and developing improved estimates of future change. For the land surface and carbon cycle, the design of an open-source system has been an important objective of the International Land Model Benchmarking (ILAMB) project. Here we evaluated CMIP5 and CLM models using a benchmarking system that enables users to specify models, data sets, and scoring systems so that results can be tailored to specific model intercomparison projects. Our scoring system used information from four different aspects of global datasets, including climatological mean spatial patterns, seasonal cycle dynamics, interannual variability, and long-term trends. Variable-to-variable comparisons enable investigation of the mechanistic underpinnings of model behavior, and allow for some control of biases in model drivers. Graphics modules allow users to evaluate model performance at local, regional, and global scales. Use of modular structures makes it relatively easy for users to add new variables, diagnostic metrics, benchmarking datasets, or model simulations. Diagnostic results are automatically organized into HTML files, so users can conveniently share results with colleagues. We used this system to evaluate atmospheric carbon dioxide, burned area, global biomass and soil carbon stocks, net ecosystem exchange, gross primary production, ecosystem respiration, terrestrial water storage, evapotranspiration, and surface radiation from CMIP5 historical and ESM historical simulations. We found that the multi-model mean often performed better than many of the individual models for most variables. We plan to publicly release a stable version of the software during fall of 2014 that has land surface, carbon cycle, hydrology, radiation and energy cycle components.

Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sam Alessi; Dennis Keiser

2012-10-01

This document is a user manual for the Dairy Analytics and Nutrient Analysis (DANA) model. DANA provides an analysis of dairy anaerobic digestion technology and allows users to calculate biogas production, co-product valuation, capital costs, expenses, revenue and financial metrics, for user customizable scenarios, dairy and digester types. The model provides results for three anaerobic digester types; Covered Lagoons, Modified Plug Flow, and Complete Mix, and three main energy production technologies; electricity generation, renewable natural gas generation, and compressed natural gas generation. Additional options include different dairy types, bedding types, backend treatment type as well as numerous production, and economicmore » parameters. DANA’s goal is to extend the National Market Value of Anaerobic Digester Products analysis (informa economics, 2012; Innovation Center, 2011) to include a greater and more flexible set of regional digester scenarios and to provide a modular framework for creation of a tool to support farmer and investor needs. Users can set up scenarios from combinations of existing parameters or add new parameters, run the model and view a variety of reports, charts and tables that are automatically produced and delivered over the web interface. DANA is based in the INL’s analysis architecture entitled Generalized Environment for Modeling Systems (GEMS) , which offers extensive collaboration, analysis, and integration opportunities and greatly speeds the ability construct highly scalable web delivered user-oriented decision tools. DANA’s approach uses server-based data processing and web-based user interfaces, rather a client-based spreadsheet approach. This offers a number of benefits over the client-based approach. Server processing and storage can scale up to handle a very large number of scenarios, so that analysis of county, even field level, across the whole U.S., can be performed. Server based databases allow dairy and digester parameters be held and managed in a single managed data repository, while allows users to customize standard values and perform individual analysis. Server-based calculations can be easily extended, versions and upgrades managed, and any changes are immediately available to all users. This user manual describes how to use and/or modify input database tables, run DANA, view and modify reports.« less

Real-time simulation of three-dimensional shoulder girdle and arm dynamics.

PubMed

Chadwick, Edward K; Blana, Dimitra; Kirsch, Robert F; van den Bogert, Antonie J

2014-07-01

Electrical stimulation is a promising technology for the restoration of arm function in paralyzed individuals. Control of the paralyzed arm under electrical stimulation, however, is a challenging problem that requires advanced controllers and command interfaces for the user. A real-time model describing the complex dynamics of the arm would allow user-in-the-loop type experiments where the command interface and controller could be assessed. Real-time models of the arm previously described have not included the ability to model the independently controlled scapula and clavicle, limiting their utility for clinical applications of this nature. The goal of this study therefore was to evaluate the performance and mechanical behavior of a real-time, dynamic model of the arm and shoulder girdle. The model comprises seven segments linked by eleven degrees of freedom and actuated by 138 muscle elements. Polynomials were generated to describe the muscle lines of action to reduce computation time, and an implicit, first-order Rosenbrock formulation of the equations of motion was used to increase simulation step-size. The model simulated flexion of the arm faster than real time, simulation time being 92% of actual movement time on standard desktop hardware. Modeled maximum isometric torque values agreed well with values from the literature, showing that the model simulates the moment-generating behavior of a real human arm. The speed of the model enables experiments where the user controls the virtual arm and receives visual feedback in real time. The ability to optimize potential solutions in simulation greatly reduces the burden on the user during development.

[Meaning of healthy living for health users, professionals and managers].

PubMed

Backes, Dirce Stein; Backes, Marli Terezinha Stein; Rangel, Rosiane Filipin; Erdmann, Alacoque Lorenzini; Büscher, Andreas

2011-01-01

Qualitative research guided by grounded theory method that aimed to understand the meaning of healthy living in a community socially vulnerable for health users, professionals and managers. Data were collected through individual interview with 25 participants, among health users, professionals and managers. Data analysis was done in a comparative way according to grounded theory. For health users, healthy living is associated with basic living conditions, with inclusion opportunities and social participation and with interaction and associative possibilities; for health professionals, healthy living is related to political and social articulations; and for managers, it is related to the development of strategies that can reorient the current health model. We conclude that healthy living is a singular, plural and complex process that is built based on the imaginary and on the experiences of each human being.

Techniques for predicting high-risk drivers for alcohol countermeasures. Volume 1, Technical report

DOT National Transportation Integrated Search

1979-05-01

This technical report, a companion to the Volume II User Manual by the same name describes the development and testing of predictive models for identifying individual with a high risk of alcohol/related (A/R) crash involvement. From a literature revi...

A Personalized Health Information Retrieval System

PubMed Central

Wang, Yunli; Liu, Zhenkai

2005-01-01

Consumers face barriers when seeking health information on the Internet. A Personalized Health Information Retrieval System (PHIRS) is proposed to recommend health information for consumers. The system consists of four modules: (1) User modeling module captures user’s preference and health interests; (2) Automatic quality filtering module identifies high quality health information; (3) Automatic text difficulty rating module classifies health information into professional or patient educational materials; and (4) User profile matching module tailors health information for individuals. The initial results show that PHIRS could assist consumers with simple search strategies. PMID:16779435

'Fly Like This': Natural Language Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.

Toward an Open-Ended BCI: A User-Centered Coadaptive Design.

PubMed

Dhindsa, Kiret; Carcone, Dean; Becker, Suzanna

2017-10-01

Brain-computer interfaces (BCIs) allow users to control a device by interpreting their brain activity. For simplicity, these devices are designed to be operated by purposefully modulating specific predetermined neurophysiological signals, such as the sensorimotor rhythm. However, the ability to modulate a given neurophysiological signal is highly variable across individuals, contributing to the inconsistent performance of BCIs for different users. These differences suggest that individuals who experience poor BCI performance with one class of brain signals might have good results with another. In order to take advantage of individual abilities as they relate to BCI control, we need to move beyond the current approaches. In this letter, we explore a new BCI design aimed at a more individualized and user-focused experience, which we call open-ended BCI. Individual users were given the freedom to discover their own mental strategies as opposed to being trained to modulate a given brain signal. They then underwent multiple coadaptive training sessions with the BCI. Our first open-ended BCI performed similarly to comparable BCIs while accommodating a wider variety of mental strategies without a priori knowledge of the specific brain signals any individual might use. Post hoc analysis revealed individual differences in terms of which sensory modality yielded optimal performance. We found a large and significant effect of individual differences in background training and expertise, such as in musical training, on BCI performance. Future research should be focused on finding more generalized solutions to user training and brain state decoding methods to fully utilize the abilities of different individuals in an open-ended BCI. Accounting for each individual's areas of expertise could have important implications on BCI training and BCI application design.

Personalized symptoms forecasting for pollen-induced allergic rhinitis sufferers

NASA Astrophysics Data System (ADS)

Voukantsis, D.; Berger, U.; Tzima, F.; Karatzas, K.; Jaeger, S.; Bergmann, K. C.

2015-07-01

Hay fever is a pollen-induced allergic reaction that strongly affects the overall quality of life of many individuals. The disorder may vary in severity and symptoms depending on patient-specific factors such as genetic disposition, individual threshold of pollen concentration levels, medication, former immunotherapy, and others. Thus, information services that improve the quality of life of hay fever sufferers must address the needs of each individual separately. In this paper, we demonstrate the development of information services that offer personalized pollen-induced symptoms forecasts. The backbone of these services consists of data of allergic symptoms reported by the users of the Personal Hay Fever Diary system and pollen concentration levels (European Aeroallergen Network) in several sampling sites. Data were analyzed using computational intelligence methods, resulting in highly customizable forecasting models that offer personalized warnings to users of the Patient Hay Fever Diary system. The overall system performance for the pilot area (Vienna and Lower Austria) reached a correlation coefficient of r = 0.71 ± 0.17 (average ± standard deviation) in a sample of 219 users with major contribution to the Pollen Hay Fever Diary system and an overall performance of r = 0.66 ± 0.18 in a second sample of 393 users, with minor contribution to the system. These findings provide an example of combining data from different sources using advanced data engineering in order to develop innovative e-health services with the capacity to provide more direct and personalized information to allergic rhinitis sufferers.

SALMOD: A population model for salmonids: user's manual. Version W3

USGS Publications Warehouse

Bartholow, John; Heasley, John; Laake, Jeff; Sandelin, Jeff; Coughlan, Beth A.K.; Moos, Alan

2002-01-01

SALMOD is a computer model that simulates the dynamics of freshwater salmonid populations, both anadromous and resident. The conceptual model was developed in a workshop setting (Williamson et al. 1993) using fish experts concerned with Trinity River chinook restoration. The model builds on the foundation laid by similar models (see Cheslak and Jacobson 1990). The model’s premise that that egg and fish mortality are directly related to spatially and temporally variable micro- and macrohabitat limitations, which themselves are related to the timing and amount of streamflow and other meteorological variables. Habitat quality and capacity are characterized by the hydraulic and thermal properties of individual mesohabitats, which we use as spatial “computation units” in the model. The model tracks a population of spatially distinct cohorts that originate as gees and grow from one life stage to another as a function of local water temperature. Individual cohorts either remain in the computational unit in which they emerged or move, in whole or in part, to nearby units (see McCormick et al. 1998). Model processes include spawning (with red superimposition and incubation losses), growth (including egg maturation), mortality, and movement (freshet-induced, habitat-induced, and seasonal). Model processes are implemented such that the user (modeler) has the ability to more-or-less program the model on the fly to create the dynamics thought to animate the population. SALMOD then tabulates the various causes of mortality and the whereabouts of fish.

Development and usability testing of a web-based cancer symptom and quality-of-life support intervention.

PubMed

Wolpin, S E; Halpenny, B; Whitman, G; McReynolds, J; Stewart, M; Lober, W B; Berry, D L

2015-03-01

The feasibility and acceptability of computerized screening and patient-reported outcome measures have been demonstrated in the literature. However, patient-centered management of health information entails two challenges: gathering and presenting data using "patient-tailored" methods and supporting "patient-control" of health information. The design and development of many symptom and quality-of-life information systems have not included opportunities for systematically collecting and analyzing user input. As part of a larger clinical trial, the Electronic Self-Report Assessment for Cancer-II project, participatory design approaches were used to build and test new features and interfaces for patient/caregiver users. The research questions centered on patient/caregiver preferences with regard to the following: (a) content, (b) user interface needs, (c) patient-oriented summary, and (d) patient-controlled sharing of information with family, caregivers, and clinicians. Mixed methods were used with an emphasis on qualitative approaches; focus groups and individual usability tests were the primary research methods. Focus group data were content analyzed, while individual usability sessions were assessed with both qualitative and quantitative methods. We identified 12 key patient/caregiver preferences through focus groups with 6 participants. We implemented seven of these preferences during the iterative design process. We deferred development for some of the preferences due to resource constraints. During individual usability testing (n = 8), we were able to identify 65 usability issues ranging from minor user confusion to critical errors that blocked task completion. The participatory development model that we used led to features and design revisions that were patient centered. We are currently evaluating new approaches for the application interface and for future research pathways. We encourage other researchers to adopt user-centered design approaches when building patient-centered technologies. © The Author(s) 2014.

Change and Anomaly Detection in Real-Time GPS Data

NASA Astrophysics Data System (ADS)

Granat, R.; Pierce, M.; Gao, X.; Bock, Y.

2008-12-01

The California Real-Time Network (CRTN) is currently generating real-time GPS position data at a rate of 1-2Hz at over 80 locations. The CRTN data presents the possibility of studying dynamical solid earth processes in a way that complements existing seismic networks. To realize this possibility we have developed a prototype system for detecting changes and anomalies in the real-time data. Through this system, we can can correlate changes in multiple stations in order to detect signals with geographical extent. Our approach involves developing a statistical model for each GPS station in the network, and then using those models to segment the time series into a number of discrete states described by the model. We use a hidden Markov model (HMM) to describe the behavior of each station; fitting the model to the data requires neither labeled training examples nor a priori information about the system. As such, HMMs are well suited to this problem domain, in which the data remains largely uncharacterized. There are two main components to our approach. The first is the model fitting algorithm, regularized deterministic annealing expectation- maximization (RDAEM), which provides robust, high-quality results. The second is a web service infrastructure that connects the data to the statistical modeling analysis and allows us to easily present the results of that analysis through a web portal interface. This web service approach facilitates the automatic updating of station models to keep pace with dynamical changes in the data. Our web portal interface is critical to the process of interpreting the data. A Google Maps interface allows users to visually interpret state changes not only on individual stations but across the entire network. Users can drill down from the map interface to inspect detailed results for individual stations, download the time series data, and inspect fitted models. Alternatively, users can use the web portal look at the evolution of changes on the network by moving backwards and forwards in time.

Grow--a computer subroutine that projects the growth of trees in the Lake States' forests.

Treesearch

Gary J. Brand

1981-01-01

A computer subroutine, Grow, has been written in 1977 Standard FORTRAN to implement a distance-independent, individual tree growth model for Lake States' forests. Grow is a small and easy-to-use version of the growth model. All the user has to do is write a calling program to read initial conditions, call Grow, and summarize the results.

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users

PubMed Central

Veksler, Vladislav D.; Buchler, Norbou; Hoffman, Blaine E.; Cassenti, Daniel N.; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting. PMID:29867661

ISBP: Understanding the Security Rule of Users' Information-Sharing Behaviors in Partnership

PubMed Central

Wu, Hongchen; Wang, Xinjun

2016-01-01

The rapid growth of social network data has given rise to high security awareness among users, especially when they exchange and share their personal information. However, because users have different feelings about sharing their information, they are often puzzled about who their partners for exchanging information can be and what information they can share. Is it possible to assist users in forming a partnership network in which they can exchange and share information with little worry? We propose a modified information sharing behavior prediction (ISBP) model that can help in understanding the underlying rules by which users share their information with partners in light of three common aspects: what types of items users are likely to share, what characteristics of users make them likely to share information, and what features of users’ sharing behavior are easy to predict. This model is applied with machine learning techniques in WEKA to predict users’ decisions pertaining to information sharing behavior and form them into trustable partnership networks by learning their features. In the experiment section, by using two real-life datasets consisting of citizens’ sharing behavior, we identify the effect of highly sensitive requests on sharing behavior adjacent to individual variables: the younger participants’ partners are more difficult to predict than those of the older participants, whereas the partners of people who are not computer majors are easier to predict than those of people who are computer majors. Based on these findings, we believe that it is necessary and feasible to offer users personalized suggestions on information sharing decisions, and this is pioneering work that could benefit college researchers focusing on user-centric strategies and website owners who want to collect more user information without raising their privacy awareness or losing their trustworthiness. PMID:26950064

Predictor Combination in Binary Decision-Making Situations

ERIC Educational Resources Information Center

McGrath, Robert E.

2008-01-01

Professional psychologists are often confronted with the task of making binary decisions about individuals, such as predictions about future behavior or employee selection. Test users familiar with linear models and Bayes's theorem are likely to assume that the accuracy of decisions is consistently improved by combination of outcomes across valid…

[Evaluation of hazards caused by magnetic field emitted from magnetotherapy applicator to the users of bone conduction hearing prostheses].

PubMed

Zradziński, Patryk; Karpowicz, Jolanta; Gryz, Krzysztof; Leszko, Wiesław

2017-06-27

Low frequency magnetic field, inducing electrical field (E_in) inside conductive structures may directly affect the human body, e.g., by electrostimulation in the nervous system. In addition, the spatial distribution and level of E_in are disturbed in tissues neighbouring the medical implant. Numerical models of magneto-therapeutic applicator (emitting sinusoidal magnetic field of frequency 100 Hz) and the user of hearing implant (based on bone conduction: Bonebridge type - IS-BB or BAHA (bone anchorde hearing aid) type - IS-BAHA) were worked out. Values of E_in were analyzed in the model of the implant user's head, e.g., physiotherapist, placed next to the applicator. It was demonstrated that the use of IS-BB or IS-BAHA makes electromagnetic hazards significantly higher (up to 4-fold) compared to the person without implant exposed to magnetic field heterogeneous in space. Hazards for IS-BAHA users are higher than those for IS-BB users. It was found that applying the principles of directive 2013/35/EU, at exposure to magnetic field below exposure limits the direct biophysical effects of exposure in hearing prosthesis users may exceed relevant limits. Whereas applying principles and limits set up by Polish labor law or the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines, the compliance with the exposure limits also ensures the compliance with relevant limits of electric field induced in the body of hearing implant user. It is necessary to assess individually electromagnetic hazard concerning hearing implant users bearing in mind significantly higher hazards to them compared to person without implant or differences between levels of hazards faced by users of implants of various structural or technological solutions. Med Pr 2017;68(4):469-477. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Modeling Traffic on the Web Graph

NASA Astrophysics Data System (ADS)

Meiss, Mark R.; Gonçalves, Bruno; Ramasco, José J.; Flammini, Alessandro; Menczer, Filippo

Analysis of aggregate and individual Web requests shows that PageRank is a poor predictor of traffic. We use empirical data to characterize properties of Web traffic not reproduced by Markovian models, including both aggregate statistics such as page and link traffic, and individual statistics such as entropy and session size. As no current model reconciles all of these observations, we present an agent-based model that explains them through realistic browsing behaviors: (1) revisiting bookmarked pages; (2) backtracking; and (3) seeking out novel pages of topical interest. The resulting model can reproduce the behaviors we observe in empirical data, especially heterogeneous session lengths, reconciling the narrowly focused browsing patterns of individual users with the extreme variance in aggregate traffic measurements. We can thereby identify a few salient features that are necessary and sufficient to interpret Web traffic data. Beyond the descriptive and explanatory power of our model, these results may lead to improvements in Web applications such as search and crawling.

Consumer-operated service program members' explanatory models of mental illness and recovery.

PubMed

Hoy, Janet M

2014-10-01

Incorporating individuals' understandings and explanations of mental illness into service delivery offers benefits relating to increased service relevance and meaning. Existing research delineates explanatory models of mental illness held by individuals in home, outpatient, and hospital-based contexts; research on models held by those in peer-support contexts is notably absent. In this article, I describe themes identified within and across explanatory models of mental illness and recovery held by mental health consumers (N = 24) at one peer center, referred to as a consumer-operated service center (COSP). Participants held explanatory models inclusive of both developmental stressors and biomedical causes, consistent with a stress-diathesis model (although no participant explicitly referenced such). Explicit incorporation of stress-diathesis constructs into programming at this COSP offers the potential of increasing service meaning and relevance. Identifying and incorporating shared meanings across individuals' understandings of mental illness likewise can increase relevance and meaning for particular subgroups of service users. © The Author(s) 2014.

Organizational performance focused on users' quality of life: The role of service climate and "contribution-to-others" wellbeing beliefs.

PubMed

Pătraș, Luminița; Martínez-Tur, Vicente; Estreder, Yolanda; Gracia, Esther; Moliner, Carolina; Peiró, José María

2018-06-01

The investigation of organizational factors as precursors of the quality of life (QoL) of service users in organizations for individuals with intellectual disability has been relatively neglected.With this in mind, this study tests the mediation of service climate between employee's "contribution-to-others" wellbeing beliefs (COWBs) and organizational performance focused on the QoL of individuals with intellectual disability. A total of 104 organizations participated in the study. Data were collected from 885 employees and 809 family members of individuals with intellectual disability. The results of the multilevel mediation model supported the hypotheses. When employees believe that their own wellbeing depends on helping others (COWBs) service climate reported by employees is stimulated. Service climate in turn was associated with organizational performance focused on QoL of people with intellectual disability, assessed by family members. The manuscript concludes with theoretical and practical implications of the study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Online irrigation service for fruit und vegetable crops at farmers site

NASA Astrophysics Data System (ADS)

Janssen, W.

2009-09-01

Online irrigation service for fruit und vegetable crops at farmers site by W. Janssen, German Weather Service, 63067 Offenbach Agrowetter irrigation advice is a product which calculates the present soil moisture as well as the soil moisture to be expected over the next 5 days for over 30 different crops. It's based on a water balance model and provides targeted recommendations for irrigation. Irrigation inputs according to the soil in order to avoid infiltration and, as a consequence thereof, the undesired movement of nitrate and plant protectants into the groundwater. This interactive 'online system' takes into account the user's individual circumstances such as crop and soil characteristics and the precipitation and irrigation amounts at the user's site. Each user may calculate up to 16 different enquiries simultaneously (different crops or different emergence dates). The user can calculate the individual soil moistures for his fields with a maximum effort of 5 minutes per week only. The sources of water are precipitation and irrigation whereas water losses occur due to evapotranspiration and infiltration of water into the ground. The evapotranspiration is calculated by multiplying a reference evapotranspiration (maximum evapotranspiration over grass) with the so-called crop coefficients (kc values) that have been developed by the Geisenheim Research Centre, Vegetable Crops Branch. Kc values depending on the crop and the individual plant development stage. The reference evapotranspiration is calculated from a base weather station user has chosen (out of around 500 weather stations) using Penman method based on daily values. After chosen a crop and soil type the user must manually enter the precipitation data measured at the site, the irrigation water inputs and the dates for a few phenological stages. Economical aspects can be considered by changing the values of soil moisture from which recommendations for irrigation start from optimal to necessary plant supply. Previous comparative measurements carried out by the Agricultural Administration of Baden-Württemberg relating to potatoes, onions, vine stocks, and strawberries agreed very well with the calculations.

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users.

PubMed

Li, Tianhao; Fu, Qian-Jie

2011-08-01

(1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. VGD was measured using two talker sets with different inter-gender fundamental frequencies (F(0)), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Eleven postlingually deaf CI users. The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments.

Modeling open-set spoken word recognition in postlingually deafened adults after cochlear implantation: some preliminary results with the neighborhood activation model.

PubMed

Meyer, Ted A; Frisch, Stefan A; Pisoni, David B; Miyamoto, Richard T; Svirsky, Mario A

2003-07-01

Do cochlear implants provide enough information to allow adult cochlear implant users to understand words in ways that are similar to listeners with acoustic hearing? Can we use a computational model to gain insight into the underlying mechanisms used by cochlear implant users to recognize spoken words? The Neighborhood Activation Model has been shown to be a reasonable model of word recognition for listeners with normal hearing. The Neighborhood Activation Model assumes that words are recognized in relation to other similar-sounding words in a listener's lexicon. The probability of correctly identifying a word is based on the phoneme perception probabilities from a listener's closed-set consonant and vowel confusion matrices modified by the relative frequency of occurrence of the target word compared with similar-sounding words (neighbors). Common words with few similar-sounding neighbors are more likely to be selected as responses than less common words with many similar-sounding neighbors. Recent studies have shown that several of the assumptions of the Neighborhood Activation Model also hold true for cochlear implant users. Closed-set consonant and vowel confusion matrices were obtained from 26 postlingually deafened adults who use cochlear implants. Confusion matrices were used to represent input errors to the Neighborhood Activation Model. Responses to the different stimuli were then generated by the Neighborhood Activation Model after incorporating the frequency of occurrence counts of the stimuli and their neighbors. Model outputs were compared with obtained performance measures on the Consonant-Vowel Nucleus-Consonant word test. Information transmission analysis was used to assess whether the Neighborhood Activation Model was able to successfully generate and predict word and individual phoneme recognition by cochlear implant users. The Neighborhood Activation Model predicted Consonant-Vowel Nucleus-Consonant test words at levels similar to those correctly identified by the cochlear implant users. The Neighborhood Activation Model also predicted phoneme feature information well. The results obtained suggest that the Neighborhood Activation Model provides a reasonable explanation of word recognition by postlingually deafened adults after cochlear implantation. It appears that multichannel cochlear implants give cochlear implant users access to their mental lexicons in a manner that is similar to listeners with acoustic hearing. The lexical properties of the test stimuli used to assess performance are important to spoken-word recognition and should be included in further models of the word recognition process.

Mining data on usage of electronic nicotine delivery systems (ENDS) from YouTube videos.

PubMed

Hua, My; Yip, Henry; Talbot, Prue

2013-03-01

The objective was to analyse and compare puff and exhalation duration for individuals using electronic nicotine delivery systems (ENDS) and conventional cigarettes in YouTube videos. Video data from YouTube videos were analysed to quantify puff duration and exhalation duration during use of conventional tobacco-containing cigarettes and ENDS. For ENDS, comparisons were also made between 'advertisers' and 'non-advertisers', genders, brands of ENDS, and models of ENDS within one brand. Puff duration (mean =2.4 s) for conventional smokers in YouTube videos (N=9) agreed well with prior publications. Puff duration was significantly longer for ENDS users (mean =4.3 s) (N = 64) than for conventional cigarette users, and puff duration varied significantly among ENDS brands. For ENDS users, puff duration and exhalation duration were not significantly affected by 'advertiser' status, gender or variation in models within a brand. Men outnumbered women by about 5:1, and most users were between 19 and 35 years of age. YouTube videos provide a valuable resource for studying ENDS usage. Longer puff duration may help ENDS users compensate for the apparently poor delivery of nicotine from ENDS. As with conventional cigarette smoking, ENDS users showed a large variation in puff duration (range =1.9-8.3 s). ENDS puff duration should be considered when designing laboratory and clinical trials and in developing a standard protocol for evaluating ENDS performance.

Semantic-gap-oriented active learning for multilabel image annotation.

PubMed

Tang, Jinhui; Zha, Zheng-Jun; Tao, Dacheng; Chua, Tat-Seng

2012-04-01

User interaction is an effective way to handle the semantic gap problem in image annotation. To minimize user effort in the interactions, many active learning methods were proposed. These methods treat the semantic concepts individually or correlatively. However, they still neglect the key motivation of user feedback: to tackle the semantic gap. The size of the semantic gap of each concept is an important factor that affects the performance of user feedback. User should pay more efforts to the concepts with large semantic gaps, and vice versa. In this paper, we propose a semantic-gap-oriented active learning method, which incorporates the semantic gap measure into the information-minimization-based sample selection strategy. The basic learning model used in the active learning framework is an extended multilabel version of the sparse-graph-based semisupervised learning method that incorporates the semantic correlation. Extensive experiments conducted on two benchmark image data sets demonstrated the importance of bringing the semantic gap measure into the active learning process.

Improved personalized recommendation based on a similarity network

NASA Astrophysics Data System (ADS)

Wang, Ximeng; Liu, Yun; Xiong, Fei

2016-08-01

A recommender system helps individual users find the preferred items rapidly and has attracted extensive attention in recent years. Many successful recommendation algorithms are designed on bipartite networks, such as network-based inference or heat conduction. However, most of these algorithms define the resource-allocation methods for an average allocation. That is not reasonable because average allocation cannot indicate the user choice preference and the influence between users which leads to a series of non-personalized recommendation results. We propose a personalized recommendation approach that combines the similarity function and bipartite network to generate a similarity network that improves the resource-allocation process. Our model introduces user influence into the recommender system and states that the user influence can make the resource-allocation process more reasonable. We use four different metrics to evaluate our algorithms for three benchmark data sets. Experimental results show that the improved recommendation on a similarity network can obtain better accuracy and diversity than some competing approaches.

Enterprise Reference Library

NASA Technical Reports Server (NTRS)

Bickham, Grandin; Saile, Lynn; Havelka, Jacque; Fitts, Mary

2011-01-01

Introduction: Johnson Space Center (JSC) offers two extensive libraries that contain journals, research literature and electronic resources. Searching capabilities are available to those individuals residing onsite or through a librarian s search. Many individuals have rich collections of references, but no mechanisms to share reference libraries across researchers, projects, or directorates exist. Likewise, information regarding which references are provided to which individuals is not available, resulting in duplicate requests, redundant labor costs and associated copying fees. In addition, this tends to limit collaboration between colleagues and promotes the establishment of individual, unshared silos of information The Integrated Medical Model (IMM) team has utilized a centralized reference management tool during the development, test, and operational phases of this project. The Enterprise Reference Library project expands the capabilities developed for IMM to address the above issues and enhance collaboration across JSC. Method: After significant market analysis for a multi-user reference management tool, no available commercial tool was found to meet this need, so a software program was built around a commercial tool, Reference Manager 12 by The Thomson Corporation. A use case approach guided the requirements development phase. The premise of the design is that individuals use their own reference management software and export to SharePoint when their library is incorporated into the Enterprise Reference Library. This results in a searchable user-specific library application. An accompanying share folder will warehouse the electronic full-text articles, which allows the global user community to access full -text articles. Discussion: An enterprise reference library solution can provide a multidisciplinary collection of full text articles. This approach improves efficiency in obtaining and storing reference material while greatly reducing labor, purchasing and duplication costs. Most importantly, increasing collaboration across research groups provides unprecedented access to information relevant to NASA s mission. Conclusion: This project is an expansion and cost-effective leveraging of the existing JSC centralized library. Adding key word and author search capabilities and an alert function for notifications about new articles, based on users profiles, represent examples of future enhancements.

A method for real-time generation of augmented reality work instructions via expert movements

NASA Astrophysics Data System (ADS)

Bhattacharya, Bhaskar; Winer, Eliot

2015-03-01

Augmented Reality (AR) offers tremendous potential for a wide range of fields including entertainment, medicine, and engineering. AR allows digital models to be integrated with a real scene (typically viewed through a video camera) to provide useful information in a variety of contexts. The difficulty in authoring and modifying scenes is one of the biggest obstacles to widespread adoption of AR. 3D models must be created, textured, oriented and positioned to create the complex overlays viewed by a user. This often requires using multiple software packages in addition to performing model format conversions. In this paper, a new authoring tool is presented which uses a novel method to capture product assembly steps performed by a user with a depth+RGB camera. Through a combination of computer vision and imaging process techniques, each individual step is decomposed into objects and actions. The objects are matched to those in a predetermined geometry library and the actions turned into animated assembly steps. The subsequent instruction set is then generated with minimal user input. A proof of concept is presented to establish the method's viability.

Combining multiple earthquake models in real time for earthquake early warning

USGS Publications Warehouse

Minson, Sarah E.; Wu, Stephen; Beck, James L; Heaton, Thomas H.

2017-01-01

The ultimate goal of earthquake early warning (EEW) is to provide local shaking information to users before the strong shaking from an earthquake reaches their location. This is accomplished by operating one or more real‐time analyses that attempt to predict shaking intensity, often by estimating the earthquake’s location and magnitude and then predicting the ground motion from that point source. Other EEW algorithms use finite rupture models or may directly estimate ground motion without first solving for an earthquake source. EEW performance could be improved if the information from these diverse and independent prediction models could be combined into one unified, ground‐motion prediction. In this article, we set the forecast shaking at each location as the common ground to combine all these predictions and introduce a Bayesian approach to creating better ground‐motion predictions. We also describe how this methodology could be used to build a new generation of EEW systems that provide optimal decisions customized for each user based on the user’s individual false‐alarm tolerance and the time necessary for that user to react.

Perceived parenting behavior in the childhood of cocaine users: relationship with genotype and personality traits.

PubMed

Gerra, G; Zaimovic, A; Garofano, L; Ciusa, F; Moi, G; Avanzini, P; Talarico, E; Gardini, F; Brambilla, F; Manfredini, M; Donnini, C

2007-01-05

Low parental care during childhood, a pattern characteristic of an "affectionless control" rearing style was frequently reported in the history of addicted individuals. Parents' childrearing regimes and children's genetic predispositions, with their own behavioral characteristics, have been seen to be closely interwoven, probably affecting children's development and addictive behavior susceptibility. In the present study, parents care perception, aggressive personality traits, and genotype (serotonin transporter promoter gene--5-HTTLPR) have been investigated in cocaine users and healthy control subjects. PBI scores (maternal and paternal care) were lower and BDHI scores (aggressiveness) higher in cocaine users in comparison with controls and significant differences in the perception of either paternal or maternal care were observed between cocaine users and non-users. The short-short (SS) genotype frequency was significantly higher among cocaine users compared with control subjects (P = 0.04). Logistic regression proves that persons bearing the SS genotype have a risk of becoming cocaine user almost three times higher than those having the LL genotype. Estimations of the effects of other factors potentially affecting the risk of being cocaine addicted clearly prove the significant impact of aggressiveness: the highest the score, the highest the risk of becoming cocaine user. Moreover, paternal and maternal care perception significantly improve the fit of the model (the log likelihood decreases passing from -105.9 to -89.8, LR test = 32.17, P-value = 0.0000). Each unit increase in the PBI score yields a significant 12% and 10% decrease of the risk of becoming cocaine user, respectively for paternal and maternal care. Interestingly, once controlled for the PBI score, the relative risk associated to the SS genotype drops strikingly and becomes no longer statistically significant. On the whole, our preliminary data suggest that the association between 5-HT transporter polymorphism and psycho-stimulant use may be mediated by mother-child relationship and parental attachment perception, both being environmental and genetic factors involved in the proneness to substance use disorders, particularly in aggressive-antisocial individuals.

Master of Puppets: An Animation-by-Demonstration Computer Puppetry Authoring Framework

NASA Astrophysics Data System (ADS)

Cui, Yaoyuan; Mousas, Christos

2018-03-01

This paper presents Master of Puppets (MOP), an animation-by-demonstration framework that allows users to control the motion of virtual characters (puppets) in real time. In the first step, the user is asked to perform the necessary actions that correspond to the character's motions. The user's actions are recorded, and a hidden Markov model is used to learn the temporal profile of the actions. During the runtime of the framework, the user controls the motions of the virtual character based on the specified activities. The advantage of the MOP framework is that it recognizes and follows the progress of the user's actions in real time. Based on the forward algorithm, the method predicts the evolution of the user's actions, which corresponds to the evolution of the character's motion. This method treats characters as puppets that can perform only one motion at a time. This means that combinations of motion segments (motion synthesis), as well as the interpolation of individual motion sequences, are not provided as functionalities. By implementing the framework and presenting several computer puppetry scenarios, its efficiency and flexibility in animating virtual characters is demonstrated.

CRUX: a Compliant Robotic Upper-Extremity eXosuit for Lightweight, Portable, Multi-DoF Muscular Augmentation

NASA Technical Reports Server (NTRS)

Lessard, Steven; Pansodtee, Pattawong; Robbins, Ash; Baltaxe-Admony, Leya Breanna; Teodorescu, Mircea; Kurniawan,Sri; Agogino, Adrian; Kurniawan, Sri

2017-01-01

Wearable robots can potentially offer their users enhanced stability and strength. These augmentations are ideally designed to actuate harmoniously with the users movements and provide extra force as needed. The creation of such robots, however, is particularly challenging due to the complexity of the underlying human body. In this paper, we present a compliant, robotic exosuit for upper-extremities called CRUX. This exosuit, inspired by tensegrity models of the human arm, features a lightweight (1.3 kg), flexible design for portability. We also show how CRUX maintains full flexibility of the upper-extremities for its users while providing multi- DoF augmentative strength to the major muscles of the arm, as evident by tracking the heart rate of an individual exercising said arm. Exosuits such as CRUX may be useful in physical therapy and in extreme environments where users are expected to exert their bodies to the fullest extent.

Individual and Environmental Correlates to Quality of Life in Park Users in Colombia

PubMed Central

Camargo, Diana Marina

2017-01-01

Purpose: To explore individual and environmental correlates to quality of life (QoL) in park users in Colombia. Methods: A cross-sectional study with face-to-face interviews was conducted with 1392 park users from ten parks in Colombia. The survey included sociodemographic questions, health condition assessed with EuroQuol-5-Dimensions-5-Levels; in addition, questions about accessibility to the parks and perceptions about quality of infrastructure and green areas were asked. The Spanish version of the questionnaire EUROHIS-QOL-8 items was applied to assess QoL. Log-binomial regression models were applied for analyses. Results: Years of schooling, visits to the park with a companion, active use of the park, a maximum score for quality of trees and walking paths, and the perception of safety on the way to the park were positively associated with a better QoL (p < 0.05). Health conditions related to problems in the ability to perform activities of daily living and anxiety/depression showed negative associations. Conclusions: The present study contributes to the Latin American studies by providing information on how parks in an intermediate city may contribute to increased QoL of park users through safety in neighborhoods, social support, active use, and aesthetics, cleanliness, and care of green areas. PMID:29048373

A Comparison of Daily Versus Weekly Electronic Cigarette Users in Treatment for Substance Abuse.

PubMed

Gubner, Noah R; Pagano, Anna; Tajima, Barbara; Guydish, Joseph

2018-04-02

This research examined electronic cigarette (e-cigarette) use by individuals in treatment for substance abuse, a population with a high prevalence of tobacco use and poor smoking cessation outcomes. We surveyed 1127 individuals from 24 substance abuse treatment centers across the United States. Bivariate analyses and logistic regression were used to examine factors associated with daily (N = 87) versus weekly (N = 81) e-cigarette use. Among the full sample, 59.8% reported any lifetime use of e-cigarettes, with 23.6% reporting past 30-day use. Daily e-cigarette users were more likely to have used second-generation, tank-type e-cigarettes, χ2(1,N = 165) = 11.54, p = .001, used more flavors overall, t(168) = 2.15, p = .03, and were more likely to report using their e-cigarette continuously throughout the day, χ2(4,N = 168) = 16.7, p = .002, compared to weekly e-cigarette users. Over half (57.7%) of the daily and weekly e-cigarette users reported having an e-cigarette device that broke. The logistic regression model adjusting for clinic type and days with poor mental health found that daily e-cigarette users were significantly more likely than weekly e-cigarette users to be from methadone clinics (adjusted odds ratio [AOR] = 2.40, p = .04), and former smokers (AOR = 6.37, p < .002). Daily e-cigarette users in substance abuse treatment were more likely to be from methadone clinics and former cigarette smokers. However, the majority (73.6%) of daily e-cigarette users were current cigarette smokers. E-cigarette device type reliability (eg, breakage) may be an important factor to consider among drug treatment and other populations with lower socioeconomic status. This study found several differences in the device type, flavors, and use characteristics of daily versus weekly e-cigarette users. While majority of e-cigarette users in substance abuse treatment were current cigarette smokers, daily e-cigarette users were more likely to be former cigarette smokers. Administrators of substance abuse treatment programs should evaluate potential benefits and harms of e-cigarettes when developing program policies.

Translating statistical species-habitat models to interactive decision support tools

USGS Publications Warehouse

Wszola, Lyndsie S.; Simonsen, Victoria L.; Stuber, Erica F.; Gillespie, Caitlyn R.; Messinger, Lindsey N.; Decker, Karie L.; Lusk, Jeffrey J.; Jorgensen, Christopher F.; Bishop, Andrew A.; Fontaine, Joseph J.

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

Translating statistical species-habitat models to interactive decision support tools.

PubMed

Wszola, Lyndsie S; Simonsen, Victoria L; Stuber, Erica F; Gillespie, Caitlyn R; Messinger, Lindsey N; Decker, Karie L; Lusk, Jeffrey J; Jorgensen, Christopher F; Bishop, Andrew A; Fontaine, Joseph J

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

Translating statistical species-habitat models to interactive decision support tools

PubMed Central

Simonsen, Victoria L.; Stuber, Erica F.; Gillespie, Caitlyn R.; Messinger, Lindsey N.; Decker, Karie L.; Lusk, Jeffrey J.; Jorgensen, Christopher F.; Bishop, Andrew A.; Fontaine, Joseph J.

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences. PMID:29236707

EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shu, Qingya; Guo, Hanqi; Che, Limei

We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based onmore » ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.« less

Remote health coaching for interactive exercise with older adults in a home environment.

PubMed

Jimison, Holly B; Hagler, Stuart; Kurillo, Gregorij; Bajcsy, Ruzena; Pavel, Misha

2015-01-01

Optimal health coaching interventions are tailored to individuals' needs, preferences, motivations, barriers, timing, and readiness to change. Technology approaches are useful in both monitoring a user's adherence to their behavior change goals and also in providing just-in-time feedback and coaching messages. User models that incorporate dynamically varying behavior change variables with algorithms that trigger tailored messages provide a framework for making health interventions more effective. These principles are applied in the described system for assisting older adults in meeting their physical exercise goals with a tailored interactive video system with just-in-time feedback and encouragement.

CHAD User's Guide: Extracting Human Activity Information from CHAD on the PC

EPA Pesticide Factsheets

User manual that includes tutorials, what's inside the CHAD databases, background on individuals studies in CHAD, using data form individual studies, caveats, problems, notes, and database design and development.

75 FR 22779 - FIFRA Scientific Advisory Panel; Notice of Public Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-30

... exposure factors to generate time series of exposure for simulated individuals. One-stage or two-stage...., built-in simple source-to- concentration module, user-entered time series from other models or field... FOR FURTHER INFORMATION CONTACT at least 10 days prior to the meeting to give EPA as much time as...

Perception of the influence of environmental factors in the use of electronic planning devices in adults with cognitive disabilities.

PubMed

Adolfsson, Päivi; Lindstedt, Helena; Pettersson, Ingvor; Hermansson, Liselotte Norling; Janeslätt, Gunnel

2016-08-01

Adults with cognitive disabilities often have difficulties in dealing with the complexity of everyday life. With cognitive assistive technology (e.g. electronic planning devices [EPDs] and individual support), they can bring order to their often chaotic life. Assumptions are that environmental factors influence with non-use of EPDs. To explore how adults with cognitive disabilities perceive the influence of environmental factors in the use of EPDs. A reference group with experience of use of EPDs assisted the researchers. Twelve adults with cognitive disabilities and experience of using EPDs participated. An interview guide was implemented covering environmental factors according to the International Classification of Functioning, Disability and Health. Qualitative content analysis was applied in the analyses. Five categories and two themes emerged, which were integrated into a model of facilitating factors influencing the use of EPDs. Measures to prevent or eliminate negative influences of the device use are important to be taken. Professionals need more knowledge about EPDs, while users need individual adaption of the EPDs. EPDs need to be user-friendly, manageable and work in any seasons. Implications for Rehabilitation The users should have access to specially trained prescribers. There is a need for development of user-friendly and manageable products to function in any climate. Knowledge is lacking on how to implement the users in all stages of the prescribing process. Prescribers should increase knowledge in the use of EPDs to influence the attitudes of the social environment.

Modeling self-consistent multi-class dynamic traffic flow

NASA Astrophysics Data System (ADS)

Cho, Hsun-Jung; Lo, Shih-Ching

2002-09-01

In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.

Predicting use of case management support services for adolescents and adults living in community following brain injury: A longitudinal Canadian database study with implications for life care planning

PubMed Central

Baptiste, B.; Dawson, D.R.; Streiner, D.

2015-01-01

Abstract OBJECTIVE: To determine factors associated with case management (CM) service use in people with traumatic brain injury (TBI), using a published model for service use. DESIGN: A retrospective cohort, with nested case-control design. Correlational and logistic regression analyses of questionnaires from a longitudinal community data base. STUDY SAMPLE: Questionnaires of 203 users of CM services and 273 non-users, complete for all outcome and predictor variables. Individuals with TBI, 15 years of age and older. Out of a dataset of 1,960 questionnaires, 476 met the inclusion criteria. METHODOLOGY: Eight predictor variables and one outcome variable (use or non-use of the service). Predictor variables considered the framework of the Behaviour Model of Health Service Use (BMHSU); specifically, pre-disposing, need and enabling factor groups as these relate to health service use and access. RESULTS: Analyses revealed significant differences between users and non-users of CM services. In particular, users were significantly younger than non-users as the older the person the less likely to use the service. Also, users had less education and more severe activity limitations and lower community integration. Persons living alone are less likely to use case management. Funding groups also significantly impact users. CONCLUSIONS: This study advances an empirical understanding of equity of access to health services usage in the practice of CM for persons living with TBI as a fairly new area of research, and considers direct relevance to Life Care Planning (LCP). Many life care planers are CM and the genesis of LCP is CM. The findings relate to health service use and access, rather than health outcomes. These findings may assist with development of a modified model for prediction of use to advance future cost of care predictions. PMID:26409333

What communication strategies do AAC users want their communication partners to use? A preliminary study.

PubMed

Midtlin, Hanne Sofie; Næss, Kari-Anne B; Taxt, Tone; Karlsen, Asgjerd Vea

2015-01-01

This study aims to investigate which communication strategies the people, who use augmentative and alternative communication (AAC), want their communication partners to use. We interviewed eight children using Talking Mats to examine the AAC users' own opinion. The results showed that they wanted their communication partners to take the initiative, to repair the breaks when communication breakdowns occurred, and to invest time in understanding what AAC users wanted to express. These results underlined the significant responsibility of communication partners and revealed the need for AAC user interventions to help them be active communicators. More research needs to emphasise AAC users' opinions about communication partner strategies to improve the communication processes for AAC-users and thereby promote social inclusion in natural environment. Implications for Rehabilitation Communication partner strategies can affect communication as well as personal development and life quality for augmentative and alternative communication (AAC) users. In AAC-users opinion, their communication partners should take the communicative initiative, repair the breaks when communication breakdowns occurred, and invest time in understanding what AAC-users want to express. There is a need to inform and educate communication partners, especially those unfamiliar to AAC users. Practical training sessions, clinician modelling and written materials may be helpful. A communication partner guide can be adapted to each individual AAC user who explains his or her communication preferences. Additionally, there is a need that the clinicians promote active rather than passive communication from AAC users, which requires that they have access to the necessary symbols.

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users

PubMed Central

Li, Tianhao; Fu, Qian-Jie

2013-01-01

Objectives (1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. Design VGD was measured using two talker sets with different inter-gender fundamental frequencies (F0), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Study sample Eleven postlingually deaf CI users. Results The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. Conclusions VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments. PMID:21696330

Mining consumer reviews to generate ratings of different product attributes while producing feature-based review-summary

NASA Astrophysics Data System (ADS)

Kangale, Akshay; Krishna Kumar, S.; Arshad Naeem, Mohd; Williams, Mark; Tiwari, M. K.

2016-10-01

With the massive growth of the internet, product reviews increasingly serve as an important source of information for customers to make choices online. Customers depend on these reviews to understand users' experience, and manufacturers rely on this user-generated content to capture user sentiments about their product. Therefore, it is in the best interest of both customers and manufacturers to have a portal where they can read a complete comprehensive summary of these reviews in minimum time. With this in mind, we arrived at our first objective which is to generate a feature-based review-summary. Our second objective is to develop a predictive model to know the next week's product sales based on numerical review ratings and textual features embedded in the reviews. When it comes to product features, every user has different priorities for different features. To capture this aspect of decision-making, we have designed a new mechanism to generate a numerical rating for every feature of the product individually. The data have been collected from a well-known commercial website for two different products. The validation of the model is carried out using a crowd-sourcing technique.

Innovation in user-centered skills and performance improvement for sustainable complex service systems.

PubMed

Karwowski, Waldemar; Ahram, Tareq Z

2012-01-01

In order to leverage individual and organizational learning and to remain competitive in current turbulent markets it is important for employees, managers, planners and leaders to perform at high levels over time. Employee competence and skills are extremely important matters in view of the general shortage of talent and the mobility of employees with talent. Two factors emerged to have the greatest impact on the competitiveness of complex service systems: improving managerial and employee's knowledge attainment for skills, and improving the training and development of the workforce. This paper introduces the knowledge-based user-centered service design approach for sustainable skill and performance improvement in education, design and modeling of the next generation of complex service systems. The rest of the paper cover topics in human factors and sustainable business process modeling for the service industry, and illustrates the user-centered service system development cycle with the integration of systems engineering concepts in service systems. A roadmap for designing service systems of the future is discussed. The framework introduced in this paper is based on key user-centered design principles and systems engineering applications to support service competitiveness.

Optimising the location of antenatal classes.

PubMed

Tomintz, Melanie N; Clarke, Graham P; Rigby, Janette E; Green, Josephine M

2013-01-01

To combine microsimulation and location-allocation techniques to determine antenatal class locations which minimise the distance travelled from home by potential users. Microsimulation modeling and location-allocation modeling. City of Leeds, UK. Potential users of antenatal classes. An individual-level microsimulation model was built to estimate the number of births for small areas by combining data from the UK Census 2001 and the Health Survey for England 2006. Using this model as a proxy for service demand, we then used a location-allocation model to optimize locations. Different scenarios show the advantage of combining these methods to optimize (re)locating antenatal classes and therefore reduce inequalities in accessing services for pregnant women. Use of these techniques should lead to better use of resources by allowing planners to identify optimal locations of antenatal classes which minimise women's travel. These results are especially important for health-care planners tasked with the difficult issue of targeting scarce resources in a cost-efficient, but also effective or accessible, manner. (169 words). Copyright © 2011 Elsevier Ltd. All rights reserved.

User's manual for UCAP: Unified Counter-Rotation Aero-Acoustics Program

NASA Technical Reports Server (NTRS)

Culver, E. M.; Mccolgan, C. J.

1993-01-01

This is the user's manual for the Unified Counter-rotation Aeroacoustics Program (UCAP), the counter-rotation derivative of the UAAP (Unified Aero-Acoustic Program). The purpose of this program is to predict steady and unsteady air loading on the blades and the noise produced by a counter-rotation Prop-Fan. The aerodynamic method is based on linear potential theory with corrections for nonlinearity associated with axial flux induction, vortex lift on the blades, and rotor-to-rotor interference. The theory for acoustics and the theory for individual blade loading and wakes are derived in Unified Aeroacoustics Analysis for High Speed Turboprop Aerodynamics and Noise, Volume 1 (NASA CR-4329). This user's manual also includes a brief explanation of the theory used for the modelling of counter-rotation.

User's manual for UCAP: Unified Counter-Rotation Aero-Acoustics Program

NASA Astrophysics Data System (ADS)

Culver, E. M.; McColgan, C. J.

1993-04-01

This is the user's manual for the Unified Counter-rotation Aeroacoustics Program (UCAP), the counter-rotation derivative of the UAAP (Unified Aero-Acoustic Program). The purpose of this program is to predict steady and unsteady air loading on the blades and the noise produced by a counter-rotation Prop-Fan. The aerodynamic method is based on linear potential theory with corrections for nonlinearity associated with axial flux induction, vortex lift on the blades, and rotor-to-rotor interference. The theory for acoustics and the theory for individual blade loading and wakes are derived in Unified Aeroacoustics Analysis for High Speed Turboprop Aerodynamics and Noise, Volume 1 (NASA CR-4329). This user's manual also includes a brief explanation of the theory used for the modelling of counter-rotation.

A new mobile ubiquitous computing application to control obesity: SapoFit.

PubMed

Rodrigues, Joel J P C; Lopes, Ivo M C; Silva, Bruno M C; Torre, Isabel de La

2013-01-01

The objective of this work was the proposal, design, construction and validation of a mobile health system for dietetic monitoring and assessment, called SapoFit. This application may be personalized to keep a daily personal health record of an individual's food intake and daily exercise and to share this with a social network. The initiative is a partnership with SAPO - Portugal Telecom. SapoFit uses Web services architecture, a relatively new model for distributed computing and application integration. SapoFit runs on a range of mobile platforms, and it has been implemented successfully in a range of mobile devices and has been evaluated by over 100 users. Most users strongly agree that SapoFit has an attractive design, the environment is user-friendly and intuitive, and the navigation options are clear.

Does this range suit me? Range satisfaction of battery electric vehicle users.

PubMed

Franke, Thomas; Günther, Madlen; Trantow, Maria; Krems, Josef F

2017-11-01

User satisfaction is a vital design criterion for sustainable systems. The present research aimed to understand factors relating to individually perceived range satisfaction of battery electric vehicle (BEV) users. Data from a large-scale BEV field trial (N = 72) were analyzed. Apart from an initial drop in range satisfaction, increasing practical experience was related to increased range satisfaction. Classical indicators of users' mobility profiles (daily travel distances) were only weakly related to lower range satisfaction (not significant), after controlling for practical experience and preferred coverage of mobility needs. The regularity/predictability of users' mobility patterns, the percentage of journeys not coverable because of range issues, and users' individual comfortable range accounted for variance in range satisfaction. Finally, range satisfaction was related to key indicators of general BEV acceptance (e.g., purchase intentions). These results underline the complex dynamics involved in individual range satisfaction, as well as its central role for BEV acceptance. Copyright © 2017 Elsevier Ltd. All rights reserved.

The individual and beyond: a socio-rational choice model of service participation among homeless adults with substance abuse problems.

PubMed

Sosin, Michael R; Grossman, Susan F

2003-01-01

While substance user service programs can help homeless adults solve their substance use and housing problems, relatively few needy individuals use and complete these programs. The lack of participation is poorly explained by typical empirical studies, most of which consider the role in service participation of various personal traits and client problems. The current article instead seeks to explain service participation through the application of an alternative, "socio-rational choice" model. This model has three premises: Clients weigh the costs and benefits of participating in services against alternative uses of their time and resources. The clients' weighing procedures reflect their personal situations and perceptions of the treatment environment. The perceptions of their personal situations and perceptions of the treatment environment are affected by the manner in which clients react to representatives of service systems, members of their social network including both housed and homeless persons, and other individuals. Secondary evidence supports many of the model's hypotheses and generally suggests that homeless clients may be heavily affected by their experiences with individuals and systems with which they come into contact.

Effect of high-potency cannabis on corpus callosum microstructure.

PubMed

Rigucci, S; Marques, T R; Di Forti, M; Taylor, H; Dell'Acqua, F; Mondelli, V; Bonaccorso, S; Simmons, A; David, A S; Girardi, P; Pariante, C M; Murray, R M; Dazzan, P

2016-03-01

The use of cannabis with higher Δ9-tetrahydrocannabinol content has been associated with greater risk, and earlier onset, of psychosis. However, the effect of cannabis potency on brain morphology has never been explored. Here, we investigated whether cannabis potency and pattern of use are associated with changes in corpus callosum (CC) microstructural organization, in patients with first-episode psychosis (FEP) and individuals without psychosis, cannabis users and non-users. The CC of 56 FEP (37 cannabis users) and 43 individuals without psychosis (22 cannabis users) was virtually dissected and segmented using diffusion tensor imaging tractography. The diffusion index of fractional anisotropy, mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity was calculated for each segment. Across the whole sample, users of high-potency cannabis had higher total CC MD and higher total CC AD than both low-potency users and those who never used (p = 0.005 and p = 0.004, respectively). Daily users also had higher total CC MD and higher total CC AD than both occasional users and those who never used (p = 0.001 and p < 0.001, respectively). However, there was no effect of group (patient/individuals without psychosis) or group x potency interaction for either potency or frequency of use. The within-group analysis showed in fact that the effects of potency and frequency were similar in FEP users and in users without psychosis. Frequent use of high-potency cannabis is associated with disturbed callosal microstructural organization in individuals with and without psychosis. Since high-potency preparations are now replacing traditional herbal drugs in many European countries, raising awareness about the risks of high-potency cannabis is crucial.

Mining Twitter Data to Improve Detection of Schizophrenia

PubMed Central

McManus, Kimberly; Mallory, Emily K.; Goldfeder, Rachel L.; Haynes, Winston A.; Tatum, Jonathan D.

2015-01-01

Individuals who suffer from schizophrenia comprise I percent of the United States population and are four times more likely to die of suicide than the general US population. Identification of at-risk individuals with schizophrenia is challenging when they do not seek treatment. Microblogging platforms allow users to share their thoughts and emotions with the world in short snippets of text. In this work, we leveraged the large corpus of Twitter posts and machine-learning methodologies to detect individuals with schizophrenia. Using features from tweets such as emoticon use, posting time of day, and dictionary terms, we trained, built, and validated several machine learning models. Our support vector machine model achieved the best performance with 92% precision and 71% recall on the held-out test set. Additionally, we built a web application that dynamically displays summary statistics between cohorts. This enables outreach to undiagnosed individuals, improved physician diagnoses, and destigmatization of schizophrenia. PMID:26306253

User's guide to the Reliability Estimation System Testbed (REST)

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Rifkin, Adam

1992-01-01

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

PubMed Central

Zhao, Qiangfu; Liu, Yong

2015-01-01

A fitness landscape presents the relationship between individual and its reproductive success in evolutionary computation (EC). However, discrete and approximate landscape in an original search space may not support enough and accurate information for EC search, especially in interactive EC (IEC). The fitness landscape of human subjective evaluation in IEC is very difficult and impossible to model, even with a hypothesis of what its definition might be. In this paper, we propose a method to establish a human model in projected high dimensional search space by kernel classification for enhancing IEC search. Because bivalent logic is a simplest perceptual paradigm, the human model is established by considering this paradigm principle. In feature space, we design a linear classifier as a human model to obtain user preference knowledge, which cannot be supported linearly in original discrete search space. The human model is established by this method for predicting potential perceptual knowledge of human. With the human model, we design an evolution control method to enhance IEC search. From experimental evaluation results with a pseudo-IEC user, our proposed model and method can enhance IEC search significantly. PMID:25879050

An emotional contagion model for heterogeneous social media with multiple behaviors

NASA Astrophysics Data System (ADS)

Xiong, Xi; Li, Yuanyuan; Qiao, Shaojie; Han, Nan; Wu, Yue; Peng, Jing; Li, Binyong

2018-01-01

The emotion varies and propagates with the spatial and temporal information of individuals through social media, which uncovers several interaction mechanisms and features the community structure in order to facilitate individuals' communication and emotional contagion in social networks. Aiming to show the detailed process and characteristics of emotional contagion within social media, we propose an emotional independent cascade model in which individual emotion can affect the subsequent emotion of his/her friends. The transmissibility is introduced to measure the capability of propagating emotion with respect to an individual in social networks. By analyzing the patterns of emotional contagion on Twitter data, we find that the value of transmissibility differs on different layers and on different community structures. Extensive experiments were conducted and the results reveal that, the polar emotion of hub users can lead to the disappearance of opposite emotion, and the transmissibility makes no sense. The final emotional distribution depends on the initial emotional distribution and the transmissibilities. Individuals from a small community are more likely to change their mood by the influence of community leaders. In addition, we compared the proposed model with two other models, the emotion-based spreader-ignorant-stifler model and the standard independent cascade model. The results demonstrate that the proposed model can reflect the real-world situation of emotional contagion for heterogeneous social media while the computational complexities of all these three models are similar.

The medical folder as an active tool in defining the clinical decision-making process.

PubMed

Ferri, F

1995-01-01

Whenever the user of a consultation system needs to know a large amount of information items that are possibly inter-related, a system that is able to cooperate with the user can simplify the interaction and increase its speed. In fact, these systems can recognize the goals of the user, individuate the information related to his goals, and finally focus their attention on this information [1]. This paper describes research work on the design and creation of a medical folder management system capable of establishing cooperative dialogue with users who have access to the information contained therein. Particular attention has thus been paid to the problems of man-computer dialogue and user models. The research work has addressed the problem of integrating into the system knowledge about the medical domain and users (physicians are only used for the time being), which are both necessary to activate a cooperative dialogue. After analysing the literature on the problems of user models, this paper presents and formalizes a study performed at the IVth Surgical Clinic of the Rome University Umberto I General Hospital to identify and represent how, when, and with what goals the physician consults the medical folder, as well as the dialogue procedures he normally adopts. The paper also illustrates important characteristics of the CADMIO prototype, which has been developed since the study was made. CADMIO stores information about users for use in recognizing and interpreting their behaviour, providing help, and in acquiring and returning further information. Whilst always bearing in mind the physician's pre-established goals, it structures information to facilitate his consultation activity, offering him options for the retrieval of further information semantically linked to that already obtained.

Evaluation of physical activity web sites for use of behavior change theories.

PubMed

Doshi, Amol; Patrick, Kevin; Sallis, James F; Calfas, Karen

2003-01-01

Physical activity (PA) Web sites were assessed for their use of behavior change theories, including constructs of the health belief model, Transtheoretical Model, social cognitive theory, and the theory of reasoned action and planned behavior. An evaluation template for assessing PA Web sites was developed, and content validity and interrater reliability were demonstrated. Two independent raters evaluated 24 PA Web sites. Web sites varied widely in application of theory-based constructs, ranging from 5 to 48 on a 100-point scale. The most common intervention strategies were general information, social support, and realistic goal areas. Coverage of theory-based strategies was low, varying from 26% for social cognitive theory to 39% for health belief model. Overall, PA Web sites provided little assessment, feedback, or individually tailored assistance for users. They were unable to substantially tailor the on-line experience for users at different stages of change or different demographic characteristics.

Effect of users' opinion evolution on information diffusion in online social networks

NASA Astrophysics Data System (ADS)

Zhu, Hengmin; Kong, Yuehan; Wei, Jing; Ma, Jing

2018-02-01

The process of topic propagation always interweaves information diffusion and opinion evolution, but most previous works studied the models of information diffusion and opinion evolution separately, and seldom focused on their interaction of each other. To shed light on the effect of users' opinion evolution on information diffusion in online social networks, we proposed a model which incorporates opinion evolution into the process of topic propagation. Several real topics propagating on Sina Microblog were collected to analyze individuals' propagation intentions, and different propagation intentions were considered in the model. The topic propagation was simulated to explore the impact of different opinion distributions and intervention with opposite opinion on information diffusion. Results show that the topic with one-sided opinions can spread faster and more widely, and intervention with opposite opinion is an effective measure to guide the topic propagation. The earlier to intervene, the more effectively the topic propagation would be guided.

Coteaching Recovery to Mental Health Care Professionals.

PubMed

Larsen, Christine; Lange, Mads; Jørgensen, Kim; Kistrup, Kristen; Petersen, Lone

2018-06-01

In 2010, the Regional Council of the Capital Region of Denmark endorsed a vision of mental health services based on personal recovery, rehabilitation, and the involvement of caregivers. Programs to achieve this vision include hiring peer support workers, a Recovery College, and service user participation at the organizational level. This column describes a cornerstone of these initiatives-an education program in the recovery model for mental health professionals. In 2013-2014, the Capital Region implemented 148 workshops on recovery-oriented services for all practitioner staff in mental health services in the region. The workshops featured a coteaching model, with both a mental health professional and an individual with lived experience serving as trainers. This model showed promise and should be expanded, including more targeted training for specific services. Such an expansion could be included in a national strategy for user involvement and recovery-oriented practice set to launch in 2018.

Interactive design and analysis of future large spacecraft concepts

NASA Technical Reports Server (NTRS)

Garrett, L. B.

1981-01-01

An interactive computer aided design program used to perform systems level design and analysis of large spacecraft concepts is presented. Emphasis is on rapid design, analysis of integrated spacecraft, and automatic spacecraft modeling for lattice structures. Capabilities and performance of multidiscipline applications modules, the executive and data management software, and graphics display features are reviewed. A single user at an interactive terminal create, design, analyze, and conduct parametric studies of Earth orbiting spacecraft with relative ease. Data generated in the design, analysis, and performance evaluation of an Earth-orbiting large diameter antenna satellite are used to illustrate current capabilities. Computer run time statistics for the individual modules quantify the speed at which modeling, analysis, and design evaluation of integrated spacecraft concepts is accomplished in a user interactive computing environment.

Privacy Policy Enforcement for Ambient Ubiquitous Services

NASA Astrophysics Data System (ADS)

Oyomno, Were; Jäppinen, Pekka; Kerttula, Esa

Ubiquitous service providers leverage miniaturised computing terminals equipped with wireless capabilities to avail new service models. These models are pivoted on personal and inexpensive terminals to customise services to individual preferences. Portability, small sizes and compact keyboards are few features popularising mobile terminals. Features enable storing and carrying of ever increasing proportions of personal data and ability to use them in service adaptations. Ubiquitous services automate deeper soliciting of personal data transparently without the need for user interactions. Transparent solicitations, acquisitions and handling of personal data legitimises privacy concerns regarding disclosures, retention and re-use of the data. This study presents a policy enforcement for ubiquitous services that safeguards handling of users personal data and monitors adherence to stipulated privacy policies. Enforcement structures towards usability and scalability are presented.

Impact of home and community-based services on hospitalisation and institutionalisation among individuals eligible for long-term care insurance in Japan.

PubMed

Tomita, Naoki; Yoshimura, Kimio; Ikegami, Naoki

2010-12-22

This population-based retrospective cohort study aimed to clarify the impact of home and community-based services on the hospitalisation and institutionalisation of individuals certified as eligible for long-term care insurance (LTCI) benefits. Health insurance data and LTCI data were combined into a database of 1,020 individuals in two farming communities in Hokkaido who were enrolled in Citizen's Health Insurance. They had not received long-term care services prior to April 1, 2000 and were newly certified as eligible for Long-Term Care Insurance benefits between April 1, 2000 and February 29, 2008. The analysis covered 565 subjects who had not been hospitalised or institutionalised at the time of first certification of LTCI benefits. The adjusted hazard ratios (HRs) of hospitalisation or institutionalisation or death after the initial certification were calculated using the Cox proportional hazard model. The predictors were age, sex, eligibility level, area of residence, income, year of initial certification and average monthly outpatient medical expenditures, in addition to average monthly total home and community-based services expenditures (analysis 1), the use or no use of each type of service (analysis 2), and average monthly expenditures for home-visit and day-care types of services, the use or no use of respite care, and the use or no use of rental services for assistive devices (analysis 3). Users of home and community-based services were less likely than non-users to be hospitalised or institutionalised. Among the types of services, users of respite care (HR: 0.71, 95% confidence interval [CI]: 0.55-0.93) and rental services for assistive devices (HR: 0.70, 95% CI: 0.54-0.92) were less likely to be hospitalised or institutionalised than non-users. For those with relatively light needs, users of day care were also less likely to be hospitalised or institutionalized than non-users (HR: 0.77, 95% CI: 0.61-0.98). Respite care, rental services for assistive devices and day care are effective in preventing hospitalisation and institutionalisation. Our results suggest that home and community-based services contribute to the goal of the LTCI system of encouraging individuals certified as needing long-term care to live independently at home for as long as possible.

Impact of home and community-based services on hospitalisation and institutionalisation among individuals eligible for long-term care insurance in Japan

PubMed Central

2010-01-01

Background This population-based retrospective cohort study aimed to clarify the impact of home and community-based services on the hospitalisation and institutionalisation of individuals certified as eligible for long-term care insurance (LTCI) benefits. Methods Health insurance data and LTCI data were combined into a database of 1,020 individuals in two farming communities in Hokkaido who were enrolled in Citizen's Health Insurance. They had not received long-term care services prior to April 1, 2000 and were newly certified as eligible for Long-Term Care Insurance benefits between April 1, 2000 and February 29, 2008. The analysis covered 565 subjects who had not been hospitalised or institutionalised at the time of first certification of LTCI benefits. The adjusted hazard ratios (HRs) of hospitalisation or institutionalisation or death after the initial certification were calculated using the Cox proportional hazard model. The predictors were age, sex, eligibility level, area of residence, income, year of initial certification and average monthly outpatient medical expenditures, in addition to average monthly total home and community-based services expenditures (analysis 1), the use or no use of each type of service (analysis 2), and average monthly expenditures for home-visit and day-care types of services, the use or no use of respite care, and the use or no use of rental services for assistive devices (analysis 3). Results Users of home and community-based services were less likely than non-users to be hospitalised or institutionalised. Among the types of services, users of respite care (HR: 0.71, 95% confidence interval [CI]: 0.55-0.93) and rental services for assistive devices (HR: 0.70, 95% CI: 0.54-0.92) were less likely to be hospitalised or institutionalised than non-users. For those with relatively light needs, users of day care were also less likely to be hospitalised or institutionalized than non-users (HR: 0.77, 95% CI: 0.61-0.98). Conclusions Respite care, rental services for assistive devices and day care are effective in preventing hospitalisation and institutionalisation. Our results suggest that home and community-based services contribute to the goal of the LTCI system of encouraging individuals certified as needing long-term care to live independently at home for as long as possible. PMID:21176165

Why do Dutch people use dietary supplements? Exploring the role of socio-cognitive and psychosocial determinants.

PubMed

Pajor, E M; Eggers, S M; Curfs, K C J; Oenema, A; de Vries, H

2017-07-01

In the Netherlands, the prevalence of dietary supplement use has doubled (from 17 to 40 per cent) since the 1980s. Yet, limited data is available on which socio-cognitive factors are associated with dietary supplement use. Therefore, the purpose of the study is to explain dietary supplement use with determinants deriving from the Integrated Change Model (ICM) and from formative research. Socio-cognitive and psychosocial factors were measured among users and non-users of dietary supplements in a longitudinal survey study, with measurements at baseline (N = 1448) and at one-month follow-up (N = 1161). Negative binomial regression analysis was applied to de data. Intention emerged as the main predictor of dietary supplement use (OR = 1.99). Further predictors of dietary supplement use with smaller effect-sizes were: health regulatory focus (promotion, OR = 1.46), social modelling (OR = 1.44), attitude (pros, OR = 1.37), attitude (cons, OR = 0.87), health locus of control (OR = 0.77), and risk perception (chance of getting ill, OR = 1.22). Individuals tend to use dietary supplements if they are promotion oriented, notice dietary supplement users in their social environment, estimate their chances of getting ill higher, and have positive attitudes towards dietary supplements. In contrast, non-users believe that external factors affect their health, and hold negative attitudes towards dietary supplements. Mapping out individuals' socio-cognitive profile may contribute to the development of online health communication. Based on socio-cognitive and demographical factors, personalised advice can be given about dietary supplement use. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing the Detection of Wakeful and Sleep-Like States for Future Electrocorticographic Brain Computer Interface Applications.

PubMed

Pahwa, Mrinal; Kusner, Matthew; Hacker, Carl D; Bundy, David T; Weinberger, Kilian Q; Leuthardt, Eric C

2015-01-01

Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Translation of this technology from the laboratory to the real world requires additional methods that allow users operate their ECoG-based BCI autonomously. In such an environment, users must be able to perform all tasks currently performed by the experimenter, including manually switching the BCI system on/off. Although a simple task, it can be challenging for target users (e.g., individuals with tetraplegia) due to severe motor disability. In this study, we present an automated and practical strategy to switch a BCI system on or off based on the cognitive state of the user. Using a logistic regression, we built probabilistic models that utilized sub-dural ECoG signals from humans to estimate in pseudo real-time whether a person is awake or in a sleep-like state, and subsequently, whether to turn a BCI system on or off. Furthermore, we constrained these models to identify the optimal anatomical and spectral parameters for delineating states. Other methods exist to differentiate wake and sleep states using ECoG, but none account for practical requirements of BCI application, such as minimizing the size of an ECoG implant and predicting states in real time. Our results demonstrate that, across 4 individuals, wakeful and sleep-like states can be classified with over 80% accuracy (up to 92%) in pseudo real-time using high gamma (70-110 Hz) band limited power from only 5 electrodes (platinum discs with a diameter of 2.3 mm) located above the precentral and posterior superior temporal gyrus.

Validation of the Inverted Pendulum Model in standing for transtibial prosthesis users.

PubMed

Rusaw, David F; Ramstrand, Simon

2016-01-01

Often in balance assessment variables associated with the center of pressure are used to draw conclusions about an individual's balance. Validity of these conclusions rests upon assumptions that movement of the center of pressure is inter-dependent on movement of the center of mass. This dependency is mechanical and is referred to as the Inverted Pendulum Model. The following study aimed to validate this model both kinematically and kinetically, in transtibial prosthesis users and a control group. Prosthesis users (n=6) and matched control participants (n=6) stood quietly while force and motion data were collected under three conditions (eyes-open, eyes-closed, and weight-bearing feedback). Correlation coefficients were used to investigate the relationships between height and excursion of markers and center of masses in mediolateral/anteroposterior-directions, difference between center of pressure and center of mass and the center of mass acceleration in mediolateral/anteroposterior directions, magnitude of mediolateral/anteroposterior-component forces and center of mass acceleration, angular position of ankle and excursion in mediolateral/anteroposterior-directions, and integrated force signals. Results indicate kinematic validity of similar magnitudes (mean (SD) marker-displacement) between prosthesis users and control group for mediolateral- (r=0.77 (0.17); 0.74 (0.19)) and anteroposterior-directions (r=0.88 (0.18); 0.88 (0.19)). Correlation between difference of center of pressure and center of mass and the center of mass acceleration was negligible on the prosthetic side (r = 0.08 (0.06)) vs. control group (r=-0.51(0.13)). Results indicate kinematic validity of the Inverted Pendulum Model in transtibial prosthesis users but kinetic validity is questionable, particularly on the side with a prosthesis. Copyright © 2015 Elsevier Ltd. All rights reserved.

EWB: The Environment WorkBench Version 4.0

NASA Technical Reports Server (NTRS)

1995-01-01

The Environment WorkBench EWB is a desktop integrated analysis tool for studying a spacecraft's interactions with its environment. Over 100 environment and analysis models are integrated into the menu-based tool. EWB, which was developed for and under the guidance of the NASA Lewis Research Center, is built atop the Module Integrator and Rule-based Intelligent Analytic Database (MIRIAD) architecture. This allows every module in EWB to communicate information to other modules in a transparent manner from the user's point of view. It removes the tedious and error-prone steps of entering data by hand from one model to another. EWB runs under UNIX operating systems (SGI and SUN workstations) and under MS Windows (3.x, 95, and NT) operating systems. MIRIAD, the unique software that makes up the core of EWB, provides the flexibility to easily modify old models and incorporate new ones as user needs change. The MIRIAD approach separates the computer assisted engineering (CAE) tool into three distinct units: 1) A modern graphical user interface to present information; 2) A data dictionary interpreter to coordinate analysis; and 3) A database for storing system designs and analysis results. The user interface is externally programmable through ASCII data files, which contain the location and type of information to be displayed on the screen. This approach provides great flexibility in tailoring the look and feel of the code to individual user needs. MIRIADbased applications, such as EWB, have utilities for viewing tabulated parametric study data, XY line plots, contour plots, and three-dimensional plots of contour data and system geometries. In addition, a Monte Carlo facility is provided to allow statistical assessments (including uncertainties) in models or data.

Relationship between fMRI response during a nonverbal memory task and marijuana use in college students.

PubMed

Dager, Alecia D; Tice, Madelynn R; Book, Gregory A; Tennen, Howard; Raskin, Sarah A; Austad, Carol S; Wood, Rebecca M; Fallahi, Carolyn R; Hawkins, Keith A; Pearlson, Godfrey D

2018-04-26

Marijuana (MJ) is widely used among college students, with peak use between ages 18-22. Research suggests memory dysfunction in adolescent and young adult MJ users, but the neural correlates are unclear. We examined functional magnetic resonance imaging (fMRI) response during a memory task among college students with varying degrees of MJ involvement. Participants were 64 college students, ages 18-20, who performed a visual encoding and recognition task during fMRI. MJ use was ascertained for 3 months prior to scanning; 27 individuals reported past 3-month MJ use, and 33 individuals did not. fMRI response was modeled during encoding based on whether targets were subsequently recognized (correct encoding), and during recognition based on target identification (hits). fMRI response in left and right inferior frontal gyrus (IFG) and hippocampal regions of interest was examined between MJ users and controls. There were no group differences between MJ users and controls on fMRI response during encoding, although single sample t-tests revealed that MJ users failed to activate the hippocampus. During recognition, MJ users showed less fMRI response than controls in right hippocampus (Cohen's d = 0.55), left hippocampus (Cohen's d = 0.67) and left IFG (Cohen's d = 0.61). Heavier MJ involvement was associated with lower fMRI response in left hippocampus and left IFG. This study provides evidence of MJ-related prefrontal and hippocampal dysfunction during recognition memory in college students. These findings may contribute to our previously identified decrements in academic performance in college MJ users and could have substantial implications for academic and occupational functioning. Copyright © 2018 Elsevier B.V. All rights reserved.

QuakeSim 2.0

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay W.; Lyzenga, Gregory A.; Granat, Robert A.; Norton, Charles D.; Rundle, John B.; Pierce, Marlon E.; Fox, Geoffrey C.; McLeod, Dennis; Ludwig, Lisa Grant

2012-01-01

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Examining individuals' adoption of healthcare wearable devices: An empirical study from privacy calculus perspective.

PubMed

Li, He; Wu, Jing; Gao, Yiwen; Shi, Yao

2016-04-01

Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals' adoption of healthcare wearable devices. Considering the importance of individuals' privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices. The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients. This study reveals several main findings: (1) individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus). In short, if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals' perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals' perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modeling Open-Set Spoken Word Recognition in Postlingually Deafened Adults after Cochlear Implantation: Some Preliminary Results with the Neighborhood Activation Model

PubMed Central

Meyer, Ted A.; Frisch, Stefan A.; Pisoni, David B.; Miyamoto, Richard T.; Svirsky, Mario A.

2012-01-01

Hypotheses Do cochlear implants provide enough information to allow adult cochlear implant users to understand words in ways that are similar to listeners with acoustic hearing? Can we use a computational model to gain insight into the underlying mechanisms used by cochlear implant users to recognize spoken words? Background The Neighborhood Activation Model has been shown to be a reasonable model of word recognition for listeners with normal hearing. The Neighborhood Activation Model assumes that words are recognized in relation to other similar-sounding words in a listener’s lexicon. The probability of correctly identifying a word is based on the phoneme perception probabilities from a listener’s closed-set consonant and vowel confusion matrices modified by the relative frequency of occurrence of the target word compared with similar-sounding words (neighbors). Common words with few similar-sounding neighbors are more likely to be selected as responses than less common words with many similar-sounding neighbors. Recent studies have shown that several of the assumptions of the Neighborhood Activation Model also hold true for cochlear implant users. Methods Closed-set consonant and vowel confusion matrices were obtained from 26 postlingually deafened adults who use cochlear implants. Confusion matrices were used to represent input errors to the Neighborhood Activation Model. Responses to the different stimuli were then generated by the Neighborhood Activation Model after incorporating the frequency of occurrence counts of the stimuli and their neighbors. Model outputs were compared with obtained performance measures on the Consonant-Vowel Nucleus-Consonant word test. Information transmission analysis was used to assess whether the Neighborhood Activation Model was able to successfully generate and predict word and individual phoneme recognition by cochlear implant users. Results The Neighborhood Activation Model predicted Consonant-Vowel Nucleus-Consonant test words at levels similar to those correctly identified by the cochlear implant users. The Neighborhood Activation Model also predicted phoneme feature information well. Conclusion The results obtained suggest that the Neighborhood Activation Model provides a reasonable explanation of word recognition by postlingually deafened adults after cochlear implantation. It appears that multichannel cochlear implants give cochlear implant users access to their mental lexicons in a manner that is similar to listeners with acoustic hearing. The lexical properties of the test stimuli used to assess performance are important to spoken-word recognition and should be included in further models of the word recognition process. PMID:12851554

Does public transport use prevent declines in walking speed among older adults living in England? A prospective cohort study

PubMed Central

Rouxel, Patrick; Webb, Elizabeth; Chandola, Tarani

2017-01-01

Objectives Although there is some evidence that public transport use confers public health benefits, the evidence is limited by cross-sectional study designs and health-related confounding factors. This study examines the effect of public transport use on changes in walking speed among older adults living in England, comparing frequent users of public transport to their peers who did not use public transport because of structural barriers (poor public transport infrastructure) or through choice. Design Prospective cohort study. Setting England, UK. Participants Older adults aged ≥60 years eligible for the walking speed test. 6246 individuals at wave 2 (2004–2005); 5909 individuals at wave 3 (2006–2007); 7321 individuals at wave 4 (2008–2009); 7535 individuals at wave 5 (2010–2011) and 7664 individuals at wave 6 (2012–2013) of the English Longitudinal Study of Ageing. Main outcome measure The walking speed was estimated from the time taken to walk 2.4 m. Fixed effects models and growth curve models were used to examine the associations between public transport use and walking speed. Results Older adults who did not use public transport through choice or because of structural reasons had slower walking speeds (−0.02 m/s (95% CI −0.03 to –0.003) and −0.02 m/s (95% CI −0.03 to –0.01), respectively) and took an extra 0.07 s to walk 2.4 m compared with their peers who used public transport frequently. The age-related trajectories of decline in walking speed were slower for frequent users of public transport compared with non-users. Conclusions Frequent use of public transport may prevent age-related decline in physical capability by promoting physical activity and lower limb muscle strength among older adults. The association between public transport use and slower decline in walking speed among older adults is unlikely to be confounded by health-related selection factors. Improving access to good quality public transport could improve the health of older adults. PMID:28963309

Three Applications of Automated Test Assembly within a User-Friendly Modeling Environment

ERIC Educational Resources Information Center

Cor, Ken; Alves, Cecilia; Gierl, Mark

2009-01-01

While linear programming is a common tool in business and industry, there have not been many applications in educational assessment and only a handful of individuals have been actively involved in conducting psychometric research in this area. Perhaps this is due, at least in part, to the complexity of existing software packages. This article…

Accounting for ethnicity in recreation demand: a flexible count data approach

Treesearch

J. Michael Bowker; V.R. Leeworthy

1998-01-01

The authors examine ethnicity and individual trip-taking behavior associated with natural resource based recreation in the Florida Keys. Bowker and Leeworthy estimate trip demand using the travel cost method. They then extend this model with a varying parameter adaptation to test the congruency of' demand and economic value across white and Hispanic user subgroups...

A Planning and Assessment Model for Developing Effective CMS Support

ERIC Educational Resources Information Center

Johnson, Douglas F.

2004-01-01

At the University of Florida, in Spring 2003, more than 32,000 individuals enrolled in courses using the centrally-supported Course Management System (CMS). Because less than 1 full time equivalent (FTE) was allocated to support the CMS, this created problems for both users and support providers. In the face of rapid growth, support resources for…

Emissions of indoor air pollutants from six user scenarios in a model room

NASA Astrophysics Data System (ADS)

Höllbacher, Eva; Ters, Thomas; Rieder-Gradinger, Cornelia; Srebotnik, Ewald

2017-02-01

In this study six common user scenarios putatively influencing indoor air quality were performed in a model room constructed according to the specifications of the European Reference Room given in the new horizontal prestandard prEN 16516 to gain further information about the influence of user activities on indoor air quality. These scenarios included the use of cleaning agent, an electric air freshener, an ethanol fireplace and cosmetics as well as cigarette smoking and peeling of oranges. Four common indoor air pollutants were monitored: volatile organic compounds (VOC), particulate matter (PM), carbonyl compounds and CO2. The development of all pollutants was determined during and after the test performance. For each measured pollutant, well-defined maximum values could be assigned to one or more of the individual user scenarios. The highest VOC concentration was measured during orange-peeling reaching a maximum value of 3547 μg m-3. Carbonyl compounds and PM were strongly elevated while cigarette smoking. Here, a maximum formaldehyde concentration of 76 μg m-3 and PM concentration of 378 μg m-3 were measured. CO2 was only slightly affected by most of the tests except the use of the ethanol fireplace where a maximum concentration of 1612 ppm was reached. Generally, the user scenarios resulted in a distinct increase of several indoor pollutants that usually decreased rapidly after the removal of the source.

Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior.

PubMed

Althoff, Tim; Jindal, Pranav; Leskovec, Jure

2017-02-01

Many of today's most widely used computing applications utilize social networking features and allow users to connect, follow each other, share content, and comment on others' posts. However, despite the widespread adoption of these features, there is little understanding of the consequences that social networking has on user retention, engagement, and online as well as offline behavior. Here, we study how social networks influence user behavior in a physical activity tracking application. We analyze 791 million online and offline actions of 6 million users over the course of 5 years, and show that social networking leads to a significant increase in users' online as well as offline activities. Specifically, we establish a causal effect of how social networks influence user behavior. We show that the creation of new social connections increases user online in-application activity by 30%, user retention by 17%, and user offline real-world physical activity by 7% (about 400 steps per day). By exploiting a natural experiment we distinguish the effect of social influence of new social connections from the simultaneous increase in user's motivation to use the app and take more steps. We show that social influence accounts for 55% of the observed changes in user behavior, while the remaining 45% can be explained by the user's increased motivation to use the app. Further, we show that subsequent, individual edge formations in the social network lead to significant increases in daily steps. These effects diminish with each additional edge and vary based on edge attributes and user demographics. Finally, we utilize these insights to develop a model that accurately predicts which users will be most influenced by the creation of new social network connections.

Quantitative analysis of bloggers' collective behavior powered by emotions

NASA Astrophysics Data System (ADS)

Mitrović, Marija; Paltoglou, Georgios; Tadić, Bosiljka

2011-02-01

Large-scale data resulting from users' online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study the emergence of emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite networks of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion classifier developed for this type of text. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore the robustness of these critical states, we design a network-automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states.

Prenatal exposure to testosterone interacts with lifetime physical abuse to predict anger rumination and cognitive flexibility among incarcerated methamphetamine users.

PubMed

Herschl, Laura C; Highland, Krista B; McChargue, Dennis E

2012-01-01

The present pilot study hypothesized that degree of exposure to prenatal testosterone interacts with a history of lifetime physical abuse (LPA) to predict the cognitive (anger rumination) and behavioral (intimate partner and interpersonal violence) components of aggression within incarcerated methamphetamine (MA) users. In addition, we hypothesized that the degree of exposure to prenatal testosterone interacts with LPA to predict cognitive flexibility (Stroop Color-Word performance). Male inmate MA users (N = 60) completed neuropsychological and paper/pencil tests. Hand photocopies were also obtained to index prenatal testosterone exposure. Five covariate-adjusted moderation models were tested using anger rumination, intimate partner violence (IPV) perpetration, interpersonal violence perpetration (before and while incarcerated), and Stroop Color-Word T-score as the criteria, prenatal testosterone exposure as the predictor, and LPA as the moderator. Results indicated that, in individuals with a history of LPA, exposure to higher levels of prenatal testosterone exposure predicted greater anger rumination, lower Stroop Color-Word test T-scores, and lower frequencies of IPV perpetration. Findings were not significant in individuals without a history of LPA. This research suggests that biochemical and psychosocial vulnerabilities influence anger rumination and cognitive flexibility, which may render incarcerated MA users at greater risk to relapse or recidivate upon release from prison. Copyright © American Academy of Addiction Psychiatry.

Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the ‘Black Box’ of Machine Learning

PubMed Central

Gillingham, Philip

2016-01-01

Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can ‘learn’, it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and their families to prevent maltreatment from occurring. As expertise in predictive modelling increases, the approach may also be applied in other areas of social work to predict and prevent adverse outcomes for vulnerable service users. In this article, a glimpse inside the ‘black box’ of predictive tools is provided to demonstrate how their development for use in social work may not be straightforward, given the nature of the data recorded about service users and service activity. The development of predictive risk modelling (PRM) in New Zealand is focused on as an example as it may be the first such tool to be applied as part of ongoing reforms to child protection services. PMID:27559213

Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the 'Black Box' of Machine Learning.

PubMed

Gillingham, Philip

2016-06-01

Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can 'learn', it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and their families to prevent maltreatment from occurring. As expertise in predictive modelling increases, the approach may also be applied in other areas of social work to predict and prevent adverse outcomes for vulnerable service users. In this article, a glimpse inside the 'black box' of predictive tools is provided to demonstrate how their development for use in social work may not be straightforward, given the nature of the data recorded about service users and service activity. The development of predictive risk modelling (PRM) in New Zealand is focused on as an example as it may be the first such tool to be applied as part of ongoing reforms to child protection services.

Iris: Constructing and Analyzing Spectral Energy Distributions with the Virtual Observatory

NASA Astrophysics Data System (ADS)

Laurino, O.; Budynkiewicz, J.; Busko, I.; Cresitello-Dittmar, M.; D'Abrusco, R.; Doe, S.; Evans, J.; Pevunova, O.

2014-05-01

We present Iris 2.0, the latest release of the Virtual Astronomical Observatory application for building and analyzing Spectral Energy Distributions (SEDs). With Iris, users may read in and display SEDs inspect and edit any selection of SED data, fit models to SEDs in arbitrary spectral ranges, and calculate confidence limits on best-fit parameters. SED data may be loaded into the application from VOTable and FITS files compliant with the International Virtual Observatoy Alliance interoperable data models, or retrieved directly from NED or the Italian Space Agency Science Data Center; data in non-standard formats may also be converted within the application. Users may seamlessy exchange data between Iris and other Virtual Observatoy tools using the Simple Application Messaging Protocol. Iris 2.0 also provides a tool for redshifting, interpolating, and measuring integratd fluxes, and allows simple aperture corrections for individual points and SED segments. Custom Python functions, template models and template libraries may be imported into Iris for fitting SEDs. Iris may be extended through Java plugins; users can install third-party packages, or develop their own plugin using Iris' Software Development Kit. Iris 2.0 is available for Linux and Mac OS X systems.

Amber Plug-In for Protein Shop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oliva, Ricardo

2004-05-10

The Amber Plug-in for ProteinShop has two main components: an AmberEngine library to compute the protein energy models, and a module to solve the energy minimization problem using an optimization algorithm in the OPTI-+ library. Together, these components allow the visualization of the protein folding process in ProteinShop. AmberEngine is a object-oriented library to compute molecular energies based on the Amber model. The main class is called ProteinEnergy. Its main interface methods are (1) "init" to initialize internal variables needed to compute the energy. (2) "eval" to evaluate the total energy given a vector of coordinates. Additional methods allow themore » user to evaluate the individual components of the energy model (bond, angle, dihedral, non-bonded-1-4, and non-bonded energies) and to obtain the energy of each individual atom. The Amber Engine library source code includes examples and test routines that illustrate the use of the library in stand alone programs. The energy minimization module uses the AmberEngine library and the nonlinear optimization library OPT++. OPT++ is open source software available under the GNU Lesser General Public License. The minimization module currently makes use of the LBFGS optimization algorithm in OPT++ to perform the energy minimization. Future releases may give the user a choice of other algorithms available in OPT++.« less

The Community WRF-Hydro Modeling System Version 4 Updates: Merging Toward Capabilities of the National Water Model

NASA Astrophysics Data System (ADS)

McAllister, M.; Gochis, D.; Dugger, A. L.; Karsten, L. R.; McCreight, J. L.; Pan, L.; Rafieeinasab, A.; Read, L. K.; Sampson, K. M.; Yu, W.

2017-12-01

The community WRF-Hydro modeling system is publicly available and provides researchers and operational forecasters a flexible and extensible capability for performing multi-scale, multi-physics options for hydrologic modeling that can be run independent or fully-interactive with the WRF atmospheric model. The core WRF-Hydro physics model contains very high-resolution descriptions of terrestrial hydrologic process representations such as land-atmosphere exchanges of energy and moisture, snowpack evolution, infiltration, terrain routing, channel routing, basic reservoir representation and hydrologic data assimilation. Complementing the core physics components of WRF-Hydro are an ecosystem of pre- and post-processing tools that facilitate the preparation of terrain and meteorological input data, an open-source hydrologic model evaluation toolset (Rwrfhydro), hydrologic data assimilation capabilities with DART and advanced model visualization capabilities. The National Center for Atmospheric Research (NCAR), through collaborative support from the National Science Foundation and other funding partners, provides community support for the entire WRF-Hydro system through a variety of mechanisms. This presentation summarizes the enhanced user support capabilities that are being developed for the community WRF-Hydro modeling system. These products and services include a new website, open-source code repositories, documentation and user guides, test cases, online training materials, live, hands-on training sessions, an email list serve, and individual user support via email through a new help desk ticketing system. The WRF-Hydro modeling system and supporting tools which now include re-gridding scripts and model calibration have recently been updated to Version 4 and are merging toward capabilities of the National Water Model.

Accessibility to Specialized Public Oral Health Services from the Perspective of Brazilian Users

PubMed Central

de Castro, Ricardo Dias; Rangel, Marianne de Lucena; da Silva, Marcos André Azevedo; de Lucena, Brunna Thaís Lucwu; Cavalcanti, Alessandro Leite; Bonan, Paulo Rogério Ferreti; Oliveira, Julyana de Araújo

2016-01-01

The Specialized Dental Clinics (SDCs) represent the first government initiative in Latin America aimed at providing specialized oral health services. This study sought to evaluate the organizational accessibility to specialized oral health care services in Brazil and to understand the factors that may be associated with accessibility from the user’s perspective. This epidemiological, cross-sectional and quantitative study was conducted by means of interviews with individuals who sought specialized public oral health services in the city of João Pessoa, Paraíba, Brazil, and consisted of a sample of 590 individuals. Users expressed a favorable view of the classification and resolutive nature of specialized services offered by Brazilian public health. The binary logistic regression analysis revealed weak points highlighting the difficulty involved in obtaining such treatments leading to unfavorable evaluations. In the resolutive nature item, difficulty in accessing the location, queues and lack of materials and equipment were highlighted as statistically significant unfavorable aspects. While many of the users considered the service to be resolutive, weaknesses were mentioned that need to be detected to promote improvements and to prevent other health models adopted worldwide from reproducing the same flaws. PMID:27775584

Marketing analysis of a positive technology app for the self-management of psychological stress.

PubMed

Wiederhold, Brenda K; Boyd, Chelsie; Sulea, Camelia; Gaggioli, Andrea; Riva, Giuseppe

2014-01-01

The INTERSTRESS project developed a completely new concept in the treatment of psychological stress: Interreality, a concept that combines cognitive behavioral therapy with a hybrid, closed-loop empowering experience bridging real and virtual worlds. This model provides the opportunity for individual citizens to become active participants in their own health and well-being. This article contains the results of the Marketing Trial and analysis of the opinions of individual consumers/end users of the INTERSTRESS product. The specific objective of this study was to evaluate the feasibility, efficacy and user acceptance of a novel mobile-based relaxation training tool in combination with biofeedback exercises and wearable biosensors. Relaxation was aided through immersion in a mobile virtual scenario (a virtual island) featuring pre-recorded audio narratives guiding a series of relaxation exercises. During biofeedback exercises, a wearable biosensor system provided data which directly modified the virtual reality experience in real-time. Thirty-six participants evaluated the product and overall feedback from users was positive, with some variation seen based on participant gender. A larger market study is now underway to understand if there are cultural variations in acceptability of the device.

Incorporating user perspectives in the design of an online intervention tool for people with visible differences: face IT.

PubMed

Bessell, Alyson; Clarke, Alex; Harcourt, Diana; Moss, Tim P; Rumsey, Nichola

2010-10-01

Individuals with visible differences can experience social anxiety in relation to their appearance. Social skills-based psychosocial interventions have to date shown only limited effectiveness at addressing their concerns. To incorporate user perspectives in the development of an online psychosocial intervention, known as Face IT. Study one consisted of a needs assessment with 12 individuals with a visible difference and six health professionals in order to identify the difficulties experienced by those with visible difference and obtain feedback on the proposed content of Face IT. The findings demonstrated support for the social skills model and the use of an online intervention. Study two consisted of an empirical usability evaluation of Face IT with 14 potential users and 14 health professionals. Based on feedback from the participants, changes were made to the graphics and navigation of the programme. The clinical content has been made more acceptable. The findings indicate support for the importance of social skills-based psychosocial interventions for addressing the needs of those with a visible difference, and have allowed modifications to be made to Face IT ahead of a randomized controlled trial of effectiveness.

Identifying the values and preferences of prosthetic users: a case study series using the repertory grid technique.

PubMed

Schaffalitzky, Elisabeth; NiMhurchadha, Sinead; Gallagher, Pamela; Hofkamp, Susan; MacLachlan, Malcolm; Wegener, Stephen T

2009-06-01

The matching of prosthetic devices to the needs of the individual is a challenge for providers and patients. The aims of this study are to explore the values and preferences that prosthetic users have of their prosthetic devices; to investigate users' perceptions of alternative prosthetic options and to demonstrate a novel method for exploring the values and preferences of prosthetic users. This study describes four case studies of upper limb and lower limb high tech and conventional prosthetic users. Participants were interviewed using the repertory grid technique (RGT), a qualitative technique to explore individual values and preferences regarding specific choices and events. The participants generated distinctive patterns of personal constructs and ratings regarding prosthetic use and different prosthetic options available. The RGT produced a unique profile of preferences regarding prosthetic technologies for each participant. User choice is an important factor when matching prosthetic technology to the user. The consumer's values regarding different prosthetic options are likely to be a critical factor in prosthetic acceptance and ultimate quality of life. The RGT offers a structured method of exploring these attitudes and values without imposing researcher or practitioner bias and identifies personalized dimensions for providers and users to evaluate the individuals' preferences in prosthetic technology.

Knowledge acquisition and learning process description in context of e-learning

NASA Astrophysics Data System (ADS)

Kiselev, B. G.; Yakutenko, V. A.; Yuriev, M. A.

2017-01-01

This paper investigates the problem of design of e-learning and MOOC systems. It describes instructional design-based approaches to e-learning systems design: IMS Learning Design, MISA and TELOS. To solve this problem we present Knowledge Field of Educational Environment with Competence boundary conditions - instructional engineering method for self-learning systems design. It is based on the simplified TELOS approach and enables a user to create their individual learning path by choosing prerequisite and target competencies. The paper provides the ontology model for the described instructional engineering method, real life use cases and the classification of the presented model. Ontology model consists of 13 classes and 15 properties. Some of them are inherited from Knowledge Field of Educational Environment and some are new and describe competence boundary conditions and knowledge validation objects. Ontology model uses logical constraints and is described using OWL 2 standard. To give TELOS users better understanding of our approach we list mapping between TELOS and KFEEC.

The 1973 NASA payload model: Space opportunities 1973 - 1991. [characteristics of payloads and requirements of user community

NASA Technical Reports Server (NTRS)

1973-01-01

The tables of schedules and descriptions which portray the 1973 NASA Payload Model are presented. The schedules cover all NASA programs and the anticipated requirements of the user community, not including the Department of Defense, for the 1973 to 1991 period. The descriptions give an indication of what the payload is expected to accomplish, its characteristics, and where it is going. The payload flight schedules shown for each of the discipline areas indicate the time frame in which individual payloads will be launched, serviced, or retrieved. These do not necessarily constitute shuttle flights, however, since more than one payload can be flown on a single shuttle flight depending on size, weight, orbital destination, and the suitability of combining them. The weight, dimension, and destination data represent approximations of the payload characteristics as estimated by the Program Offices. Payload codes are provided for easy correlation between the schedules and descriptions of the Payload Model and subsequent documentation which may reference this model.

The global diabetes model: user friendly version 3.0.

PubMed

Brown, J B; Russell, A; Chan, W; Pedula, K; Aickin, M

2000-11-01

The attributes of Release 3.0 of the user friendly version (UFV) of the global diabetes model (GDM) are described and documented in detail. The GDM is a continuous, stochastic microsimulation model of type 2 diabetes. Suitable for predicting the medical futures of both individuals with diabetes and representative diabetic populations, the GDM predicts medical events (complications of diabetes), survival, utilities, and medical care costs. Incidence rate functions for microvascular and macrovascular complications are based on a combination of published studies and analyses of data describing diabetic members of Kaiser Permanente Northwest Region, a non-profit group-model health maintenance organization. Active risk factors include average blood glucose (HbAlc), systolic blood pressure (SBP), low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), triglycerides, smoking status, and use of prophylactic aspirin. Events predicted include diabetic eye disease, diabetic nephropathy, peripheral neuropathy amputation, myocardial infarction, stroke, peripheral artery disease, congestive heart failure, coronary artery surgery, coronary angioplasty, and death.

Space-based Ornithology-Studying Bird Migration and Environmental Change in North America

NASA Technical Reports Server (NTRS)

Smith, James; Deppe, Jill

2008-01-01

Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. We have developed an individual-based, spatially explicit bird migration model that simulates the migration routes, timing and energy budgets of individual birds under dynamic weather and land surface conditions. Our model incorporates biophysical constraints, individual bird energy status, bird behavior, and flight aerodynamics. We model the speed, direction, and timing of individual birds moving through a user specified Lagrangian grid. The model incorporates environmental properties including wind speed and direction, topography, dynamic hydrologic properties of the landscape, and environmental suitability. The model is driven by important variables estimated from satellite observations of the land surface, by data assimilation products from weather and climate models, and biological field data. We illustrate the use of the model to study the impact of both short- and long-term environmental variatios, e.g. climate, drought, anthropogenic, on migration timing (phenology), spatial pattern, and fitness (survival and reproductive success). We present several theoretical simulations of the spring migration of Pectoral Sandpiper (Calidris melanotos) in North America with emphasis on the Central flyway from the Gulf of Mexico to Alaska.

MOPADS (Models of Operator Performance in Air Defense Systems). Appendices

DTIC Science & Technology

1984-11-01

differential equation models which aggregate and smooth individual events to obtain overall average performance measures. The advantages, in the MOPADS...Positive z is up. Each critical asset is specified by its coordinates anod a label. Growth potential is allowed in the data base for differentiating among...OlUI Figure IX-1. (Continued) C- 115 MAIN CATEGORY SELtCTION:SAINT USER ITATISITICS SECONDARY CATEGORT HE ,U1 * lIlT PRINT COMMAND MN - TATIS [TICS

Interface Usability Across and Within EHR Vendors and Medical Settings: The Often Unexamined Need for Interface Similarities.

PubMed

Koppel, Ross; Kuziemsky, Craig

2017-01-01

Usability of health information technology (HIT), if considered at all, is usually focused on individual providers, settings and vendors. However, in light of transformative models of healthcare delivery such as collaborative care delivery that crosses providers and settings, we need to think of usability as a collective and constantly emerging process. To address this new reality we develop a matrix of usability that spans several dimensions and contexts, incorporating differing vendors, user, settings, disciplines, and display configurations. The matrix, while conceptual, extends existing work by providing the means for discussion of usability issues and needs beyond one setting and one user type.

Social networking sites: a novel portal for communication.

PubMed

Farmer, A D; Bruckner Holt, C E M; Cook, M J; Hearing, S D

2009-09-01

The internet has transformed many spheres of society. Most notably the advent of social networking websites, such as MySpace, Bebo and Facebook, have attracted many millions of users worldwide. There are over 350 such sites in operation across the internet. There is a paucity of data in the adult literature examining the medical usage of this interesting facet of modern life. To ascertain whether Facebook has user groups that are connected with common medical conditions, and to classify the user groups that were identified as well as enumerating the number of individual users contained therein. We conducted a search of the entire Facebook website between December 2007 and January 2009. We used medical and lay nomenclature for the most prevalent non-communicable diseases as identified from the World Health Organisation Burden of Disease publication to identify whether they were represented among individual Facebook users and user groups. We identified 290,962 individual users who were part of 757 groups. Patient groups accounted for 47.4%, patient/carer support groups 28.1%, fund raising groups 18.6%, and others 5.8%. Notably, there were other groups containing representations from the scientific research community in addition to educational resources. The groups with the most individual members pertained to malignant neoplasms and cardiovascular disease (141,458 users) consistent with their worldwide prevalence. Facebook is providing a readily accessible portal for patients, carers and healthcare professionals to share their experiences of investigation, diagnosis and management of disease. Furthermore, this technology is being used for research, education and fundraising. Further research is warranted to explore the further potential of this new technology.

Injection Drug Users’ Involvement In Drug Economy: Dynamics of Sociometric and Egocentric Social Networks

PubMed Central

Yang, Cui; Latkin, Carl; Muth, Stephen Q.; Rudolph, Abby

2014-01-01

The purpose of this analysis was to examine the effect of social network cohesiveness on drug economy involvement, and to test whether this relationship is mediated by drug support network size in a sample of active injection drug users. Involvement in the drug economy was defined by self-report of participation in at least one of the following activities: selling drugs, holding drugs or money for drugs, providing street security for drug sellers, cutting/packaging/cooking drugs, selling or renting drug paraphernalia (e.g., pipes, tools, rigs), and injecting drugs in others’ veins. The sample consists of 273 active injection drug users in Baltimore, Maryland who reported having injected drugs in the last 6 months and were recruited through either street outreach or by their network members. Egocentric drug support networks were assessed through a social network inventory at baseline. Sociometric networks were built upon the linkages by selected matching characteristics, and k-plex rank was used to characterize the level of cohesiveness of the individual to others in the social network. Although no direct effect was observed, structural equation modeling indicated k-plex rank was indirectly associated with drug economy involvement through drug support network size. These findings suggest the effects of large-scale sociometric networks on injectors’ drug economy involvement may occur through their immediate egocentric networks. Future harm reduction programs for injection drug users (IDUs) should consider providing programs coupled with economic opportunities to those drug users within a cohesive network subgroup. Moreover, individuals with a high connectivity to others in their network may be optimal individuals to train for diffusing HIV prevention messages. PMID:25309015

Analyzing structural changes in SNOMED CT's Bacterial infectious diseases using a visual semantic delta.

PubMed

Ochs, Christopher; Case, James T; Perl, Yehoshua

2017-03-01

Thousands of changes are applied to SNOMED CT's concepts during each release cycle. These changes are the result of efforts to improve or expand the coverage of health domains in the terminology. Understanding which concepts changed, how they changed, and the overall impact of a set of changes is important for editors and end users. Each SNOMED CT release comes with delta files, which identify all of the individual additions and removals of concepts and relationships. These files typically contain tens of thousands of individual entries, overwhelming users. They also do not identify the editorial processes that were applied to individual concepts and they do not capture the overall impact of a set of changes on a subhierarchy of concepts. In this paper we introduce a methodology and accompanying software tool called a SNOMED CT Visual Semantic Delta ("semantic delta" for short) to enable a comprehensive review of changes in SNOMED CT. The semantic delta displays a graphical list of editing operations that provides semantics and context to the additions and removals in the delta files. However, there may still be thousands of editing operations applied to a set of concepts. To address this issue, a semantic delta includes a visual summary of changes that affected sets of structurally and semantically similar concepts. The software tool for creating semantic deltas offers views of various granularities, allowing a user to control how much change information they view. In this tool a user can select a set of structurally and semantically similar concepts and review the editing operations that affected their modeling. The semantic delta methodology is demonstrated on SNOMED CT's Bacterial infectious disease subhierarchy, which has undergone a significant remodeling effort over the last two years. Copyright © 2017 Elsevier Inc. All rights reserved.

Analyzing Structural Changes in SNOMED CT’s Bacterial Infectious Diseases Using a Visual Semantic Delta

PubMed Central

Ochs, Christopher; Case, James T.; Perl, Yehoshua

2017-01-01

Thousands of changes are applied to SNOMED CT’s concepts during each release cycle. These changes are the result of efforts to improve or expand the coverage of health domains in the terminology. Understanding which concepts changed, how they changed, and the overall impact of a set of changes is important for editors and end users. Each SNOMED CT release comes with delta files, which identify all of the individual additions and removals of concepts and relationships. These files typically contain tens of thousands of individual entries, overwhelming users. They also do not identify the editorial processes that were applied to individual concepts and they do not capture the overall impact of a set of changes on a subhierarchy of concepts. In this paper we introduce a methodology and accompanying software tool called a SNOMED CT Visual Semantic Delta (“semantic delta” for short) to enable a comprehensive review of changes in SNOMED CT. The semantic delta displays a graphical list of editing operations that provides semantics and context to the additions and removals in the delta files. However, there may still be thousands of editing operations applied to a set of concepts. To address this issue, a semantic delta includes a visual summary of changes that affected sets of structurally and semantically similar concepts. The software tool for creating semantic deltas offers views of various granularities, allowing a user to control how much change information they view. In this tool a user can select a set of structurally and semantically similar concepts and review the editing operations that affected their modeling. The semantic delta methodology is demonstrated on SNOMED CT’s Bacterial infectious disease subhierarchy, which has undergone a significant remodeling effort over the last two years. PMID:28215561

Designing Messaging to Engage Patients in an Online Suicide Prevention Intervention: Survey Results From Patients With Current Suicidal Ideation

PubMed Central

Lungu, Anita; Richards, Julie; Simon, Gregory E; Clingan, Sarah; Siler, Jaeden; Snyder, Lorilei; Ludman, Evette

2014-01-01

Background Computerized, Internet-delivered interventions can be efficacious; however, uptake and maintaining sustained client engagement are still big challenges. We see the development of effective engagement strategies as the next frontier in online health interventions, an area where much creative research has begun. We also argue that for engagement strategies to accomplish their purpose with novel targeted populations, they need to be tailored to such populations (ie, content is designed with the target population in mind). User-centered design frameworks provide a theoretical foundation for increasing user engagement and uptake by including users in development. However, deciding how to implement this approach to enage users in mental health intervention development is challenging. Objective The aim of this study was to get user input and feedback on acceptability of messaging content intended to engage suicidal individuals. Methods In March 2013, clinic intake staff distributed flyers announcing the study, “Your Feedback Counts” to potential participants (individuals waiting to be seen for a mental health appointment) together with the Patient Health Questionnaire. The flyer explained that a score of two or three (“more than half the days” or “nearly every day” respectively) on the suicide ideation question made them eligible to provide feedback on components of a suicide prevention intervention under development. The patient could access an anonymous online survey by following a link. After providing consent online, participants completed the anonymous survey. Results Thirty-four individuals provided data on past demographic information. Participants reported that they would be most drawn to an intervention where they knew that they were cared about, that was personalized, that others like them had found it helpful, and that included examples with real people. Participants preferred email invitations with subject lines expressing concern and availability of extra resources. Participants also provided feedback about a media prototype including a brand design and advertisement video for introducing the intervention. Conclusions This paper provides one model (including development of an engagement survey, audience for an engagement survey, methods for presenting results of an engagement survey) for including target users in the development of uptake strategies for online mental health interventions. PMID:24509475

Digital divide, biometeorological data infrastructures and human vulnerability definition

NASA Astrophysics Data System (ADS)

Fdez-Arroyabe, Pablo; Lecha Estela, Luis; Schimt, Falko

2018-05-01

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user's geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.

Design and implementation of location-based wireless targeted advertising

NASA Astrophysics Data System (ADS)

Li, Benjamin; Xu, Deyin

2001-10-01

As advertisements are time and location sensitive, a challenge for wireless marketing is to have advertisements delivered when and where they are most convenient. In this paper we introduce a two-stage auction model for location-based wireless targeted advertising. This system extends the notion of location-based service by using location information to target advertising, and does so specifically by enabling advertisers to specify their preferences and bid for advertisement delivery, where those preferences are then used in a subsequent automated auction of actual deliveries to wireless data users. The automated auction in the second stage is especially effective because it can use information about the individual user profile data, including customer relationship management system contents as well as location from the wireless system's location management service, including potentially location history such as current trajectory from recent history and longer-term historical trip records for that user. Through two-stage auction, real-time bidding by advertisers and matching ads contents to mobile users help advertising information reach maximal value.

Experiencing mental health diagnosis: a systematic review of service user, clinician, and carer perspectives across clinical settings.

PubMed

Perkins, Amorette; Ridler, Joseph; Browes, Daniel; Peryer, Guy; Notley, Caitlin; Hackmann, Corinna

2018-04-18

Receiving a mental health diagnosis can be pivotal for service users, and it has been described in both positive and negative terms. What influences service-user experience of the diagnostic process is unclear; consequently, clinicians report uncertainty regarding best practice. This Review aims to understand and inform diagnostic practice through a comprehensive synthesis of qualitative data on views and experiences from key stakeholders (service users, clinicians, carers, and family). We searched five databases and identified 78 papers for inclusion, originating from 13 countries and including 2228 participants. Eligible papers were assessed for quality, and data were coded and then developed into themes, which generated a model representing factors to consider for clinicians conveying, and individuals receiving, mental health diagnoses. Themes included disclosure, information provision, collaboration, timing, stigma, and functional value of diagnosis for recovery. Variations between different stakeholders and clinical contexts are explored. Findings support an individualised, collaborative, and holistic approach to mental health diagnosis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Studying Psychosocial Barriers to Drug Treatment Among Chinese Methamphetamine Users Using A 3-Step Latent Class Analysis.

PubMed

Wang, Jichuan; Kelly, Brian C; Liu, Tieqiao; Hao, Wei

2016-03-01

Given the growth in methamphetamine use in China during the 21st century, we assessed perceived psychosocial barriers to drug treatment among this population. Using a sample of 303 methamphetamine users recruited via Respondent Driven Sampling, we use Latent Class Analysis (LCA) to identify possible distinct latent groups among Chinese methamphetamine users on the basis of their perceptions of psychosocial barriers to drug treatment. After covariates were included to predict latent class membership, the 3-step modeling approach was applied. Our findings indicate that the Chinese methamphetamine using population was heterogeneous on perceptions of drug treatment barriers; four distinct latent classes (subpopulations) were identified--Unsupported Deniers, Deniers, Privacy Anxious, and Low Barriers--and individual characteristics shaped the probability of class membership. Efforts to link Chinese methamphetamine users to treatment may require a multi-faceted approach that attends to differing perceptions about impediments to drug treatment. Copyright © 2015. Published by Elsevier Inc.

Digital divide, biometeorological data infrastructures and human vulnerability definition.

PubMed

Fdez-Arroyabe, Pablo; Lecha Estela, Luis; Schimt, Falko

2018-05-01

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user's geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.

Digital divide, biometeorological data infrastructures and human vulnerability definition

NASA Astrophysics Data System (ADS)

Fdez-Arroyabe, Pablo; Lecha Estela, Luis; Schimt, Falko

2017-06-01

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user's geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.

CRUX: A compliant robotic upper-extremity exosuit for lightweight, portable, multi-joint muscular augmentation.

PubMed

Lessard, Steven; Pansodtee, Pattawong; Robbins, Ash; Baltaxe-Admony, Leya Breanna; Trombadore, James M; Teodorescu, Mircea; Agogino, Adrian; Kurniawan, Sri

2017-07-01

Wearable robots can potentially offer their users enhanced stability and strength. These augmentations are ideally designed to actuate harmoniously with the user's movements and provide extra force as needed. The creation of such robots, however, is particularly challenging due to the underlying complexity of the human body. In this paper, we present a compliant, robotic exosuit for upper extremities called CRUX. This exosuit, inspired by tensegrity models of the human arm, features a lightweight (1.3 kg), flexible multi-joint design for portable augmentation. We also illustrate how CRUX maintains the full range of motion of the upper-extremities for its users while providing multi-DoF strength amplification to the major muscles of the arm, as evident by tracking the heart rate of an individual exercising said arm. Exosuits such as CRUX may be useful in physical therapy and in extreme environments where users are expected to exert their bodies to the fullest extent.

PEGASO: A Personalised and Motivational ICT System to Empower Adolescents Towards Healthy Lifestyles.

PubMed

Carrino, Stefano; Caon, Maurizio; Angelini, Leonardo; Mugellini, Elena; Abou Khaled, Omar; Orte, Silvia; Vargiu, Eloisa; Coulson, Neil; Serrano, José C E; Tabozzi, Sarah; Lafortuna, Claudio; Rizzo, Giovanna

2014-01-01

Unhealthy alimentary behaviours and physical inactivity habits are key risk factors for major non communicable diseases. Several researches demonstrate that juvenile obesity can lead to serious medical conditions, pathologies and have important psycho-social consequences. PEGASO is a multidisciplinary project aimed at promoting healthy lifestyles among teenagers through assistive technology. The core of this project is represented by the ICT system, which allows providing tailored interventions to the users through their smartphones in order to motivate them. The novelty of this approach consists of developing a Virtual Individual Model (VIM) for user characterization, which is based on physical, functional and behavioural parameters opportunely selected by experts. These parameters are digitised and updated thanks to the user monitoring through smartphone; data mining algorithms are applied for the detection of activity and nutrition habits and this information is used to provide personalised feedback. The user interface will be developed using gamified approaches and integrating serious games to effectively promote health literacy and facilitate behaviour change.

VOC-PLAN: Individual Vocational Education Plan (A Quick, Efficient and Creative Way to Generate Vocational I.E.P.s), Users Manual and Preview Manual.

ERIC Educational Resources Information Center

Robinson, Jim; Seabolt, Pete

This User's Manual is intended to accompany VOC-PLAN, a computer (Apple) program designed to assist in the preparation of an Individualized Vocational Education Program (IVEP) for handicapped, disadvantaged, or regular vocational secondary and postsecondary students. The program is presented in standard IEP (Individualized Education Program)…

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

PubMed Central

Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

2015-01-01

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

The Trip Itinerary Optimization Platform: A Framework for Personalized Travel Information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kwasnik, Ted; Carmichael, Scott P.; Arent, Douglas J

The New Concepts Incubator team at the National Renewable Energy Laboratory (NREL) developed a three-stage online platform for travel diary collection, personal travel plan optimization and travel itinerary visualization. In the first stage, users provide a travel diary for the previous day through an interactive map and calendar interface and survey for travel attitudes and behaviors. One or more days later, users are invited via email to engage in a second stage where they view a personal mobility dashboard displaying recommended travel itineraries generated from a novel framework that optimizes travel outcomes over a sequence of interrelated trips. A weekmore » or more after viewing these recommended travel itineraries on the dashboard, users are emailed again to engage in a third stage where they complete a final survey about travel attitudes and behaviors. A usability study of the platform conducted online showed that, in general, users found the system valuable for informing their travel decisions. A total of 274 individuals were recruited through Amazon Mechanical Turk, an online survey platform, to participate in a transportation study using this platform. On average, the platform distilled 65 feasible travel plans per individual into two recommended itineraries, each optimal according to one or more outcomes and dependent on the fixed times and locations from the travel diary. For 45 percent of users, the trip recommendation algorithm returned only a single, typically automobile-centric, itinerary because there were no other viable alternative transportation modes available. Platform users generally agreed that the dashboard was enjoyable and easy to use, and that it would be a helpful tool in adopting new travel behaviors. Users generally agreed most that the time, cost and user preferred recommendations 'made sense' to them, and were most willing to implement these itineraries. Platform users typically expressed low willingness to try the carbon and calories optimized itineraries. Of the platform users who viewed the dashboard, 13 percent reported changing their travel behavior, most adopting the time, calories or carbon optimized itineraries. While the algorithm incorporates a wealth of travel data obtained from online APIs pertaining to a travelers route such as historic traffic condition data, public transit time-tables, and bike path routes, open-ended responses from users expressed an interest in the integration of even more fine-grained traffic data and the ability to dynamically model the effect of changes in travel times. Users also commonly expressed concerns over the safety of walking and biking recommendations. Responses indicate that more information about the amenities available to cyclists and pedestrians (sidewalks, shade from trees, access to food) and routes that avoid areas of perceived elevated danger would reduce barriers to implementing these recommendations. More accurate representations of personal vehicle trips (based on vehicle make and model, implications of parking) and the identification of routes that optimize caloric intensity (seeking out elevation changes or longer walks to public transit) are promising avenues for future research.« less

FlexibleSUSY-A spectrum generator generator for supersymmetric models

NASA Astrophysics Data System (ADS)

Athron, Peter; Park, Jae-hyeon; Stöckinger, Dominik; Voigt, Alexander

2015-05-01

We introduce FlexibleSUSY, a Mathematica and C++ package, which generates a fast, precise C++ spectrum generator for any SUSY model specified by the user. The generated code is designed with both speed and modularity in mind, making it easy to adapt and extend with new features. The model is specified by supplying the superpotential, gauge structure and particle content in a SARAH model file; specific boundary conditions e.g. at the GUT, weak or intermediate scales are defined in a separate FlexibleSUSY model file. From these model files, FlexibleSUSY generates C++ code for self-energies, tadpole corrections, renormalization group equations (RGEs) and electroweak symmetry breaking (EWSB) conditions and combines them with numerical routines for solving the RGEs and EWSB conditions simultaneously. The resulting spectrum generator is then able to solve for the spectrum of the model, including loop-corrected pole masses, consistent with user specified boundary conditions. The modular structure of the generated code allows for individual components to be replaced with an alternative if available. FlexibleSUSY has been carefully designed to grow as alternative solvers and calculators are added. Predefined models include the MSSM, NMSSM, E6SSM, USSM, R-symmetric models and models with right-handed neutrinos.

Our Deming Users' Group.

ERIC Educational Resources Information Center

Dinklocker, Christina

1992-01-01

After training in the Total Quality Management concept, a suburban Ohio school district created a Deming Users' Group to link agencies, individuals, and ideas. The group has facilitated ongoing school/business collaboration, networking among individuals from diverse school systems, mentoring and cooperative learning activities, and resource…

Capture-recapture methodology

USGS Publications Warehouse

Gould, William R.; Kendall, William L.

2013-01-01

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

Persuasive user experiences of a health Behavior Change Support System: A 12-month study for prevention of metabolic syndrome.

PubMed

Karppinen, Pasi; Oinas-Kukkonen, Harri; Alahäivälä, Tuomas; Jokelainen, Terhi; Keränen, Anna-Maria; Salonurmi, Tuire; Savolainen, Markku

2016-12-01

Obesity has become a severe health problem in the world. Even a moderate 5% weight loss can significantly reduce the prevalence of metabolic syndrome, which can be vital for preventing comorbidities caused by the obesity. Health Behavior Change Support Systems (hBCSS) emphasize an autogenous approach, where an individual uses the system to influence one's own attitude or behavior to achieve his or her own goal. Regardless of promising results, such health interventions technology has often been considered merely as a tool for delivering content that has no effect or value of its own. More research on actual system features is required. The objective of this study is to describe how users perceive persuasive software features designed and implemented into a support system. The research medium in this study is a web-based information system designed as a lifestyle intervention for participants who are at risk of developing a metabolic syndrome or who are already suffering from it. The system was designed closely following the principles of the Persuasive Systems Design (PSD) model and the Behavior Change Support Systems (BCSS) framework. A total of 43 system users were interviewed for this study during and after a 52 week intervention period. In addition, the system's login data and subjects' Body Mass Index (BMI) measures were used to interpret the results. This study explains in detail how the users perceived using the system and its persuasive features. Self-monitoring, reminders, and tunneling were perceived as especially beneficial persuasive features. The need for social support appeared to grow along the duration of the intervention. Unobtrusiveness was found to be very important in all stages of the intervention rather than only at the beginning. Persuasive software features have power to affect individuals' health behaviors. Through their systematicity the PSD model and the BCSS framework provide effective support for the design and development of technological health interventions. Designers of such systems may choose, for instance, to implement more self-monitoring tools to help individuals to adjust their personal goals with the system's offerings better. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

How happy is your web browsing? A model to quantify satisfaction of an Internet user searching for desired information

NASA Astrophysics Data System (ADS)

Banerji, Anirban; Magarkar, Aniket

2012-09-01

We feel happy when web browsing operations provide us with necessary information; otherwise, we feel bitter. How to measure this happiness (or bitterness)? How does the profile of happiness grow and decay during the course of web browsing? We propose a probabilistic framework that models the evolution of user satisfaction, on top of his/her continuous frustration at not finding the required information. It is found that the cumulative satisfaction profile of a web-searching individual can be modeled effectively as the sum of a random number of random terms, where each term is a mutually independent random variable, originating from ‘memoryless’ Poisson flow. Evolution of satisfaction over the entire time interval of a user’s browsing was modeled using auto-correlation analysis. A utilitarian marker, a magnitude of greater than unity of which describes happy web-searching operations, and an empirical limit that connects user’s satisfaction with his frustration level-are proposed too. The presence of pertinent information in the very first page of a website and magnitude of the decay parameter of user satisfaction (frustration, irritation etc.) are found to be two key aspects that dominate the web user’s psychology. The proposed model employed different combinations of decay parameter, searching time and number of helpful websites. The obtained results are found to match the results from three real-life case studies.

Profiles of Cyberpornography Use and Sexual Well-Being in Adults.

PubMed

Vaillancourt-Morel, Marie-Pier; Blais-Lecours, Sarah; Labadie, Chloé; Bergeron, Sophie; Sabourin, Stéphane; Godbout, Natacha

2017-01-01

Although findings concerning sexual outcomes associated with cyberpornography use are mixed, viewing explicit sexual content online is becoming a common activity for an increasing number of individuals. To investigate heterogeneity in cyberpornography-related sexual outcomes by examining a theoretically and clinically based model suggesting that individuals who spend time viewing online pornography form three distinct profiles (recreational, at-risk, and compulsive) and to examine whether these profiles were associated with sexual well-being, sex, and interpersonal context of pornography use. The present cluster-analytic study was conducted using a convenience sample of 830 adults who completed online self-reported measurements of cyberpornography use and sexual well-being, which included sexual satisfaction, compulsivity, avoidance, and dysfunction. Dimensions of cyberpornography use were assessed using the Cyber Pornography Use Inventory. Sexual well-being measurements included the Global Measure of Sexual Satisfaction, the Sexual Compulsivity Scale, the Sexual Avoidance Subscale, and the Arizona Sexual Experiences Scale. Cluster analyses indicated three distinct profiles: recreational (75.5%), highly distressed non-compulsive (12.7%), and compulsive (11.8%). Recreational users reported higher sexual satisfaction and lower sexual compulsivity, avoidance, and dysfunction, whereas users with a compulsive profile presented lower sexual satisfaction and dysfunction and higher sexual compulsivity and avoidance. Highly distressed less active users were sexually less satisfied and reported less sexual compulsivity and more sexual dysfunction and avoidance. A larger proportion of women and of dyadic users was found among recreational users, whereas solitary users were more likely to be in the highly distressed less active profile and men were more likely to be in the compulsive profile. This pattern of results confirms the existence of recreational and compulsive profiles but also demonstrates the existence of an important subgroup of not particularly active, yet highly distressed consumers. Cyberpornography users represent a heterogeneous population, in which each subgroup is associated with specific sexual outcomes. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Supporting Shared Resource Usage for a Diverse User Community: the OSG Experience and Lessons Learned

NASA Astrophysics Data System (ADS)

Garzoglio, Gabriele; Levshina, Tanya; Rynge, Mats; Sehgal, Chander; Slyz, Marko

2012-12-01

The Open Science Grid (OSG) supports a diverse community of new and existing users in adopting and making effective use of the Distributed High Throughput Computing (DHTC) model. The LHC user community has deep local support within the experiments. For other smaller communities and individual users the OSG provides consulting and technical services through the User Support area. We describe these sometimes successful and sometimes not so successful experiences and analyze lessons learned that are helping us improve our services. The services offered include forums to enable shared learning and mutual support, tutorials and documentation for new technology, and troubleshooting of problematic or systemic failure modes. For new communities and users, we bootstrap their use of the distributed high throughput computing technologies and resources available on the OSG by following a phased approach. We first adapt the application and run a small production campaign on a subset of “friendly” sites. Only then do we move the user to run full production campaigns across the many remote sites on the OSG, adding to the community resources up to hundreds of thousands of CPU hours per day. This scaling up generates new challenges - like no determinism in the time to job completion, and diverse errors due to the heterogeneity of the configurations and environments - so some attention is needed to get good results. We cover recent experiences with image simulation for the Large Synoptic Survey Telescope (LSST), small-file large volume data movement for the Dark Energy Survey (DES), civil engineering simulation with the Network for Earthquake Engineering Simulation (NEES), and accelerator modeling with the Electron Ion Collider group at BNL. We will categorize and analyze the use cases and describe how our processes are evolving based on lessons learned.

McGurk stimuli for the investigation of multisensory integration in cochlear implant users: The Oldenburg Audio Visual Speech Stimuli (OLAVS).

PubMed

Stropahl, Maren; Schellhardt, Sebastian; Debener, Stefan

2017-06-01

The concurrent presentation of different auditory and visual syllables may result in the perception of a third syllable, reflecting an illusory fusion of visual and auditory information. This well-known McGurk effect is frequently used for the study of audio-visual integration. Recently, it was shown that the McGurk effect is strongly stimulus-dependent, which complicates comparisons across perceivers and inferences across studies. To overcome this limitation, we developed the freely available Oldenburg audio-visual speech stimuli (OLAVS), consisting of 8 different talkers and 12 different syllable combinations. The quality of the OLAVS set was evaluated with 24 normal-hearing subjects. All 96 stimuli were characterized based on their stimulus disparity, which was obtained from a probabilistic model (cf. Magnotti & Beauchamp, 2015). Moreover, the McGurk effect was studied in eight adult cochlear implant (CI) users. By applying the individual, stimulus-independent parameters of the probabilistic model, the predicted effect of stronger audio-visual integration in CI users could be confirmed, demonstrating the validity of the new stimulus material.

Optimization Model for Web Based Multimodal Interactive Simulations.

PubMed

Halic, Tansel; Ahn, Woojin; De, Suvranu

2015-07-15

This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update . In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.

An extension of technology acceptance model to determine factors that influence the intention to use electronic collection system in Nigerian federal hospitals

NASA Astrophysics Data System (ADS)

Kabir, Muhammad Auwal; Saidin, Siti Zabedah; Ahmi, Aidi

2017-10-01

The aim of this paper is to develop a conceptual framework that would be used in determining the factors that influence the behavioral intention to use electronic collection system in federal government owned hospitals in Nigeria. The framework is supported by Technology Acceptance Model (TAM) as the underlying theory of the study. Past literature on individual user intention were thoroughly reviewed and found that TAM is fit appropriate in explaining the phenomenon under study. Based on the reviewed literature, it is expected that perceived usefulness and perceived ease of use will influence the intention of users (employees) to use e-collection system in the performance of their job tasks in Nigerian federal hospitals. In other words, users with higher perception on the system's usefulness and its ease of use are more likely to express their interest and willingness to use the system. In addition, the study has extended TAM with facilitating conditions construct and the research is expected to discover the level of its influence on behavioral intention to use e-collection system.

Optimization Model for Web Based Multimodal Interactive Simulations

PubMed Central

Halic, Tansel; Ahn, Woojin; De, Suvranu

2015-01-01

This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update. In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach. PMID:26085713

Impulsivity, Attention, Memory, and Decision-Making among Adolescent Marijuana Users

PubMed Central

Dougherty, Donald M.; Mathias, Charles W.; Dawes, Michael A.; Furr, R. Michael; Charles, Nora E.; Liguori, Anthony; Shannon, Erin E.; Acheson, Ashley

2012-01-01

Rationale Marijuana is a popular drug of abuse among adolescents, and they may be uniquely vulnerable to resulting cognitive and behavioral impairments. Previous studies have found impairments among adolescent marijuana users. However, the majority of this research has examined measures individually rather than multiple domains in a single cohesive analysis. This study used a logistic regression model that combines performance on a range of tasks to identify which measures were most altered among adolescent marijuana users. Objectives The purpose of this research was to determine unique associations between adolescent marijuana user and performances on multiple cognitive and behavioral domains (attention, memory, decision-making, and impulsivity) in 14- to 17-year-olds while simultaneously controlling for performances across the measures to determine which measures most strongly distinguish marijuana users from non-users. Methods Marijuana-using adolescents (n=45) and controls (n=48) were tested. Logistic regression analyses were conducted to test for: (a) differences between marijuana users and non-users on each measure, (b) associations between marijuana use and each measure after controlling for the other measures, and (c) the degree to which (a) and (b) together elucidated differences among marijuana users and non-users. Results Of all the cognitive and behavioral domains tested, impaired short-term recall memory and consequence sensitivity impulsivity were associated with marijuana use after controlling for performances across all measures. Conclusions This study extends previous findings by identifying cognitive and behavioral impairments most strongly associated with adolescent marijuana users. These specific deficits are potential targets of intervention for this at-risk population. PMID:23138434

Exploring beliefs about dietary supplement use: focus group discussions with Dutch adults.

PubMed

Pajor, Emília Margit; Oenema, Anke; Eggers, Sander Matthijs; de Vries, Hein

2017-10-01

Although dietary supplement use is increasing in Europe and the USA, little research involving adults' beliefs regarding dietary supplements has been conducted. Therefore, the present study aimed to explore and compare users' and non-users' beliefs towards dietary supplements. Thirteen focus group discussions were conducted of which seven groups were dietary supplement users and six groups were non-users. Based on the socio-cognitive factors of the Integrated Change Model, a semi-structured topic guide was set up. The discussions were audio-recorded and subjected to qualitative content analysis, applying the framework approach. Data were collected in Maastricht, the Netherlands, in 2014 and 2015. In total fifty-six individuals participated in the study, of whom twenty-eight were dietary supplement users and twenty-eight non-users. The average age of participants was 42·9 years. Dietary supplement users' attitude beliefs were mainly related to mental and physical health enhancement, illness prevention and curative health benefits. Users were critical of the nutritional knowledge of health professionals and of the quality of food products. Non-users were convinced that the human body does not need any support and that regular food is enough to cover one's nutritional needs. Users and non-users held comparable beliefs regarding the definition and risks of dietary supplements, and perceived social influences. In their decision about dietary supplement use, both groups were guided by their own convictions to a great extent. Both groups would benefit from improved understanding of the health effects of dietary supplements to improve informed decision making.

CUAHSI Hydrologic Information Systems

NASA Astrophysics Data System (ADS)

Maidment, D.; Zaslavsky, I.; Tarboton, D.; Piasecki, M.; Goodall, J.

2006-12-01

The Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has a Hydrologic Information System (HIS) project, which is supported by NSF to develop infrastructure and services to support the advance of hydrologic science in the United States. This paper provides an overview of the HIS project. A set of web services called WaterOneFlow is being developed to provide better access to water observations data (point measurements of streamflow, water quality, climate and groundwater levels) from government agencies and individual investigator projects. Successful partnerships have been created with the USGS National Water Information System, EPA Storet and the NCDC Climate Data Online. Observations catalogs have been created for stations in the measurement networks of each of these data systems so that they can be queried in a uniform manner through CUAHSI HIS, and data delivered from them directly to the user via web services. A CUAHSI Observations Data Model has been designed for storing individual investigator data and an equivalent set of web services created for that so that individual investigators can publish their data onto the internet in the same format CUAHSI is providing for the federal agency data. These data will be accessed through HIS Servers hosted at the national level by CUAHSI and also by research centers and academic departments for regional application of HIS. An individual user application called HIS Analyst will enable individual hydrologic scientists to access the information from the network of HIS Servers. The present focus is on water observations data but later development of this system will include weather and climate grid information, GIS data, remote sensing data and linkages between data and hydrologic simulation models.

Empowered genome community: leveraging a bioinformatics platform as a citizen-scientist collaboration tool.

PubMed

Wendelsdorf, Katherine; Shah, Sohela

2015-09-01

There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS) technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy - to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC) is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen-scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public.

iBoard/CDX User Guide for Nonfederal Individuals and Company/Organization Points of Contact

EPA Pesticide Factsheets

This user guide describes the process that individuals or company/organization points of contact (POCs) must follow to submit non-EPA personnel data through the EPA’s Central Data Exchange (CDX) iBoard application for review and approval.

Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN.

PubMed

Hao, Jie; Liebeke, Manuel; Astle, William; De Iorio, Maria; Bundy, Jacob G; Ebbels, Timothy M D

2014-01-01

Data processing for 1D NMR spectra is a key bottleneck for metabolomic and other complex-mixture studies, particularly where quantitative data on individual metabolites are required. We present a protocol for automated metabolite deconvolution and quantification from complex NMR spectra by using the Bayesian automated metabolite analyzer for NMR (BATMAN) R package. BATMAN models resonances on the basis of a user-controllable set of templates, each of which specifies the chemical shifts, J-couplings and relative peak intensities for a single metabolite. Peaks are allowed to shift position slightly between spectra, and peak widths are allowed to vary by user-specified amounts. NMR signals not captured by the templates are modeled non-parametrically by using wavelets. The protocol covers setting up user template libraries, optimizing algorithmic input parameters, improving prior information on peak positions, quality control and evaluation of outputs. The outputs include relative concentration estimates for named metabolites together with associated Bayesian uncertainty estimates, as well as the fit of the remainder of the spectrum using wavelets. Graphical diagnostics allow the user to examine the quality of the fit for multiple spectra simultaneously. This approach offers a workflow to analyze large numbers of spectra and is expected to be useful in a wide range of metabolomics studies.

Decision support system development at the Upper Midwest Environmental Sciences Center

USGS Publications Warehouse

Fox, Timothy J.; Nelson, J. C.; Rohweder, Jason J.

2014-01-01

A Decision Support System (DSS) can be defined in many ways. The working definition used by the U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) is, “A spatially based computer application or data that assists a researcher or manager in making decisions.” This is quite a broad definition—and it needs to be, because the possibilities for types of DSSs are limited only by the user group and the developer’s imagination. There is no one DSS; the types of DSSs are as diverse as the problems they help solve. This diversity requires that DSSs be built in a variety of ways, using the most appropriate methods and tools for the individual application. The skills of potential DSS users vary widely as well, further necessitating multiple approaches to DSS development. Some small, highly trained user groups may want a powerful modeling tool with extensive functionality at the expense of ease of use. Other user groups less familiar with geographic information system (GIS) and spatial data may want an easy-to-use application for a nontechnical audience. UMESC has been developing DSSs for almost 20 years. Our DSS developers offer our partners a wide variety of technical skills and development options, ranging from the most simple Web page or small application to complex modeling application development.

Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study.

PubMed

Ghomi, Haniyeh; Bagheri, Morteza; Fu, Liping; Miranda-Moreno, Luis F

2016-11-16

The main objective of this study is to identify the main factors associated with injury severity of vulnerable road users (VRUs) involved in accidents at highway railroad grade crossings (HRGCs) using data mining techniques. This article applies an ordered probit model, association rules, and classification and regression tree (CART) algorithms to the U.S. Federal Railroad Administration's (FRA) HRGC accident database for the period 2007-2013 to identify VRU injury severity factors at HRGCs. The results show that train speed is a key factor influencing injury severity. Further analysis illustrated that the presence of illumination does not reduce the severity of accidents for high-speed trains. In addition, there is a greater propensity toward fatal accidents for elderly road users compared to younger individuals. Interestingly, at night, injury accidents involving female road users are more severe compared to those involving males. The ordered probit model was the primary technique, and CART and association rules act as the supporter and identifier of interactions between variables. All 3 algorithms' results consistently show that the most influential accident factors are train speed, VRU age, and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGCs.

Arkheia: Data Management and Communication for Open Computational Neuroscience

PubMed Central

Antolík, Ján; Davison, Andrew P.

2018-01-01

Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science toward more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development toward more integrative approaches and more intense communication within and outside of the field poses major new challenges for modelers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user's ability to collaborate in the field and outreach to a wider audience. PMID:29556187

Arkheia: Data Management and Communication for Open Computational Neuroscience.

PubMed

Antolík, Ján; Davison, Andrew P

2018-01-01

Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science toward more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development toward more integrative approaches and more intense communication within and outside of the field poses major new challenges for modelers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user's ability to collaborate in the field and outreach to a wider audience.

Internet Usage, User Satisfaction, Task-Technology Fit, and Performance Impact among Public Sector Employees in Yemen

ERIC Educational Resources Information Center

Isaac, Osama; Abdullah, Zaini; Ramayah, T.; Mutahar, Ahmed M.

2017-01-01

Purpose: The internet technology becomes an essential tool for individuals, organizations, and nations for growth and prosperity. The purpose of this paper is to integrate the DeLone and McLean IS success model with task-technology fit (TTF) to explain the performance impact of Yemeni Government employees. Design/methodology/approach:…

[Introduction of long-term care insurance: changes in service usage].

PubMed

Matsuda, Tomoyuki; Tamiya, Nanako; Kashiwagi, Masayo; Moriyama, Yoko

2013-09-01

With the aging of the population, Japan's long-term care system has shifted from a welfare-placement system to a social-insurance system, which is a precedent of policies for the elderly. We examined how individuals who used care services before the implementation of long-term care insurance (LTCI) (previous service users) currently use the LTCI services, with a focus on the processes of service use. Panel data were obtained from the Nihon University Japanese Longitudinal Study of Aging database. These data were collected by interviews conducted before (November 1999 and March 2000) and after (November 2001 and December 2001) the establishment of LTCI. Among the 3992 individuals who participated in these interviews, 416 of the previous service users, aged ≥65 years, were sampled. The outcome measures were the processes of using LTCI services (application for LTCI, certification of long-term care need, and contract with LTCI service providers). Logistic regression analysis was performed to identify individual factors associated with the process of application for LTCI. There were 133 LTCI users among the 416 previous service users (32.0%). Of the service processes used, 45.5% of previous service users were applicants, 85.7% of the applicants were certified individuals, and 88.7% of those certified used services with service contracts. The application process was significantly easier for individuals with disease (odds ratio[OR], 8.34 : 95% confidence interval [CI], 1.86-37.46), those dependent for their instrumental activities of daily living (IADL) (OR, 11.21 : 95% CI, 5.22-24.07), those with an equivalent income of <1.25 million yen (OR, 2.72 : 95% CI, 1.30-5.69), and those who had used respite care (OR, 3.29 : 95% CI, 1.16-9.35) previously. In contrast, the application process was significantly difficult for community rehabilitation users (OR, 0.38 : 95% CI, 0.17-0.82). Only half of the previous service users were applicants, and they had severe diseases or were more dependent for their IADL. Our findings suggest that many individuals who were functionally independent were covered under the welfare-placement system. Additionally, low-income individuals did not refrain from applying.

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Scalable, MEMS-enabled, vibrational tactile actuators for high resolution tactile displays

NASA Astrophysics Data System (ADS)

Xie, Xin; Zaitsev, Yuri; Velásquez-García, Luis Fernando; Teller, Seth J.; Livermore, Carol

2014-12-01

The design, fabrication, and characterization of a new type of tactile display for people with blindness or low vision is reported. Each tactile element comprises a piezoelectric extensional actuator that vibrates in plane, with a microfabricated scissor mechanism to convert the in-plane actuations into robust, higher-amplitude, out-of-plane (vertical) vibrations that are sensed with the finger pads. When the tactile elements are formed into a 2D array, information can be conveyed to the user by varying the pattern of vibrations in space and time. Analytical models and finite element analysis were used to design individual tactile elements, which were implemented with PZT actuators and both SU-8 and 3D-printed scissor amplifiers. The measured displacements of these 3 mm × 10 mm, MEMS-enabled tactile elements exceed 10 µm, in agreement with models, with measured forces exceeding 45 mN. The performance of the MEMS-enabled tactile elements is compared with the performance of larger, fully-macroscale tactile elements to demonstrate the scale dependence of the devices. The creation of a 28-element prototype is also reported, and the qualitative user experience with the individual tactile elements and displays is described.

Smart City Mobility Application--Gradient Boosting Trees for Mobility Prediction and Analysis Based on Crowdsourced Data.

PubMed

Semanjski, Ivana; Gautama, Sidharta

2015-07-03

Mobility management represents one of the most important parts of the smart city concept. The way we travel, at what time of the day, for what purposes and with what transportation modes, have a pertinent impact on the overall quality of life in cities. To manage this process, detailed and comprehensive information on individuals' behaviour is needed as well as effective feedback/communication channels. In this article, we explore the applicability of crowdsourced data for this purpose. We apply a gradient boosting trees algorithm to model individuals' mobility decision making processes (particularly concerning what transportation mode they are likely to use). To accomplish this we rely on data collected from three sources: a dedicated smartphone application, a geographic information systems-based web interface and weather forecast data collected over a period of six months. The applicability of the developed model is seen as a potential platform for personalized mobility management in smart cities and a communication tool between the city (to steer the users towards more sustainable behaviour by additionally weighting preferred suggestions) and users (who can give feedback on the acceptability of the provided suggestions, by accepting or rejecting them, providing an additional input to the learning process).

Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package

PubMed Central

Ahn, Woo-Young; Haines, Nathaniel; Zhang, Lei

2017-01-01

Reinforcement learning and decision-making (RLDM) provide a quantitative framework and computational theories with which we can disentangle psychiatric conditions into the basic dimensions of neurocognitive functioning. RLDM offer a novel approach to assessing and potentially diagnosing psychiatric patients, and there is growing enthusiasm for both RLDM and computational psychiatry among clinical researchers. Such a framework can also provide insights into the brain substrates of particular RLDM processes, as exemplified by model-based analysis of data from functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). However, researchers often find the approach too technical and have difficulty adopting it for their research. Thus, a critical need remains to develop a user-friendly tool for the wide dissemination of computational psychiatric methods. We introduce an R package called hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks), which offers computational modeling of an array of RLDM tasks and social exchange games. The hBayesDM package offers state-of-the-art hierarchical Bayesian modeling, in which both individual and group parameters (i.e., posterior distributions) are estimated simultaneously in a mutually constraining fashion. At the same time, the package is extremely user-friendly: users can perform computational modeling, output visualization, and Bayesian model comparisons, each with a single line of coding. Users can also extract the trial-by-trial latent variables (e.g., prediction errors) required for model-based fMRI/EEG. With the hBayesDM package, we anticipate that anyone with minimal knowledge of programming can take advantage of cutting-edge computational-modeling approaches to investigate the underlying processes of and interactions between multiple decision-making (e.g., goal-directed, habitual, and Pavlovian) systems. In this way, we expect that the hBayesDM package will contribute to the dissemination of advanced modeling approaches and enable a wide range of researchers to easily perform computational psychiatric research within different populations. PMID:29601060

Association Among Periodontitis and the Use of Crack Cocaine and Other Illicit Drugs.

PubMed

Antoniazzi, Raquel P; Zanatta, Fabricio B; Rösing, Cassiano K; Feldens, Carlos Alberto

2016-12-01

Crack cocaine can alter functions related to the immune system and exert a negative influence on progression and severity of periodontitis. The aim of this study is to compare periodontal status between crack cocaine users and crack cocaine non-users and investigate the association between crack cocaine and periodontitis after adjustments for confounding variables. This cross-sectional study evaluated 106 individuals exposed to crack cocaine and 106 never exposed, matched for age, sex, and tobacco use. An examiner determined visible plaque index (VPI), marginal bleeding index, supragingival dental calculus, probing depth (PD), clinical attachment level (CAL), and bleeding on probing (BOP). Logistic regression was used to model associations between crack cocaine and periodontitis (at least three sites with CAL >4 mm and at least two sites with PD >3 mm, not in the same site or tooth). Prevalence of periodontitis among crack non-users and crack users was 20.8% and 43.4%, respectively. Crack users had greater VPI, BOP, PD ≥3 mm, and CAL ≥4 mm than crack non-users. Periodontitis was associated with age >24 years, schooling ≤8 years, smoking, moderate/heavy alcohol use, and plaque rate ≥41%. Crack users had an approximately three-fold greater chance (odds ratio: 3.44; 95% confidence interval: 1.51 to 7.86) of periodontitis than non-users. Occurrence of periodontitis, visible plaque, and gingival bleeding was significantly higher among crack users, and crack use was associated with occurrence of periodontitis.

Evaluation of a co-delivered training package for community mental health professionals on service user- and carer-involved care planning.

PubMed

Grundy, A C; Walker, L; Meade, O; Fraser, C; Cree, L; Bee, P; Lovell, K; Callaghan, P

2017-08-01

WHAT IS KNOWN ON THE SUBJECT?: There is consistent evidence that service users and carers feel marginalized in the process of mental health care planning. Mental health professionals have identified ongoing training needs in relation to involving service users and carers in care planning. There is limited research on the acceptability of training packages for mental health professionals which involve service users and carers as co-facilitators. WHAT DOES THIS PAPER ADD TO EXISTING KNOWLEDGE?: A co-produced and co-delivered training package on service user- and carer-involved care planning was acceptable to mental health professionals. Aspects of the training that were particularly valued were the co-production model, small group discussion and the opportunity for reflective practice. The organizational context of care planning may need more consideration in future training models. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Mental health nurses using co-production models of delivering training to other mental health professionals can be confident that such initiatives will be warmly welcomed, acceptable and engaging. On the basis of the results reported here, we encourage mental health nurses to use co-production approaches more often. Further research will show how clinically effective this training is in improving outcomes for service users and carers. Background There is limited evidence for the acceptability of training for mental health professionals on service user- and carer-involved care planning. Aim To investigate the acceptability of a co-delivered, two-day training intervention on service user- and carer-involved care planning. Methods Community mental health professionals were invited to complete the Training Acceptability Rating Scale post-training. Responses to the quantitative items were summarized using descriptive statistics (Miles, ), and qualitative responses were coded using content analysis (Weber, ). Results Of 350 trainees, 310 completed the questionnaire. The trainees rated the training favourably (median overall TARS scores = 56/63; median 'acceptability' score = 34/36; median 'perceived impact' score = 22/27). There were six qualitative themes: the value of the co-production model; time to reflect on practice; delivery preferences; comprehensiveness of content; need to consider organizational context; and emotional response. Discussion The training was found to be acceptable and comprehensive with participants valuing the co-production model. Individual differences were apparent in terms of delivery preferences and emotional reactions. There may be a need to further address the organizational context of care planning in future training. Implications for practice Mental health nurses should use co-production models of continuing professional development training that involve service users and carers as co-facilitators. © 2017 The Authors. Journal of Psychiatric and Mental Health Nursing Published by John Wiley & Sons Ltd.

User Manual for Personnel Inventory Aging and Promotion Model

DTIC Science & Technology

2009-06-01

increased by 12. Now, an SQL 9 statement deletes records where [target] = NULL, and the model calculates the number of E8s that need to be promoted to...the run, the [Likelihood] and [Expected] tables are created. The first step in this process is to dy- namically build an SQL statement, based on the...This table has individual-level, longitudinal records. Next, a dy- namically built SQL statement based on the Number of Years, cre- ates a new data

Characterizing super-spreading in microblog: An epidemic-based information propagation model

NASA Astrophysics Data System (ADS)

Liu, Yu; Wang, Bai; Wu, Bin; Shang, Suiming; Zhang, Yunlei; Shi, Chuan

2016-12-01

As the microblogging services are becoming more prosperous in everyday life for users on Online Social Networks (OSNs), it is more favorable for hot topics and breaking news to gain more attraction very soon than ever before, which are so-called "super-spreading events". In the information diffusion process of these super-spreading events, messages are passed on from one user to another and numerous individuals are influenced by a relatively small portion of users, a.k.a. super-spreaders. Acquiring an awareness of super-spreading phenomena and an understanding of patterns of wide-ranged information propagations benefits several social media data mining tasks, such as hot topic detection, predictions of information propagation, harmful information monitoring and intervention. Taking into account that super-spreading in both information diffusion and spread of a contagious disease are analogous, in this study, we build a parameterized model, the SAIR model, based on well-known epidemic models to characterize super-spreading phenomenon in tweet information propagation accompanied with super-spreaders. For the purpose of modeling information diffusion, empirical observations on a real-world Weibo dataset are statistically carried out. Both the steady-state analysis on the equilibrium and the validation on real-world Weibo dataset of the proposed model are conducted. The case study that validates the proposed model shows that the SAIR model is much more promising than the conventional SIR model in characterizing a super-spreading event of information propagation. In addition, numerical simulations are carried out and discussed to discover how sensitively the parameters affect the information propagation process.

An interactive app for color deficient viewers

NASA Astrophysics Data System (ADS)

Lau, Cheryl; Perdu, Nicolas; Rodríguez-Pardo, Carlos E.; Süsstrunk, Sabine; Sharma, Gaurav

2015-01-01

Color deficient individuals have trouble seeing color contrasts that could be very apparent to individuals with normal color vision. For example, for some color deficient individuals, red and green apples do not have the striking contrast they have for those with normal color vision, or the abundance of red cherries in a tree is not immediately clear due to a lack of perceived contrast. We present a smartphone app that enables color deficient users to visualize such problematic color contrasts in order to help them with daily tasks. The user interacts with the app through the touchscreen. As the user traces a path around the touchscreen, the colors in the image change continuously via a transform that enhances contrasts that are weak or imperceptible for the user under native viewing conditions. Specifically, we propose a transform that shears the data along lines parallel to the dimension corresponding to the affected cone sensitivity of the user. The amount and direction of shear are controlled by the user's finger movement over the touchscreen allowing them to visualize these contrasts. Using the GPU, this simple transformation, consisting of a linear shear and translation, is performed efficiently on each pixel and in real-time with the changing position of the user's finger. The user can use the app to aid daily tasks such as distinguishing between red and green apples or picking out ripe bananas.

Thought-based row-column scanning communication board for individuals with cerebral palsy.

PubMed

Scherer, Reinhold; Billinger, Martin; Wagner, Johanna; Schwarz, Andreas; Hettich, Dirk Tassilo; Bolinger, Elaina; Lloria Garcia, Mariano; Navarro, Juan; Müller-Putz, Gernot

2015-02-01

Impairment of an individual's ability to communicate is a major hurdle for active participation in education and social life. A lot of individuals with cerebral palsy (CP) have normal intelligence, however, due to their inability to communicate, they fall behind. Non-invasive electroencephalogram (EEG) based brain-computer interfaces (BCIs) have been proposed as potential assistive devices for individuals with CP. BCIs translate brain signals directly into action. Motor activity is no longer required. However, translation of EEG signals may be unreliable and requires months of training. Moreover, individuals with CP may exhibit high levels of spontaneous and uncontrolled movement, which has a large impact on EEG signal quality and results in incorrect translations. We introduce a novel thought-based row-column scanning communication board that was developed following user-centered design principles. Key features include an automatic online artifact reduction method and an evidence accumulation procedure for decision making. The latter allows robust decision making with unreliable BCI input. Fourteen users with CP participated in a supporting online study and helped to evaluate the performance of the developed system. Users were asked to select target items with the row-column scanning communication board. The results suggest that seven among eleven remaining users performed better than chance and were consequently able to communicate by using the developed system. Three users were excluded because of insufficient EEG signal quality. These results are very encouraging and represent a good foundation for the development of real-world BCI-based communication devices for users with CP. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Something for nothing: understanding purchasing behaviors in social virtual environments.

PubMed

Chung, Donghun

2005-12-01

The present paper is composed of two studies. The first study explored the variables influencing the purchase of avatar-related products through the avatar users' survey research. This proposed a theoretical model of the purchase of avatar-related products using attitude toward an avatar, subjective norm, self-presentation, identification, and immersion. Although significant relationships were found for the individual links, the model was not supported. The second study focused on which variables predict the intention to use avatar-related products. A model was tested with avatar non-users. Results indicated that all relationships among variables in the Technology Acceptance Model (TAM), such as perceived ease of use of avatar, perceived usefulness of avatar, attitude toward using avatar, and intention to use avatar-related products, were strongly supported, as was the link between Internet self-efficacy and perceived ease of use of avatar. Also, the peer groups' subjective norm component which was a unique variable successfully predicted intention to use avatar-related products. Overall, all hypotheses were supported and the data were judged to be consistent with the model.

Factors of collaborative working: a framework for a collaboration model.

PubMed

Patel, Harshada; Pettitt, Michael; Wilson, John R

2012-01-01

The ability of organisations to support collaborative working environments is of increasing importance as they move towards more distributed ways of working. Despite the attention collaboration has received from a number of disparate fields, there is a lack of a unified understanding of the component factors of collaboration. As part of our work on a European Integrated Project, CoSpaces, collaboration and collaborative working and the factors which define it were examined through the literature and new empirical work with a number of partner user companies in the aerospace, automotive and construction sectors. This was to support development of a descriptive human factors model of collaboration - the CoSpaces Collaborative Working Model (CCWM). We identified seven main categories of factors involved in collaboration: Context, Support, Tasks, Interaction Processes, Teams, Individuals, and Overarching Factors, and summarised these in a framework which forms a basis for the model. We discuss supporting evidence for the factors which emerged from our fieldwork with user partners, and use of the model in activities such as collaboration readiness profiling. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Development and Feasibility Testing of a Smartphone Intervention to Improve Adherence to Antipsychotic Medications.

PubMed

Kreyenbuhl, Julie; Record, Elizabeth J; Himelhoch, Seth; Charlotte, Melanie; Palmer-Bacon, Jessica; Dixon, Lisa B; Medoff, Deborah R; Li, Lan

2016-07-25

Approximately 60% of individuals with schizophrenia do not take their antipsychotic medications as prescribed, and nonadherence is associated with exacerbation of psychotic symptoms, increased hospital and emergency room use, and increased healthcare costs. Behavioral-tailoring strategies that incorporate medication taking into the daily routine and use environmental supports have shown promise as adherence-enhancing interventions. Informed by the Information-Motivation-Behavioral (IMB) Skills Model and using the iterative process of user-centered design, we collaborated with individuals with schizophrenia and psychiatrists to develop an interactive smartphone application and web-based clinician interface, MedActive, for improving adherence to oral antipsychotic treatment. MedActive facilitates the active involvement of individuals with schizophrenia in managing their antipsychotic medication regimen by providing automated reminders for medication administration and tailored motivational feedback to encourage adherence, and by displaying user-friendly results of daily ecological momentary assessments (EMAs) of medication adherence, positive psychotic symptoms, and medication side effects for individuals and their psychiatrists. In a 2-week open trial completed by 7 individuals with schizophrenia and their psychiatrists, MedActive was determined to be both feasible and acceptable, with patient participants responding to 80% of all scheduled EMAs and providing positive evaluations of their use of the application. Psychiatrist participants were interested in viewing the information provided on the MedActive clinician interface, but cited practical barriers to regularly accessing it and integrating into their daily practice.

The Influence of Genetic and Environmental Factors among MDMA Users in Cognitive Performance

PubMed Central

Cuyàs, Elisabet; Verdejo-García, Antonio; Fagundo, Ana Beatriz; Khymenets, Olha; Rodríguez, Joan; Cuenca, Aida; de Sola Llopis, Susana; Langohr, Klaus; Peña-Casanova, Jordi; Torrens, Marta; Martín-Santos, Rocío; Farré, Magí; de la Torre, Rafael

2011-01-01

This study is aimed to clarify the association between MDMA cumulative use and cognitive dysfunction, and the potential role of candidate genetic polymorphisms in explaining individual differences in the cognitive effects of MDMA. Gene polymorphisms related to reduced serotonin function, poor competency of executive control and memory consolidation systems, and high enzymatic activity linked to bioactivation of MDMA to neurotoxic metabolites may contribute to explain variations in the cognitive impact of MDMA across regular users of this drug. Sixty ecstasy polydrug users, 110 cannabis users and 93 non-drug users were assessed using cognitive measures of Verbal Memory (California Verbal Learning Test, CVLT), Visual Memory (Rey-Osterrieth Complex Figure Test, ROCFT), Semantic Fluency, and Perceptual Attention (Symbol Digit Modalities Test, SDMT). Participants were also genotyped for polymorphisms within the 5HTT, 5HTR2A, COMT, CYP2D6, BDNF, and GRIN2B genes using polymerase chain reaction and TaqMan polymerase assays. Lifetime cumulative MDMA use was significantly associated with poorer performance on visuospatial memory and perceptual attention. Heavy MDMA users (>100 tablets lifetime use) interacted with candidate gene polymorphisms in explaining individual differences in cognitive performance between MDMA users and controls. MDMA users carrying COMT val/val and SERT s/s had poorer performance than paired controls on visuospatial attention and memory, and MDMA users with CYP2D6 ultra-rapid metabolizers performed worse than controls on semantic fluency. Both MDMA lifetime use and gene-related individual differences influence cognitive dysfunction in ecstasy users. PMID:22110616

OxyContin® as Currency: OxyContin® Use and Increased Social Capital among Rural Appalachian Drug Users

PubMed Central

Jonas, Adam B.; Young, April M.; Oser, Carrie B.; Leukefeld, Carl G.; Havens, Jennifer R.

2012-01-01

Studies have shown that position within networks of social relations can have direct implications on the health behaviors of individuals. The present study examines connections between drug use and individual social capital within social networks of drug users (n=503) from rural Appalachian Kentucky, U.S.A. Respondent driven sampling was used to recruit individuals age 18 and older who had used one of the following drugs to get high: cocaine, crack, heroin, methamphetamine, or prescription opioids. Substance use was measured via self-report and social network analysis of participants’ drug use network was used to compute effective size, a measure of social capital. Drug network ties were based on sociometric data on recent (past 6 month) drug co-usage. Multivariate multi-level ordinal regression was used to model the independent effect of sociodemographic and drug use characteristics on social capital. Adjusting for gender, income, and education, daily OxyContin® use was found to be significantly associated with greater social capital, and daily marijuana use was associated with less social capital. These results suggest that in regions with marked economic disparities such as rural Appalachia, OxyContin® may serve as a form of currency that is associated with increased social capital among drug users. Interventions focusing on increasing alternate pathways to acquiring social capital may be one way in which to alleviate the burden of drug use in this high-risk population. PMID:22465379

Gym-based exoskeleton walking: A preliminary exploration of non-ambulatory end-user perspectives.

PubMed

Cahill, Aoife; Ginley, Orna Mc; Bertrand, Courtney; Lennon, Olive

2018-07-01

Robotic walking devices (RWD) have shown many physical benefits in Spinal Cord Injury (SCI) rehabilitation. No study to date has explored end-user perceptions of these devices or gained insight into the use of these devices in a gym-based setting. This preliminary study explores the perspectives of four non-ambulatory individuals with SCI on using an exoskeleton walking device in a gym-based community setting. In-depth, semi-structured interviews were conducted with four SCI individuals living in the community. Interviews were audio-recorded and transcribed verbatim. Inductive thematic analysis established common overarching themes and subthemes. Four primary themes emerged addressing "The Psychological Adjustments Around Using RWDs with Respect to Disability", "Perceived Physical, Social and Psychological Benefits of Using an Exoskeleton", "The Role of External Influences", and "A Wellness Model to Health". A fully integrated gym setting was found to provide a positive and encouraging space to utilise the device. In addition, both the ability to set training goals and the positive attitude of robotic trainers were deemed to be important factors. This preliminary study provides detailed perspectives of four non-ambulatory individuals with SCI on utilising an exoskeleton walking device in a community setting. It suggests that gym-based RWDs impact positively on the users' lives and enhance their perceived wellbeing and sense of community integration. Enabling access to similar, community-based facilities should be prioritised for those with longstanding SCI disability. Copyright © 2018 Elsevier Inc. All rights reserved.

Individual and couple-level risk factors for hepatitis C infection among heterosexual drug users: a multilevel dyadic analysis.

PubMed

McMahon, James M; Pouget, Enrique R; Tortu, Stephanie

2007-06-01

Hepatitis C virus (HCV) is the most common bloodborne pathogen in the United States and is a leading cause of liver-related morbidity and mortality. Although it is known that HCV is most commonly transmitted among injection drug users, the role of sexual transmission in the spread of HCV remains controversial because of inconsistent findings across studies involving heterosexual couples. A novel multilevel modeling technique designed to overcome the limitations of previous research was performed to assess multiple risk factors for HCV while partitioning the source of risk at the individual and couple level. The analysis was performed on risk exposure and HCV screening data obtained from 265 drug-using couples in East Harlem, New York City. In multivariable analysis, significant individual risk factors for HCV included a history of injection drug use, tattooing, and older age. At the couple level, HCV infection tended to cluster within couples, and this interdependence was accounted for by couples' drug-injection behavior. Individual and couple-level sexual behavior was not associated with HCV infection. Our results are consistent with prior research indicating that sexual contact plays little role in HCV transmission. Rather, couples' injection behavior appears to account for the clustering of HCV within heterosexual dyads.

A reference model for scientific information interchange

NASA Technical Reports Server (NTRS)

Reich, Lou; Sawyer, Don; Davis, Randy

1993-01-01

This paper presents an overview of an Information Interchange Reference Model (IIRM) currently being developed by individuals participating in the Consultative Committee for Space Data Systems (CCSDS) Panel 2, the Planetary Data Systems (PDS), and the Committee on Earth Observing Satellites (CEOS). This is an ongoing research activity and is not an official position by these bodies. This reference model provides a framework for describing and assessing current and proposed methodologies for information interchange within and among the space agencies. It is hoped that this model will improve interoperability between the various methodologies. As such, this model attempts to address key information interchange issues as seen by the producers and users of space-related data and to put them into a coherent framework. Information is understood as the knowledge (e.g., the scientific content) represented by data. Therefore, concern is not primarily on mechanisms for transferring data from user to user (e.g., compact disk read-only memory (CD-ROM), wide-area networks, optical tape, and so forth) but on how information is encoded as data and how the information content is maintained with minimal loss or distortion during transmittal. The model assumes open systems, which means that the protocols or methods used should be fully described and the descriptions publicly available. Ideally these protocols are promoted by recognized standards organizations using processes that permit involvement by those most likely to be affected, thereby enhancing the protocol's stability and the likelihood of wide support.

SCAMP and the ASP

NASA Astrophysics Data System (ADS)

Idehara, H.; Carbon, D. F.

2004-12-01

We present two new, publicly available tools to support the examination and interpretation of spectra. SCAMP is a specialized graphical user interface for MATLAB. It allows researchers to rapidly intercompare sets of observational, theoretical, and/or laboratory spectra. Users have extensive control over the colors and placement of individual spectra, and over spectrum normalization from one spectral region to another. Spectra can be interactively assigned to user-defined groups and the groupings recalled at a later time. The user can measure/record positions and intensities of spectral features, interactively spline-fit spectra, and normalize spectra by fitted splines. User-defined wavelengths can be automatically highlighted in SCAMP plots. The user can save/print annotated graphical output suitable for a scientific notebook depicting the work at any point. The ASP is a WWW portal that provides interactive access to two spectrum data sets: a library of synthetic stellar spectra and a library of laboratory PAH spectra. The synthetic stellar spectra in the ASP are appropriate to the giant branch with an assortment of compositions. Each spectrum spans the full range from 2 to 600 microns at a variety of resolutions. The ASP is designed to allow users to quickly identify individual features at any resolution that arise from any of the included isotopic species. The user may also retrieve the depth of formation of individual features at any resolution. PAH spectra accessible through the ASP are drawn from the extensive library of spectra measured by the NASA Ames Astrochemistry Laboratory. The user may interactively choose any subset of PAHs in the data set, combine them with user-defined weights and temperatures, and view/download the resultant spectrum at any user-defined resolution. This work was funded by the NASA Advanced Supercomputing Division, NASA Ames Research Center.

Parental cancer: Characteristics of users of child-centred counselling versus individual psycho-oncological treatment.

PubMed

Inhestern, Laura; Geertz, Wiebke; Schulz-Kindermann, Frank; Bergelt, Corinna

2018-03-01

The aims of this study were to investigate the characteristics of users of a specific child-centred counselling service (COSIP) and to compare those to parents using an individual psycho-oncological treatment (PO). We conducted a retrospective analysis on data of users of COSIP and users of PO. Database was the routine assessment (demographic and disease-related characteristics, GAD-7, PHQ-9, EORTC QLQ-C30, and current concerns) of an outpatient psycho-oncological clinic with additional child-centred counselling. A total of 151 patients and 49 partners with children ≤21 years were included. We conducted descriptive analyses and group comparisons. Fifty-nine patients and partners used COSIP only or additionally to individual psycho-oncological service. PO users were more depressed and were more anxious than COSIP users. Patients using PO reported worse emotional functioning than patients using COSIP. Partners using PO reported worse global quality of life and more symptoms of fatigue than partners using COSIP. With regard to current concerns, patients using COSIP reported child-related issues more frequently than PO users. PO users reported symptoms of anxiety, depressive symptoms, or exhaustion more frequently than COSIP users. The findings demonstrate that patients and partners self-referring to PO or COSIP are highly burdened. COSIP users experience different psychosocial burden than PO users. As poor mental state of parents is a risk factor for the development of mental problems in children, parents using only PO may benefit from additional child-centred support. Accordingly, the need for COSIP should be assessed continuously during PO of patients with children ≤21 years. Copyright © 2017 John Wiley & Sons, Ltd.

Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior

PubMed Central

Althoff, Tim; Jindal, Pranav; Leskovec, Jure

2017-01-01

Many of today’s most widely used computing applications utilize social networking features and allow users to connect, follow each other, share content, and comment on others’ posts. However, despite the widespread adoption of these features, there is little understanding of the consequences that social networking has on user retention, engagement, and online as well as offline behavior. Here, we study how social networks influence user behavior in a physical activity tracking application. We analyze 791 million online and offline actions of 6 million users over the course of 5 years, and show that social networking leads to a significant increase in users’ online as well as offline activities. Specifically, we establish a causal effect of how social networks influence user behavior. We show that the creation of new social connections increases user online in-application activity by 30%, user retention by 17%, and user offline real-world physical activity by 7% (about 400 steps per day). By exploiting a natural experiment we distinguish the effect of social influence of new social connections from the simultaneous increase in user’s motivation to use the app and take more steps. We show that social influence accounts for 55% of the observed changes in user behavior, while the remaining 45% can be explained by the user’s increased motivation to use the app. Further, we show that subsequent, individual edge formations in the social network lead to significant increases in daily steps. These effects diminish with each additional edge and vary based on edge attributes and user demographics. Finally, we utilize these insights to develop a model that accurately predicts which users will be most influenced by the creation of new social network connections. PMID:28345078

The HydroShare Collaborative Repository for the Hydrology Community

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Couch, A.; Hooper, R. P.; Dash, P. K.; Stealey, M.; Yi, H.; Bandaragoda, C.; Castronova, A. M.

2017-12-01

HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of, and collaboration around, "resources" which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. This presentation will describe the functionality and architecture of HydroShare highlighting our approach to making this system easy to use and serving the needs of the hydrology community represented by the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI). Metadata for uploaded files is harvested automatically or captured using easy to use web user interfaces. Users are encouraged to add or create resources in HydroShare early in the data life cycle. To encourage this we allow users to share and collaborate on HydroShare resources privately among individual users or groups, entering metadata while doing the work. HydroShare also provides enhanced functionality for users through web apps that provide tools and computational capability for actions on resources. HydroShare's architecture broadly is comprised of: (1) resource storage, (2) resource exploration website, and (3) web apps for actions on resources. System components are loosely coupled and interact through APIs, which enhances robustness, as components can be upgraded and advanced relatively independently. The full power of this paradigm is the extensibility it supports. Web apps are hosted on separate servers, which may be 3rd party servers. They are registered in HydroShare using a web app resource that configures the connectivity for them to be discovered and launched directly from resource types they are associated with.

IPR 1.0: an efficient method for calculating solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities

NASA Astrophysics Data System (ADS)

Zhang, Y.; Chen, W.; Li, J.

2014-07-01

Climate change may alter the spatial distribution, composition, structure and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate the solar radiation absorbed by individual plants in order to understand and predict their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming that crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the results of random distribution of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and can be included in vegetation models to simulate long-term transient responses of plant communities to climate change. The code and a user's manual are provided as Supplement of the paper.

Agenda Setting for Health Promotion: Exploring an Adapted Model for the Social Media Era.

PubMed

Albalawi, Yousef; Sixsmith, Jane

2015-01-01

The foundation of best practice in health promotion is a robust theoretical base that informs design, implementation, and evaluation of interventions that promote the public's health. This study provides a novel contribution to health promotion through the adaptation of the agenda-setting approach in response to the contribution of social media. This exploration and proposed adaptation is derived from a study that examined the effectiveness of Twitter in influencing agenda setting among users in relation to road traffic accidents in Saudi Arabia. The proposed adaptations to the agenda-setting model to be explored reflect two levels of engagement: agenda setting within the social media sphere and the position of social media within classic agenda setting. This exploratory research aims to assess the veracity of the proposed adaptations on the basis of the hypotheses developed to test these two levels of engagement. To validate the hypotheses, we collected and analyzed data from two primary sources: Twitter activities and Saudi national newspapers. Keyword mentions served as indicators of agenda promotion; for Twitter, interactions were used to measure the process of agenda setting within the platform. The Twitter final dataset comprised 59,046 tweets and 38,066 users who contributed by tweeting, replying, or retweeting. Variables were collected for each tweet and user. In addition, 518 keyword mentions were recorded from six popular Saudi national newspapers. The results showed significant ratification of the study hypotheses at both levels of engagement that framed the proposed adaptions. The results indicate that social media facilitates the contribution of individuals in influencing agendas (individual users accounted for 76.29%, 67.79%, and 96.16% of retweet impressions, total impressions, and amplification multipliers, respectively), a component missing from traditional constructions of agenda-setting models. The influence of organizations on agenda setting is also highlighted (in the data of user interactions, organizational accounts registered 17% and 14.74% as source and target of interactions, respectively). In addition, 13 striking similarities showed the relationship between newspapers and Twitter on the mentions trends line. The effective use of social media platforms in health promotion intervention programs requires new strategies that consider the limitations of traditional communication channels. Conducting research is vital to establishing a strong basis for modifying, designing, and developing new health promotion strategies and approaches.

Agenda Setting for Health Promotion: Exploring an Adapted Model for the Social Media Era

PubMed Central

2015-01-01

Background The foundation of best practice in health promotion is a robust theoretical base that informs design, implementation, and evaluation of interventions that promote the public’s health. This study provides a novel contribution to health promotion through the adaptation of the agenda-setting approach in response to the contribution of social media. This exploration and proposed adaptation is derived from a study that examined the effectiveness of Twitter in influencing agenda setting among users in relation to road traffic accidents in Saudi Arabia. Objective The proposed adaptations to the agenda-setting model to be explored reflect two levels of engagement: agenda setting within the social media sphere and the position of social media within classic agenda setting. This exploratory research aims to assess the veracity of the proposed adaptations on the basis of the hypotheses developed to test these two levels of engagement. Methods To validate the hypotheses, we collected and analyzed data from two primary sources: Twitter activities and Saudi national newspapers. Keyword mentions served as indicators of agenda promotion; for Twitter, interactions were used to measure the process of agenda setting within the platform. The Twitter final dataset comprised 59,046 tweets and 38,066 users who contributed by tweeting, replying, or retweeting. Variables were collected for each tweet and user. In addition, 518 keyword mentions were recorded from six popular Saudi national newspapers. Results The results showed significant ratification of the study hypotheses at both levels of engagement that framed the proposed adaptions. The results indicate that social media facilitates the contribution of individuals in influencing agendas (individual users accounted for 76.29%, 67.79%, and 96.16% of retweet impressions, total impressions, and amplification multipliers, respectively), a component missing from traditional constructions of agenda-setting models. The influence of organizations on agenda setting is also highlighted (in the data of user interactions, organizational accounts registered 17% and 14.74% as source and target of interactions, respectively). In addition, 13 striking similarities showed the relationship between newspapers and Twitter on the mentions trends line. Conclusions The effective use of social media platforms in health promotion intervention programs requires new strategies that consider the limitations of traditional communication channels. Conducting research is vital to establishing a strong basis for modifying, designing, and developing new health promotion strategies and approaches. PMID:27227139

Routes to short-term memory indexing: lessons from deaf native users of American Sign Language.

PubMed

Hirshorn, Elizabeth A; Fernandez, Nina M; Bavelier, Daphne

2012-01-01

Models of working memory (WM) have been instrumental in understanding foundational cognitive processes and sources of individual differences. However, current models cannot conclusively explain the consistent group differences between deaf signers and hearing speakers on a number of short-term memory (STM) tasks. Here we take the perspective that these results are not due to a temporal order-processing deficit in deaf individuals, but rather reflect different biases in how different types of memory cues are used to do a given task. We further argue that the main driving force behind the shifts in relative biasing is a consequence of language modality (sign vs. speech) and the processing they afford, and not deafness, per se.

Routes to short term memory indexing: Lessons from deaf native users of American Sign Language

PubMed Central

Hirshorn, Elizabeth A.; Fernandez, Nina M.; Bavelier, Daphne

2012-01-01

Models of working memory (WM) have been instrumental in understanding foundational cognitive processes and sources of individual differences. However, current models cannot conclusively explain the consistent group differences between deaf signers and hearing speakers on a number of short-term memory (STM) tasks. Here we take the perspective that these results are not due to a temporal order-processing deficit in deaf individuals, but rather reflect different biases in how different types of memory cues are used to do a given task. We further argue that the main driving force behind the shifts in relative biasing is a consequence of language modality (sign vs. speech) and the processing they afford, and not deafness, per se. PMID:22871205

Personalizing Information Retrieval Using Task Features, Topic Knowledge, and Task Products

ERIC Educational Resources Information Center

Liu, Jingjing

2010-01-01

Personalization of information retrieval tailors search towards individual users to meet their particular information needs by taking into account information about users and their contexts, often through implicit sources of evidence such as user behaviors and contextual factors. The current study looks particularly at users' dwelling behavior,…

Health-care users, key community informants and primary health care workers' views on health, health promotion, health assets and deficits: qualitative study in seven Spanish regions.

PubMed

Pons-Vigués, Mariona; Berenguera, Anna; Coma-Auli, Núria; Pombo-Ramos, Haizea; March, Sebastià; Asensio-Martínez, Angela; Moreno-Peral, Patricia; Mora-Simón, Sara; Martínez-Andrés, Maria; Pujol-Ribera, Enriqueta

2017-06-13

Although some articles have analysed the definitions of health and health promotion from the perspective of health-care users and health care professionals, no published studies include the simultaneous participation of health-care users, primary health care professionals and key community informants. Understanding the perception of health and health promotion amongst these different stakeholders is crucial for the design and implementation of successful, equitable and sustainable measures that improve the health and wellbeing of populations. Furthermore, the identification of different health assets and deficits by the different informants will generate new evidence to promote healthy behaviours, improve community health and wellbeing and reduce preventable inequalities. The objective of this study is to explore the concept of health and health promotion and to compare health assets and deficits as identified by health-care users, key community informants and primary health care workers with the ultimate purpose to collect the necessary data for the design and implementation of a successful health promotion intervention. A descriptive-interpretive qualitative research was conducted with 276 participants from 14 primary care centres of 7 Spanish regions. Theoretical sampling was used for selection. We organized 11 discussion groups and 2 triangular groups with health-care users; 30 semi-structured interviews with key community informants; and 14 discussion groups with primary health care workers. A thematic content analysis was carried out. Health-care users and key community informants agree that health is a complex, broad, multifactorial concept that encompasses several interrelated dimensions (physical, psychological-emotional, social, occupational, intellectual, spiritual and environmental). The three participants' profiles consider health promotion indispensable despite defining it as complex and vague. In fact, most health-care users admit to having implemented some change to promote their health. The most powerful motivators to change lifestyles are having a disease, fear of becoming ill and taking care of oneself to maintain health. Health-care users believe that the main difficulties are associated with the physical, social, working and family environment, as well as lack of determination and motivation. They also highlight the need for more information. In relation to the assets and deficits of the neighbourhood, each group identifies those closer to their role. Generally, participants showed a holistic and positive concept of health and a more traditional, individual approach to health promotion. We consider therefore crucial to depart from the model of health services that focuses on the individual and the disease toward a socio-ecological health model that substantially increases the participation of health-care users and emphasizes health promotion, wellbeing and community participation.

A Robotic Coach Architecture for Elder Care (ROCARE) Based on Multi-user Engagement Models

PubMed Central

Fan, Jing; Bian, Dayi; Zheng, Zhi; Beuscher, Linda; Newhouse, Paul A.; Mion, Lorraine C.; Sarkar, Nilanjan

2017-01-01

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment. PMID:28113672

The Impact of Social Structures on Deviant Behaviors: The Study of 402 High Risk Street Drug Users in Iran.

PubMed

Mehrabi, Maryam; Eskandarieh, Sharareh; Khodadost, Mahmoud; Sadeghi, Maneli; Nikfarjam, Ali; Hajebi, Ahmad

2016-01-01

This study is a sociological analysis of the three dimensions of social structure including institutional, relational, and embodied structures that have an impact on the individuals' deviant behaviors in the society. The authors used a mix method to analyze the qualitative and quantitative data of 402 high risk abandoned substance users in 2008 in Tehran, capital city of Iran. The leading reasons of substance use were categorized into four fundamental themes as follows: stress, deviant social networks, and low social capital and weak social support sources. In addition, the epidemiology model of regression analysis provides a brief explanation to assess the association between the demographical and etiological variables, and the drug users' deviant behaviors. In sum, substance use is discussed as a deviant behavior pattern which stems from a comorbidity of weak social structures.

A Robotic Coach Architecture for Elder Care (ROCARE) Based on Multi-User Engagement Models.

PubMed

Fan, Jing; Bian, Dayi; Zheng, Zhi; Beuscher, Linda; Newhouse, Paul A; Mion, Lorraine C; Sarkar, Nilanjan

2017-08-01

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment.

ADAPT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reynolds, John; Jankovsky, Zachary; Metzroth, Kyle G

2018-04-04

The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model various aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specifiedmore » times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at separate times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst-case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.« less

Measuring sense of presence and user characteristics to predict effective training in an online simulated virtual environment.

PubMed

De Leo, Gianluca; Diggs, Leigh A; Radici, Elena; Mastaglio, Thomas W

2014-02-01

Virtual-reality solutions have successfully been used to train distributed teams. This study aimed to investigate the correlation between user characteristics and sense of presence in an online virtual-reality environment where distributed teams are trained. A greater sense of presence has the potential to make training in the virtual environment more effective, leading to the formation of teams that perform better in a real environment. Being able to identify, before starting online training, those user characteristics that are predictors of a greater sense of presence can lead to the selection of trainees who would benefit most from the online simulated training. This is an observational study with a retrospective postsurvey of participants' user characteristics and degree of sense of presence. Twenty-nine members from 3 Air Force National Guard Medical Service expeditionary medical support teams participated in an online virtual environment training exercise and completed the Independent Television Commission-Sense of Presence Inventory survey, which measures sense of presence and user characteristics. Nonparametric statistics were applied to determine the statistical significance of user characteristics to sense of presence. Comparing user characteristics to the 4 scales of the Independent Television Commission-Sense of Presence Inventory using Kendall τ test gave the following results: the user characteristics "how often you play video games" (τ(26)=-0.458, P<0.01) and "television/film production knowledge" (τ(27)=-0.516, P<0.01) were significantly related to negative effects. Negative effects refer to adverse physiologic reactions owing to the virtual environment experience such as dizziness, nausea, headache, and eyestrain. The user characteristic "knowledge of virtual reality" was significantly related to engagement (τ(26)=0.463, P<0.01) and negative effects (τ(26)=-0.404, P<0.05). Individuals who have knowledge about virtual environments and experience with gaming environments report a higher sense of presence that indicates that they will likely benefit more from online virtual training. Future research studies could include a larger population of expeditionary medical support, and the results obtained could be used to create a model that predicts the level of presence based on the user characteristics. To maximize results and minimize costs, only those individuals who, based on their characteristics, are supposed to have a higher sense of presence and less negative effects could be selected for online simulated virtual environment training.

Developing a change model for peer worker interventions in mental health services: a qualitative research study.

PubMed

Gillard, S; Gibson, S L; Holley, J; Lucock, M

2015-10-01

A range of peer worker roles are being introduced into mental health services internationally. There is some evidence that attests to the benefits of peer workers for the people they support but formal trial evidence in inconclusive, in part because the change model underpinning peer support-based interventions is underdeveloped. Complex intervention evaluation guidance suggests that understandings of how an intervention is associated with change in outcomes should be modelled, theoretically and empirically, before the intervention can be robustly evaluated. This paper aims to model the change mechanisms underlying peer worker interventions. In a qualitative, comparative case study of ten peer worker initiatives in statutory and voluntary sector mental health services in England in-depth interviews were carried out with 71 peer workers, service users, staff and managers, exploring their experiences of peer working. Using a Grounded Theory approach we identified core processes within the peer worker role that were productive of change for service users supported by peer workers. Key change mechanisms were: (i) building trusting relationships based on shared lived experience; (ii) role-modelling individual recovery and living well with mental health problems; (iii) engaging service users with mental health services and the community. Mechanisms could be further explained by theoretical literature on role-modelling and relationship in mental health services. We were able to model process and downstream outcomes potentially associated with peer worker interventions. An empirically and theoretically grounded change model can be articulated that usefully informs the development, evaluation and planning of peer worker interventions.

Selecting a climate model subset to optimise key ensemble properties

NASA Astrophysics Data System (ADS)

Herger, Nadja; Abramowitz, Gab; Knutti, Reto; Angélil, Oliver; Lehmann, Karsten; Sanderson, Benjamin M.

2018-02-01

End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

Ketamine use among regular tobacco and alcohol users as revealed by respondent driven sampling in Taipei: prevalence, expectancy, and users’ risky decision making

PubMed Central

Chen, Wei J.; Ting, Te-Tien; Chang, Chao-Ming; Liu, Ying-Chun; Chen, Chuan-Yu

2014-01-01

The popularity of ketamine for recreational use among young people began to increase, particularly in Asia, in 2000. To gain more knowledge about the use of ketamine among high risk individuals, a respondent-driven sampling (RDS) was implemented among regular alcohol and tobacco users in the Taipei metropolitan area from 2007 to 2010. The sampling was initiated in three different settings (i.e., two in the community and one in a clinic) to recruit seed individuals. Each participant was asked to refer one to five friends known to be regular tobacco smokers and alcohol drinkers to participate in the present study. Incentives were offered differentially upon the completion of an interview and successful referral. Information pertaining to drug use experience was collected by an audio computer-assisted self-interview instrument. Software built for RDS analyses was used for data analyses. Of the 1,115 subjects recruited, about 11.7% of the RDS respondents reported ever having used ketamine. Positive expectancy of ketamine use was positively associated with ketamine use; in contrast, negative expectancy inversely associated with ketamine use. Decision-making characteristics as measured on the Iowa Gambling Task using reinforcement learning models revealed that ketamine users learned less from the most recent event than both tobacco- and drug-naïve controls and regular tobacco and alcohol users. These findings about ketamine use among young people have implications for its prevention and intervention. PMID:25264412

Development of a Multi-Behavioral mHealth App for Women Smokers.

PubMed

Armin, Julie; Johnson, Thienne; Hingle, Melanie; Giacobbi, Peter; Gordon, Judith S

2017-02-01

This article describes the development of the See Me Smoke-Free™ (SMSF) mobile health application, which uses guided imagery to support women in smoking cessation, eating a healthy diet, and increasing physical activity. Focus group discussions, with member checks, were conducted to refine the intervention content and app user interface. Data related to the context of app deployment were collected via user testing sessions and internal quality control testing, which identified and addressed functionality issues, content problems, and bugs. Interactive app features include playback of guided imagery audio files, notification pop-ups, award-sharing on social media, a tracking calendar, content resources, and direct call to the local tobacco quitline. Focus groups helped design the user interface and identified several themes for incorporation into app content, including positivity, the rewards of smoking cessation, and the integrated benefits of maintaining a healthy lifestyle. User testing improved app functionality and usability on many Android phone models. Changes to the app content and function were made iteratively by the development team as a result of focus group and user testing. Despite extensive internal and user testing, unanticipated data collection and reporting issues emerged during deployment due not only to the variety of Android software and hardware but also to individual phone settings and use.

The Role of Diverse Strategies in Sustainable Knowledge Production

PubMed Central

Wu, Lingfei; Baggio, Jacopo A.; Janssen, Marco A.

2016-01-01

Online communities are becoming increasingly important as platforms for large-scale human cooperation. These communities allow users seeking and sharing professional skills to solve problems collaboratively. To investigate how users cooperate to complete a large number of knowledge-producing tasks, we analyze Stack Exchange, one of the largest question and answer systems in the world. We construct attention networks to model the growth of 110 communities in the Stack Exchange system and quantify individual answering strategies using the linking dynamics on attention networks. We identify two answering strategies. Strategy A aims at performing maintenance by doing simple tasks, whereas strategy B aims at investing time in doing challenging tasks. Both strategies are important: empirical evidence shows that strategy A decreases the median waiting time for answers and strategy B increases the acceptance rate of answers. In investigating the strategic persistence of users, we find that users tends to stick on the same strategy over time in a community, but switch from one strategy to the other across communities. This finding reveals the different sets of knowledge and skills between users. A balance between the population of users taking A and B strategies that approximates 2:1, is found to be optimal to the sustainable growth of communities. PMID:26934733

The Role of Diverse Strategies in Sustainable Knowledge Production.

PubMed

Wu, Lingfei; Baggio, Jacopo A; Janssen, Marco A

2016-01-01

Online communities are becoming increasingly important as platforms for large-scale human cooperation. These communities allow users seeking and sharing professional skills to solve problems collaboratively. To investigate how users cooperate to complete a large number of knowledge-producing tasks, we analyze Stack Exchange, one of the largest question and answer systems in the world. We construct attention networks to model the growth of 110 communities in the Stack Exchange system and quantify individual answering strategies using the linking dynamics on attention networks. We identify two answering strategies. Strategy A aims at performing maintenance by doing simple tasks, whereas strategy B aims at investing time in doing challenging tasks. Both strategies are important: empirical evidence shows that strategy A decreases the median waiting time for answers and strategy B increases the acceptance rate of answers. In investigating the strategic persistence of users, we find that users tends to stick on the same strategy over time in a community, but switch from one strategy to the other across communities. This finding reveals the different sets of knowledge and skills between users. A balance between the population of users taking A and B strategies that approximates 2:1, is found to be optimal to the sustainable growth of communities.

Statistical modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

User Values in the Selection of Information Services. Final Report.

ERIC Educational Resources Information Center

Hall, Homer J.

The value systems by which the users of purchased information services select which one to use or buy are found to differ sharply among different user populations, but the variable found to control them is a function of use, not of the user as an individual. Selection variables are summarized in a matrix of user values and interaction effects. The…

The FITS model office ergonomics program: a model for best practice.

PubMed

Chim, Justine M Y

2014-01-01

An effective office ergonomics program can predict positive results in reducing musculoskeletal injury rates, enhancing productivity, and improving staff well-being and job satisfaction. Its objective is to provide a systematic solution to manage the potential risk of musculoskeletal disorders among computer users in an office setting. A FITS Model office ergonomics program is developed. The FITS Model Office Ergonomics Program has been developed which draws on the legislative requirements for promoting the health and safety of workers using computers for extended periods as well as previous research findings. The Model is developed according to the practical industrial knowledge in ergonomics, occupational health and safety management, and human resources management in Hong Kong and overseas. This paper proposes a comprehensive office ergonomics program, the FITS Model, which considers (1) Furniture Evaluation and Selection; (2) Individual Workstation Assessment; (3) Training and Education; (4) Stretching Exercises and Rest Break as elements of an effective program. An experienced ergonomics practitioner should be included in the program design and implementation. Through the FITS Model Office Ergonomics Program, the risk of musculoskeletal disorders among computer users can be eliminated or minimized, and workplace health and safety and employees' wellness enhanced.

A resource facility for kinetic analysis: modeling using the SAAM computer programs.

PubMed

Foster, D M; Boston, R C; Jacquez, J A; Zech, L

1989-01-01

Kinetic analysis and integrated system modeling have contributed significantly to understanding the physiology and pathophysiology of metabolic systems in humans and animals. Many experimental biologists are aware of the usefulness of these techniques and recognize that kinetic modeling requires special expertise. The Resource Facility for Kinetic Analysis (RFKA) provides this expertise through: (1) development and application of modeling technology for biomedical problems, and (2) development of computer-based kinetic modeling methodologies concentrating on the computer program Simulation, Analysis, and Modeling (SAAM) and its conversational version, CONversational SAAM (CONSAM). The RFKA offers consultation to the biomedical community in the use of modeling to analyze kinetic data and trains individuals in using this technology for biomedical research. Early versions of SAAM were widely applied in solving dosimetry problems; many users, however, are not familiar with recent improvements to the software. The purpose of this paper is to acquaint biomedical researchers in the dosimetry field with RFKA, which, together with the joint National Cancer Institute-National Heart, Lung and Blood Institute project, is overseeing SAAM development and applications. In addition, RFKA provides many service activities to the SAAM user community that are relevant to solving dosimetry problems.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Facebook and its effects on users' empathic social skills and life satisfaction: a double-edged sword effect.

PubMed

Chan, Terri H

2014-05-01

This study examines how Facebook usage affects individual's empathic social skills and life satisfaction. Following the self-presentational theory, the study explores a key component of the Internet paradox-whether Facebook suppresses or enhances users' interpersonal competence (specifically empathic social skills), given their respective personality makeup. Going further, the study assesses these events' subsequent impacts on users' psychological well-being. Analogous to a double-edged sword, Facebook activities are hypothesized to suppress the positive effect of a user's extraversion orientation on empathic social skills but lessen the negative effect of neuroticism on these skills. The study examines a sample of college-aged Facebook users (n=515), who responded to a large-scale online survey. The findings from a structural equation modeling analysis indicate that while empathic social skills are positively associated with life satisfaction, Facebook activities mainly exert suppression effects. Only upon low usage can Facebook activities lessen the negative effect of neuroticism on empathic social skills, suggesting that Facebook may appear as a less threatening platform for social interactions among neurotics. Yet, results in general suggest that undesirable effects may occur at high levels of Facebook usage whereby both extroverted and neurotic users displace real world social ties to online ones. The findings point to the complex ways in which social media usage may impact the livelihood of users.

Don't Judge a Book by its Cover: Examiner Expectancy Effects Predict Neuropsychological Performance for Individuals Judged as Chronic Cannabis Users.

PubMed

Sodos, Louise M; Hirst, Rayna B; Watson, Jessica; Vaughn, Dylan

2018-01-12

The experimenter expectancy effect confound remains largely unexplored in neuropsychological research and has never been investigated among cannabis users. This study investigated whether examiner expectancies of cannabis user status affected examinees' neuropsychological performance. Participants included 41 cannabis users and 20 non-users. Before testing, examiners who were blind to participant user status privately rated whether they believed the examinee was a cannabis user or non-user. Examiners then administered a battery of neuropsychological and performance validity measures. Multiple regression analyses compared performance between examinees judged as cannabis users (n = 37) and those judged as non-users (n = 24). Examiners' judgments of cannabis users were 75% accurate; judgments of non-users were at chance. After controlling for age, gender, and actual user status, examiner judgments of cannabis user status predicted performance on two measures (California Verbal Learning Test-II, and Trail Making Test B; p < .05), as individuals judged as cannabis users obtained lower scores than those judged as non-users. Examiners' judgments of cannabis user status predicted performance even after controlling for actual user status, indicating vulnerability to examiner expectancy effects. These findings have important implications for both research and clinical settings, as scores may partially reflect examiners' expectations regarding cannabis effects rather than participants' cognitive abilities. These results demonstrate the need for expectancy effect research in the neuropsychological assessment of all populations, not just cannabis users. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Towards collaborative filtering recommender systems for tailored health communications.

PubMed

Marlin, Benjamin M; Adams, Roy J; Sadasivam, Rajani; Houston, Thomas K

2013-01-01

The goal of computer tailored health communications (CTHC) is to promote healthy behaviors by sending messages tailored to individual patients. Current CTHC systems collect baseline patient "profiles" and then use expert-written, rule-based systems to target messages to subsets of patients. Our main interest in this work is the study of collaborative filtering-based CTHC systems that can learn to tailor future message selections to individual patients based explicit feedback about past message selections. This paper reports the results of a study designed to collect explicit feedback (ratings) regarding four aspects of messages from 100 subjects in the smoking cessation support domain. Our results show that most users have positive opinions of most messages and that the ratings for all four aspects of the messages are highly correlated with each other. Finally, we conduct a range of rating prediction experiments comparing several different model variations. Our results show that predicting future ratings based on each user's past ratings contributes the most to predictive accuracy.

Lamprey: tracking users on the World Wide Web.

PubMed

Felciano, R M; Altman, R B

1996-01-01

Tracking individual web sessions provides valuable information about user behavior. This information can be used for general purpose evaluation of web-based user interfaces to biomedical information systems. To this end, we have developed Lamprey, a tool for doing quantitative and qualitative analysis of Web-based user interfaces. Lamprey can be used from any conforming browser, and does not require modification of server or client software. By rerouting WWW navigation through a centralized filter, Lamprey collects the sequence and timing of hyperlinks used by individual users to move through the web. Instead of providing marginal statistics, it retains the full information required to recreate a user session. We have built Lamprey as a standard Common Gateway Interface (CGI) that works with all standard WWW browsers and servers. In this paper, we describe Lamprey and provide a short demonstration of this approach for evaluating web usage patterns.

Proposing Electronic Health Record Usability Requirements Based on Enriched ISO 9241 Metric Usability Model

PubMed Central

Farzandipour, Mehrdad; Riazi, Hossein; Jabali, Monireh Sadeqi

2018-01-01

Introduction: System usability assessment is among the important aspects in assessing the quality of clinical information technology, especially when the end users of the system are concerned. This study aims at providing a comprehensive list of system usability. Methods: This research is a descriptive cross-sectional one conducted using Delphi technique in three phases in 2013. After experts’ ideas were concluded, the final version of the questionnaire including 163 items in three phases was presented to 40 users of information systems in hospitals. The grading ranged from 0-4. Data analysis was conducted using SPSS software. Those requirements with a mean point of three or higher were finally confirmed. Results: The list of system usability requirements for electronic health record was designed and confirmed in nine areas including suitability for the task (24 items), self-descriptiveness (22 items), controllability (19 questions), conformity with user expectations (25 items), error tolerance (21 items), suitability for individualization (7 items), suitability for learning (19 items), visual clarity (18 items) and auditory presentation (8 items). Conclusion: A relatively comprehensive model including useful requirements for using EHR was presented which can increase functionality, effectiveness and users’ satisfaction. Thus, it is suggested that the present model be adopted by system designers and healthcare system institutions to assess those systems. PMID:29719310

Modelling health care processes for eliciting user requirements: a way to link a quality paradigm and clinical information system design.

PubMed

Staccini, P; Joubert, M; Quaranta, J F; Fieschi, D; Fieschi, M

2000-01-01

Hospital information systems have to support quality improvement objectives. The design issues of health care information system can be classified into three categories: 1) time-oriented and event-labelled storage of patient data; 2) contextual support of decision-making; 3) capabilities for modular upgrading. The elicitation of the requirements has to meet users' needs in relation to both the quality (efficacy, safety) and the monitoring of all health care activities (traceability). Information analysts need methods to conceptualize clinical information systems that provide actors with individual benefits and guide behavioural changes. A methodology is proposed to elicit and structure users' requirements using a process-oriented analysis, and it is applied to the field of blood transfusion. An object-oriented data model of a process has been defined in order to identify its main components: activity, sub-process, resources, constrains, guidelines, parameters and indicators. Although some aspects of activity, such as "where", "what else", and "why" are poorly represented by the data model alone, this method of requirement elicitation fits the dynamic of data input for the process to be traced. A hierarchical representation of hospital activities has to be found for this approach to be generalised within the organisation, for the processes to be interrelated, and for their characteristics to be shared.

Modelling health care processes for eliciting user requirements: a way to link a quality paradigm and clinical information system design.

PubMed

Staccini, P; Joubert, M; Quaranta, J F; Fieschi, D; Fieschi, M

2001-12-01

Healthcare institutions are looking at ways to increase their efficiency by reducing costs while providing care services with a high level of safety. Thus, hospital information systems have to support quality improvement objectives. The elicitation of the requirements has to meet users' needs in relation to both the quality (efficacy, safety) and the monitoring of all health care activities (traceability). Information analysts need methods to conceptualise clinical information systems that provide actors with individual benefits and guide behavioural changes. A methodology is proposed to elicit and structure users' requirements using a process-oriented analysis, and it is applied to the blood transfusion process. An object-oriented data model of a process has been defined in order to organise the data dictionary. Although some aspects of activity, such as 'where', 'what else', and 'why' are poorly represented by the data model alone, this method of requirement elicitation fits the dynamic of data input for the process to be traced. A hierarchical representation of hospital activities has to be found for the processes to be interrelated, and for their characteristics to be shared, in order to avoid data redundancy and to fit the gathering of data with the provision of care.

Experiences with collaborative climate impacts assessments for regional governments in southwestern British Columbia

NASA Astrophysics Data System (ADS)

Sobie, S. R.; Murdock, T. Q.

2016-12-01

Infrastructure vulnerability assessments and adaptation planning have created demand for detailed information about climate change and extreme events from local and regional governments. Individual communities often have distinct priorities regarding climate change impacts. While projections from climate models are available to investigate these impacts, they are not always applicable or easily interpreted by local agencies. We discuss a series of climate impacts assessments for several regional and local governments in southwestern British Columbia. Each of the assessments was conducted with input from the users on project definition from the start of the process and on interpretation of results throughout each project. To produce sufficient detail for the assessment regions, we produce high-resolution (800m) simulations of precipitation and temperature using downscaled climate model projections. Sets of derived climate parameters tailored to each region are calculated from both standard indices such as CLIMDEX and from an energy-balance snowpack model. Involving user groups from the beginning of the analysis helps to convey the meaning and confidence of each set of climate change parameters to users and also clarifies what projections are feasible or not for impact assessments. We discuss the different levels of involvement and collaboration with each organization, and the resulting decisions implemented following each of the projects.

Based on user interest level of modeling scenarios and browse content

NASA Astrophysics Data System (ADS)

Zhao, Yang

2017-08-01

User interest modeling is the core of personalized service, taking into account the impact of situational information on user preferences, the user behavior days of financial information. This paper proposes a method of user interest modeling based on scenario information, which is obtained by calculating the similarity of the situation. The user's current scene of the approximate scenario set; on the "user - interest items - scenarios" three-dimensional model using the situation pre-filtering method of dimension reduction processing. View the content of the user interested in the theme, the analysis of the page content to get each topic of interest keywords, based on the level of vector space model user interest. The experimental results show that the user interest model based on the scenario information is within 9% of the user's interest prediction, which is effective.

Outlier Detection in Infrared Signatures

DTIC Science & Technology

1992-01-01

for model idcntification. Gnanadcsikan (1977) pointed out that Hampci’s influence function (Huampcl (1974)) can bc used to estimate the effect...individual outliers have on sample estimates of parameters. Chernick noted that the influence function for parameters of intcrcst to the users of a data...important outliers, while those with amall estimated influence are not). In this way the influence function provides a "distance" measure for multi

Visual Predictive Check in Models with Time-Varying Input Function.

PubMed

Largajolli, Anna; Bertoldo, Alessandra; Campioni, Marco; Cobelli, Claudio

2015-11-01

The nonlinear mixed effects models are commonly used modeling techniques in the pharmaceutical research as they enable the characterization of the individual profiles together with the population to which the individuals belong. To ensure a correct use of them is fundamental to provide powerful diagnostic tools that are able to evaluate the predictive performance of the models. The visual predictive check (VPC) is a commonly used tool that helps the user to check by visual inspection if the model is able to reproduce the variability and the main trend of the observed data. However, the simulation from the model is not always trivial, for example, when using models with time-varying input function (IF). In this class of models, there is a potential mismatch between each set of simulated parameters and the associated individual IF which can cause an incorrect profile simulation. We introduce a refinement of the VPC by taking in consideration a correlation term (the Mahalanobis or normalized Euclidean distance) that helps the association of the correct IF with the individual set of simulated parameters. We investigate and compare its performance with the standard VPC in models of the glucose and insulin system applied on real and simulated data and in a simulated pharmacokinetic/pharmacodynamic (PK/PD) example. The newly proposed VPC performance appears to be better with respect to the standard VPC especially for the models with big variability in the IF where the probability of simulating incorrect profiles is higher.

Biomass universal district heating systems

NASA Astrophysics Data System (ADS)

Soltero, Victor Manuel; Rodríguez-Artacho, Salvador; Velázquez, Ramón; Chacartegui, Ricardo

2017-11-01

In mild climate regions Directive 27/2012 EU application for developing sustainable district heating networks in consolidated urban nucleus is a challenge. In Spain most of the municipalities above 5,000 inhabitants have a reliable natural gas network and individual heating systems at homes. In this work a new heating network paradigm is proposed, the biomass universal heating network in rural areas. This model involves all the economic, legal and technical aspects and interactions between the different agents of the systems: provider company, individual and collective end-users and local and regional administration. The continental region in Spain has 588 municipalities with a population above 1,500 inhabitants close to forest biomass with renewable use. In many of these cases the regulation identifies the ownership of the forest resources use. The universal heating networks are a great opportunity for energy saving of 2,000 GWh, avoiding 2.7 million tons of CO2 emissions and with a global annual savings for end users of 61.8 million of euros. The presented model is easily extrapolated to other small municipalities in Europe. The real application of the model is presented for three municipalities in different locations of Spain where Universal Heating Networks are under development. The analysis show the interest of the integrated model for the three cases with different structural agents and relationships between them. The use of sustainable forest resources, extracted and managed by local companies, strengths circular economy in the region with a potential global economic impact above 200 M€.

30/20 GHz communications systems baseband processor development

NASA Astrophysics Data System (ADS)

Brown, L.; Sabourin, D.; Stilwell, J.; McCallister, R.; Borota, M.

The architecture and system design concepts for a commercial satellite communications system planned for the 1990's has been developed. The system provides data communications between the individual users via trunking and customer premise service terminals utilizing a central switching satellite operating in a time-division multiple-access mode. Baseband processing is employed to route and control traffic on an individual message basis while providing significant advantages in improved link margins and system flexibility. Key technology developments required to prove the flight readiness of the baseband processor design are being verified in the baseband processor proof-of-concept model described herein.

30/20 GHz communications systems baseband processor development

NASA Technical Reports Server (NTRS)

Brown, L.; Sabourin, D.; Stilwell, J.; Mccallister, R.; Borota, M.

1982-01-01

The architecture and system design concepts for a commercial satellite communications system planned for the 1990's has been developed. The system provides data communications between the individual users via trunking and customer premise service terminals utilizing a central switching satellite operating in a time-division multiple-access mode. Baseband processing is employed to route and control traffic on an individual message basis while providing significant advantages in improved link margins and system flexibility. Key technology developments required to prove the flight readiness of the baseband processor design are being verified in the baseband processor proof-of-concept model described herein.

Setting Priorities in Behavioral Interventions: An Application to Reducing Phishing Risk.

PubMed

Canfield, Casey Inez; Fischhoff, Baruch

2018-04-01

Phishing risk is a growing area of concern for corporations, governments, and individuals. Given the evidence that users vary widely in their vulnerability to phishing attacks, we demonstrate an approach for assessing the benefits and costs of interventions that target the most vulnerable users. Our approach uses Monte Carlo simulation to (1) identify which users were most vulnerable, in signal detection theory terms; (2) assess the proportion of system-level risk attributable to the most vulnerable users; (3) estimate the monetary benefit and cost of behavioral interventions targeting different vulnerability levels; and (4) evaluate the sensitivity of these results to whether the attacks involve random or spear phishing. Using parameter estimates from previous research, we find that the most vulnerable users were less cautious and less able to distinguish between phishing and legitimate emails (positive response bias and low sensitivity, in signal detection theory terms). They also accounted for a large share of phishing risk for both random and spear phishing attacks. Under these conditions, our analysis estimates much greater net benefit for behavioral interventions that target these vulnerable users. Within the range of the model's assumptions, there was generally net benefit even for the least vulnerable users. However, the differences in the return on investment for interventions with users with different degrees of vulnerability indicate the importance of measuring that performance, and letting it guide interventions. This study suggests that interventions to reduce response bias, rather than to increase sensitivity, have greater net benefit. © 2017 Society for Risk Analysis.

Adherence and Persistence Among Statin Users Aged 65 Years and Over: A Systematic Review and Meta-analysis.

PubMed

Ofori-Asenso, Richard; Jakhu, Avtar; Zomer, Ella; Curtis, Andrea J; Korhonen, Maarit Jaana; Nelson, Mark; Gambhir, Manoj; Tonkin, Andrew; Liew, Danny; Zoungas, Sophia

2018-05-09

Older people (aged ≥ 65 years) have distinctive challenges with medication adherence. However, adherence and persistence patterns among older statin users have not been comprehensively reviewed. As part of a broader systematic review, we searched Medline, Embase, PsycINFO, CINAHL, Database of Abstracts of Reviews of Effects, CENTRAL, and the National Health Service Economic Evaluation Database through December 2016 for English articles reporting adherence and/or persistence among older statin users. Data were analyzed via descriptive methods and meta-analysis using random-effect modeling. Data from more than 3 million older statin users in 82 studies conducted in over 40 countries were analyzed. At 1-year follow-up, 59.7% (primary prevention 47.9%; secondary prevention 62.3%) of users were adherent (medication possession ratio [MPR] or proportion of days covered [PDC] ≥ 80%). For both primary and secondary prevention subjects, 1-year adherence was worse among individuals aged more than 75 years than those aged 65-75 years. At 3 and ≥10 years, 55.3% and 28.4% of users were adherent, respectively. The proportion of users persistent at 1-year was 76.7% (primary prevention 76.0%; secondary prevention 82.6%). Additionally, 68.1% and 61.2% of users were persistent at 2 and 4 years, respectively. Among new statin users, 48.2% were nonadherent and 23.9% discontinued within the first year. The proportion of statin users who were adherent based on self-report was 85.5%. There is poor short and long term adherence and persistence among older statin users. Strategies to improve adherence and reduce discontinuation are needed if the intended cardiovascular benefits of statin treatment are to be realized.

Between-User Reliability of Tier 1 Exposure Assessment Tools Used Under REACH.

PubMed

Lamb, Judith; Galea, Karen S; Miller, Brian G; Hesse, Susanne; Van Tongeren, Martie

2017-10-01

When applying simple screening (Tier 1) tools to estimate exposure to chemicals in a given exposure situation under the Registration, Evaluation, Authorisation and restriction of CHemicals Regulation 2006 (REACH), users must select from several possible input parameters. Previous studies have suggested that results from exposure assessments using expert judgement and from the use of modelling tools can vary considerably between assessors. This study aimed to investigate the between-user reliability of Tier 1 tools. A remote-completion exercise and in person workshop were used to identify and evaluate tool parameters and factors such as user demographics that may be potentially associated with between-user variability. Participants (N = 146) generated dermal and inhalation exposure estimates (N = 4066) from specified workplace descriptions ('exposure situations') and Tier 1 tool combinations (N = 20). Interactions between users, tools, and situations were investigated and described. Systematic variation associated with individual users was minor compared with random between-user variation. Although variation was observed between choices made for the majority of input parameters, differing choices of Process Category ('PROC') code/activity descriptor and dustiness level impacted most on the resultant exposure estimates. Exposure estimates ranging over several orders of magnitude were generated for the same exposure situation by different tool users. Such unpredictable between-user variation will reduce consistency within REACH processes and could result in under-estimation or overestimation of exposure, risking worker ill-health or the implementation of unnecessary risk controls, respectively. Implementation of additional support and quality control systems for all tool users is needed to reduce between-assessor variation and so ensure both the protection of worker health and avoidance of unnecessary business risk management expenditure. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Effect of direct reciprocity and network structure on continuing prosperity of social networking services.

PubMed

Osaka, Kengo; Toriumi, Fujio; Sugawara, Toshihauru

2017-01-01

Social networking services (SNSs) are widely used as communicative tools for a variety of purposes. SNSs rely on the users' individual activities associated with some cost and effort, and thus it is not known why users voluntarily continue to participate in SNSs. Because the structures of SNSs are similar to that of the public goods (PG) game, some studies have focused on why voluntary activities emerge as an optimal strategy by modifying the PG game. However, their models do not include direct reciprocity between users, even though reciprocity is a key mechanism that evolves and sustains cooperation in human society. We developed an abstract SNS model called the reciprocity rewards and meta-rewards games that include direct reciprocity by extending the existing models. Then, we investigated how direct reciprocity in an SNS facilitates cooperation that corresponds to participation in SNS by posting articles and comments and how the structure of the networks of users exerts an influence on the strategies of users using the reciprocity rewards game. We run reciprocity rewards games on various complex networks and an instance network of Facebook and found that two types of stable cooperation emerged. First, reciprocity slightly improves the rate of cooperation in complete graphs but the improvement is insignificant because of the instability of cooperation. However, this instability can be avoided by making two assumptions: high degree of fun, i.e. articles are read with high probability, and different attitudes to reciprocal and non-reciprocal agents. We then propose the concept of half free riders to explain what strategy sustains cooperation-dominant situations. Second, we indicate that a certain WS network structure affects users' optimal strategy and facilitates stable cooperation without any extra assumptions. We give a detailed analysis of the different characteristics of the two types of cooperation-dominant situations and the effect of the memory of reciprocal agents on cooperation.

Suggestions for Improvement of User Access to GOCE L2 Data

NASA Astrophysics Data System (ADS)

Tscherning, C. C.

2011-07-01

ESA's has required that most GOCE L2 products are delivered in XML format. This creates difficulties for the users because a Parser written in Perl is needed to convert the files to files without XML tags. However several products, such as the coefficients of spherical harmonic coefficients are made available on standard form through the International Center for Global Gravity Field Models. The variance-covariance information for the gravity field models is only available without XML tags. It is suggested that all XML products are made available in the Virtual Data Archive as files without tags. This will besides making the data directly usable by a FORTRAN program also reduce the size (storage requirements) of the product to about 30 %. A further reduction of used storage should be made by tuning the number of digits for the individual quantities in the products, so that it corresponds to the actual number of significant digits.

Exploring mobile health in a private online social network.

PubMed

Memon, Qurban A; Mustafa, Asma Fayes

2015-01-01

Health information is very vulnerable. Certain individuals or corporate organisations will continue to steal it similar to bank account data once data is on wireless channels. Once health information is part of a social network, corresponding privacy issues also surface. Insufficiently trained employees at hospitals that pay less attention to creating a privacy-aware culture will suffer loss when mobile devices containing health information are lost, stolen or sniffed. In this work, a social network system is explored as a m-health system from a privacy perspective. A model is developed within a framework of data-driven privacy and implemented on Android operating system. In order to check feasibility of the proposed model, a prototype application is developed on Facebook for different services, including: i) sharing user location; ii) showing nearby friends; iii) calculating and sharing distance moved, and calories burned; iv) calculating, tracking and sharing user heart rate; etc.

Economic and hydrogeologic disparities govern the vulnerability of shared groundwater to strategic overdraft

NASA Astrophysics Data System (ADS)

Mullen, C.; Muller, M. F.

2017-12-01

Groundwater resources are depleting globally at an alarming rate. When the resource is shared, exploitation by individual users affects groundwater levels and increases pumping costs to all users. This incentivizes individual users to strategically over-pump, an effect that is challenging to keep in check because the underground nature of the resource often precludes regulations from being effectively implemented. As a result, shared groundwater resources are prone to tragedies of the commons that exacerbate their rapid depletion. However, we showed in a recent study that the vulnerability of aquifer systems to strategic overuse is strongly affected by local economic and physical characteristics, which suggests that not all shared aquifers are subject to tragedies of the commons. Building on these findings, we develop a vulnerability index based on coupled game theoretical and groundwater flow models. We show that vulnerability to strategic overdraft is driven by four intuitively interpretable adimensional parameters that describe economic and hydrogeologic disparities between the agents exploiting the aquifer. This suggests a scale-independent relation between the vulnerability of groundwater systems to common-pool overdraft and their economic and physical characteristics. We investigate this relation for a sample of existing aquifer systems and explore implications for enforceable groundwater agreements that would effectively mitigate strategic overdraft.

Arabidopsis Gene Family Profiler (aGFP)--user-oriented transcriptomic database with easy-to-use graphic interface.

PubMed

Dupl'áková, Nikoleta; Renák, David; Hovanec, Patrik; Honysová, Barbora; Twell, David; Honys, David

2007-07-23

Microarray technologies now belong to the standard functional genomics toolbox and have undergone massive development leading to increased genome coverage, accuracy and reliability. The number of experiments exploiting microarray technology has markedly increased in recent years. In parallel with the rapid accumulation of transcriptomic data, on-line analysis tools are being introduced to simplify their use. Global statistical data analysis methods contribute to the development of overall concepts about gene expression patterns and to query and compose working hypotheses. More recently, these applications are being supplemented with more specialized products offering visualization and specific data mining tools. We present a curated gene family-oriented gene expression database, Arabidopsis Gene Family Profiler (aGFP; http://agfp.ueb.cas.cz), which gives the user access to a large collection of normalised Affymetrix ATH1 microarray datasets. The database currently contains NASC Array and AtGenExpress transcriptomic datasets for various tissues at different developmental stages of wild type plants gathered from nearly 350 gene chips. The Arabidopsis GFP database has been designed as an easy-to-use tool for users needing an easily accessible resource for expression data of single genes, pre-defined gene families or custom gene sets, with the further possibility of keyword search. Arabidopsis Gene Family Profiler presents a user-friendly web interface using both graphic and text output. Data are stored at the MySQL server and individual queries are created in PHP script. The most distinguishable features of Arabidopsis Gene Family Profiler database are: 1) the presentation of normalized datasets (Affymetrix MAS algorithm and calculation of model-based gene-expression values based on the Perfect Match-only model); 2) the choice between two different normalization algorithms (Affymetrix MAS4 or MAS5 algorithms); 3) an intuitive interface; 4) an interactive "virtual plant" visualizing the spatial and developmental expression profiles of both gene families and individual genes. Arabidopsis GFP gives users the possibility to analyze current Arabidopsis developmental transcriptomic data starting with simple global queries that can be expanded and further refined to visualize comparative and highly selective gene expression profiles.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor.

PubMed

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor

PubMed Central

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application. PMID:27445783

Feasibility and effectiveness of a combined individual and psychoeducational group intervention in psychiatric residential facilities: A controlled, non-randomized study.

PubMed

Magliano, Lorenza; Puviani, Marta; Rega, Sonia; Marchesini, Nadia; Rossetti, Marisa; Starace, Fabrizio

2016-01-30

This controlled, non-randomized study explored the feasibility of introducing a Combined Individual and Group Intervention (CIGI) for users with mental disorders in residential facilities, and tested whether users who received the CIGI had better functioning than users who received the Treatment-As-Usual (TAU), at two-year follow up. In the CIGI, a structured cognitivebehavioral approach called VADO (in English, Skills Assessment and Definition of Goals) was used to set specific goals with each user, while Falloon's psychoeducational treatment was applied with the users as a group. Thirty-one professionals attended a training course in CIGI, open to users' voluntary participation, and applied it for two years with all users living in 8 residential facilities of the Mental Health Department of Modena, Italy. In the same department, 5 other residential facilities providing TAU were used as controls. ANOVA for repeated measures showed a significant interaction effect between users' functioning at baseline and follow up assessments, and the intervention. In particular, change in global functioning was higher in the 55 CIGI users than in the 44 TAU users. These results suggest that CIGI can be successfully introduced in residential facilities and may be useful to improve functioning in users with severe mental disorders. Copyright © 2016. Published by Elsevier Ireland Ltd.

Cloud Computing and the Power to Choose

ERIC Educational Resources Information Center

Bristow, Rob; Dodds, Ted; Northam, Richard; Plugge, Leo

2010-01-01

Some of the most significant changes in information technology are those that have given the individual user greater power to choose. The first of these changes was the development of the personal computer. The PC liberated the individual user from the limitations of the mainframe and minicomputers and from the rules and regulations of centralized…

User Centered Reading Intervention for Individuals with Autism and Intellectual Disability.

PubMed

Yakkundi, Anita; Dillenburger, Karola; Goodman, Lizbeth; Dounavi, Katerina

2017-01-01

Individuals with autism and intellectual disability (ID) have complex learning needs and often have difficulty in acquiring reading comprehension skills using conventional teaching tools. Evidence based reading interventions for these learners and the use of assistive technology and application of behaviour analysis to develop user-centered teaching is discussed in this paper.

Linkages Between Library Uses Through the Study of Individual Patron Behavior.

ERIC Educational Resources Information Center

Clark, Philip M.; Benson, James

1985-01-01

Proposes and investigates feasibility of using three new variables in addition to simple activity counts in measuring reference services: (1) user questioning regardless of where activity occurs; (2) treating individual user and question as unit of analysis; and (3) examination of questioning in context of other library use. (11 references) (EJS)

A Comparison of Password Techniques for Multilevel Authentication Mechanisms

DTIC Science & Technology

1990-06-01

an individual user’s perceptions, personal interests and personal history . This information is unique to the individual and is neither commonly...a user may associative passwords profile around the Beatles . In this case, cues may include "abbey", "john", "yellow" and "george" and have responses

The simple rules of social contagion.

PubMed

Hodas, Nathan O; Lerman, Kristina

2014-03-11

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

The Simple Rules of Social Contagion

NASA Astrophysics Data System (ADS)

Hodas, Nathan O.; Lerman, Kristina

2014-03-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

Influence of age on androgen deprivation therapy-associated Alzheimer’s disease

NASA Astrophysics Data System (ADS)

Nead, Kevin T.; Gaskin, Greg; Chester, Cariad; Swisher-McClure, Samuel; Dudley, Joel T.; Leeper, Nicholas J.; Shah, Nigam H.

2016-10-01

We recently found an association between androgen deprivation therapy (ADT) and Alzheimer’s disease. As Alzheimer’s disease is a disease of advanced age, we hypothesize that older individuals on ADT may be at greatest risk. We conducted a retrospective multi-institutional analysis among 16,888 individuals with prostate cancer using an informatics approach. We tested the effect of ADT on Alzheimer’s disease using Kaplan-Meier age stratified analyses in a propensity score matched cohort. We found a lower cumulative probability of remaining Alzheimer’s disease-free between non-ADT users age ≥70 versus those age <70 years (p < 0.001) and between ADT versus non-ADT users ≥70 years (p = 0.034). The 5-year probability of developing Alzheimer’s disease was 2.9%, 1.9% and 0.5% among ADT users ≥70, non-ADT users ≥70 and individuals <70 years, respectively. Compared to younger individuals older men on ADT may have the greatest absolute Alzheimer’s disease risk. Future work should investigate the ADT Alzheimer’s disease association in advanced age populations given the greater potential clinical impact.

Model-Based GUI Testing Using Uppaal at Novo Nordisk

NASA Astrophysics Data System (ADS)

Hjort, Ulrik H.; Illum, Jacob; Larsen, Kim G.; Petersen, Michael A.; Skou, Arne

This paper details a collaboration between Aalborg University and Novo Nordiskin developing an automatic model-based test generation tool for system testing of the graphical user interface of a medical device on an embedded platform. The tool takes as input an UML Statemachine model and generates a test suite satisfying some testing criterion, such as edge or state coverage, and converts the individual test case into a scripting language that can be automatically executed against the target. The tool has significantly reduced the time required for test construction and generation, and reduced the number of test scripts while increasing the coverage.

Predicting cannabis abuse screening test (CAST) scores: a recursive partitioning analysis using survey data from Czech Republic, Italy, the Netherlands and Sweden.

PubMed

Blankers, Matthijs; Frijns, Tom; Belackova, Vendula; Rossi, Carla; Svensson, Bengt; Trautmann, Franz; van Laar, Margriet

2014-01-01

Cannabis is Europe's most commonly used illicit drug. Some users do not develop dependence or other problems, whereas others do. Many factors are associated with the occurrence of cannabis-related disorders. This makes it difficult to identify key risk factors and markers to profile at-risk cannabis users using traditional hypothesis-driven approaches. Therefore, the use of a data-mining technique called binary recursive partitioning is demonstrated in this study by creating a classification tree to profile at-risk users. 59 variables on cannabis use and drug market experiences were extracted from an internet-based survey dataset collected in four European countries (Czech Republic, Italy, Netherlands and Sweden), n = 2617. These 59 potential predictors of problematic cannabis use were used to partition individual respondents into subgroups with low and high risk of having a cannabis use disorder, based on their responses on the Cannabis Abuse Screening Test. Both a generic model for the four countries combined and four country-specific models were constructed. Of the 59 variables included in the first analysis step, only three variables were required to construct a generic partitioning model to classify high risk cannabis users with 65-73% accuracy. Based on the generic model for the four countries combined, the highest risk for cannabis use disorder is seen in participants reporting a cannabis use on more than 200 days in the last 12 months. In comparison to the generic model, the country-specific models led to modest, non-significant improvements in classification accuracy, with an exception for Italy (p = 0.01). Using recursive partitioning, it is feasible to construct classification trees based on only a few variables with acceptable performance to classify cannabis users into groups with low or high risk of meeting criteria for cannabis use disorder. The number of cannabis use days in the last 12 months is the most relevant variable. The identified variables may be considered for use in future screeners for cannabis use disorders.

Linking Earth Observations and Models to Societal Information Needs: The Case of Coastal Flooding

NASA Astrophysics Data System (ADS)

Buzzanga, B. A.; Plag, H. P.

2016-12-01

Coastal flooding is expected to increase in many areas due to sea level rise (SLR). Many societal applications such as emergency planning and designing public services depend on information on how the flooding spectrum may change as a result of SLR. To identify the societal information needs a conceptual model is needed that identifies the key stakeholders, applications, and information and observation needs. In the context of the development of the Global Earth Observation System of Systems (GEOSS), which is implemented by the Group on Earth Observations (GEO), the Socio-Economic and Environmental Information Needs Knowledge Base (SEE-IN KB) is developed as part of the GEOSS Knowledge Base. A core function of the SEE-IN KB is to facilitate the linkage of societal information needs to observations, models, information and knowledge. To achieve this, the SEE-IN KB collects information on objects such as user types, observational requirements, societal goals, models, and datasets. Comprehensive information concerning the interconnections between instances of these objects is used to capture the connectivity and to establish a conceptual model as a network of networks. The captured connectivity can be used in searches to allow users to discover products and services for their information needs, and providers to search for users and applications benefiting from their products. It also allows to answer "What if?" questions and supports knowledge creation. We have used the SEE-IN KB to develop a conceptual model capturing the stakeholders in coastal flooding and their information needs, and to link these elements to objects. We show how the knowledge base enables the transition of scientific data to useable information by connecting individuals such as city managers to flood maps. Within the knowledge base, these same users can request information that improves their ability to make specific planning decisions. These needs are linked to entities within research institutions that have the capabilities to meet them. Further, current research such as that investigating precipitation-induced flooding under different SLR scenarios is linked to the users who benefit from the knowledge, effectively creating a bi-directional channel between science and society that increases knowledge and improves foresight.

GoPhast: a graphical user interface for PHAST

USGS Publications Warehouse

Winston, Richard B.

2006-01-01

GoPhast is a graphical user interface (GUI) for the USGS model PHAST. PHAST simulates multicomponent, reactive solute transport in three-dimensional, saturated, ground-water flow systems. PHAST can model both equilibrium and kinetic geochemical reactions. PHAST is derived from HST3D (flow and transport) and PHREEQC (geochemical calculations). The flow and transport calculations are restricted to constant fluid density and constant temperature. The complexity of the input required by PHAST makes manual construction of its input files tedious and error-prone. GoPhast streamlines the creation of the input file and helps reduce errors. GoPhast allows the user to define the spatial input for the PHAST flow and transport data file by drawing points, lines, or polygons on top, front, and side views of the model domain. These objects can have up to two associated formulas that define their extent perpendicular to the view plane, allowing the objects to be three-dimensional. Formulas are also used to specify the values of spatial data (data sets) both globally and for individual objects. Objects can be used to specify the values of data sets independent of the spatial and temporal discretization of the model. Thus, the grid and simulation periods for the model can be changed without respecifying spatial data pertaining to the hydrogeologic framework and boundary conditions. This report describes the operation of GoPhast and demonstrates its use with examples. GoPhast runs on Windows 2000, Windows XP, and Linux operating systems.

Exploring the critical quality attributes and models of smart homes.

PubMed

Ted Luor, Tainyi; Lu, Hsi-Peng; Yu, Hueiju; Lu, Yinshiu

2015-12-01

Research on smart homes has significantly increased in recent years owing to their considerably improved affordability and simplicity. However, the challenge is that people have different needs (or attitudes toward smart homes), and provision should be tailored to individuals. A few studies have classified the functions of smart homes. Therefore, the Kano model is first adopted as a theoretical base to explore whether the functional classifications of smart homes are attractive or necessary, or both. Second, three models and test user attitudes toward three function types of smart homes are proposed. Based on the Kano model, the principal results, namely, two "Attractive Quality" and nine "Indifferent Quality" items, are found. Verification of the hypotheses also indicates that the entertainment, security, and automation functions are significantly correlated with the variables "perceive useful" and "attitude." Cost consideration is negatively correlated with attitudes toward entertainment and automation. Results suggest that smart home providers should survey user needs for their product instead of merely producing smart homes based on the design of the builder or engineer. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Online-specific fear of missing out and Internet-use expectancies contribute to symptoms of Internet-communication disorder.

PubMed

Wegmann, Elisa; Oberst, Ursula; Stodt, Benjamin; Brand, Matthias

2017-06-01

Some of the most frequently used online applications are Facebook, WhatsApp, and Twitter. These applications allow individuals to communicate with other users, to share information or pictures, and to stay in contact with friends all over the world. However, a growing number of users suffer from negative consequences due to their excessive use of these applications, which can be referred to as Internet-communication disorder. The frequent use and easy access of these applications may also trigger the individual's fear of missing out on content when not accessing these applications. Using a sample of 270 participants, a structural equation model was analyzed to investigate the role of psychopathological symptoms and the fear of missing out on expectancies towards Internet-communication applications in the development of symptoms of an Internet-communication disorder. The results suggest that psychopathological symptoms predict higher fear of missing out on the individual's Internet-communication applications and higher expectancies to use these applications as a helpful tool to escape from negative feelings. These specific cognitions mediate the effect of psychopathological symptoms on Internet-communication disorder. Our results are in line with the theoretical model by Brand et al. (2016) as they show how Internet-related cognitive bias mediates the relationship between a person's core characteristics (e.g., psychopathological symptoms) and Internet-communication disorder. However, further studies should investigate the role of the fear of missing out as a specific predisposition, as well as specific cognition in the online context.

[Clinical and social vulnerabilities in crack users according to housing status: a multicenter study in six Brazilian state capitals].

PubMed

Halpern, Silvia Chwartzmann; Scherer, Juliana Nichterwitz; Roglio, Vinicius; Faller, Sibele; Sordi, Anne; Ornell, Felipe; Dalbosco, Carla; Pechansky, Flavio; Kessler, Félix; Diemen, Lísia von

2017-07-03

The study had the goal to evaluate psychoactive substance use severity, violence, physical and emotional health of crack users who seeks specialized treatment in Psychosocial Care Centers for Alcohol and Drugs (CAPSad) concerning housing status. This is a multicenter cross-sectional study in six Brazilian capitals with 564 crack users categorized into two groups (1) users who have been homeless sometime in life (n = 266) and (2) individuals who have never lived on streets (n = 298). To assess the substance use severity and the characteristics of the individuals, the Addiction Severity Index, 6th version (ASI-6) was used. Group 1 users showed worse indicators regarding alcohol, medical and psychiatric problems, employment and family support subscales, as well as greater involvement with legal problems, violence, sexual abuse, suicide risk and health related problems such as HIV/AIDS, hepatitis and tuberculosis. In addition they have lower income to pay for basic needs. After analysis and control for possible confounders, not having enough income to pay for basic needs, showing depression symptoms, and having been arrested for theft remained statistically significant. This study evaluated more deeply drug use severity and housing status of crack users. Interventions developed in outpatient treatment should be designed and tailored to specific profiles and demands of drug users, especially homeless individuals.

TVB-EduPack—An Interactive Learning and Scripting Platform for The Virtual Brain

PubMed Central

Matzke, Henrik; Schirner, Michael; Vollbrecht, Daniel; Rothmeier, Simon; Llarena, Adalberto; Rojas, Raúl; Triebkorn, Paul; Domide, Lia; Mersmann, Jochen; Solodkin, Ana; Jirsa, Viktor K.; McIntosh, Anthony Randal; Ritter, Petra

2015-01-01

The Virtual Brain (TVB; thevirtualbrain.org) is a neuroinformatics platform for full brain network simulation based on individual anatomical connectivity data. The framework addresses clinical and neuroscientific questions by simulating multi-scale neural dynamics that range from local population activity to large-scale brain function and related macroscopic signals like electroencephalography and functional magnetic resonance imaging. TVB is equipped with a graphical and a command-line interface to create models that capture the characteristic biological variability to predict the brain activity of individual subjects. To enable researchers from various backgrounds a quick start into TVB and brain network modeling in general, we developed an educational module: TVB-EduPack. EduPack offers two educational functionalities that seamlessly integrate into TVB's graphical user interface (GUI): (i) interactive tutorials introduce GUI elements, guide through the basic mechanics of software usage and develop complex use-case scenarios; animations, videos and textual descriptions transport essential principles of computational neuroscience and brain modeling; (ii) an automatic script generator records model parameters and produces input files for TVB's Python programming interface; thereby, simulation configurations can be exported as scripts that allow flexible customization of the modeling process and self-defined batch- and post-processing applications while benefitting from the full power of the Python language and its toolboxes. This article covers the implementation of TVB-EduPack and its integration into TVB architecture. Like TVB, EduPack is an open source community project that lives from the participation and contribution of its users. TVB-EduPack can be obtained as part of TVB from thevirtualbrain.org. PMID:26635597

Association between community pharmacy loyalty and persistence and implementation of antipsychotic treatment among individuals with schizophrenia.

PubMed

Zongo, Frank E; Moisan, Jocelyne; Grégoire, Jean-Pierre; Lesage, Alain; Dossa, Anara Richi; Lauzier, Sophie

2018-01-01

Non-adherence is a major obstacle to optimal treatment of schizophrenia. Community pharmacists are in a key position to detect non-adherence and put in place interventions. Their role is likely to be more efficient when individuals are loyal to a single pharmacy. To assess the association between the level of community pharmacy loyalty and persistence with and implementation of antipsychotic drug treatment among individuals with schizophrenia. A cohort study using databases from the Quebec health insurance board (Canada) was conducted among new antipsychotic users insured by Quebec's public drug plan. Level of community pharmacy loyalty was assessed as the number of pharmacies visited in the year after antipsychotics initiation. Persistence was defined as having an antipsychotic supply in the user's possession on the 730 th day after its initiation and implementation as having antipsychotics in the user's possession for ≥80% of the days in the second year after antipsychotics initiation (among persistent only). Generalized linear models were used to estimate adjusted prevalence ratios (aPR) and 95% confidence intervals (95%CI). 6,251 individuals were included in the cohort and 54.1% had their drug prescriptions filled in >1 pharmacy. When compared to those who had their prescriptions filled in a single pharmacy, those who had their prescriptions filled in ≥4 different pharmacies were 22% more likely to be non-persistent (aPR = 1.22; 95%CI = 1.10-1.37) and 49% more likely to have an antipsychotic for <80% of the days (aPR = 1.49; 95%IC = 1.28-1.74). This first exploration of community pharmacy loyalty in the context of severe mental illness indicates that this healthcare organisation factor might be associated with antipsychotics persistence and implementation. Identification of individuals with low community pharmacy loyalty and initiatives to optimize community pharmacy loyalty could contribute to enhanced persistence and implementation. Copyright © 2016 Elsevier Inc. All rights reserved.

Cognitive deficit in methamphetamine users relative to childhood academic performance: link to cortical thickness.

PubMed

Dean, Andy C; Morales, Angelica M; Hellemann, Gerhard; London, Edythe D

2018-04-20

Individuals with cognitive problems may be predisposed to develop substance use disorders; therefore, differences in cognitive function between methamphetamine users and control participants may be attributable to premorbid factors rather than methamphetamine use. The goal of this study was to clarify the extent to which this is the case. Childhood academic transcripts were obtained for 37 methamphetamine-dependent adults and 41 control participants of similar educational level and premorbid IQ. Each participant completed a comprehensive cognitive battery and received a structural magnetic resonance imaging scan. Data from control participants and linear regression were used to develop a normative model to describe the relationship between childhood academic performance and scores on the cognitive battery. Using this model, cognitive performance of methamphetamine users was predicted from their premorbid academic scores. Results indicated that methamphetamine users' childhood grade point average was significantly lower than that of the control group (p < 0.05). Further, methamphetamine users' overall cognitive performance was lower than was predicted from their grade point average prior to methamphetamine use (p = 0.001), with specific deficits in attention/concentration and memory (ps < 0.01). Memory deficits were associated with lower whole-brain cortical thickness (p < 0.05). Thus, in addition to having an apparent premorbid weakness in cognition, methamphetamine users exhibit subsequent cognitive function that is significantly lower than premorbid estimates would predict. The results support the view that chronic methamphetamine use causes a decline in cognition and/or a failure to develop normative cognitive abilities, although aside from methamphetamine use per se, other drug use and unidentified factors likely contribute to the observed effects.

An Item Response Theory Modeling of Alcohol and Marijuana Dependences: A National Drug Abuse Treatment Clinical Trials Network Study*

PubMed Central

Wu, Li-Tzy; Pan, Jeng-Jong; Blazer, Dan G.; Tai, Betty; Stitzer, Maxine L.; Brooner, Robert K.; Woody, George E.; Patkar, Ashwin A.; Blaine, Jack D.

2009-01-01

Objective: The aim of this study was to examine psychometric properties of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), diagnostics criteria for alcohol and marijuana dependences among 462 alcohol users and 311 marijuana users enrolled in two multisite trials of the National Drug Abuse Treatment Clinical Trials Network. Method: Diagnostic questions were assessed by the DSM-IV checklist. Data were analyzed by the item response theory and the multiple indicators–multiple causes method procedures. Results: Criterion symptoms of alcohol and marijuana dependences exhibited a high level of internal consistency. All individual symptoms showed good discrimination in distinguishing alcohol or marijuana users between high and low severity levels of the continuum. In both groups, “withdrawal” appeared to measure the most severe symptom of the dependence continuum. There was little evidence of measurement nonequivalence in assessing symptoms of dependence by gender, age, race/ethnicity, and educational level. Conclusions: These findings highlight the clinical utility of the DSM-IV checklist in assessing alcohol- and marijuana-dependence syndromes among treatment-seeking substance users. PMID:19371493

Multi-focused geospatial analysis using probes.

PubMed

Butkiewicz, Thomas; Dou, Wenwen; Wartell, Zachary; Ribarsky, William; Chang, Remco

2008-01-01

Traditional geospatial information visualizations often present views that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in for local inspection, spatial awareness and comparison between regions become limited. In our model, coordinated visualizations are integrated within individual probe interfaces, which depict the local data in user-defined regions-of-interest. Our probe concept can be incorporated into a variety of geospatial visualizations to empower users with the ability to observe, coordinate, and compare data across multiple local regions. It is especially useful when dealing with complex simulations or analyses where behavior in various localities differs from other localities and from the system as a whole. We illustrate the effectiveness of our technique over traditional interfaces by incorporating it within three existing geospatial visualization systems: an agent-based social simulation, a census data exploration tool, and an 3D GIS environment for analyzing urban change over time. In each case, the probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users.

Towards a Ubiquitous User Model for Profile Sharing and Reuse

PubMed Central

de Lourdes Martinez-Villaseñor, Maria; Gonzalez-Mendoza, Miguel; Hernandez-Gress, Neil

2012-01-01

People interact with systems and applications through several devices and are willing to share information about preferences, interests and characteristics. Social networking profiles, data from advanced sensors attached to personal gadgets, and semantic web technologies such as FOAF and microformats are valuable sources of personal information that could provide a fair understanding of the user, but profile information is scattered over different user models. Some researchers in the ubiquitous user modeling community envision the need to share user model's information from heterogeneous sources. In this paper, we address the syntactic and semantic heterogeneity of user models in order to enable user modeling interoperability. We present a dynamic user profile structure based in Simple Knowledge Organization for the Web (SKOS) to provide knowledge representation for ubiquitous user model. We propose a two-tier matching strategy for concept schemas alignment to enable user modeling interoperability. Our proposal is proved in the application scenario of sharing and reusing data in order to deal with overweight and obesity. PMID:23201995

User modeling for distributed virtual environment intelligent agents

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.

1999-07-01

This paper emphasizes the requirement for user modeling by presenting the necessary information to motivate the need for and use of user modeling for intelligent agent development. The paper will present information on our current intelligent agent development program, the Symbiotic Information Reasoning and Decision Support (SIRDS) project. We then discuss the areas of intelligent agents and user modeling, which form the foundation of the SIRDS project. Included in the discussion of user modeling are its major components, which are cognitive modeling and behavioral modeling. We next motivate the need for and user of a methodology to develop user models to encompass work within cognitive task analysis. We close the paper by drawing conclusions from our current intelligent agent research project and discuss avenues of future research in the utilization of user modeling for the development of intelligent agents for virtual environments.

Seventeen-Year Nationwide Trends in Use of Long-acting Bronchodilators and Inhaled Corticosteroids among Adults - A Danish Drug Utilization Study.

PubMed

Reilev, Mette; Pottegård, Anton; Davidsen, Jesper Rømhild; Rasmussen, Lotte; Søndergaard, Jens; Laursen, Christian B; Henriksen, Daniel Pilsgaard

2018-02-08

Long-acting bronchodilators and inhaled corticosteroids (ICS) are the cornerstones in treatment of chronic obstructive and inflammatory pulmonary diseases. However, non-adherence to guidelines is widespread. Detailed information on real-life treatment patterns is needed to promote rational use. We aimed to investigate nationwide time trends in individual-level treatment patterns of long-acting bronchodilators and ICS. Using nationwide Danish health registries, we identified all Danish adults with a prescription for long-acting bronchodilators and/or ICS from 2000 to 2016. We investigated the total use of long-acting bronchodilators and ICS, the proportion of current users and the rate of new users over time. Finally, we assessed treatment persistence. We included 23,061,681 prescriptions for long-acting bronchodilators and ICS issued to 805,860 individuals from 2000 to 2016. Over this period, the total annual amount of prescribed long-acting bronchodilators and ICS increased by 39%. Similarly, the proportion of adult users increased from 2.6% to 4.5%, mainly driven by the introduction of combination therapy and long-acting muscarinic antagonist (LAMA). Although the rate of new users of fixed-dose combination drugs increased substantially over time, the overall rate of new users was stable. In general, the proportion of patients on therapy after 1 year was low (25-53%), especially among young individuals and users of ICS. We document a pronounced increase in the total use of long-acting bronchodilators and ICS over time, mainly driven by the introduction of combination drugs and LAMA. Special attention should be paid to the low level of persistence, especially among young individuals and users of ICS. © 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package

PubMed Central

2012-01-01

Background Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. Results In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Conclusions Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org. PMID:23281941

Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package.

PubMed

El-Kalioby, Mohamed; Abouelhoda, Mohamed; Krüger, Jan; Giegerich, Robert; Sczyrba, Alexander; Wall, Dennis P; Tonellato, Peter

2012-01-01

Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org.

Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making.

PubMed

Harlé, Katia M; Guo, Dalin; Zhang, Shunan; Paulus, Martin P; Yu, Angela J

2017-01-01

Depressive pathology, which includes both heightened negative affect (e.g., anxiety) and reduced positive affect (e.g., anhedonia), is known to be associated with sub-optimal decision-making, particularly in uncertain environments. Here, we use a computational approach to quantify and disambiguate how individual differences in these affective measures specifically relate to different aspects of learning and decision-making in reward-based choice behavior. Fifty-three individuals with a range of depressed mood completed a two-armed bandit task, in which they choose between two arms with fixed but unknown reward rates. The decision-making component, which chooses among options based on current expectations about reward rates, is modeled by two different decision policies: a learning-independent Win-stay/Lose-shift (WSLS) policy that ignores all previous experiences except the last trial, and Softmax, which prefers the arm with the higher expected reward. To model the learning component for the Softmax choice policy, we use a Bayesian inference model, which updates estimated reward rates based on the observed history of trial outcomes. Softmax with Bayesian learning better fits the behavior of 55% of the participants, while the others are better fit by a learning-independent WSLS strategy. Among Softmax "users", those with higher anhedonia are less likely to choose the option estimated to be most rewarding. Moreover, the Softmax parameter mediates the inverse relationship between anhedonia and overall monetary gains. On the other hand, among WSLS "users", higher state anxiety correlates with increasingly better ability of WSLS, relative to Softmax, to explain subjects' trial-by-trial choices. In summary, there is significant variability among individuals in their reward-based, exploratory decision-making, and this variability is at least partly mediated in a very specific manner by affective attributes, such as hedonic tone and state anxiety.

Information About Users and Usages: A Literature Review.

ERIC Educational Resources Information Center

Hensley, Susan E.; Nelson, Carnot

Identified in this study are the factors which affect the user's capacity to seek out and utilize information, and the factors which serve as obstacles to information use. Factors relating to both organizational and individual use include level of use, user skills, and user motivation; differentiation of level of use is presented in three levels:…

National Environmental Data Referral Service (NEDRES) User Survey. Final Report.

ERIC Educational Resources Information Center

MAXIMA Corp., Silver Spring, MD.

A survey was conducted to assess environmental data users' interest in a referral system such as the National Environmental Data Referral Service (NEDRES) and to gauge user willingness to participate in a proposed NEDRES network and to comply with a system of NEDRES user fees. Twenty-one organizations were identified and 3,200 individuals were…

Impact of heterogeneity and socioeconomic factors on individual behavior in decentralized sharing ecosystems.

PubMed

Gavaldà-Miralles, Arnau; Choffnes, David R; Otto, John S; Sánchez, Mario A; Bustamante, Fabián E; Amaral, Luís A N; Duch, Jordi; Guimerà, Roger

2014-10-28

Tens of millions of individuals around the world use decentralized content distribution systems, a fact of growing social, economic, and technological importance. These sharing systems are poorly understood because, unlike in other technosocial systems, it is difficult to gather large-scale data about user behavior. Here, we investigate user activity patterns and the socioeconomic factors that could explain the behavior. Our analysis reveals that (i) the ecosystem is heterogeneous at several levels: content types are heterogeneous, users specialize in a few content types, and countries are heterogeneous in user profiles; and (ii) there is a strong correlation between socioeconomic indicators of a country and users behavior. Our findings open a research area on the dynamics of decentralized sharing ecosystems and the socioeconomic factors affecting them, and may have implications for the design of algorithms and for policymaking.

Evaluating gaze-driven power wheelchair with navigation support for persons with disabilities.

PubMed

Wästlund, Erik; Sponseller, Kay; Pettersson, Ola; Bared, Anders

2015-01-01

This article describes a novel add-on for powered wheelchairs that is composed of a gaze-driven control system and a navigation support system. The add-on was tested by three users. All of the users were individuals with severe disabilities and no possibility of moving independently. The system is an add-on to a standard power wheelchair and can be customized for different levels of support according to the cognitive level, motor control, perceptual skills, and specific needs of the user. The primary aim of this study was to test the functionality and safety of the system in the user's home environment. The secondary aim was to evaluate whether access to a gaze-driven powered wheelchair with navigation support is perceived as meaningful in terms of independence and participation. The results show that the system has the potential to provide safe, independent indoor mobility and that the users perceive doing so as fun, meaningful, and a way to reduce dependency on others. Independent mobility has numerous benefits in addition to psychological and emotional well-being. By observing users' actions, caregivers and healthcare professionals can assess the individual's capabilities, which was not previously possible. Rehabilitation can be better adapted to the individual's specific needs, and driving a wheelchair independently can be a valuable, motivating training tool.

Characteristics of patients seeking health information online via social health networks versus general Internet sites: a comparative study.

PubMed

Magnezi, Racheli; Grosberg, Dafna; Novikov, Ilya; Ziv, Arnona; Shani, Mordechai; Freedman, Laurence S

2015-03-01

Camoni.co.il, a Hebrew-language social health network offers advice, consultation, and connection to others with chronic illness. This study compared characteristics and objectives of Camoni.co.il users and individuals seeking medical information through general Internet sites. Similar questionnaires were sent to 1009 Internet and 900 Camoni users. Cluster analysis defined four modes of online social health network use: "acquiring information and support", "communicating", "networking" and "browsing". Six hundred and five Internet and 125 Camoni users responded. Diabetes, hypertension, obesity and lung diseases were found more often among general Internet users than Camoni users. Among Camoni users, "acquiring information and support" was the main motivation for individuals over age 55 years, women, those with lower income, chronic pain, obesity and depression. "Communicating" was the main incentive of men, those 20-34 years old, those with less education, or an eating disorder. "Networking" was the most significant motivation for those with multiple sclerosis or depression. Browsing was most frequent among individuals with multiple sclerosis. Identifying needs of social health network surfers will allow planning unique contents and enhancing social health sites. Physicians might advise patients to use them to obtain support and information regarding their conditions, possibly leading to improved compliance and self-management.

Pruning a decision tree for selecting computer-related assistive devices for people with disabilities.

PubMed

Chi, Chia-Fen; Tseng, Li-Kai; Jang, Yuh

2012-07-01

Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson's decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients' individual needs in an efficient manner.

CDPOP Users Manual

Treesearch

E. L. Landguth; B. K. Hand; J. M. Glassy; S. A. Cushman; M. Jacobi; T. J. Julian

2011-01-01

The goal of this user manual is to explain the technical aspects of the current release of the CDPOP program. CDPOP v1.0 is a major extension of the CDPOP program (Landguth and Cushman 2010). CDPOP is an individual-based program that simulates the influences of landscape structure on emergence of spatial patterns in population genetic data as functions of individual-...

Guidance from the Graphical User Interface (GUI) Experience: What GUI Teaches about Technology Access.

ERIC Educational Resources Information Center

National Council on Disability, Washington, DC.

This report investigates the use of the graphical user interface (GUI) in computer programs, the problems it creates for individuals with visual impairments or blindness, and advocacy efforts concerning this issue, which have been targeted primarily at Microsoft, producer of Windows. The report highlights the concerns of individuals with visual…

Using Unix system auditing for detecting network intrusions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christensen, M.J.

1993-03-01

Intrusion Detection Systems (IDSs) are designed to detect actions of individuals who use computer resources without authorization as well as legitimate users who exceed their privileges. This paper describes a novel approach to IDS research, namely a decision aiding approach to intrusion detection. The introduction of a decision tree represents the logical steps necessary to distinguish and identify different types of attacks. This tool, the Intrusion Decision Aiding Tool (IDAT), utilizes IDS-based attack models and standard Unix audit data. Since attacks have certain characteristics and are based on already developed signature attack models, experienced and knowledgeable Unix system administrators knowmore » what to look for in system audit logs to determine if a system has been attacked. Others, however, are usually less able to recognize common signatures of unauthorized access. Users can traverse the tree using available audit data displayed by IDAT and general knowledge they possess to reach a conclusion regarding suspicious activity. IDAT is an easy-to-use window based application that gathers, analyzes, and displays pertinent system data according to Unix attack characteristics. IDAT offers a more practical approach and allows the user to make an informed decision regarding suspicious activity.« less

The Simple Rules of Social Contagion

PubMed Central

Hodas, Nathan O.; Lerman, Kristina

2014-01-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior. PMID:24614301

Food abundance, prey morphology, and diet specialization influence individual sea otter tool use

USGS Publications Warehouse

Fujii, Jessica A.; Ralls, Katherine; Tinker, M. Tim

2017-01-01

Sea otters are well-known tool users, employing objects such as rocks or shells to break open invertebrate prey. We used a series of generalized linear mixed effect models to examine observational data on prey capture and tool use from 211 tagged individuals from 5 geographically defined study areas throughout the sea otter’s range in California. Our best supported model was able to explain 75% of the variation in the frequency of tool use by individual sea otters with only ecological and demographic variables. In one study area, where sea otter food resources were abundant, all individuals had similar diets focusing on preferred prey items and used tools at low to moderate frequencies (4–38% of prey captures). In the remaining areas, where sea otters were food-limited, individuals specialized on different subsets of the available prey and had a wider range of average tool-use frequency (0–98% of prey captures). The prevalence of difficult-to-access prey in individual diets was a major predictor of tool use and increased the likelihood of using tools on prey that were not difficult to access as well. Age, sex, and feeding habitat also contributed to the probability of tool use but to a smaller extent. We developed a conceptual model illustrating how food abundance, the prevalence of difficult-to-access prey, and individual diet specialization interacted to determine the likelihood that individual sea otters would use tools and considered the model’s relevance to other tool-using species.

Speech intelligibility and subjective benefit in single-sided deaf adults after cochlear implantation.

PubMed

Finke, Mareike; Strauß-Schier, Angelika; Kludt, Eugen; Büchner, Andreas; Illg, Angelika

2017-05-01

Treatment with cochlear implants (CIs) in single-sided deaf individuals started less than a decade ago. CIs can successfully reduce incapacitating tinnitus on the deaf ear and allow, so some extent, the restoration of binaural hearing. Until now, systematic evaluations of subjective CI benefit in post-lingually single-sided deaf individuals and analyses of speech intelligibility outcome for the CI in isolation have been lacking. For the prospective part of this study, the Bern Benefit in Single-Sided Deafness Questionnaire (BBSS) was administered to 48 single-sided deaf CI users to evaluate the subjectively perceived CI benefit across different listening situations. In the retrospective part, speech intelligibility outcome with the CI up to 12 month post-activation was compared between 100 single-sided deaf CI users and 125 bilaterally implanted CI users (2nd implant). The positive median ratings in the BBSS differed significantly from zero for all items suggesting that most individuals with single-sided deafness rate their CI as beneficial across listening situations. The speech perception scores in quiet and noise improved significantly over time in both groups of CI users. Speech intelligibility with the CI in isolation was significantly better in bilaterally implanted CI users (2nd implant) compared to the scores obtained from single-sided deaf CI users. Our results indicate that CI users with single-sided deafness can reach open set speech understanding with their CI in isolation, encouraging the extension of the CI indication to individuals with normal hearing on the contralateral ear. Compared to the performance reached with bilateral CI users' second implant, speech reception threshold are lower, indicating an aural preference and dominance of the normal hearing ear. The results from the BBSS propose good satisfaction with the CI across several listening situations. Copyright © 2017 Elsevier B.V. All rights reserved.

Web-Based Model Visualization Tools to Aid in Model Optimization and Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Alder, J.; van Griensven, A.; Meixner, T.

2003-12-01

Individuals applying hydrologic models have a need for a quick easy to use visualization tools to permit them to assess and understand model performance. We present here the Interactive Hydrologic Modeling (IHM) visualization toolbox. The IHM utilizes high-speed Internet access, the portability of the web and the increasing power of modern computers to provide an online toolbox for quick and easy model result visualization. This visualization interface allows for the interpretation and analysis of Monte-Carlo and batch model simulation results. Often times a given project will generate several thousands or even hundreds of thousands simulations. This large number of simulations creates a challenge for post-simulation analysis. IHM's goal is to try to solve this problem by loading all of the data into a database with a web interface that can dynamically generate graphs for the user according to their needs. IHM currently supports: a global samples statistics table (e.g. sum of squares error, sum of absolute differences etc.), top ten simulations table and graphs, graphs of an individual simulation using time step data, objective based dotty plots, threshold based parameter cumulative density function graphs (as used in the regional sensitivity analysis of Spear and Hornberger) and 2D error surface graphs of the parameter space. IHM is ideal for the simplest bucket model to the largest set of Monte-Carlo model simulations with a multi-dimensional parameter and model output space. By using a web interface, IHM offers the user complete flexibility in the sense that they can be anywhere in the world using any operating system. IHM can be a time saving and money saving alternative to spending time producing graphs or conducting analysis that may not be informative or being forced to purchase or use expensive and proprietary software. IHM is a simple, free, method of interpreting and analyzing batch model results, and is suitable for novice to expert hydrologic modelers.

Socialising Health Burden Through Different Network Topologies: A Simulation Study.

PubMed

Peacock, Adrian; Cheung, Anthony; Kim, Peter; Poon, Simon K

2017-01-01

An aging population and the expectation of premium quality health services combined with the increasing economic burden of the healthcare system requires a paradigm shift toward patient oriented healthcare. The guardian angel theory described by Szolovits [1] explores the notion of enlisting patients as primary providers of information and motivation to patients with similar clinical history through social connections. In this study, an agent based model was developed to simulate to explore how individuals are affected through their levels of intrinsic positivity. Ring, point-to-point (paired buddy), and random networks were modelled, with individuals able to send messages to each other given their levels of variables positivity and motivation. Of the 3 modelled networks it is apparent that the ring network provides the most equal, collective improvement in positivity and motivation for all users. Further study into other network topologies should be undertaken in the future.

Co-production of Health enabled by next generation personal health systems.

PubMed

Boye, Niels

2012-01-01

This paper describes the theoretical principles for the establishment of a parallel and complementary modality of healthcare delivery - named Coproduction of Health (CpH). This service-model activates digital data, information, and knowledge about health, healthy choices, and the individuals' health-state and computes through personalized models context-aware communication and advice. "Lightweight technologies" (smartphones, tablets, application stores) would serve as the technology close to the end-users (citizens, patients, clients, customers), connecting them with "big data" in conventionally and non-conventionally organized data repositories. The CpH modality aims at providing synergies between professional healthcare, selfcare, informal care and provides data-fusion from several sources such as health characteristics of consumer goods, from sensors, actuators, and health related data-repositories, and turns this into "health added value" for the individual. A theoretical business model respecting healthcare values, ethics, and legal foundation is also sketched out.

Scientific and conceptual flaws of coercive treatment models in addiction.

PubMed

Uusitalo, Susanne; van der Eijk, Yvette

2016-01-01

In conceptual debates on addiction, neurobiological research has been used to support the idea that addicted drug users lack control over their addiction-related actions. In some interpretations, this has led to coercive treatment models, in which, the purpose is to 'restore' control. However, neurobiological studies that go beyond what is typically presented in conceptual debates paint a different story. In particular, they indicate that though addiction has neurobiological manifestations that make the addictive behaviour difficult to control, it is possible for individuals to reverse these manifestations through their own efforts. Thus, addicted individuals should not be considered incapable of making choices voluntarily, simply on the basis that addiction has neurobiological manifestations, and coercive treatment models of addiction should be reconsidered in this respect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

PubMed

Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

2016-01-01

We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

Use of Inverse Reinforcement Learning for Identity Prediction

NASA Technical Reports Server (NTRS)

Hayes, Roy; Bao, Jonathan; Beling, Peter; Horowitz, Barry

2011-01-01

We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.

US adult tobacco users' absolute harm perceptions of traditional and alternative tobacco products, information-seeking behaviors, and (mis)beliefs about chemicals in tobacco products.

PubMed

Bernat, Jennifer K; Ferrer, Rebecca A; Margolis, Katherine A; Blake, Kelly D

2017-08-01

Harm perceptions about tobacco products may influence initiation, continued use, and cessation efforts. We assessed associations between adult traditional tobacco product use and absolute harm perceptions of traditional and alternative tobacco products. We also described the topics individuals looked for during their last search for information, their beliefs about chemicals in cigarettes/cigarette smoke, and how both relate to harm perceptions. We ran multivariable models with jackknife replicate weights to analyze data from the 2015 administration of the National Cancer Institute's Health Information National Trends Survey (N=3376). Compared to never users, individuals reported lower perceived levels of harm for products they use. Among current tobacco users, ethnicity, thinking about chemicals in tobacco, and information-seeking were all factors associated with tobacco product harm perceptions. In the full sample, some respondents reported searching for information about health effects and cessation and held misperceptions about the source of chemicals in tobacco. This study fills a gap in the literature by assessing the absolute harm perceptions of a variety of traditional and alternative tobacco products. Harm perceptions vary among tobacco products, and the relationship among tobacco use, information seeking, thoughts about chemicals in tobacco products, and harm perceptions is complex. Data suggest that some individuals search for information about health effects and cessation and hold misperceptions about chemicals in tobacco products. Future inquiry could seek to understand the mechanisms that contribute to forming harm perceptions and beliefs about chemicals in tobacco products. Published by Elsevier Ltd.

The dynamics of injection drug users' personal networks and HIV risk behaviors.

PubMed

Costenbader, Elizabeth C; Astone, Nan M; Latkin, Carl A

2006-07-01

While studies of the social networks of injection drug users (IDUs) have provided insight into how the structures of interpersonal relationships among IDUs affect HIV risk behaviors, the majority of these studies have been cross-sectional. The present study examined the dynamics of IDUs' social networks and HIV risk behaviors over time. Using data from a longitudinal HIV-intervention study conducted in Baltimore, MD, this study assessed changes in the composition of the personal networks of 409 IDUs. We used a multi-nomial logistic regression analysis to assess the association between changes in network composition and simultaneous changes in levels of injection HIV risk behaviors. Using the regression parameters generated by the multi-nomial model, we estimated the predicted probability of being in each of four HIV risk behavior change groups. Compared to the base case, individuals who reported an entirely new set of drug-using network contacts at follow-up were more than three times as likely to be in the increasing risk group. In contrast, reporting all new non-drug-using contacts at follow-up increased the likelihood of being in the stable low-risk group by almost 50% and decreased the probability of being in the consistently high-risk group by more than 70%. The findings from this study show that, over and above IDUs' baseline characteristics, changes in their personal networks are associated with changes in individuals' risky injection behaviors. They also suggest that interventions aimed at reducing HIV risk among IDUs might benefit from increasing IDUs' social contacts with individuals who are not drug users.

Development and Feasibility Testing of a Smartphone Intervention to Improve Adherence to Antipsychotic Medications

PubMed Central

Kreyenbuhl, Julie; Record, Elizabeth J.; Himelhoch, Seth; Charlotte, Melanie; Palmer-Bacon, Jessica; Dixon, Lisa B.; Medoff, Deborah R.; Li, Lan

2017-01-01

Approximately 60% of individuals with schizophrenia do not take their antipsychotic medications as prescribed, and nonadherence is associated with exacerbation of psychotic symptoms, increased hospital and emergency room use, and increased healthcare costs. Behavioral-tailoring strategies that incorporate medication taking into the daily routine and use environmental supports have shown promise as adherence-enhancing interventions. Informed by the Information-Motivation-Behavioral (IMB) Skills Model and using the iterative process of user-centered design, we collaborated with individuals with schizophrenia and psychiatrists to develop an interactive smartphone application and web-based clinician interface, MedActive, for improving adherence to oral antipsychotic treatment. MedActive facilitates the active involvement of individuals with schizophrenia in managing their antipsychotic medication regimen by providing automated reminders for medication administration and tailored motivational feedback to encourage adherence, and by displaying user-friendly results of daily ecological momentary assessments (EMAs) of medication adherence, positive psychotic symptoms, and medication side effects for individuals and their psychiatrists. In a 2-week open trial completed by 7 individuals with schizophrenia and their psychiatrists, MedActive was determined to be both feasible and acceptable, with patient participants responding to 80% of all scheduled EMAs and providing positive evaluations of their use of the application. Psychiatrist participants were interested in viewing the information provided on the MedActive clinician interface, but cited practical barriers to regularly accessing it and integrating into their daily practice. PMID:27454213

GenCade Version 1 Model Theory and User’s Guide

DTIC Science & Technology

2012-12-01

summer, severe waves associated with extratropical storms frequent during winter and spring, and severe waves associated with tropical storms during...that the majority of waves are from the southeast and the more severe waves associated with extratropical storms are from the east- southeast. This...decades to centuries. However, these tools should also resolve processes that occur at the scale of individual storms and tidal cycles to calculate

Technology and its role in rehabilitation for people with cognitive-communication disability following a traumatic brain injury (TBI).

PubMed

Brunner, Melissa; Hemsley, Bronwyn; Togher, Leanne; Palmer, Stuart

2017-01-01

To review the literature on communication technologies in rehabilitation for people with a traumatic brain injury (TBI), and: (a) determine its application to cognitive-communicative rehabilitation, and b) develop a model to guide communication technology use with people after TBI. This integrative literature review of communication technology in TBI rehabilitation and cognitive-communication involved searching nine scientific databases and included 95 studies. Three major types of communication technologies (assistive technology, augmentative and alternative communication technology, and information communication technology) and multiple factors relating to use of technology by or with people after TBI were categorized according to: (i) individual needs, motivations and goals; (ii) individual impairments, activities, participation and environmental factors; and (iii) technologies. While there is substantial research relating to communication technologies and cognitive rehabilitation after TBI, little relates specifically to cognitive-communication rehabilitation. Further investigation is needed into the experiences and views of people with TBI who use communication technologies, to provide the 'user' perspective and influence user-centred design. Research is necessary to investigate the training interventions that address factors fundamental for success, and any impact on communication. The proposed model provides an evidence-based framework for incorporating technology into speech pathology clinical practice and research.

Analysis of user cost and service trade-offs in transit and paratransit services

DOE Office of Scientific and Technical Information (OSTI.GOV)

Louviere, J.; Kocur, G.

1979-08-01

The Xenia Model Transit Service served as a test of several alternative transit services operated in a small city setting. Research was designed to test a new method for assessing user tradeoffs in costs and service based on attitudinal methods. Termed direct response assessment, the methods were developed in psychology and have been extended to application in utility assessment. A tradeoff survey was administered as part of a home interview survey. Data from the tradeoff survey were used to develop separate equations for each sample respondent to explain and describe their tradeoffs over transit fare, travel time, walk distance, typemore » of service, and headway. An aggregate equation was also developed, assuming that all respondents shared common tradeoffs. These equations were employed to retrospectively predict changes in transit system patronage since system inception in 1974. Both sets of models performed well, producing forecasts that were in the same direction and range of experience, although magnitudes were somewhat different. Coefficients of the individual tradeoff equations were then analyzed to see if they could be predicted on the basis of interpersonal characteristics of the respondents. Results indicated that differences in coefficients could be attributed to some differences in individuals such as income and auto ownership. Overall results were promising for policy evaluation and forecasting.« less

Anthropometry and Biomechanics Facility Presentation to Open EVA Research Forum

NASA Technical Reports Server (NTRS)

Rajulu, Sudhakar

2017-01-01

NASA is required to accommodate individuals who fall within a 1st to 99th percentile range on a variety of critical dimensions. The hardware the crew interacts with must therefore be designed and verified to allow these selected individuals to complete critical mission tasks safely and at an optimal performance level. Until now, designers have been provided simpler univariate critical dimensional analyses. The multivariate characteristics of intra-individual and inter-individual size variation must be accounted for, since an individual who is 1st percentile in one body dimension will not be 1st percentile in all other dimensions. A more simplistic approach, assuming every measurement of an individual will fall within the same percentile range, can lead to a model that does not represent realistic members of the population. In other words, there is no '1st percentile female' or '99th percentile male', and designing for these unrealistic body types can lead to hardware issues down the road. Furthermore, due to budget considerations, designers are normally limited to providing only 1 size of a prototype suit, thus requiring other possible means to ensure that a given suit architecture would yield the necessary suit sizes to accommodate the entire user population. Fortunately, modeling tools can be used to more accurately model the types of human body sizes and shapes that will be encountered in a population. Anthropometry toolkits have been designed with a variety of capabilities, including grouping the population into clusters based on critical dimensions, providing percentile information given test subject measurements, and listing measurement ranges for critical dimensions in the 1st-99th percentile range. These toolkits can be combined with full body laser scans to allow designers to build human models that better represent the astronaut population. More recently, some rescaling and reposing capabilities have been developed, to allow reshaping of these static laser scans in more representative postures, such as an abducted shoulder. All of the hardware designed for use with the crew must be sized to accommodate the user population, but the interaction between subject size and hardware fit is complicated with multi-component, complex systems like a space suit. Again, prototype suits are normally only provided in a limited size range, and suited testing is an expensive endeavor; both of these factors limit the number and size of people who can be used to benchmark a spacesuit. However, modeling tools for assessing suit-human interaction can allow potential issues to be modeled and visualized. These types of modeling tools can be used for analysis of a larger combination of anthropometries and hardware types than could feasibly be done with actual human subjects and physical mockups.

flexCloud: Deployment of the FLEXPART Atmospheric Transport Model as a Cloud SaaS Environment

NASA Astrophysics Data System (ADS)

Morton, Don; Arnold, Dèlia

2014-05-01

FLEXPART (FLEXible PARTicle dispersion model) is a Lagrangian transport and dispersion model used by a growing international community. We have used it to simulate and forecast the atmospheric transport of wildfire smoke, volcanic ash and radionuclides. Additionally, FLEXPART may be run in backwards mode to provide information for the determination of emission sources such as nuclear emissions and greenhouse gases. This open source software is distributed in source code form, and has several compiler and library dependencies that users need to address. Although well-documented, getting it compiled, set up, running, and post-processed is often tedious, making it difficult for the inexperienced user. Our interest is in moving scientific modeling and simulation activities from site-specific clusters and supercomputers to a cloud model as a service paradigm. Choosing FLEXPART for our prototyping, our vision is to construct customised IaaS images containing fully-compiled and configured FLEXPART codes, including pre-processing, execution and postprocessing components. In addition, with the inclusion of a small web server in the image, we introduce a web-accessible graphical user interface that drives the system. A further initiative being pursued is the deployment of multiple, simultaneous FLEXPART ensembles in the cloud. A single front-end web interface is used to define the ensemble members, and separate cloud instances are launched, on-demand, to run the individual models and to conglomerate the outputs into a unified display. The outcome of this work is a Software as a Service (Saas) deployment whereby the details of the underlying modeling systems are hidden, allowing modelers to perform their science activities without the burden of considering implementation details.

Mobile agent location in distributed environments

NASA Astrophysics Data System (ADS)

Fountoukis, S. G.; Argyropoulos, I. P.

2012-12-01

An agent is a small program acting on behalf of a user or an application which plays the role of a user. Artificial intelligence can be encapsulated in agents so that they can be capable of both behaving autonomously and showing an elementary decision ability regarding movement and some specific actions. Therefore they are often called autonomous mobile agents. In a distributed system, they can move themselves from one processing node to another through the interconnecting network infrastructure. Their purpose is to collect useful information and to carry it back to their user. Also, agents are used to start, monitor and stop processes running on the individual interconnected processing nodes of computer cluster systems. An agent has a unique id to discriminate itself from other agents and a current position. The position can be expressed as the address of the processing node which currently hosts the agent. Very often, it is necessary for a user, a processing node or another agent to know the current position of an agent in a distributed system. Several procedures and algorithms have been proposed for the purpose of position location of mobile agents. The most basic of all employs a fixed computing node, which acts as agent position repository, receiving messages from all the moving agents and keeping records of their current positions. The fixed node, responds to position queries and informs users, other nodes and other agents about the position of an agent. Herein, a model is proposed that considers pairs and triples of agents instead of single ones. A location method, which is investigated in this paper, attempts to exploit this model.

Service user governors in mental health foundation trusts: accountability or business as usual?

PubMed

MacDonald, Dee; Barnes, Marian; Crawford, Mike; Omeni, Edward; Wilson, Aaron; Rose, Diana

2015-12-01

National Health Foundation Trusts present opportunities for individual mental health service users to be active in the governance of trusts. This is one of a range of mechanisms for patient and public involvement and one which promotes an individual rather than collective approach to involvement. Within the context of a broader study of the impact of service user involvement in mental health services, the objective of this article was to explore the experience of service user governors in foundation trusts and their capacity to hold boards to account. The Council of Governors in three foundation trusts were observed for a year. Focus groups with service user governors were undertaken in each trust. Service users had different expectations and understandings of the role and approached it in different ways. Key themes that emerged concerned: the role of a governor, conduct and content of meetings, agenda setting, relationships and representation. The experiences of mental health service user governors need to be understood within the complex environment of patient and public involvement in general and of mental health service user involvement in particular. The dislocation of the service user governor role from other forms of service user activity and involvement result in confusion about how notions of holding a trust to account and representation of other service users can be addressed within a boundaried institutional environment. © 2014 John Wiley & Sons Ltd.

A 3-year study of high-cost users of health care.

PubMed

Wodchis, Walter P; Austin, Peter C; Henry, David A

2016-02-16

Characterizing high-cost users of health care resources is essential for the development of appropriate interventions to improve the management of these patients. We sought to determine the concentration of health care spending, characterize demographic characteristics and clinical diagnoses of high-cost users and examine the consistency of their health care consumption over time. We conducted a retrospective analysis of all residents of Ontario, Canada, who were eligible for publicly funded health care between 2009 and 2011. We estimated the total attributable government health care spending for every individual in all health care sectors. More than $30 billion in annual health expenditures, representing 75% of total government health care spending, was attributed to individual costs. One-third of high-cost users (individuals with the highest 5% of costs) in 2009 remained in this category in the subsequent 2 years. Most spending among high-cost users was for institutional care, in contrast to lower-cost users, among whom spending was predominantly for ambulatory care services. Costs were far more concentrated among children than among older adults. The most common reasons for hospital admissions among high-cost users were chronic diseases, infections, acute events and palliative care. Although high health care costs were concentrated in a small minority of the population, these related to a diverse set of patient health care needs and were incurred in a wide array of health care settings. Improving the sustainability of the health care system through better management of high-cost users will require different tactics for different high-cost populations. © 2016 Canadian Medical Association or its licensors.

Personalizing public health: your health avatar.

PubMed

Pereira, Chrystian; McNamara, Anusha; Sorge, Lindsay; Arya, Vibhuti

2013-01-01

To describe the creation of a health avatar, with the goals of providing patients with complete health information from various sources, establishing an interactive and customizable platform, empowering users to determine how the health information best fits or speaks to their personal needs, and providing perspective by comparing the health status of the individual with that of the individual's community. The Internet is rapidly becoming integrated into Americans' daily lives. According to the 2007 Health Information National Trends Study, 69% of U.S. adults had access to the Internet and 23% reported using a social networking site. The impact of social media has further grown, and an estimated 50% of adults in America have a profile on social media. The potential for using cyber communities to improve health messaging is great. Several health care organizations have implemented the use of social media in a variety of ways to varying degrees of success. We propose a platform that automatically gathers information and reflects the health status of an individual back to the user. An avatar, which is a representation of a user, could be created and assigned characteristics that allow users to appreciate their health status. The health avatar platform also would allow users to compare their personal status with that of their community. The overall goal is to engage and then motivate users to improve their overall health status. Medicine must acknowledge the evolving relationships that the next generation of patients will have with technology. The health avatar is a platform that incorporates a connection with the health system through electronic medical records and connects individuals to the greater community.

Psychosocial impact of wheelchair usage on individuals with mobility disability in Ibadan, Nigeria.

PubMed

Hamzat, T K; Olaleye, O A; Agbomeji, O T

2015-03-01

Wheelchairs provide individuals with mobility impairments opportunity for independent living within their environment. However, using this device may have psychosocial impacts with consequent influence on the quality of life of the users. The psychosocial impact of wheelchair usage among individuals with mobility disability in a Nigerian community was investigated. The study is a descriptive cross-sectional survey. People who have been independent users of wheelchair for a minimum of six months prior to the study were recruited from centres for people with disabilities in Ibadan, Nigeria into the study. A profile of their use of the device was documented and the psychosocial impact of wheelchair was assessed using the Psychosocial Impact ofAssistive Devices Scale. Data were analysed using descriptive and inferential statistics at p = 0.05. Sixty consenting individuals with mobility disability participated in this study. Their mean age was 38.7 +/- 14.1 years. Majority (90%) were manual wheelchair users and two-thirds (63.3%) had been using the wheelchair for < or = five years. Approximately a third of the participants use their wheelchairs occasionally. There was no significant difference (p=0.26) in the psychosocial impact of wheelchair usage between male and female users. The psychosocial impact of wheelchair was similar between male and female users. However, the impact was higher on the self-esteem of male than female users and lower on their competence than that of their female counterparts. This may be due to stigmatization or a culturally-related unwillingness of men in our environment to be dependent on others.

A kinesthetic washout filter for force-feedback rendering.

PubMed

Danieau, Fabien; Lecuyer, Anatole; Guillotel, Philippe; Fleureau, Julien; Mollet, Nicolas; Christie, Marc

2015-01-01

Today haptic feedback can be designed and associated to audiovisual content (haptic-audiovisuals or HAV). Although there are multiple means to create individual haptic effects, the issue of how to properly adapt such effects on force-feedback devices has not been addressed and is mostly a manual endeavor. We propose a new approach for the haptic rendering of HAV, based on a washout filter for force-feedback devices. A body model and an inverse kinematics algorithm simulate the user's kinesthetic perception. Then, the haptic rendering is adapted in order to handle transitions between haptic effects and to optimize the amplitude of effects regarding the device capabilities. Results of a user study show that this new haptic rendering can successfully improve the HAV experience.

New security infrastructure model for distributed computing systems

NASA Astrophysics Data System (ADS)

Dubenskaya, J.; Kryukov, A.; Demichev, A.; Prikhodko, N.

2016-02-01

At the paper we propose a new approach to setting up a user-friendly and yet secure authentication and authorization procedure in a distributed computing system. The security concept of the most heterogeneous distributed computing systems is based on the public key infrastructure along with proxy certificates which are used for rights delegation. In practice a contradiction between the limited lifetime of the proxy certificates and the unpredictable time of the request processing is a big issue for the end users of the system. We propose to use unlimited in time hashes which are individual for each request instead of proxy certificate. Our approach allows to avoid using of the proxy certificates. Thus the security infrastructure of distributed computing system becomes easier for development, support and use.

Comparing architectural solutions of IPT application SDKs utilizing H.323 and SIP

NASA Astrophysics Data System (ADS)

Keskinarkaus, Anja; Korhonen, Jani; Ohtonen, Timo; Kilpelanaho, Vesa; Koskinen, Esa; Sauvola, Jaakko J.

2001-07-01

This paper presents two approaches to efficient service development for Internet Telephony. In first approach we consider services ranging from core call signaling features and media control as stated in ITU-T's H.323 to end user services that supports user interaction. The second approach supports IETF's SIP protocol. We compare these from differing architectural perspectives, economy of network and terminal development, and propose efficient architecture models for both protocols. In their design, the main criteria were component independence, lightweight operation and portability in heterogeneous end-to-end environments. In proposed architecture, the vertical division of call signaling and streaming media control logic allows for using the components either individually or combined, depending on the level of functionality required by an application.

Impulsivity, attention, memory, and decision-making among adolescent marijuana users.

PubMed

Dougherty, Donald M; Mathias, Charles W; Dawes, Michael A; Furr, R Michael; Charles, Nora E; Liguori, Anthony; Shannon, Erin E; Acheson, Ashley

2013-03-01

Marijuana is a popular drug of abuse among adolescents, and they may be uniquely vulnerable to resulting cognitive and behavioral impairments. Previous studies have found impairments among adolescent marijuana users. However, the majority of this research has examined measures individually rather than multiple domains in a single cohesive analysis. This study used a logistic regression model that combines performance on a range of tasks to identify which measures were most altered among adolescent marijuana users. The purpose of this research was to determine unique associations between adolescent marijuana use and performances on multiple cognitive and behavioral domains (attention, memory, decision-making, and impulsivity) in 14- to 17-year-olds while simultaneously controlling for performances across the measures to determine which measures most strongly distinguish marijuana users from nonusers. Marijuana-using adolescents (n = 45) and controls (n = 48) were tested. Logistic regression analyses were conducted to test for: (1) differences between marijuana users and nonusers on each measure, (2) associations between marijuana use and each measure after controlling for the other measures, and (3) the degree to which (1) and (2) together elucidated differences among marijuana users and nonusers. Of all the cognitive and behavioral domains tested, impaired short-term recall memory and consequence sensitivity impulsivity were associated with marijuana use after controlling for performances across all measures. This study extends previous findings by identifying cognitive and behavioral impairments most strongly associated with adolescent marijuana users. These specific deficits are potential targets of intervention for this at-risk population.

Impact of music on the quality of life of cochlear implant users: a focus group study.

PubMed

Dritsakis, Giorgos; van Besouw, Rachel M; O' Meara, Aoife

2017-07-01

To study the aspects of the quality of life (QoL) on which music has an impact in adult cochlear implant (CI) users. Thirty adult CI users aged between 18 and 81 years old with a wide range of patient characteristics and musical backgrounds participated in the study. Six focus group discussions about music in everyday life were conducted and data were analysed using template analysis based on the QoL model of the World Health Organisation Quality of Life BREF questionnaire. A theoretical framework of the impact of music on the QoL was developed. Music was reported to contribute to many aspects of physical, psychological, and social well-being in adult CI users. These positive effects of music on QoL were similar to what has been reported in the literature for normal-hearing adults. However, difficulties in music perception and enjoyment were found to have a negative impact on CI users' QoL, especially by causing unpleasant feelings and limited participation in music-related or routine daily activities. These findings suggest that an improvement in music experiences of CI users may lead to improvements in QoL and therefore support the need for music rehabilitation. However, the relative importance of music overall and of specific aspects of music for each individual should be measured for an accurate assessment of the impact of music on the QoL of CI users.

Development of a multi-behavioral mHealth app for women smokers

PubMed Central

Armin, Julie; Johnson, Thienne; Hingle, Melanie; Giacobbi, Peter; Gordon, Judith S.

2017-01-01

Objective This paper describes the development of the See Me Smoke-Free™ (SMSF) mobile health application, which uses guided imagery to support women in smoking cessation, eating a healthy diet, and increasing physical activity. Materials and Methods Focus group discussions, with member checks, were conducted to refine the intervention content and app user interface. Data related to the context of app deployment were collected via user testing sessions and internal quality control testing, which identified and addressed functionality issues, content problems, and bugs. Results Interactive app features include playback of guided imagery audio files, notification pop-ups, award-sharing on social media, a tracking calendar, content resources, and direct call to the local tobacco quitline. Focus groups helped design the user interface, and identified several themes for incorporation into app content, including positivity, the rewards of smoking cessation, and the integrated benefits maintaining a healthy lifestyle. User testing improved app functionality and usability on many Android phone models. Discussion Changes to the app content and function were made iteratively by the development team as a result of focus group and user testing. Despite extensive internal and user testing, unanticipated data collection and reporting issues emerged during deployment due to the variety of Android software and hardware, but also due to individual phone settings and use. Conclusion Focus group interviews helped thematically frame the intervention and maximize user engagement. Testing caught many bugs and usability concerns, but missed some of the data transmission problems encountered during deployment. PMID:28121240

Trajectories of Marijuana Use from Adolescence to Adulthood as Predictors of Unemployment Status in the Early Forties

PubMed Central

Zhang, Chenshu; Brook, Judith S.; Leukefeld, Carl G.; Brook, David W.

2016-01-01

Objectives To study the degree to which individuals in different trajectories of marijuana use are similar or different in terms of unemployment status at mean age 43. Methods We gathered longitudinal data on a prospective cohort taken from a community sample (N = 548). Forty nine percent of the original participants were females. Over 90% of the participants were white. The participants were followed from adolescence to early midlife. The mean ages of participants at the follow-up interviews were 14.1, 16.3, 22.3, 27.0, 31.9, 36.6, and 43.0, respectively. We used the growth mixture modeling (GMM) approach to identify the trajectories of marijuana use over a 29 year period. Results Five trajectories of marijuana use were identified: chronic users/decreasers (8.3%), quitters (18.6%), increasing users (7.3%), chronic occasional users (25.6%), and nonusers/experimenters (40.2%). Compared with nonusers/experimenters, chronic users/decreasers had a significantly higher likelihood of unemployment at mean age 43 (Adjusted Odds Ratio =3.51, 95% Confidence Interval = 1.13 – 10.91), even after controlling for the covariates. Conclusions and Scientific Significance The results of the associations between the distinct trajectories of marijuana use and unemployment in early midlife indicate that it is important to develop intervention programs targeting chronic marijuana use as well as unemployment in individuals at this stage of development. Results from this study should encourage clinicians, teachers, and parents to assess and treat chronic marijuana use in adolescents. PMID:26991779

Potential Field Modeling at Global to Prospect Scales - Adding Value to the Geological, Seismic, Gravity, Magnetic and Rock Property Datasets of Australia

NASA Astrophysics Data System (ADS)

Lane, R. J. L.

2015-12-01

At Geoscience Australia, we are upgrading our gravity and magnetic modeling tools to provide new insights into the composition, properties, and structure of the subsurface. The scale of the investigations varies from the size of tectonic plates to the size of a mineral prospect. To accurately model potential field data at all of these scales, we require modeling software that can operate in both spherical and Cartesian coordinate frameworks. The models are in the form of a mesh, with spherical prismatic (tesseroid) elements for spherical coordinate models of large volumes, and rectangular prisms for smaller volumes evaluated in a Cartesian coordinate framework. The software can compute the forward response of supplied rock property models and can perform inversions using constraints that vary from weak generic smoothness through to very specific reference models compiled from various types of "hard facts" (i.e., surface mapping, drilling information, crustal seismic interpretations). To operate efficiently, the software is being specifically developed to make use of the resources of the National Computational Infrastructure (NCI) at the Australian National University (ANU). The development of these tools is been carried out in collaboration with researchers from the Colorado School of Mines (CSM) and the China University of Geosciences (CUG) and is at the stage of advanced testing. The creation of individual 3D geological models will provide immediate insights. Users will also be able to combine models, either by stitching them together or by nesting smaller and more detailed models within a larger model. Comparison of the potential field response of a composite model with the observed fields will give users a sense of how comprehensively these models account for the observations. Users will also be able to model the residual fields (i.e., the observed minus calculated response) to discover features that are not represented in the input composite model.

On the control of brain-computer interfaces by users with cerebral palsy.

PubMed

Daly, Ian; Billinger, Martin; Laparra-Hernández, José; Aloise, Fabio; García, Mariano Lloria; Faller, Josef; Scherer, Reinhold; Müller-Putz, Gernot

2013-09-01

Brain-computer interfaces (BCIs) have been proposed as a potential assistive device for individuals with cerebral palsy (CP) to assist with their communication needs. However, it is unclear how well-suited BCIs are to individuals with CP. Therefore, this study aims to investigate to what extent these users are able to gain control of BCIs. This study is conducted with 14 individuals with CP attempting to control two standard online BCIs (1) based upon sensorimotor rhythm modulations, and (2) based upon steady state visual evoked potentials. Of the 14 users, 8 are able to use one or other of the BCIs, online, with a statistically significant level of accuracy, without prior training. Classification results are driven by neurophysiological activity and not seen to correlate with occurrences of artifacts. However, many of these users' accuracies, while statistically significant, would require either more training or more advanced methods before practical BCI control would be possible. The results indicate that BCIs may be controlled by individuals with CP but that many issues need to be overcome before practical application use may be achieved. This is the first study to assess the ability of a large group of different individuals with CP to gain control of an online BCI system. The results indicate that six users could control a sensorimotor rhythm BCI and three a steady state visual evoked potential BCI at statistically significant levels of accuracy (SMR accuracies; mean ± STD, 0.821 ± 0.116, SSVEP accuracies; 0.422 ± 0.069). Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A New Method to Retrieve the Data Requirements of the Remote Sensing Community – Exemplarily Demonstrated for Hyperspectral User Needs

PubMed Central

Nieke, Jens; Reusen, Ils

2007-01-01

User-driven requirements for remote sensing data are difficult to define, especially details on geometric, spectral and radiometric parameters. Even more difficult is a decent assessment of the required degrees of processing and corresponding data quality. It is therefore a real challenge to appropriately assess data costs and services to be provided. In 2006, the HYRESSA project was initiated within the framework 6 programme of the European Commission to analyze the user needs of the hyperspectral remote sensing community. Special focus was given to finding an answer to the key question, “What are the individual user requirements for hyperspectral imagery and its related data products?”. A Value-Benefit Analysis (VBA) was performed to retrieve user needs and address open items accordingly. The VBA is an established tool for systematic problem solving by supporting the possibility of comparing competing projects or solutions. It enables evaluation on the basis of a multidimensional objective model and can be augmented with expert's preferences. After undergoing a VBA, the scaling method (e.g., Law of Comparative Judgment) was applied for achieving the desired ranking judgments. The result, which is the relative value of projects with respect to a well-defined main objective, can therefore be produced analytically using a VBA. A multidimensional objective model adhering to VBA methodology was established. Thereafter, end users and experts were requested to fill out a Questionnaire of User Needs (QUN) at the highest level of detail - the value indicator level. The end user was additionally requested to report personal preferences for his particular research field. In the end, results from the experts' evaluation and results from a sensor data survey can be compared in order to understand user needs and the drawbacks of existing data products. The investigation – focusing on the needs of the hyperspectral user community in Europe – showed that a VBA is a suitable method for analyzing the needs of hyperspectral data users and supporting the sensor/data specification-building process. The VBA has the advantage of being easy to handle, resulting in a comprehensive evaluation. The primary disadvantage is the large effort in realizing such an analysis because the level of detail is extremely high.