A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation.

PubMed

Yoon, Sung Hoon; Nam, Kyoung Won; Yook, Sunhyun; Cho, Baek Hwan; Jang, Dong Pyo; Hong, Sung Hwa; Kim, In Young

2017-03-01

In an effort to improve hearing aid users' satisfaction, recent studies on trainable hearing aids have attempted to implement one or two environmental factors into training. However, it would be more beneficial to train the device based on the owner's personal preferences in a more expanded environmental acoustic conditions. Our study aimed at developing a trainable hearing aid algorithm that can reflect the user's individual preferences in a more extensive environmental acoustic conditions (ambient sound level, listening situation, and degree of noise suppression) and evaluated the perceptual benefit of the proposed algorithm. Ten normal hearing subjects participated in this study. Each subjects trained the algorithm to their personal preference and the trained data was used to record test sounds in three different settings to be utilized to evaluate the perceptual benefit of the proposed algorithm by performing the Comparison Mean Opinion Score test. Statistical analysis revealed that of the 10 subjects, four showed significant differences in amplification constant settings between the noise-only and speech-in-noise situation ( P <0.05) and one subject also showed significant difference between the speech-only and speech-in-noise situation ( P <0.05). Additionally, every subject preferred different β settings for beamforming in all different input sound levels. The positive findings from this study suggested that the proposed algorithm has potential to improve hearing aid users' personal satisfaction under various ambient situations.

Evolutionary algorithms for multi-objective optimization: fuzzy preference aggregation and multisexual EAs

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.

2001-11-01

There are many approaches to solving multi-objective optimization problems using evolutionary algorithms. We need to select methods for representing and aggregating preferences, as well as choosing strategies for searching in multi-dimensional objective spaces. First we suggest the use of linguistic variables to represent preferences and the use of fuzzy rule systems to implement tradeoff aggregations. After a review of alternatives EA methods for multi-objective optimizations, we explore the use of multi-sexual genetic algorithms (MSGA). In using a MSGA, we need to modify certain parts of the GAs, namely the selection and crossover operations. The selection operator groups solutions according to their gender tag to prepare them for crossover. The crossover is modified by appending a gender tag at the end of the chromosome. We use single and double point crossovers. We determine the gender of the offspring by the amount of genetic material provided by each parent. The parent that contributed the most to the creation of a specific offspring determines the gender that the offspring will inherit. This is still a work in progress, and in the conclusion we examine many future extensions and experiments.

Extension of the firefly algorithm and preference rules for solving MINLP problems

NASA Astrophysics Data System (ADS)

Costa, M. Fernanda P.; Francisco, Rogério B.; Rocha, Ana Maria A. C.; Fernandes, Edite M. G. P.

2017-07-01

An extension of the firefly algorithm (FA) for solving mixed-integer nonlinear programming (MINLP) problems is presented. Although penalty functions are nowadays frequently used to handle integrality conditions and inequality and equality constraints, this paper proposes the implementation within the FA of a simple rounded-based heuristic and four preference rules to find and converge to MINLP feasible solutions. Preliminary numerical experiments are carried out to validate the proposed methodology.

Preferable adsorption of phosphate using lanthanum-incorporated porous zeolite: Characteristics and mechanism

NASA Astrophysics Data System (ADS)

He, Yinhai; Lin, Hai; Dong, Yingbo; Wang, Liang

2017-12-01

The adsorbent, where lanthanum oxide was incorporated onto porous zeolite (La-Z), of preferable adsorption towards phosphate was prepared by hydrothermal synthesis. Based on pH effect results, La-Z would effectively sequestrate phosphate over wider pH range of 3.0-7.0, alkaline conditions were unfavorable for phosphate. The adsorption of phosphate was not significantly influenced by ionic strength and by coexisting anions of chloride, nitrate and sulfate but bicarbonate showed slightly greater negative effects, indicating La-Z possessed highly selectivity to phosphate. Adsorption of phosphate could be well fitted by pseudo-second-order model and the process was mainly controlled by intra-particle diffusion. Equilibrium adsorption demonstrated that Langmuir model was more suitable than Freundlich model for description phosphate adsorption and the adsorption capacity was 17.2 mg P g-1, which exhibited 95% utilization of incorporated La. Over 95% phosphate was eliminated in real effluent treatment when the dose was 2 g L-1. The underlying mechanism for phosphate capture was probed with Zeta potential and X-ray photoelectron spectroscope analysis, and the formation of La-P inner-sphere complexation was testified to be the dominant pathway. All the results suggested that the porous zeolite-supported lanthanum oxide can serve as a promising adsorbent for phosphate removal in realistic application.

Simultaneously learning DNA motif along with its position and sequence rank preferences through expectation maximization algorithm.

PubMed

Zhang, ZhiZhuo; Chang, Cheng Wei; Hugo, Willy; Cheung, Edwin; Sung, Wing-Kin

2013-03-01

Although de novo motifs can be discovered through mining over-represented sequence patterns, this approach misses some real motifs and generates many false positives. To improve accuracy, one solution is to consider some additional binding features (i.e., position preference and sequence rank preference). This information is usually required from the user. This article presents a de novo motif discovery algorithm called SEME (sampling with expectation maximization for motif elicitation), which uses pure probabilistic mixture model to model the motif's binding features and uses expectation maximization (EM) algorithms to simultaneously learn the sequence motif, position, and sequence rank preferences without asking for any prior knowledge from the user. SEME is both efficient and accurate thanks to two important techniques: the variable motif length extension and importance sampling. Using 75 large-scale synthetic datasets, 32 metazoan compendium benchmark datasets, and 164 chromatin immunoprecipitation sequencing (ChIP-Seq) libraries, we demonstrated the superior performance of SEME over existing programs in finding transcription factor (TF) binding sites. SEME is further applied to a more difficult problem of finding the co-regulated TF (coTF) motifs in 15 ChIP-Seq libraries. It identified significantly more correct coTF motifs and, at the same time, predicted coTF motifs with better matching to the known motifs. Finally, we show that the learned position and sequence rank preferences of each coTF reveals potential interaction mechanisms between the primary TF and the coTF within these sites. Some of these findings were further validated by the ChIP-Seq experiments of the coTFs. The application is available online.

Investigating preferences for color-shape combinations with gaze driven optimization method based on evolutionary algorithms.

PubMed

Holmes, Tim; Zanker, Johannes M

2013-01-01

Studying aesthetic preference is notoriously difficult because it targets individual experience. Eye movements provide a rich source of behavioral measures that directly reflect subjective choice. To determine individual preferences for simple composition rules we here use fixation duration as the fitness measure in a Gaze Driven Evolutionary Algorithm (GDEA), which has been demonstrated as a tool to identify aesthetic preferences (Holmes and Zanker, 2012). In the present study, the GDEA was used to investigate the preferred combination of color and shape which have been promoted in the Bauhaus arts school. We used the same three shapes (square, circle, triangle) used by Kandinsky (1923), with the three color palette from the original experiment (A), an extended seven color palette (B), and eight different shape orientation (C). Participants were instructed to look for their preferred circle, triangle or square in displays with eight stimuli of different shapes, colors and rotations, in an attempt to test for a strong preference for red squares, yellow triangles and blue circles in such an unbiased experimental design and with an extended set of possible combinations. We Tested six participants extensively on the different conditions and found consistent preferences for color-shape combinations for individuals, but little evidence at the group level for clear color/shape preference consistent with Kandinsky's claims, apart from some weak link between yellow and triangles. Our findings suggest substantial inter-individual differences in the presence of stable individual associations of color and shapes, but also that these associations are robust within a single individual. These individual differences go some way toward challenging the claims of the universal preference for color/shape combinations proposed by Kandinsky, but also indicate that a much larger sample size would be needed to confidently reject that hypothesis. Moreover, these experiments highlight the

Freeing Space for NASA: Incorporating a Lossless Compression Algorithm into NASA's FOSS System

NASA Technical Reports Server (NTRS)

Fiechtner, Kaitlyn; Parker, Allen

2011-01-01

NASA's Fiber Optic Strain Sensing (FOSS) system can gather and store up to 1,536,000 bytes (1.46 megabytes) per second. Since the FOSS system typically acquires hours - or even days - of data, the system can gather hundreds of gigabytes of data for a given test event. To store such large quantities of data more effectively, NASA is modifying a Lempel-Ziv-Oberhumer (LZO) lossless data compression program to compress data as it is being acquired in real time. After proving that the algorithm is capable of compressing the data from the FOSS system, the LZO program will be modified and incorporated into the FOSS system. Implementing an LZO compression algorithm will instantly free up memory space without compromising any data obtained. With the availability of memory space, the FOSS system can be used more efficiently on test specimens, such as Unmanned Aerial Vehicles (UAVs) that can be in flight for days. By integrating the compression algorithm, the FOSS system can continue gathering data, even on longer flights.

A dynamic model of the marriage market-part 1: matching algorithm based on age preference and availability.

PubMed

Matthews, A P; Garenne, M L

2013-09-01

The matching algorithm in a dynamic marriage market model is described in this first of two companion papers. Iterative Proportional Fitting is used to find a marriage function (an age distribution of new marriages for both sexes), in a stable reference population, that is consistent with the one-sex age distributions of new marriages, and includes age preference. The one-sex age distributions (which are the marginals of the two-sex distribution) are based on the Picrate model, and age preference on a normal distribution, both of which may be adjusted by choice of parameter values. For a population that is perturbed from the reference state, the total number of new marriages is found as the harmonic mean of target totals for men and women obtained by applying reference population marriage rates to the perturbed population. The marriage function uses the age preference function, assumed to be the same for the reference and the perturbed populations, to distribute the total number of new marriages. The marriage function also has an availability factor that varies as the population changes with time, where availability depends on the supply of unmarried men and women. To simplify exposition, only first marriage is treated, and the algorithm is illustrated by application to Zambia. In the second paper, remarriage and dissolution are included. Copyright © 2013 Elsevier Inc. All rights reserved.

Automatic page layout using genetic algorithms for electronic albuming

NASA Astrophysics Data System (ADS)

Geigel, Joe; Loui, Alexander C. P.

2000-12-01

In this paper, we describe a flexible system for automatic page layout that makes use of genetic algorithms for albuming applications. The system is divided into two modules, a page creator module which is responsible for distributing images amongst various album pages, and an image placement module which positions images on individual pages. Final page layouts are specified in a textual form using XML for printing or viewing over the Internet. The system makes use of genetic algorithms, a class of search and optimization algorithms that are based on the concepts of biological evolution, for generating solutions with fitness based on graphic design preferences supplied by the user. The genetic page layout algorithm has been incorporated into a web-based prototype system for interactive page layout over the Internet. The prototype system is built using client-server architecture and is implemented in java. The system described in this paper has demonstrated the feasibility of using genetic algorithms for automated page layout in albuming and web-based imaging applications. We believe that the system adequately proves the validity of the concept, providing creative layouts in a reasonable number of iterations. By optimizing the layout parameters of the fitness function, we hope to further improve the quality of the final layout in terms of user preference and computation speed.

A discrete artificial bee colony algorithm incorporating differential evolution for the flow-shop scheduling problem with blocking

NASA Astrophysics Data System (ADS)

Han, Yu-Yan; Gong, Dunwei; Sun, Xiaoyan

2015-07-01

A flow-shop scheduling problem with blocking has important applications in a variety of industrial systems but is underrepresented in the research literature. In this study, a novel discrete artificial bee colony (ABC) algorithm is presented to solve the above scheduling problem with a makespan criterion by incorporating the ABC with differential evolution (DE). The proposed algorithm (DE-ABC) contains three key operators. One is related to the employed bee operator (i.e. adopting mutation and crossover operators of discrete DE to generate solutions with good quality); the second is concerned with the onlooker bee operator, which modifies the selected solutions using insert or swap operators based on the self-adaptive strategy; and the last is for the local search, that is, the insert-neighbourhood-based local search with a small probability is adopted to improve the algorithm's capability in exploitation. The performance of the proposed DE-ABC algorithm is empirically evaluated by applying it to well-known benchmark problems. The experimental results show that the proposed algorithm is superior to the compared algorithms in minimizing the makespan criterion.

Maximizing the nurses' preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Jafari, Hamed; Salmasi, Nasser

2015-09-01

The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.

Community detection using preference networks

NASA Astrophysics Data System (ADS)

Tasgin, Mursel; Bingol, Haluk O.

2018-04-01

Community detection is the task of identifying clusters or groups of nodes in a network where nodes within the same group are more connected with each other than with nodes in different groups. It has practical uses in identifying similar functions or roles of nodes in many biological, social and computer networks. With the availability of very large networks in recent years, performance and scalability of community detection algorithms become crucial, i.e. if time complexity of an algorithm is high, it cannot run on large networks. In this paper, we propose a new community detection algorithm, which has a local approach and is able to run on large networks. It has a simple and effective method; given a network, algorithm constructs a preference network of nodes where each node has a single outgoing edge showing its preferred node to be in the same community with. In such a preference network, each connected component is a community. Selection of the preferred node is performed using similarity based metrics of nodes. We use two alternatives for this purpose which can be calculated in 1-neighborhood of nodes, i.e. number of common neighbors of selector node and its neighbors and, the spread capability of neighbors around the selector node which is calculated by the gossip algorithm of Lind et.al. Our algorithm is tested on both computer generated LFR networks and real-life networks with ground-truth community structure. It can identify communities accurately in a fast way. It is local, scalable and suitable for distributed execution on large networks.

Successful Manipulation in Stable Marriage Model with Complete Preference Lists

NASA Astrophysics Data System (ADS)

Kobayashi, Hirotatsu; Matsui, Tomomi

This paper deals with a strategic issue in the stable marriage model with complete preference lists (i.e., a preference list of an agent is a permutation of all the members of the opposite sex). Given complete preference lists of n men over n women, and a marriage µ, we consider the problem for finding preference lists of n women over n men such that the men-proposing deferred acceptance algorithm (Gale-Shapley algorithm) adopted to the lists produces µ. We show a simple necessary and sufficient condition for the existence of a set of preference lists of women over men. Our condition directly gives an O(n2) time algorithm for finding a set of preference lists, if it exists.

Scenario-based stakeholder engagement: incorporating stakeholders preferences into coastal planning for climate change.

PubMed

Tompkins, Emma L; Few, Roger; Brown, Katrina

2008-09-01

Climate change poses many challenges for ecosystem and resource management. In particular, coastal planners are struggling to find ways to prepare for the potential impacts of future climate change while dealing with immediate pressures. Decisions on how to respond to future risks are complicated by the long time horizons and the uncertainty associated with the distribution of impacts. Existing coastal zone management approaches in the UK either do not adequately incorporate changing stakeholder preferences, or effectively ensure that stakeholders are aware of the trade-offs inherent in any coastal management decision. Using a novel method, scenario-based stakeholder engagement, which brings together stakeholder analysis, climate change management scenarios and deliberative techniques, the necessary trade-offs associated with long term coastal planning are explored. The method is applied to two case studies of coastal planning in Christchurch Bay on the south coast of England and the Orkney Islands off the north coast of Scotland. A range of conflicting preferences exist on the ideal governance structure to manage the coast under different climate change scenarios. In addition, the results show that public understanding of the trade-offs that have to be made is critical in gaining some degree of public support for long term coastal decision-making. We conclude that scenario-based stakeholder engagement is a useful tool to facilitate coastal management planning that takes into account the complexities and challenges of climate change, and could be used in conjunction with existing approaches such as the Shoreline Management Planning process.

Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

2016-05-01

Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert

Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

PubMed Central

Jiang, Yanhua; Xiong, Guangming; Chen, Huiyan; Lee, Dah-Jye

2014-01-01

This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. PMID:25256109

Food Culture, Preferences and Ethics in Dysphagia Management.

PubMed

Kenny, Belinda

2015-11-01

Adults with dysphagia experience difficulties swallowing food and fluids with potentially harmful health and psychosocial consequences. Speech pathologists who manage patients with dysphagia are frequently required to address ethical issues when patients' food culture and/ or preferences are inconsistent with recommended diets. These issues incorporate complex links between food, identity and social participation. A composite case has been developed to reflect ethical issues identified by practising speech pathologists for the purposes of illustrating ethical concerns in dysphagia management. The case examines a speech pathologist's role in supporting patient autonomy when patients and carers express different goals and values. The case presents a 68-year-old man of Australian/Italian heritage with severe swallowing impairment and strong values attached to food preferences. The case is examined through application of the dysphagia algorithm, a tool for shared decision-making when patients refuse dietary modifications. Case analysis revealed the benefits and challenges of shared decision-making processes in dysphagia management. Four health professional skills and attributes were identified as synonymous with shared decision making: communication, imagination, courage and reflection. © 2015 John Wiley & Sons Ltd.

Bridging Ground Validation and Algorithms: Using Scattering and Integral Tables to Incorporate Observed DSD Correlations into Satellite Algorithms

NASA Astrophysics Data System (ADS)

Williams, C. R.

2012-12-01

The NASA Global Precipitation Mission (GPM) raindrop size distribution (DSD) Working Group is composed of NASA PMM Science Team Members and is charged to "investigate the correlations between DSD parameters using Ground Validation (GV) data sets that support, or guide, the assumptions used in satellite retrieval algorithms." Correlations between DSD parameters can be used to constrain the unknowns and reduce the degrees-of-freedom in under-constrained satellite algorithms. Over the past two years, the GPM DSD Working Group has analyzed GV data and has found correlations between the mass-weighted mean raindrop diameter (Dm) and the mass distribution standard deviation (Sm) that follows a power-law relationship. This Dm-Sm power-law relationship appears to be robust and has been observed in surface disdrometer and vertically pointing radar observations. One benefit of a Dm-Sm power-law relationship is that a three parameter DSD can be modeled with just two parameters: Dm and Nw that determines the DSD amplitude. In order to incorporate observed DSD correlations into satellite algorithms, the GPM DSD Working Group is developing scattering and integral tables that can be used by satellite algorithms. Scattering tables describe the interaction of electromagnetic waves on individual particles to generate cross sections of backscattering, extinction, and scattering. Scattering tables are independent of the distribution of particles. Integral tables combine scattering table outputs with DSD parameters and DSD correlations to generate integrated normalized reflectivity, attenuation, scattering, emission, and asymmetry coefficients. Integral tables contain both frequency dependent scattering properties and cloud microphysics. The GPM DSD Working Group has developed scattering tables for raindrops at both Dual Precipitation Radar (DPR) frequencies and at all GMI radiometer frequencies less than 100 GHz. Scattering tables include Mie and T-matrix scattering with H- and V

A simple computational algorithm of model-based choice preference.

PubMed

Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

2017-08-01

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

On the performance of explicit and implicit algorithms for transient thermal analysis

NASA Astrophysics Data System (ADS)

Adelman, H. M.; Haftka, R. T.

1980-09-01

The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, have been selected and finite element models of the configurations are discribed. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system and a model of the space shuttle orbiter wing. Calculations were carried out using the SPAR finite element program, the MITAS lumped parameter program and a special purpose finite element program incorporating the GEAR algorithms. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff. Careful attention to modeling detail such as avoiding thin or short high-conducting elements can sometimes reduce the stiffness to the extent that explicit methods become advantageous.

The Texas Medication Algorithm Project antipsychotic algorithm for schizophrenia: 2006 update.

PubMed

Moore, Troy A; Buchanan, Robert W; Buckley, Peter F; Chiles, John A; Conley, Robert R; Crismon, M Lynn; Essock, Susan M; Finnerty, Molly; Marder, Stephen R; Miller, Del D; McEvoy, Joseph P; Robinson, Delbert G; Schooler, Nina R; Shon, Steven P; Stroup, T Scott; Miller, Alexander L

2007-11-01

A panel of academic psychiatrists and pharmacists, clinicians from the Texas public mental health system, advocates, and consumers met in June 2006 in Dallas, Tex., to review recent evidence in the pharmacologic treatment of schizophrenia. The goal of the consensus conference was to update and revise the Texas Medication Algorithm Project (TMAP) algorithm for schizophrenia used in the Texas Implementation of Medication Algorithms, a statewide quality assurance program for treatment of major psychiatric illness. Four questions were identified via premeeting teleconferences. (1) Should antipsychotic treatment of first-episode schizophrenia be different from that of multiepisode schizophrenia? (2) In which algorithm stages should first-generation antipsychotics (FGAs) be an option? (3) How many antipsychotic trials should precede a clozapine trial? (4) What is the status of augmentation strategies for clozapine? Subgroups reviewed the evidence in each area and presented their findings at the conference. The algorithm was updated to incorporate the following recommendations. (1) Persons with first-episode schizophrenia typically require lower antipsychotic doses and are more sensitive to side effects such as weight gain and extrapyramidal symptoms (group consensus). Second-generation antipsychotics (SGAs) are preferred for treatment of first-episode schizophrenia (majority opinion). (2) FGAs should be included in algorithm stages after first episode that include SGAs other than clozapine as options (group consensus). (3) The recommended number of trials of other antipsychotics that should precede a clozapine trial is 2, but earlier use of clozapine should be considered in the presence of persistent problems such as suicidality, comorbid violence, and substance abuse (group consensus). (4) Augmentation is reasonable for persons with inadequate response to clozapine, but published results on augmenting agents have not identified replicable positive results (group

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario.

PubMed

Alvarado-Uribe, Joanna; Gómez-Oliva, Andrea; Barrera-Animas, Ari Yair; Molina, Germán; Gonzalez-Mendoza, Miguel; Parra-Meroño, María Concepción; Jara, Antonio J

2018-03-17

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs' context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs' categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs' categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs' categories are provided. The experimental results show that the recommendations suggested by HyRA are promising.

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario

PubMed Central

Gómez-Oliva, Andrea; Molina, Germán

2018-01-01

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs’ context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs’ categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs’ categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs’ categories are provided. The experimental results show that the recommendations suggested by HyRA are promising. PMID:29562590

Workflow of the Grover algorithm simulation incorporating CUDA and GPGPU

NASA Astrophysics Data System (ADS)

Lu, Xiangwen; Yuan, Jiabin; Zhang, Weiwei

2013-09-01

The Grover quantum search algorithm, one of only a few representative quantum algorithms, can speed up many classical algorithms that use search heuristics. No true quantum computer has yet been developed. For the present, simulation is one effective means of verifying the search algorithm. In this work, we focus on the simulation workflow using a compute unified device architecture (CUDA). Two simulation workflow schemes are proposed. These schemes combine the characteristics of the Grover algorithm and the parallelism of general-purpose computing on graphics processing units (GPGPU). We also analyzed the optimization of memory space and memory access from this perspective. We implemented four programs on CUDA to evaluate the performance of schemes and optimization. Through experimentation, we analyzed the organization of threads suited to Grover algorithm simulations, compared the storage costs of the four programs, and validated the effectiveness of optimization. Experimental results also showed that the distinguished program on CUDA outperformed the serial program of libquantum on a CPU with a speedup of up to 23 times (12 times on average), depending on the scale of the simulation.

Preferences in Data Production Planning

NASA Technical Reports Server (NTRS)

Golden, Keith; Brafman, Ronen; Pang, Wanlin

2005-01-01

This paper discusses the data production problem, which consists of transforming a set of (initial) input data into a set of (goal) output data. There are typically many choices among input data and processing algorithms, each leading to significantly different end products. To discriminate among these choices, the planner supports an input language that provides a number of constructs for specifying user preferences over data (and plan) properties. We discuss these preference constructs, how we handle them to guide search, and additional challenges in the area of preference management that this important application domain offers.

Multitarget mixture reduction algorithm with incorporated target existence recursions

NASA Astrophysics Data System (ADS)

Ristic, Branko; Arulampalam, Sanjeev

2000-07-01

The paper derives a deferred logic data association algorithm based on the mixture reduction approach originally due to Salmond [SPIE vol.1305, 1990]. The novelty of the proposed algorithm provides the recursive formulae for both data association and target existence (confidence) estimation, thus allowing automatic track initiation and termination. T he track initiation performance of the proposed filter is investigated by computer simulations. It is observed that at moderately high levels of clutter density the proposed filter initiates tracks more reliably than its corresponding PDA filter. An extension of the proposed filter to the multi-target case is also presented. In addition, the paper compares the track maintenance performance of the MR algorithm with an MHT implementation.

Student Preferences for Instructional Methods in an Accounting Curriculum

ERIC Educational Resources Information Center

Abeysekera, Indra

2015-01-01

Student preferences among instructional methods are largely unexplored across the accounting curriculum. The algorithmic rigor of courses and the societal culture can influence these preferences. This study explored students' preferences of instructional methods for learning in six courses of the accounting curriculum that differ in algorithmic…

Base Preferences in Non-Templated Nucleotide Incorporation by MMLV-Derived Reverse Transcriptases

PubMed Central

Zajac, Pawel; Islam, Saiful; Hochgerner, Hannah; Lönnerberg, Peter; Linnarsson, Sten

2013-01-01

Reverse transcriptases derived from Moloney Murine Leukemia Virus (MMLV) have an intrinsic terminal transferase activity, which causes the addition of a few non-templated nucleotides at the 3´ end of cDNA, with a preference for cytosine. This mechanism can be exploited to make the reverse transcriptase switch template from the RNA molecule to a secondary oligonucleotide during first-strand cDNA synthesis, and thereby to introduce arbitrary barcode or adaptor sequences in the cDNA. Because the mechanism is relatively efficient and occurs in a single reaction, it has recently found use in several protocols for single-cell RNA sequencing. However, the base preference of the terminal transferase activity is not known in detail, which may lead to inefficiencies in template switching when starting from tiny amounts of mRNA. Here, we used fully degenerate oligos to determine the exact base preference at the template switching site up to a distance of ten nucleotides. We found a strong preference for guanosine at the first non-templated nucleotide, with a greatly reduced bias at progressively more distant positions. Based on this result, and a number of careful optimizations, we report conditions for efficient template switching for cDNA amplification from single cells. PMID:24392002

SortNet: learning to rank by a neural preference function.

PubMed

Rigutini, Leonardo; Papini, Tiziano; Maggini, Marco; Scarselli, Franco

2011-09-01

Relevance ranking consists in sorting a set of objects with respect to a given criterion. However, in personalized retrieval systems, the relevance criteria may usually vary among different users and may not be predefined. In this case, ranking algorithms that adapt their behavior from users' feedbacks must be devised. Two main approaches are proposed in the literature for learning to rank: the use of a scoring function, learned by examples, that evaluates a feature-based representation of each object yielding an absolute relevance score, a pairwise approach, where a preference function is learned to determine the object that has to be ranked first in a given pair. In this paper, we present a preference learning method for learning to rank. A neural network, the comparative neural network (CmpNN), is trained from examples to approximate the comparison function for a pair of objects. The CmpNN adopts a particular architecture designed to implement the symmetries naturally present in a preference function. The learned preference function can be embedded as the comparator into a classical sorting algorithm to provide a global ranking of a set of objects. To improve the ranking performances, an active-learning procedure is devised, that aims at selecting the most informative patterns in the training set. The proposed algorithm is evaluated on the LETOR dataset showing promising performances in comparison with other state-of-the-art algorithms.

Strategies for Global Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Paul; Morris, Robert; Khatib, Lina; Ramakrishnan, Sailesh

2004-01-01

A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of different notions of global preference, and to identify tractable sub-classes of temporal reasoning problems incorporating these notions. This paper extends previous results by refining the class of useful notions of global temporal preference that are associated with problems that admit of tractable solution techniques. This paper also answers the hitherto open question of whether problems that seek solutions that are globally preferred from a Utilitarian criterion for global preference can be found tractably.

Radiologists' preferences for digital mammographic display. The International Digital Mammography Development Group.

PubMed

Pisano, E D; Cole, E B; Major, S; Zong, S; Hemminger, B M; Muller, K E; Johnston, R E; Walsh, R; Conant, E; Fajardo, L L; Feig, S A; Nishikawa, R M; Yaffe, M J; Williams, M B; Aylward, S R

2000-09-01

To determine the preferences of radiologists among eight different image processing algorithms applied to digital mammograms obtained for screening and diagnostic imaging tasks. Twenty-eight images representing histologically proved masses or calcifications were obtained by using three clinically available digital mammographic units. Images were processed and printed on film by using manual intensity windowing, histogram-based intensity windowing, mixture model intensity windowing, peripheral equalization, multiscale image contrast amplification (MUSICA), contrast-limited adaptive histogram equalization, Trex processing, and unsharp masking. Twelve radiologists compared the processed digital images with screen-film mammograms obtained in the same patient for breast cancer screening and breast lesion diagnosis. For the screening task, screen-film mammograms were preferred to all digital presentations, but the acceptability of images processed with Trex and MUSICA algorithms were not significantly different. All printed digital images were preferred to screen-film radiographs in the diagnosis of masses; mammograms processed with unsharp masking were significantly preferred. For the diagnosis of calcifications, no processed digital mammogram was preferred to screen-film mammograms. When digital mammograms were preferred to screen-film mammograms, radiologists selected different digital processing algorithms for each of three mammographic reading tasks and for different lesion types. Soft-copy display will eventually allow radiologists to select among these options more easily.

Preliminary assessment of the impact of incorporating a detailed algorithm for the effects of nuclear irradiation on combat crew performance into the Janus combat simulation

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

Warshawsky, A.S.; Uzelac, M.J.; Pimper, J.E.

The Crew III algorithm for assessing time and dose dependent combat crew performance subsequent to nuclear irradiation was incorporated into the Janus combat simulation system. Battle outcomes using this algorithm were compared to outcomes based on the currently used time-independent cookie-cutter'' assessment methodology. The results illustrate quantifiable differences in battle outcome between the two assessment techniques. Results suggest that tactical nuclear weapons are more effective than currently assumed if performance degradation attributed to radiation doses between 150 to 3000 rad are taken into account. 6 refs., 9 figs.

Predicting Human Preferences Using the Block Structure of Complex Social Networks

PubMed Central

Guimerà, Roger; Llorente, Alejandro; Moro, Esteban; Sales-Pardo, Marta

2012-01-01

With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point of view, as part of what has been called a “new” computational social science. Here, we propose a novel approach based on stochastic block models, which have been developed by sociologists as plausible models of complex networks of social interactions. Our model is in the spirit of predicting individuals' preferences based on the preferences of others but, rather than fitting a particular model, we rely on a Bayesian approach that samples over the ensemble of all possible models. We show that our approach is considerably more accurate than leading recommender algorithms, with major relative improvements between 38% and 99% over industry-level algorithms. Besides, our approach sheds light on decision-making processes by identifying groups of individuals that have consistently similar preferences, and enabling the analysis of the characteristics of those groups. PMID:22984533

A novel application of PageRank and user preference algorithms for assessing the relative performance of track athletes in competition.

PubMed

Beggs, Clive B; Shepherd, Simon J; Emmonds, Stacey; Jones, Ben

2017-01-01

Ranking enables coaches, sporting authorities, and pundits to determine the relative performance of individual athletes and teams in comparison to their peers. While ranking is relatively straightforward in sports that employ traditional leagues, it is more difficult in sports where competition is fragmented (e.g. athletics, boxing, etc.), with not all competitors competing against each other. In such situations, complex points systems are often employed to rank athletes. However, these systems have the inherent weakness that they frequently rely on subjective assessments in order to gauge the calibre of the competitors involved. Here we show how two Internet derived algorithms, the PageRank (PR) and user preference (UP) algorithms, when utilised with a simple 'who beat who' matrix, can be used to accurately rank track athletes, avoiding the need for subjective assessment. We applied the PR and UP algorithms to the 2015 IAAF Diamond League men's 100m competition and compared their performance with the Keener, Colley and Massey ranking algorithms. The top five places computed by the PR and UP algorithms, and the Diamond League '2016' points system were all identical, with the Kendall's tau distance between the PR standings and '2016' points system standings being just 15, indicating that only 5.9% of pairs differed in their order between these two lists. By comparison, the UP and '2016' standings displayed a less strong relationship, with a tau distance of 95, indicating that 37.6% of the pairs differed in their order. When compared with the standings produced using the Keener, Colley and Massey algorithms, the PR standings appeared to be closest to the Keener standings (tau distance = 67, 26.5% pair order disagreement), whereas the UP standings were more similar to the Colley and Massey standings, with the tau distances between these ranking lists being only 48 (19.0% pair order disagreement) and 59 (23.3% pair order disagreement) respectively. In particular, the

A novel application of PageRank and user preference algorithms for assessing the relative performance of track athletes in competition

PubMed Central

Shepherd, Simon J.; Emmonds, Stacey; Jones, Ben

2017-01-01

Ranking enables coaches, sporting authorities, and pundits to determine the relative performance of individual athletes and teams in comparison to their peers. While ranking is relatively straightforward in sports that employ traditional leagues, it is more difficult in sports where competition is fragmented (e.g. athletics, boxing, etc.), with not all competitors competing against each other. In such situations, complex points systems are often employed to rank athletes. However, these systems have the inherent weakness that they frequently rely on subjective assessments in order to gauge the calibre of the competitors involved. Here we show how two Internet derived algorithms, the PageRank (PR) and user preference (UP) algorithms, when utilised with a simple ‘who beat who’ matrix, can be used to accurately rank track athletes, avoiding the need for subjective assessment. We applied the PR and UP algorithms to the 2015 IAAF Diamond League men’s 100m competition and compared their performance with the Keener, Colley and Massey ranking algorithms. The top five places computed by the PR and UP algorithms, and the Diamond League ‘2016’ points system were all identical, with the Kendall’s tau distance between the PR standings and ‘2016’ points system standings being just 15, indicating that only 5.9% of pairs differed in their order between these two lists. By comparison, the UP and ‘2016’ standings displayed a less strong relationship, with a tau distance of 95, indicating that 37.6% of the pairs differed in their order. When compared with the standings produced using the Keener, Colley and Massey algorithms, the PR standings appeared to be closest to the Keener standings (tau distance = 67, 26.5% pair order disagreement), whereas the UP standings were more similar to the Colley and Massey standings, with the tau distances between these ranking lists being only 48 (19.0% pair order disagreement) and 59 (23.3% pair order disagreement) respectively

Dopant Adsorption and Incorporation at Irradiated GaN Surfaces

NASA Astrophysics Data System (ADS)

Sun, Qiang; Selloni, Annabella; Myers, Thomas; Doolittle, W. Alan

2006-03-01

Mg and O are two of the common dopants in GaN, but, in spite of extensive investigation, the atomic scale understanding of their adsorption and incorporation is still incomplete. In particular, high-energy electron irradiation, such as occurring during RHEED, has been reported to have an important effect on the incorporation of these impurities, but no study has addressed the detailed mechanisms of this effect yet. Here we use DFT calculations to study the adsorption and incorporation of Mg and O at the Ga- and N-polar GaN surfaces under various Ga, Mg and O coverage conditions as well as in presence of light or electron beam-induced electronic excitation. We find that the adsorption and incorporation of the two impurities have opposite surface polarity dependence: substitutional Mg prefers to incorporate at the GaN(0001) surface, while O prefers to adsorb and incorporate at the N-polar surface. In addition, our results indicate that in presence of light irradiation the tendency of Mg to surface-segregate is reduced. The O adsorption energy on the N-polar surface is also significantly reduced, consistent with the experimental observation of a much smaller concentration of oxygen in the irradiated samples.

Approximate dynamic programming approaches for appointment scheduling with patient preferences.

PubMed

Li, Xin; Wang, Jin; Fung, Richard Y K

2018-04-01

During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future possible requests is also necessary for a successful appointment system. This paper proposes a Markov decision process model for optimizing the scheduling of sequential appointments with patient preferences. In contrast to existing models, the evaluation of a booking decision in this model focuses on the extent to which preferences are satisfied. Characteristics of the model are analysed to develop a system for formulating booking policies. Based on these characteristics, two types of approximate dynamic programming algorithms are developed to avoid the curse of dimensionality. Experimental results suggest directions for further fine-tuning of the model, as well as improving the efficiency of the two proposed algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.

Temporal Constraint Reasoning With Preferences

NASA Technical Reports Server (NTRS)

Khatib, Lina; Morris, Paul; Morris, Robert; Rossi, Francesca

2001-01-01

A number of reasoning problems involving the manipulation of temporal information can naturally be viewed as implicitly inducing an ordering of potential local decisions involving time (specifically, associated with durations or orderings of events) on the basis of preferences. For example. a pair of events might be constrained to occur in a certain order, and, in addition. it might be preferable that the delay between them be as large, or as small, as possible. This paper explores problems in which a set of temporal constraints is specified, where each constraint is associated with preference criteria for making local decisions about the events involved in the constraint, and a reasoner must infer a complete solution to the problem such that, to the extent possible, these local preferences are met in the best way. A constraint framework for reasoning about time is generalized to allow for preferences over event distances and durations, and we study the complexity of solving problems in the resulting formalism. It is shown that while in general such problems are NP-hard, some restrictions on the shape of the preference functions, and on the structure of the preference set, can be enforced to achieve tractability. In these cases, a simple generalization of a single-source shortest path algorithm can be used to compute a globally preferred solution in polynomial time.

Patients' preferences for selection of endpoints in cardiovascular clinical trials.

PubMed

Chow, Robert D; Wankhedkar, Kashmira P; Mete, Mihriye

2014-01-01

To reduce the duration and overall costs of cardiovascular trials, use of the combined endpoints in trial design has become commonplace. Though this methodology may serve the needs of investigators and trial sponsors, the preferences of patients or potential trial subjects in the trial design process has not been studied. To determine the preferences of patients in the design of cardiovascular trials. Participants were surveyed in a pilot study regarding preferences among various single endpoints commonly used in cardiovascular trials, preference for single vs. composite endpoints, and the likelihood of compliance with a heart medication if patients similar to them participated in the trial design process. One hundred adult English-speaking patients, 38% male, from a primary care ambulatory practice located in an urban setting. Among single endpoints, participants rated heart attack as significantly more important than death from other causes (4.53 vs. 3.69, p=0.004) on a scale of 1-6. Death from heart disease was rated as significantly more important than chest pain (4.73 vs. 2.47, p<0.001), angioplasty/PCI/CABG (4.73 vs. 2.43, p<0.001), and stroke (4.73 vs. 2.43, p<0.001). Participants also expressed a slight preference for combined endpoints over single endpoint (43% vs. 57%), incorporation of the opinions of the study patient population into the design of trials (48% vs. 41% for researchers), and a greater likelihood of medication compliance if patient preferences were considered during trial design (67% indicated a significant to major effect). Patients are able to make judgments and express preferences regarding trial design. They prefer that the opinions of the study population rather than the general population be incorporated into the design of the study. This novel approach to study design would not only incorporate patient preferences into medical decision making, but it also has the potential to improve compliance with cardiovascular medications.

MADM-based smart parking guidance algorithm

PubMed Central

Li, Bo; Pei, Yijian; Wu, Hao; Huang, Dijiang

2017-01-01

In smart parking environments, how to choose suitable parking facilities with various attributes to satisfy certain criteria is an important decision issue. Based on the multiple attributes decision making (MADM) theory, this study proposed a smart parking guidance algorithm by considering three representative decision factors (i.e., walk duration, parking fee, and the number of vacant parking spaces) and various preferences of drivers. In this paper, the expected number of vacant parking spaces is regarded as an important attribute to reflect the difficulty degree of finding available parking spaces, and a queueing theory-based theoretical method was proposed to estimate this expected number for candidate parking facilities with different capacities, arrival rates, and service rates. The effectiveness of the MADM-based parking guidance algorithm was investigated and compared with a blind search-based approach in comprehensive scenarios with various distributions of parking facilities, traffic intensities, and user preferences. Experimental results show that the proposed MADM-based algorithm is effective to choose suitable parking resources to satisfy users’ preferences. Furthermore, it has also been observed that this newly proposed Markov Chain-based availability attribute is more effective to represent the availability of parking spaces than the arrival rate-based availability attribute proposed in existing research. PMID:29236698

Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)

2000-01-01

In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.

Packing Boxes into Multiple Containers Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Menghani, Deepak; Guha, Anirban

2016-07-01

Container loading problems have been studied extensively in the literature and various analytical, heuristic and metaheuristic methods have been proposed. This paper presents two different variants of a genetic algorithm framework for the three-dimensional container loading problem for optimally loading boxes into multiple containers with constraints. The algorithms are designed so that it is easy to incorporate various constraints found in real life problems. The algorithms are tested on data of standard test cases from literature and are found to compare well with the benchmark algorithms in terms of utilization of containers. This, along with the ability to easily incorporate a wide range of practical constraints, makes them attractive for implementation in real life scenarios.

Evaluating progressive-rendering algorithms in appearance design tasks.

PubMed

Jiawei Ou; Karlik, Ondrej; Křivánek, Jaroslav; Pellacini, Fabio

2013-01-01

Progressive rendering is becoming a popular alternative to precomputational approaches to appearance design. However, progressive algorithms create images exhibiting visual artifacts at early stages. A user study investigated these artifacts' effects on user performance in appearance design tasks. Novice and expert subjects performed lighting and material editing tasks with four algorithms: random path tracing, quasirandom path tracing, progressive photon mapping, and virtual-point-light rendering. Both the novices and experts strongly preferred path tracing to progressive photon mapping and virtual-point-light rendering. None of the participants preferred random path tracing to quasirandom path tracing or vice versa; the same situation held between progressive photon mapping and virtual-point-light rendering. The user workflow didn’t differ significantly with the four algorithms. The Web Extras include a video showing how four progressive-rendering algorithms converged (at http://youtu.be/ck-Gevl1e9s), the source code used, and other supplementary materials.

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.

2005-01-01

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Effects of Style, Tempo, and Performing Medium on Children's Music Preference.

ERIC Educational Resources Information Center

LeBlanc, Albert

1981-01-01

Fifth-graders listened to a tape incorporating fast and slow vocal and instrumental excerpts within the generic styles of rock/pop, country, older jazz, newer jazz, art music, and band music. A preference hierarchy emerged favoring the popular styles. Across pooled styles, faster tempos and instrumentals were slightly preferred. (Author/SJL)

Algorithmic Case Pedagogy, Learning and Gender

ERIC Educational Resources Information Center

Bromley, Robert; Huang, Zhenyu

2015-01-01

Great investment has been made in developing algorithmically-based cases within online homework management systems. This has been done because publishers are convinced that textbook adoption decisions are influenced by the incorporation of these systems within their products. These algorithmic assignments are thought to promote learning while…

Incorporating Learning Style and Personality Preferences into an Oral Communication Course Syllabus

ERIC Educational Resources Information Center

Hadas, Michael

2011-01-01

Individual difference factors of personality typology and learning style preference and their effect on second language acquisition have been the focus of several prominent SLA theorists over the past twenty-five years. However, few articles have demonstrated how individual learner difference research can be applied within a classroom by second…

Rhombicuboctahedron unit cell based scaffolds for bone regeneration: geometry optimization with a mechanobiology - driven algorithm.

PubMed

Boccaccio, Antonio; Fiorentino, Michele; Uva, Antonio E; Laghetti, Luca N; Monno, Giuseppe

2018-02-01

In a context more and more oriented towards customized medical solutions, we propose a mechanobiology-driven algorithm to determine the optimal geometry of scaffolds for bone regeneration that is the most suited to specific boundary and loading conditions. In spite of the huge number of articles investigating different unit cells for porous biomaterials, no studies are reported in the literature that optimize the geometric parameters of such unit cells based on mechanobiological criteria. Parametric finite element models of scaffolds with rhombicuboctahedron unit cell were developed and incorporated into an optimization algorithm that combines them with a computational mechanobiological model. The algorithm perturbs iteratively the geometry of the unit cell until the best scaffold geometry is identified, i.e. the geometry that allows to maximize the formation of bone. Performances of scaffolds with rhombicuboctahedron unit cell were compared with those of other scaffolds with hexahedron unit cells. We found that scaffolds with rhombicuboctahedron unit cell are particularly suited for supporting medium-low loads, while, for higher loads, scaffolds with hexahedron unit cells are preferable. The proposed algorithm can guide the orthopaedic/surgeon in the choice of the best scaffold to be implanted in a patient-specific anatomic region. Copyright © 2017 Elsevier B.V. All rights reserved.

Algorithm Optimally Allocates Actuation of a Spacecraft

NASA Technical Reports Server (NTRS)

Motaghedi, Shi

2007-01-01

A report presents an algorithm that solves the following problem: Allocate the force and/or torque to be exerted by each thruster and reaction-wheel assembly on a spacecraft for best performance, defined as minimizing the error between (1) the total force and torque commanded by the spacecraft control system and (2) the total of forces and torques actually exerted by all the thrusters and reaction wheels. The algorithm incorporates the matrix vector relationship between (1) the total applied force and torque and (2) the individual actuator force and torque values. It takes account of such constraints as lower and upper limits on the force or torque that can be applied by a given actuator. The algorithm divides the aforementioned problem into two optimization problems that it solves sequentially. These problems are of a type, known in the art as semi-definite programming problems, that involve linear matrix inequalities. The algorithm incorporates, as sub-algorithms, prior algorithms that solve such optimization problems very efficiently. The algorithm affords the additional advantage that the solution requires the minimum rate of consumption of fuel for the given best performance.

The DEP-6D, a new preference-based measure to assess health states of dependency.

PubMed

Rodríguez-Míguez, E; Abellán-Perpiñán, J M; Alvarez, X C; González, X M; Sampayo, A R

2016-03-01

In medical literature there are numerous multidimensional scales to measure health states for dependence in activities of daily living. However, these scales are not preference-based and are not able to yield QALYs. On the contrary, the generic preference-based measures are not sensitive enough to measure changes in dependence states. The objective of this paper is to propose a new dependency health state classification system, called DEP-6D, and to estimate its value set in such a way that it can be used in QALY calculations. DEP-6D states are described as a combination of 6 attributes (eat, incontinence, personal care, mobility, housework and cognition problems), with 3-4 levels each. A sample of 312 Spanish citizens was surveyed in 2011 to estimate the DEP-6D preference-scoring algorithm. Each respondent valued six out of the 24 states using time trade-off questions. After excluding those respondents who made two or more inconsistencies (6% out of the sample), each state was valued between 66 and 77 times. The responses present a high internal and external consistency. A random effect model accounting for main effects was the preferred model to estimate the scoring algorithm. The DEP-6D describes, in general, more severe problems than those usually described by means of generic preference-based measures. The minimum score predicted by the DEP-6D algorithm is -0.84, which is considerably lower than the minimum value predicted by the EQ-5D and SF-6D algorithms. The DEP-6D value set is based on community preferences. Therefore it is consistent with the so-called 'societal perspective'. Moreover, DEP-6D preference weights can be used in QALY calculations and cost-utility analysis. Copyright © 2016. Published by Elsevier Ltd.

Incorporating Auditory Models in Speech/Audio Applications

NASA Astrophysics Data System (ADS)

Krishnamoorthi, Harish

2011-12-01

Following the success in incorporating perceptual models in audio coding algorithms, their application in other speech/audio processing systems is expanding. In general, all perceptual speech/audio processing algorithms involve minimization of an objective function that directly/indirectly incorporates properties of human perception. This dissertation primarily investigates the problems associated with directly embedding an auditory model in the objective function formulation and proposes possible solutions to overcome high complexity issues for use in real-time speech/audio algorithms. Specific problems addressed in this dissertation include: 1) the development of approximate but computationally efficient auditory model implementations that are consistent with the principles of psychoacoustics, 2) the development of a mapping scheme that allows synthesizing a time/frequency domain representation from its equivalent auditory model output. The first problem is aimed at addressing the high computational complexity involved in solving perceptual objective functions that require repeated application of auditory model for evaluation of different candidate solutions. In this dissertation, a frequency pruning and a detector pruning algorithm is developed that efficiently implements the various auditory model stages. The performance of the pruned model is compared to that of the original auditory model for different types of test signals in the SQAM database. Experimental results indicate only a 4-7% relative error in loudness while attaining up to 80-90 % reduction in computational complexity. Similarly, a hybrid algorithm is developed specifically for use with sinusoidal signals and employs the proposed auditory pattern combining technique together with a look-up table to store representative auditory patterns. The second problem obtains an estimate of the auditory representation that minimizes a perceptual objective function and transforms the auditory pattern back to

Algorithmic problems of nontransitive (SSB) utilities

NASA Technical Reports Server (NTRS)

Kosheleva, O. M.; Kreinovich, V. YA.

1991-01-01

The standard utility theory is based on several natural axioms including transitivity of preference; however, real preference is often not transitive. To describe such preferences, Fishburn (1988) introduced a new formalism (SSB-utilities), in which preference is described by a skew-symmetric function F:M x M - R, where M is the set of all alternatives. He also showed that it is in principle possible to reconstruct this function F by asking the person to compare different alternatives and lotteries. In the present paper we propose a new algorithm for reconstructing F that is asymptotically optimal in the sense that the number of binary (yes-no) questions that one has to ask to determine the values of F with given precision is of minimal possible order.

Conducting preference assessments for youth with disorders of consciousness during rehabilitation.

PubMed

Amari, Adrianna; Suskauer, Stacy J; Paasch, Valerie; Grodin, Lauren K; Slomine, Beth S

2017-08-01

Care and rehabilitation for individuals with disorders of consciousness (DOC) can be challenging; the use of observational data collection, individualized treatment programs, and incorporation of preferred, personally meaningful and salient items may be helpful in addressing such challenges during assessment and intervention. In this article, we extend the predominantly adult literature on use of salient items to promote differential responding by describing our methodology to identify preferred items across sensory domains for application during inpatient rehabilitation with children with DOC. Details on the indirect and direct preference assessment procedures rooted in applied behavior analysis that we have tailored for this population are provided. We describe steps of the procedures, including structured caregiver interview, staff survey, item inclusion, in vivo single-item stimulus preference assessment, and treatment. Clinical case examples further illustrate implementation of our methodology, observed response topographies, individually identified preferred items, and their application for 3 children in a minimally conscious state. In addition, we introduce a new structured caregiver interview, the Preference Assessment for Youth with Disorders of Consciousness (PAYDOC), modeled on the Reinforcer Assessment for Individuals with Severe Disabilities (RAISD; Fisher, Piazza, Bowman, & Amari, 1996) and modified to be appropriate for future use as a clinical tool to enhance assessment of preferences with this pediatric brain injury population. This methodology can be used to identify highly idiosyncratic stimuli that can be incorporated in multiple ways throughout rehabilitation to optimize care for youth with DOC. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Weighted Description Logics Preference Formulas for Multiattribute Negotiation

NASA Astrophysics Data System (ADS)

Ragone, Azzurra; di Noia, Tommaso; Donini, Francesco M.; di Sciascio, Eugenio; Wellman, Michael P.

We propose a framework to compute the utility of an agreement w.r.t a preference set in a negotiation process. In particular, we refer to preferences expressed as weighted formulas in a decidable fragment of First-order Logic and agreements expressed as a formula. We ground our framework in Description Logics (DL) endowed with disjunction, to be compliant with Semantic Web technologies. A logic based approach to preference representation allows, when a background knowledge base is exploited, to relax the often unrealistic assumption of additive independence among attributes. We provide suitable definitions of the problem and present algorithms to compute utility in our setting. We also validate our approach through an experimental evaluation.

Carotenoid incorporation into microsomes: yields, stability and membrane dynamics

NASA Astrophysics Data System (ADS)

Socaciu, Carmen; Jessel, Robert; Diehl, Horst A.

2000-12-01

The carotenoids β-carotene (BC), lycopene (LYC), lutein (LUT), zeaxanthin (ZEA), canthaxanthin (CTX) and astaxanthin (ASTA) have been incorporated into pig liver microsomes. Effective incorporation concentrations in the range of about 1-6 nmol/mg microsomal protein were obtained. A stability test at room temperature revealed that after 3 h BC and LYC had decayed totally whereas, gradually, CTX (46%), LUT (21%), ASTA (17%) and ZEA (5%) decayed. Biophysical parameters of the microsomal membrane were changed hardly by the incorporation of carotenoids. A small rigidification may occur. Membrane anisotropy seems to offer only a small tolerance for incorporation of carotenoids and seems to limit the achievable incorporation concentrations of the carotenoids into microsomes. Microsomes instead of liposomes should be preferred as a membrane model to study mutual effects of carotenoids and membrane dynamics.

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment.

PubMed

Bidargaddi, Niranjan P; Chetty, Madhu; Kamruzzaman, Joarder

2008-06-01

Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.

A Framework for Incorporating Patient Preferences Regarding Benefits and Risks into Regulatory Assessment of Medical Technologies.

PubMed

Ho, Martin; Saha, Anindita; McCleary, K Kimberly; Levitan, Bennett; Christopher, Stephanie; Zandlo, Kristen; Braithwaite, R Scott; Hauber, A Brett

In response to 2012 guidance in which the US Food and Drug Administration's (FDA) Center for Devices and Radiological Health (CDRH) stated the importance of patient-centric measures in regulatory benefit-risk assessments, the Medical Device Innovation Consortium (MDIC) initiated a project. The project was used to develop a framework to help the Food and Drug Administration (FDA) and industry sponsors understand how patient preferences regarding benefit and risk might be integrated into the review of innovative medical devices. A public-private partnership of experts from medical device industry, government, academia and non-profits collaborated on development of the MDIC patient centered benefit-risk framework. The MDIC Framework examines what patient preference information is and the potential use and value of patient preference information in the regulatory process and across the product development life cycle. The MDIC Framework also includes a catalog of patient preference assessment methods and an agenda for future research to advance the field. This article discusses key concepts in patient preference assessment of particular importance for regulators and researchers that are addressed in the MDIC Framework for patient centered benefit-risk assessment as well as the unique public-private collaboration that led its development. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Expanding a First-Order Logic Mitigation Framework to Handle Multimorbid Patient Preferences

PubMed Central

Michalowski, Martin; Wilk, Szymon; Rosu, Daniela; Kezadri, Mounira; Michalowski, Wojtek; Carrier, Marc

2015-01-01

The increasing prevalence of multimorbidity is a challenge for physicians who have to manage a constantly growing number of patients with simultaneous diseases. Adding to this challenge is the need to incorporate patient preferences as key components of the care process, thanks in part to the emergence of personalized and participatory medicine. In our previous work we proposed a framework employing first order logic to represent clinical practice guidelines (CPGs) and to mitigate possible adverse interactions when concurrently applying multiple CPGs to a multimorbid patient. In this paper, we describe extensions to our methodological framework that (1) broaden our definition of revision operators to support required and desired types of revisions defined in secondary knowledge sources, and (2) expand the mitigation algorithm to apply revisions based on their type. We illustrate the capabilities of the expanded framework using a clinical case study of a multimorbid patient with stable cardiac artery disease who suffers a sudden onset of deep vein thrombosis. PMID:26958226

Tractable Pareto Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Robert; Morris, Paul; Khatib, Lina; Venable, Brent

2003-01-01

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call 'Weakest Link Optimization' (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that re-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.

A Gaze-Driven Evolutionary Algorithm to Study Aesthetic Evaluation of Visual Symmetry

PubMed Central

Bertamini, Marco; Jones, Andrew; Holmes, Tim; Zanker, Johannes M.

2016-01-01

Empirical work has shown that people like visual symmetry. We used a gaze-driven evolutionary algorithm technique to answer three questions about symmetry preference. First, do people automatically evaluate symmetry without explicit instruction? Second, is perfect symmetry the best stimulus, or do people prefer a degree of imperfection? Third, does initial preference for symmetry diminish after familiarity sets in? Stimuli were generated as phenotypes from an algorithmic genotype, with genes for symmetry (coded as deviation from a symmetrical template, deviation–symmetry, DS gene) and orientation (0° to 90°, orientation, ORI gene). An eye tracker identified phenotypes that were good at attracting and retaining the gaze of the observer. Resulting fitness scores determined the genotypes that passed to the next generation. We recorded changes to the distribution of DS and ORI genes over 20 generations. When participants looked for symmetry, there was an increase in high-symmetry genes. When participants looked for the patterns they preferred, there was a smaller increase in symmetry, indicating that people tolerated some imperfection. Conversely, there was no increase in symmetry during free viewing, and no effect of familiarity or orientation. This work demonstrates the viability of the evolutionary algorithm approach as a quantitative measure of aesthetic preference. PMID:27433324

Automated Spectroscopic Analysis Using the Particle Swarm Optimization Algorithm: Implementing a Guided Search Algorithm to Autofit

NASA Astrophysics Data System (ADS)

Ervin, Katherine; Shipman, Steven

2017-06-01

While rotational spectra can be rapidly collected, their analysis (especially for complex systems) is seldom straightforward, leading to a bottleneck. The AUTOFIT program was designed to serve that need by quickly matching rotational constants to spectra with little user input and supervision. This program can potentially be improved by incorporating an optimization algorithm in the search for a solution. The Particle Swarm Optimization Algorithm (PSO) was chosen for implementation. PSO is part of a family of optimization algorithms called heuristic algorithms, which seek approximate best answers. This is ideal for rotational spectra, where an exact match will not be found without incorporating distortion constants, etc., which would otherwise greatly increase the size of the search space. PSO was tested for robustness against five standard fitness functions and then applied to a custom fitness function created for rotational spectra. This talk will explain the Particle Swarm Optimization algorithm and how it works, describe how Autofit was modified to use PSO, discuss the fitness function developed to work with spectroscopic data, and show our current results. Seifert, N.A., Finneran, I.A., Perez, C., Zaleski, D.P., Neill, J.L., Steber, A.L., Suenram, R.D., Lesarri, A., Shipman, S.T., Pate, B.H., J. Mol. Spec. 312, 13-21 (2015)

Generation of referring expressions: assessing the Incremental Algorithm.

PubMed

van Deemter, Kees; Gatt, Albert; van der Sluis, Ielka; Power, Richard

2012-07-01

A substantial amount of recent work in natural language generation has focused on the generation of ''one-shot'' referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out that the success of the IA depends substantially on the ''preference order'' (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO. Copyright © 2011 Cognitive Science Society, Inc.

Preferred Roles in Treatment Decision Making Among Patients With Cancer: A Pooled Analysis of Studies Using the Control Preferences Scale

PubMed Central

Singh, Jasvinder A.; Sloan, Jeff A.; Atherton, Pamela J.; Smith, Tenbroeck; Hack, Thomas F.; Huschka, Mashele M.; Rummans, Teresa A.; Clark, Matthew M.; Diekmann, Brent; Degner, Lesley F.

2010-01-01

Objectives To collect normative data, assess differences between demographic groups, and indirectly compare US and Canadian medical systems relative to patient expectations of involvement in cancer treatment decision making. Study Design Meta-analysis. Methods Individual patient data were compiled across 6 clinical studies among 3491 patients with cancer who completed the 2-item Control Preferences Scale indicating the roles they preferred versus actually experienced in treatment decision making. Results The roles in treatment decision making that patients preferred were 26% active, 49% collaborative, and 25% passive. The roles that patients reported actually experiencing were 30% active, 34% collaborative, and 36% passive. Roughly 61% of patients reported having their preferred role; only 6% experienced extreme discordance between their preferred versus actual roles. More men than women (66% vs 60%, P = .001) and more US patients than Canadian patients (84% vs 54%, P <.001) reported concordance between their preferred versus actual roles. More Canadian patients than US patients preferred and actually experienced (42% vs 18%, P <.001) passive roles. More women than men reported taking a passive role (40% vs 24%, P <.001). Older patients preferred and were more likely than younger patients to assume a passive role. Conclusions Roughly half of the studied patients with cancer indicated that they preferred to have a collaborative relationship with physicians. Although most patients had the decision-making role they preferred, about 40% experienced discordance. This highlights the need for incorporation of individualized patient communication styles into treatment plans. PMID:20873956

Construction project selection with the use of fuzzy preference relation

NASA Astrophysics Data System (ADS)

Ibadov, Nabi

2016-06-01

In the article, author describes the problem of the construction project variant selection during pre-investment phase. As a solution, the algorithm basing on fuzzy preference relation is presented. The article provides an example of the algorithm used for selection of the best variant for construction project. The choice is made basing on criteria such as: net present value (NPV), level of technological difficulty, financing possibilities, and level of organizational difficulty.

Solar cells incorporating light harvesting arrays

DOEpatents

Lindsey, Jonathan S.; Meyer, Gerald J.

2003-07-22

A solar cell incorporates a light harvesting array that comprises: (a) a first substrate comprising a first electrode; and (b) a layer of light harvesting rods electrically coupled to the first electrode, each of the light harvesting rods comprising a polymer of Formula I: ##EQU1## wherein m is at least 1, and may be from two, three or four to 20 or more; X.sup.1 is a charge separation group (and preferably a porphyrinic macrocycle, which may be one ligand of a double-decker sandwich compound) having an excited-state of energy equal to or lower than that of X.sup.2 ; and X.sup.2 through X.sup.m+1 are chromophores (and again are preferably porphyrinic macrocycles).

An Online Scheduling Algorithm with Advance Reservation for Large-Scale Data Transfers

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

Balman, Mehmet; Kosar, Tevfik

Scientific applications and experimental facilities generate massive data sets that need to be transferred to remote collaborating sites for sharing, processing, and long term storage. In order to support increasingly data-intensive science, next generation research networks have been deployed to provide high-speed on-demand data access between collaborating institutions. In this paper, we present a practical model for online data scheduling in which data movement operations are scheduled in advance for end-to-end high performance transfers. In our model, data scheduler interacts with reservation managers and data transfer nodes in order to reserve available bandwidth to guarantee completion of jobs that aremore » accepted and confirmed to satisfy preferred time constraint given by the user. Our methodology improves current systems by allowing researchers and higher level meta-schedulers to use data placement as a service where theycan plan ahead and reserve the scheduler time in advance for their data movement operations. We have implemented our algorithm and examined possible techniques for incorporation into current reservation frameworks. Performance measurements confirm that the proposed algorithm is efficient and scalable.« less

Incorporating Duration Information in Activity Recognition

NASA Astrophysics Data System (ADS)

Chaurasia, Priyanka; Scotney, Bryan; McClean, Sally; Zhang, Shuai; Nugent, Chris

Activity recognition has become a key issue in smart home environments. The problem involves learning high level activities from low level sensor data. Activity recognition can depend on several variables; one such variable is duration of engagement with sensorised items or duration of intervals between sensor activations that can provide useful information about personal behaviour. In this paper a probabilistic learning algorithm is proposed that incorporates episode, time and duration information to determine inhabitant identity and the activity being undertaken from low level sensor data. Our results verify that incorporating duration information consistently improves the accuracy.

Multi-objective engineering design using preferences

NASA Astrophysics Data System (ADS)

Sanchis, J.; Martinez, M.; Blasco, X.

2008-03-01

System design is a complex task when design parameters have to satisy a number of specifications and objectives which often conflict with those of others. This challenging problem is called multi-objective optimization (MOO). The most common approximation consists in optimizing a single cost index with a weighted sum of objectives. However, once weights are chosen the solution does not guarantee the best compromise among specifications, because there is an infinite number of solutions. A new approach can be stated, based on the designer's experience regarding the required specifications and the associated problems. This valuable information can be translated into preferences for design objectives, and will lead the search process to the best solution in terms of these preferences. This article presents a new method, which enumerates these a priori objective preferences. As a result, a single objective is built automatically and no weight selection need be performed. Problems occuring because of the multimodal nature of the generated single cost index are managed with genetic algorithms (GAs).

In Vivo Substrate Diversity and Preference of Small Heat Shock Protein IbpB as Revealed by Using a Genetically Incorporated Photo-cross-linker*

PubMed Central

Fu, Xinmiao; Shi, Xiaodong; Yan, Linxuan; Zhang, Hanlin; Chang, Zengyi

2013-01-01

Small heat shock proteins (sHSPs), as ubiquitous molecular chaperones found in all forms of life, are known to be able to protect cells against stresses and suppress the aggregation of a variety of model substrate proteins under in vitro conditions. Nevertheless, it is poorly understood what natural substrate proteins are protected by sHSPs in living cells. Here, by using a genetically incorporated photo-cross-linker (p-benzoyl-l-phenylalanine), we identified a total of 95 and 54 natural substrate proteins of IbpB (an sHSP from Escherichia coli) in living cells with and without heat shock, respectively. Functional profiling of these proteins (110 in total) suggests that IbpB, although binding to a wide range of cellular proteins, has a remarkable substrate preference for translation-related proteins (e.g. ribosomal proteins and amino-acyl tRNA synthetases) and moderate preference for metabolic enzymes. Furthermore, these two classes of proteins were found to be more prone to aggregation and/or inactivation in cells lacking IbpB under stress conditions (e.g. heat shock). Together, our in vivo data offer novel insights into the chaperone function of IbpB, or sHSPs in general, and suggest that the preferential protection on the protein synthesis machine and metabolic enzymes may dominantly contribute to the well known protective effect of sHSPs on cell survival against stresses. PMID:24045939

Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands.

PubMed

Salem, Salem Ibrahim; Higa, Hiroto; Kim, Hyungjun; Kobayashi, Hiroshi; Oki, Kazuo; Oki, Taikan

2017-07-31

Numerous algorithms have been proposed to retrieve chlorophyll- a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m -3 , 16.25 mg·m -3 , and 19.05 mg·m -3 , respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll- a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the

Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands

PubMed Central

Higa, Hiroto; Kobayashi, Hiroshi; Oki, Kazuo

2017-01-01

Numerous algorithms have been proposed to retrieve chlorophyll-a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m−3, 16.25 mg·m−3, and 19.05 mg·m−3, respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll-a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the

Smell Detection Agent Based Optimization Algorithm

NASA Astrophysics Data System (ADS)

Vinod Chandra, S. S.

2016-09-01

In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

Physicians' preferences for asthma guidelines implementation.

PubMed

Kang, Min-Koo; Kim, Byung-Keun; Kim, Tae-Wan; Kim, Sae-Hoon; Kang, Hye-Ryun; Park, Heung-Woo; Chang, Yoon-Seok; Kim, Sun-Sin; Min, Kyung-Up; Kim, You-Young; Cho, Sang-Heon

2010-10-01

Patient care based on asthma guidelines is cost-effective and leads to improved treatment outcomes. However, ineffective implementation strategies interfere with the use of these recommendations in clinical practice. This study investigated physicians' preferences for asthma guidelines, including content, supporting evidence, learning strategies, format, and placement in the clinical workplace. We obtained information through a questionnaire survey. The questionnaire was distributed to physicians attending continuing medical education courses and sent to other physicians by airmail, e-mail, and facsimile. A total of 183 physicians responded (male to female ratio, 2.3:1; mean age, 40.4±9.9 years); 89.9% of respondents were internists or pediatricians, and 51.7% were primary care physicians. Physicians preferred information that described asthma medications, classified the disease according to severity and level of control, and provided methods of evaluation/treatment/monitoring and management of acute exacerbation. The most effective strategies for encouraging the use of the guidelines were through continuing medical education and discussions with colleagues. Physicians required supporting evidence in the form of randomized controlled trials and expert consensus. They preferred that the guidelines be presented as algorithms or flow charts/flow diagrams on plastic sheets, pocket cards, or in electronic medical records. This study identified the items of the asthma guidelines preferred by physicians in Korea. Asthma guidelines with physicians' preferences would encourage their implementation in clinical practice.

Solar cells incorporating light harvesting arrays

DOEpatents

Lindsey, Jonathan S.; Meyer, Gerald J.

2002-01-01

A solar cell incorporates a light harvesting array that comprises: (a) a first substrate comprising a first electrode; and (b) a layer of light harvesting rods electrically coupled to the first electrode, each of the light harvesting rods comprising a polymer of Formula I: X.sup.1.paren open-st.X.sup.m+1).sub.m (I) wherein m is at least 1, and may be from two, three or four to 20 or more; X.sup.1 is a charge separation group (and preferably a porphyrinic macrocycle, which may be one ligand of a double-decker sandwich compound) having an excited-state of energy equal to or lower than that of X.sup.2 ; and X.sup.2 through X.sup.m+1 are chromophores (and again are preferably porphyrinic macrocycles).

An extension of the QZ algorithm for solving the generalized matrix eigenvalue problem

NASA Technical Reports Server (NTRS)

Ward, R. C.

1973-01-01

This algorithm is an extension of Moler and Stewart's QZ algorithm with some added features for saving time and operations. Also, some additional properties of the QR algorithm which were not practical to implement in the QZ algorithm can be generalized with the combination shift QZ algorithm. Numerous test cases are presented to give practical application tests for algorithm. Based on results, this algorithm should be preferred over existing algorithms which attempt to solve the class of generalized eigenproblems where both matrices are singular or nearly singular.

Older adults' preferences for religion/spirituality in treatment for anxiety and depression.

PubMed

Stanley, Melinda A; Bush, Amber L; Camp, Mary E; Jameson, John P; Phillips, Laura L; Barber, Catherine R; Zeno, Darrell; Lomax, James W; Cully, Jeffrey A

2011-04-01

To examine patient preferences for incorporating religion and/or spirituality into therapy for anxiety or depression and examine the relations between patient preferences and religious and spiritual coping styles, beliefs and behaviors. Participants (66 adults, 55 years or older, from earlier studies of cognitive-behavioral therapy for late-life anxiety and/or depression in primary care) completed these measures by telephone or in-person: Geriatric Anxiety Inventory, Client Attitudes Toward Spirituality in Therapy, Patient Interview, Brief Religious Coping, Religious Problem Solving Scale, Santa Clara Strength of Religious Faith, and Brief Multidimensional Measure of Religiousness and Spirituality. Spearman's rank-order correlations and ordinal logistic regression examined religious/spiritual variables as predictors of preferences for inclusion of religion or spirituality into counseling. Most participants (77-83%) preferred including religion and/or spirituality in therapy for anxiety and depression. Participants who thought it was important to include religion or spirituality in therapy reported more positive religious-based coping, greater strength of religious faith, and greater collaborative and less self-directed problem-solving styles than participants who did not think it was important. For individuals like most participants in this study (Christians), incorporating spirituality/religion into counseling for anxiety and depression was desirable.

Synthesis of Greedy Algorithms Using Dominance Relations

NASA Technical Reports Server (NTRS)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2010-01-01

Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.

Sorting on STAR. [CDC computer algorithm timing comparison

NASA Technical Reports Server (NTRS)

Stone, H. S.

1978-01-01

Timing comparisons are given for three sorting algorithms written for the CDC STAR computer. One algorithm is Hoare's (1962) Quicksort, which is the fastest or nearly the fastest sorting algorithm for most computers. A second algorithm is a vector version of Quicksort that takes advantage of the STAR's vector operations. The third algorithm is an adaptation of Batcher's (1968) sorting algorithm, which makes especially good use of vector operations but has a complexity of N(log N)-squared as compared with a complexity of N log N for the Quicksort algorithms. In spite of its worse complexity, Batcher's sorting algorithm is competitive with the serial version of Quicksort for vectors up to the largest that can be treated by STAR. Vector Quicksort outperforms the other two algorithms and is generally preferred. These results indicate that unusual instruction sets can introduce biases in program execution time that counter results predicted by worst-case asymptotic complexity analysis.

Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

Treesearch

Denys Yemshanov; Frank H Koch; Mark Ducey

2015-01-01

Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

Ascent guidance algorithm using lidar wind measurements

NASA Technical Reports Server (NTRS)

Cramer, Evin J.; Bradt, Jerre E.; Hardtla, John W.

1990-01-01

The formulation of a general nonlinear programming guidance algorithm that incorporates wind measurements in the computation of ascent guidance steering commands is discussed. A nonlinear programming (NLP) algorithm that is designed to solve a very general problem has the potential to address the diversity demanded by future launch systems. Using B-splines for the command functional form allows the NLP algorithm to adjust the shape of the command profile to achieve optimal performance. The algorithm flexibility is demonstrated by simulation of ascent with dynamic loading constraints through a set of random wind profiles with and without wind sensing capability.

Ecological criteria, participant preferences and location models: A GIS approach toward ATV trail planning

Treesearch

Stephanie A. Snyder; Jay H. Whitmore; Ingrid E. Schneider; Dennis R. Becker

2008-01-01

This paper presents a geographic information system (GIS)-based method for recreational trail location for all-terrain vehicles (ATVs) which considers environmental factors, as well as rider preferences for trail attributes. The method utilizes the Least-Cost Path algorithm within a GIS framework to optimize trail location. The trail location algorithm considered trail...

The Texas Medication Algorithm Project antipsychotic algorithm for schizophrenia: 2003 update.

PubMed

Miller, Alexander L; Hall, Catherine S; Buchanan, Robert W; Buckley, Peter F; Chiles, John A; Conley, Robert R; Crismon, M Lynn; Ereshefsky, Larry; Essock, Susan M; Finnerty, Molly; Marder, Stephen R; Miller, Del D; McEvoy, Joseph P; Rush, A John; Saeed, Sy A; Schooler, Nina R; Shon, Steven P; Stroup, Scott; Tarin-Godoy, Bernardo

2004-04-01

The Texas Medication Algorithm Project (TMAP) has been a public-academic collaboration in which guidelines for medication treatment of schizophrenia, bipolar disorder, and major depressive disorder were used in selected public outpatient clinics in Texas. Subsequently, these algorithms were implemented throughout Texas and are being used in other states. Guidelines require updating when significant new evidence emerges; the antipsychotic algorithm for schizophrenia was last updated in 1999. This article reports the recommendations developed in 2002 and 2003 by a group of experts, clinicians, and administrators. A conference in January 2002 began the update process. Before the conference, experts in the pharmacologic treatment of schizophrenia, clinicians, and administrators reviewed literature topics and prepared presentations. Topics included ziprasidone's inclusion in the algorithm, the number of antipsychotics tried before clozapine, and the role of first generation antipsychotics. Data were rated according to Agency for Healthcare Research and Quality criteria. After discussing the presentations, conference attendees arrived at consensus recommendations. Consideration of aripiprazole's inclusion was subsequently handled by electronic communications. The antipsychotic algorithm for schizophrenia was updated to include ziprasidone and aripiprazole among the first-line agents. Relative to the prior algorithm, the number of stages before clozapine was reduced. First generation antipsychotics were included but not as first-line choices. For patients refusing or not responding to clozapine and clozapine augmentation, preference was given to trying monotherapy with another antipsychotic before resorting to antipsychotic combinations. Consensus on algorithm revisions was achieved, but only further well-controlled research will answer many key questions about sequence and type of medication treatments of schizophrenia.

Incorporating User Input in Template-Based Segmentation

PubMed Central

Vidal, Camille; Beggs, Dale; Younes, Laurent; Jain, Sanjay K.; Jedynak, Bruno

2015-01-01

We present a simple and elegant method to incorporate user input in a template-based segmentation method for diseased organs. The user provides a partial segmentation of the organ of interest, which is used to guide the template towards its target. The user also highlights some elements of the background that should be excluded from the final segmentation. We derive by likelihood maximization a registration algorithm from a simple statistical image model in which the user labels are modeled as Bernoulli random variables. The resulting registration algorithm minimizes the sum of square differences between the binary template and the user labels, while preventing the template from shrinking, and penalizing for the inclusion of background elements into the final segmentation. We assess the performance of the proposed algorithm on synthetic images in which the amount of user annotation is controlled. We demonstrate our algorithm on the segmentation of the lungs of Mycobacterium tuberculosis infected mice from μCT images. PMID:26146532

High-dynamic range imaging techniques based on both color-separation algorithms used in conventional graphic arts and the human visual perception modeling

NASA Astrophysics Data System (ADS)

Lo, Mei-Chun; Hsieh, Tsung-Hsien; Perng, Ruey-Kuen; Chen, Jiong-Qiao

2010-01-01

The aim of this research is to derive illuminant-independent type of HDR imaging modules which can optimally multispectrally reconstruct of every color concerned in high-dynamic-range of original images for preferable cross-media color reproduction applications. Each module, based on either of broadband and multispectral approach, would be incorporated models of perceptual HDR tone-mapping, device characterization. In this study, an xvYCC format of HDR digital camera was used to capture HDR scene images for test. A tone-mapping module was derived based on a multiscale representation of the human visual system and used equations similar to a photoreceptor adaptation equation, proposed by Michaelis-Menten. Additionally, an adaptive bilateral type of gamut mapping algorithm, using approach of a multiple conversing-points (previously derived), was incorporated with or without adaptive Un-sharp Masking (USM) to carry out the optimization of HDR image rendering. An LCD with standard color space of Adobe RGB (D65) was used as a soft-proofing platform to display/represent HDR original RGB images, and also evaluate both renditionquality and prediction-performance of modules derived. Also, another LCD with standard color space of sRGB was used to test gamut-mapping algorithms, used to be integrated with tone-mapping module derived.

An environment-adaptive management algorithm for hearing-support devices incorporating listening situation and noise type classifiers.

PubMed

Yook, Sunhyun; Nam, Kyoung Won; Kim, Heepyung; Hong, Sung Hwa; Jang, Dong Pyo; Kim, In Young

2015-04-01

In order to provide more consistent sound intelligibility for the hearing-impaired person, regardless of environment, it is necessary to adjust the setting of the hearing-support (HS) device to accommodate various environmental circumstances. In this study, a fully automatic HS device management algorithm that can adapt to various environmental situations is proposed; it is composed of a listening-situation classifier, a noise-type classifier, an adaptive noise-reduction algorithm, and a management algorithm that can selectively turn on/off one or more of the three basic algorithms-beamforming, noise-reduction, and feedback cancellation-and can also adjust internal gains and parameters of the wide-dynamic-range compression (WDRC) and noise-reduction (NR) algorithms in accordance with variations in environmental situations. Experimental results demonstrated that the implemented algorithms can classify both listening situation and ambient noise type situations with high accuracies (92.8-96.4% and 90.9-99.4%, respectively), and the gains and parameters of the WDRC and NR algorithms were successfully adjusted according to variations in environmental situation. The average values of signal-to-noise ratio (SNR), frequency-weighted segmental SNR, Perceptual Evaluation of Speech Quality, and mean opinion test scores of 10 normal-hearing volunteers of the adaptive multiband spectral subtraction (MBSS) algorithm were improved by 1.74 dB, 2.11 dB, 0.49, and 0.68, respectively, compared to the conventional fixed-parameter MBSS algorithm. These results indicate that the proposed environment-adaptive management algorithm can be applied to HS devices to improve sound intelligibility for hearing-impaired individuals in various acoustic environments. Copyright © 2014 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Prioritising health service innovation investments using public preferences: a discrete choice experiment.

PubMed

Erdem, Seda; Thompson, Carl

2014-08-28

Prioritising scarce resources for investment in innovation by publically funded health systems is unavoidable. Many healthcare systems wish to foster transparency and accountability in the decisions they make by incorporating the public in decision-making processes. This paper presents a unique conceptual approach exploring the public's preferences for health service innovations by viewing healthcare innovations as 'bundles' of characteristics. This decompositional approach allows policy-makers to compare numerous competing health service innovations without repeatedly administering surveys for specific innovation choices. A Discrete Choice Experiment (DCE) was used to elicit preferences. Individuals chose from presented innovation options that they believe the UK National Health Service (NHS) should invest the most in. Innovations differed according to: (i) target population; (ii) target age; (iii) implementation time; (iv) uncertainty associated with their likely effects; (v) potential health benefits; and, (vi) cost to a taxpayer. This approach fosters multidimensional decision-making, rather than imposing a single decision criterion (e.g., cost, target age) in prioritisation. Choice data was then analysed using scale-adjusted Latent Class models to investigate variability in preferences and scale and valuations amongst respondents. Three latent classes with considerable heterogeneity in the preferences were present. Each latent class is composed of two consumer subgroups varying in the level of certainty in their choices. All groups preferred scientifically proven innovations, those with potential health benefits that cost less. There were, however, some important differences in their preferences for innovation investment choices: Class-1 (54%) prefers innovations benefitting adults and young people and does not prefer innovations targeting people with 'drug addiction' and 'obesity'. Class- 2 (34%) prefers innovations targeting 'cancer' patients only and has

The Role of Work-Integrated Learning in Student Preferences of Instructional Methods in an Accounting Curriculum

ERIC Educational Resources Information Center

Abeysekera, Indra

2015-01-01

The role of work-integrated learning in student preferences of instructional methods is largely unexplored across the accounting curriculum. This study conducted six experiments to explore student preferences of instructional methods for learning, in six courses of the accounting curriculum that differed in algorithmic rigor, in the context of a…

Algorithmic Mechanism Design of Evolutionary Computation.

PubMed

Pei, Yan

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.

Algorithmic Mechanism Design of Evolutionary Computation

PubMed Central

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm. PMID:26257777

Music-Based iPad App Preferences of Young Children

ERIC Educational Resources Information Center

Burton, Suzanne L.; Pearsall, Aimee

2016-01-01

Music-based technology is frequently included in early childhood classrooms as an attempt to incorporate music education in the curriculum. However, there is a lack of research that addresses the educational benefits of music-based tablet applications (apps) for young children. Researchers in this study explored the preferences of 4-year-old…

Dynamic image fusion and general observer preference

NASA Astrophysics Data System (ADS)

Burks, Stephen D.; Doe, Joshua M.

2010-04-01

Recent developments in image fusion give the user community many options for ways of presenting the imagery to an end-user. Individuals at the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate have developed an electronic system that allows users to quickly and efficiently determine optimal image fusion algorithms and color parameters based upon collected imagery and videos from environments that are typical to observers in a military environment. After performing multiple multi-band data collections in a variety of military-like scenarios, different waveband, fusion algorithm, image post-processing, and color choices are presented to observers as an output of the fusion system. The observer preferences can give guidelines as to how specific scenarios should affect the presentation of fused imagery.

A preference for some types of complexity comment on "perceived beauty of random texture patterns: A preference for complexity".

PubMed

Gauvrit, Nicolas; Soler-Toscano, Fernando; Guida, Alessandro

2017-03-01

In two experiments, Friedenberg and Liby (2016) studied how a diversity of complexity estimates such as density, number of blocks, GIF compression rate and edge length impact the perception of beauty of semi-random two-dimensional patterns. They concluded that aesthetics ratings are positively linked with GIF compression metrics and edge length, but not with the number of blocks. They also found an inverse U-shaped link between aesthetic judgments and density. These mixed results originate in the variety of metrics used to estimate what is loosely called "complexity" in psychology and indeed refers to conflicting notions. Here, we reanalyze their data adding two more conventional and normative mathematical measures of complexity: entropy and algorithmic complexity. We show that their results can be interpreted as an aesthetic preference for low redundancy, balanced patterns and "crooked" figures, but not for high algorithmic complexity. We conclude that participants tend to have a preference for some types of complexity, but not for all. These findings may help understand divergent results in the study of perceived beauty and complexity, and illustrate the need to specify the notion of complexity used in psychology. The field would certainly benefit from a precise taxonomy of complexity measures. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization techniques for incorporating backgrounds into DIRSIG

NASA Astrophysics Data System (ADS)

Brown, Scott D.; Schott, John R.

2000-07-01

The appearance of operation hyperspectral imaging spectrometers in both solar and thermal regions has lead to the development of a variety of spectral detection algorithms. The development and testing of these algorithms requires well characterized field collection campaigns that can be time and cost prohibitive. Radiometrically robust synthetic image generation (SIG) environments that can generate appropriate images under a variety of atmospheric conditions and with a variety of sensors offers an excellent supplement to reduce the scope of the expensive field collections. In addition, SIG image products provide the algorithm developer with per-pixel truth, allowing for improved characterization of the algorithm performance. To meet the needs of the algorithm development community, the image modeling community needs to supply synthetic image products that contain all the spatial and spectral variability present in real world scenes, and that provide the large area coverage typically acquired with actual sensors. This places a heavy burden on synthetic scene builders to construct well characterized scenes that span large areas. Several SIG models have demonstrated the ability to accurately model targets (vehicles, buildings, etc.) Using well constructed target geometry (from CAD packages) and robust thermal and radiometry models. However, background objects (vegetation, infrastructure, etc.) dominate the percentage of real world scene pixels and utilizing target building techniques is time and resource prohibitive. This paper discusses new methods that have been integrated into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model to characterize backgrounds. The new suite of scene construct types allows the user to incorporate both terrain and surface properties to obtain wide area coverage. The terrain can be incorporated using a triangular irregular network (TIN) derived from elevation data or digital elevation model (DEM) data from actual

The role of advanced reconstruction algorithms in cardiac CT

PubMed Central

Halliburton, Sandra S.; Tanabe, Yuki; Partovi, Sasan

2017-01-01

Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice. PMID:29255694

Counseling women with early pregnancy failure: utilizing evidence, preserving preference.

PubMed

Wallace, Robin R; Goodman, Suzan; Freedman, Lori R; Dalton, Vanessa K; Harris, Lisa H

2010-12-01

To apply principles of shared decision-making to EPF management counseling. To present a patient treatment priority checklist developed from review of available literature on patient priorities for EPF management. Review of evidence for patient preferences; personal, emotional, physical and clinical factors that may influence patient priorities for EPF management; and the clinical factors, resources, and provider bias that may influence current practice. Women have strong and diverse preferences for EPF management and report higher satisfaction when treated according to these preferences. However, estimates of actual treatment patterns suggest that current practice does not reflect the evidence for safety and acceptability of all options, or patient preferences. Multiple practice barriers and biases exist that may be influencing provider counseling about options for EPF management. Choosing management for EPF is a preference-sensitive decision. A patient-centered approach to EPF management should incorporate counseling about all treatment options. Providers can integrate a counseling model into EPF management practice that utilizes principles of shared decision-making and an organized method for eliciting patient preferences, priorities, and concerns about treatment options. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Writing on the board as students' preferred teaching modality in a physiology course.

PubMed

Armour, Chris; Schneid, Stephen D; Brandl, Katharina

2016-06-01

The introduction of PowerPoint presentation software has generated a paradigm shift in the delivery of lectures. PowerPoint has now almost entirely replaced chalkboard or whiteboard teaching at the undergraduate and graduate levels. This study investigated whether undergraduate biology students preferred to have lectures delivered by PowerPoint or written on the board as well as the reasons behind their preference. Two upper-division physiology courses were surveyed over a period of 7 yr. A total of 1,905 students (86.7%) indicated they preferred lectures delivered by "writing on the board" compared to 291 students (13.3%) who preferred PowerPoint. Common themes drawn from explanations reported by students in favor of writing on the board included: 1) more appropriate pace, 2) facilitation of note taking, and 3) greater alertness and attention. Common themes in favor of PowerPoint included 1) increased convenience, 2) focus on listening, and 3) more accurate and readable notes. Based on the students' very strong preference for writing on the board and the themes supporting that preference, we recommend that instructors incorporate elements of the writing on the board delivery style into whatever teaching modality is used. If instructors plan to use PowerPoint, the presentation should be paced, constructed, and delivered to provide the benefits of lectures written on the board. The advantages of writing on the board can be also incorporated into instruction intended to occur outside the classroom, such as animated narrated videos as part of the flipped classroom approach. Copyright © 2016 The American Physiological Society.

External Memory Aid Preferences of Individuals with Mild Memory Impairments.

PubMed

Lanzi, Alyssa; Wallace, Sarah E; Bourgeois, Michelle S

2018-07-01

Individuals with mild memory impairments often rely on external memory aids (EMAs) to compensate for impaired cognitive abilities and to support independent completion of activities of daily living. These strategies are evidence based; however, professionals have limited knowledge regarding individual preferences and guidance on how to incorporate a person-centered approach into the EMA development phase. The purpose of the current study was to qualitatively investigate individuals' preferences and experiences as they relate to EMAs. Data analysis included (1) evaluation of a posttreatment questionnaire to explore individual strategy preferences following intervention and (2) evaluation of group intervention videos using thematic coding to investigate individuals' experiences with strategies during intervention. Results suggest that older adults with mild memory impairments have unique preferences and experiences, despite limited variability in demographic characteristics. Some themes that emerged included memory ability awareness and attitudes toward technology. Within a person-centered approach, skilled professionals must consider individuals' unique needs, preferences, and experiences when developing strategies throughout the continuum of care to promote sustained EMA use within everyday settings. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Incorporating a constrained optimization algorithm into remote sensing/precision agriculture methodology

NASA Astrophysics Data System (ADS)

Moreenthaler, George W.; Khatib, Nader; Kim, Byoungsoo

2003-08-01

Optimization Algorithm" to further improve these processes will be presented. The objective function of the model will used to maximize the farmer's profit via increasing yields while decreasing environmental damage and decreasing applications of costly treatments. This model will incorporate information from Remote Sensing, from in-situ weather sources, from soil history, and from tacit farmer knowledge of the relative productivity of selected "Management Zones" of the farm, to provide incremental advice throughout the growing season on the optimum usage of water and chemical treatments.

Incorporating a Constrained Optimization Algorithm into Remote- Sensing/Precision Agriculture Methodology

NASA Astrophysics Data System (ADS)

Morgenthaler, George; Khatib, Nader; Kim, Byoungsoo

application of costly treatments. This model will incorporate information from remote sensing, in-situ weather sources, soil measurements, crop models, and tacit farmer knowledge of the relative productivity of the selected control regions of the farm to provide incremental advice throughout the growing season on water and chemical treatments. Genetic and meta-heuristic algorithms will be used to solve the constrained optimization problem that possesses complex constraints and a non-linear objective function. *

Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

PubMed

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

A Preference Test for Sweet Taste That Uses Edible Strips

PubMed Central

Smutzer, Gregory; Patel, Janki Y.; Stull, Judith C.; Abarintos, Ray A.; Khan, Neiladri K.; Park, Kevin C.

2014-01-01

A novel delivery method is described for the rapid determination of taste preferences for sweet taste in humans. This forced-choice paired comparison approach incorporates the non-caloric sweetener sucralose into a set of one-inch square edible strips for the rapid determination of sweet taste preferences. When compared to aqueous sucrose solutions, significantly lower amounts of sucralose were required to identify the preference for sweet taste. The validity of this approach was determined by comparing sweet taste preferences obtained with five different sucralose-containing edible strips to a set of five intensity-matched sucrose solutions. When compared to the solution test, edible strips required approximately the same number of steps to identify the preferred amount of sweet taste stimulus. Both approaches yielded similar distribution patterns for the preferred amount of sweet taste stimulus. In addition, taste intensity values for the preferred amount of sucralose in strips were similar to that of sucrose in solution. The hedonic values for the preferred amount of sucralose were lower than for sucrose, but the taste quality of the preferred sucralose strip was described as sweet. When taste intensity values between sucralose strips and sucralose solutions containing identical amounts of taste stimulus were compared, sucralose strips produced a greater taste intensity and more positive hedonic response. A preference test that uses edible strips for stimulus delivery should be useful for identifying preferences for sweet taste in young children, and in clinical populations. This test should also be useful for identifying sweet taste preferences outside of the lab or clinic. Finally, edible strips should be useful for developing preference tests for other primary taste stimuli and for taste mixtures. PMID:24225255

A method to incorporate leakage and head scatter corrections into a tomotherapy inverse treatment planning algorithm

NASA Astrophysics Data System (ADS)

Holmes, Timothy W.

2001-01-01

A detailed tomotherapy inverse treatment planning method is described which incorporates leakage and head scatter corrections during each iteration of the optimization process, allowing these effects to be directly accounted for in the optimized dose distribution. It is shown that the conventional inverse planning method for optimizing incident intensity can be extended to include a `concurrent' leaf sequencing operation from which the leakage and head scatter corrections are determined. The method is demonstrated using the steepest-descent optimization technique with constant step size and a least-squared error objective. The method was implemented using the MATLAB scientific programming environment and its feasibility demonstrated for 2D test cases simulating treatment delivery using a single coplanar rotation. The results indicate that this modification does not significantly affect convergence of the intensity optimization method when exposure times of individual leaves are stratified to a large number of levels (>100) during leaf sequencing. In general, the addition of aperture dependent corrections, especially `head scatter', reduces incident fluence in local regions of the modulated fan beam, resulting in increased exposure times for individual collimator leaves. These local variations can result in 5% or greater local variation in the optimized dose distribution compared to the uncorrected case. The overall efficiency of the modified intensity optimization algorithm is comparable to that of the original unmodified case.

Radiation shielding materials and containers incorporating same

DOEpatents

Mirsky, Steven M.; Krill, Stephen J.; Murray, Alexander P.

2005-11-01

An improved radiation shielding material and storage systems for radioactive materials incorporating the same. The PYRolytic Uranium Compound ("PYRUC") shielding material is preferably formed by heat and/or pressure treatment of a precursor material comprising microspheres of a uranium compound, such as uranium dioxide or uranium carbide, and a suitable binder. The PYRUC shielding material provides improved radiation shielding, thermal characteristic, cost and ease of use in comparison with other shielding materials. The shielding material can be used to form containment systems, container vessels, shielding structures, and containment storage areas, all of which can be used to house radioactive waste. The preferred shielding system is in the form of a container for storage, transportation, and disposal of radioactive waste. In addition, improved methods for preparing uranium dioxide and uranium carbide microspheres for use in the radiation shielding materials are also provided.

Radiation Shielding Materials and Containers Incorporating Same

DOEpatents

Mirsky, Steven M.; Krill, Stephen J.; and Murray, Alexander P.

2005-11-01

An improved radiation shielding material and storage systems for radioactive materials incorporating the same. The PYRolytic Uranium Compound (''PYRUC'') shielding material is preferably formed by heat and/or pressure treatment of a precursor material comprising microspheres of a uranium compound, such as uranium dioxide or uranium carbide, and a suitable binder. The PYRUC shielding material provides improved radiation shielding, thermal characteristic, cost and ease of use in comparison with other shielding materials. The shielding material can be used to form containment systems, container vessels, shielding structures, and containment storage areas, all of which can be used to house radioactive waste. The preferred shielding system is in the form of a container for storage, transportation, and disposal of radioactive waste. In addition, improved methods for preparing uranium dioxide and uranium carbide microspheres for use in the radiation shielding materials are also provided.

WHAT IS THE ROLE OF COMMUNITY PREFERENCE INFORMATION IN HEALTH TECHNOLOGY ASSESSMENT DECISION MAKING? A CASE STUDY OF COLORECTAL CANCER SCREENING.

PubMed

Wortley, Sally; Flitcroft, Kathy; Howard, Kirsten

2015-01-01

The aim of this study was to determine the role of community preference information from discrete choice studies of colorectal cancer (CRC) screening in health technology assessment (HTA) reports and subsequent policy decisions. We undertook a systematic review of discrete choice studies of CRC screening. Included studies were reviewed to assess the policy context of the research. For those studies that cited a recent or pending review of CRC screening, further searches were undertaken to determine the extent to which community preference information was incorporated into the HTA decision-making process. Eight discrete choice studies that evaluated preferences for CRC screening were identified. Four of these studies referred to a national or local review of CRC screening in three countries: Australia, Canada, and the Netherlands. Our review of subsequently released health policy documents showed that while consideration was given to community views on CRC, policy was not informed by discrete choice evidence. Preferences and values of patients are increasingly being considered "evidence" to be incorporated into HTA reports. Discrete choice methodology is a rigorous quantitative method for eliciting preferences and while as a methodology it is growing in profile, it would appear that the results of such research are not being systematically translated or integrated into HTA reports. A formalized approach is needed to incorporate preference literature into the HTA decision-making process.

Gender identity rather than sexual orientation impacts on facial preferences.

PubMed

Ciocca, Giacomo; Limoncin, Erika; Cellerino, Alessandro; Fisher, Alessandra D; Gravina, Giovanni Luca; Carosa, Eleonora; Mollaioli, Daniele; Valenzano, Dario R; Mennucci, Andrea; Bandini, Elisa; Di Stasi, Savino M; Maggi, Mario; Lenzi, Andrea; Jannini, Emmanuele A

2014-10-01

Differences in facial preferences between heterosexual men and women are well documented. It is still a matter of debate, however, how variations in sexual identity/sexual orientation may modify the facial preferences. This study aims to investigate the facial preferences of male-to-female (MtF) individuals with gender dysphoria (GD) and the influence of short-term/long-term relationships on facial preference, in comparison with healthy subjects. Eighteen untreated MtF subjects, 30 heterosexual males, 64 heterosexual females, and 42 homosexual males from university students/staff, at gay events, and in Gender Clinics were shown a composite male or female face. The sexual dimorphism of these pictures was stressed or reduced in a continuous fashion through an open-source morphing program with a sequence of 21 pictures of the same face warped from a feminized to a masculinized shape. An open-source morphing program (gtkmorph) based on the X-Morph algorithm. MtF GD subjects and heterosexual females showed the same pattern of preferences: a clear preference for less dimorphic (more feminized) faces for both short- and long-term relationships. Conversely, both heterosexual and homosexual men selected significantly much more dimorphic faces, showing a preference for hyperfeminized and hypermasculinized faces, respectively. These data show that the facial preferences of MtF GD individuals mirror those of the sex congruent with their gender identity. Conversely, heterosexual males trace the facial preferences of homosexual men, indicating that changes in sexual orientation do not substantially affect preference for the most attractive faces. © 2014 International Society for Sexual Medicine.

Contextual classification of multispectral image data: Approximate algorithm

NASA Technical Reports Server (NTRS)

Tilton, J. C. (Principal Investigator)

1980-01-01

An approximation to a classification algorithm incorporating spatial context information in a general, statistical manner is presented which is computationally less intensive. Classifications that are nearly as accurate are produced.

Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI.

PubMed

Hu, Changwei; Qu, Xiaobo; Guo, Di; Bao, Lijun; Chen, Zhong

2011-09-01

Undersampling k-space is an effective way to decrease acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of magnetic resonance images, which often contain important information for clinical diagnosis. Moreover, k-space data is often contaminated by the noise signals of unknown intensity. To better preserve the edge features while suppressing the aliasing artifacts and noises, we present a new wavelet-based algorithm for undersampled MRI reconstruction. The algorithm solves the image reconstruction as a standard optimization problem including a ℓ(2) data fidelity term and ℓ(1) sparsity regularization term. Rather than manually setting the regularization parameter for the ℓ(1) term, which is directly related to the threshold, an automatic estimated threshold adaptive to noise intensity is introduced in our proposed algorithm. In addition, a prior matrix based on edge correlation in wavelet domain is incorporated into the regularization term. Compared with nonlinear conjugate gradient descent algorithm, iterative shrinkage/thresholding algorithm, fast iterative soft-thresholding algorithm and the iterative thresholding algorithm using exponentially decreasing threshold, the proposed algorithm yields reconstructions with better edge recovery and noise suppression. Copyright © 2011 Elsevier Inc. All rights reserved.

A preference test for sweet taste that uses edible strips.

PubMed

Smutzer, Gregory; Patel, Janki Y; Stull, Judith C; Abarintos, Ray A; Khan, Neiladri K; Park, Kevin C

2014-02-01

A novel delivery method is described for the rapid determination of taste preferences for sweet taste in humans. This forced-choice paired comparison approach incorporates the non-caloric sweetener sucralose into a set of one-inch square edible strips for the rapid determination of sweet taste preferences. When compared to aqueous sucrose solutions, significantly lower amounts of sucralose were required to identify the preference for sweet taste. The validity of this approach was determined by comparing sweet taste preferences obtained with five different sucralose-containing edible strips to a set of five intensity-matched sucrose solutions. When compared to the solution test, edible strips required approximately the same number of steps to identify the preferred amount of sweet taste stimulus. Both approaches yielded similar distribution patterns for the preferred amount of sweet taste stimulus. In addition, taste intensity values for the preferred amount of sucralose in strips were similar to that of sucrose in solution. The hedonic values for the preferred amount of sucralose were lower than for sucrose, but the taste quality of the preferred sucralose strip was described as sweet. When taste intensity values between sucralose strips and sucralose solutions containing identical amounts of taste stimulus were compared, sucralose strips produced a greater taste intensity and more positive hedonic response. A preference test that uses edible strips for stimulus delivery should be useful for identifying preferences for sweet taste in young children, and in clinical populations. This test should also be useful for identifying sweet taste preferences outside of the lab or clinic. Finally, edible strips should be useful for developing preference tests for other primary taste stimuli and for taste mixtures. Copyright © 2013 Elsevier Ltd. All rights reserved.

A fuzzy set preference model for market share analysis

NASA Technical Reports Server (NTRS)

Turksen, I. B.; Willson, Ian A.

1992-01-01

Consumer preference models are widely used in new product design, marketing management, pricing, and market segmentation. The success of new products depends on accurate market share prediction and design decisions based on consumer preferences. The vague linguistic nature of consumer preferences and product attributes, combined with the substantial differences between individuals, creates a formidable challenge to marketing models. The most widely used methodology is conjoint analysis. Conjoint models, as currently implemented, represent linguistic preferences as ratio or interval-scaled numbers, use only numeric product attributes, and require aggregation of individuals for estimation purposes. It is not surprising that these models are costly to implement, are inflexible, and have a predictive validity that is not substantially better than chance. This affects the accuracy of market share estimates. A fuzzy set preference model can easily represent linguistic variables either in consumer preferences or product attributes with minimal measurement requirements (ordinal scales), while still estimating overall preferences suitable for market share prediction. This approach results in flexible individual-level conjoint models which can provide more accurate market share estimates from a smaller number of more meaningful consumer ratings. Fuzzy sets can be incorporated within existing preference model structures, such as a linear combination, using the techniques developed for conjoint analysis and market share estimation. The purpose of this article is to develop and fully test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation), and how much to make (market share

Effective Partnering in Conducting Benefit-Risk Patient Preference Studies: Perspectives From a Patient Advocacy Organization, a Pharmaceutical Company, and Academic Stated-Preference Researchers.

PubMed

Wolka, Anne M; Fairchild, Angelyn O; Reed, Shelby D; Anglin, Greg; Johnson, F Reed; Siegel, Michael; Noel, Rebecca

2017-01-01

Formal incorporation of patients' perspectives is becoming increasingly important in medical product development and decision making. This article shares practical advice regarding how patient advocacy organizations, the pharmaceutical industry, and academic experts in stated-preference research can effectively partner on benefit-risk patient preference studies. The authors partnered on a benefit-risk patient preference study related to the treatment of psoriasis. The authors from Duke Clinical Research Institute also share their experiences in collaborating with numerous other organizations in conducting benefit-risk patient preference studies. Upon initiation of the study partnership with appropriate experts, training is important to ensure all collaborators have a common understanding of the methodology, what objectives stated-preference methods can support, and expectations for the project. To the extent possible, partners should align on and document relevant clinical and logistical details prior to study implementation. During study implementation, partners should use good communication practices and document and maintain a record of any changes to the original plan. Presentation of the study results should be tailored to the particular audience, with the appropriate partner leading the presentation based on its format and audience. Partners from patient advocacy organizations, the pharmaceutical industry, and academia can effectively collaborate on benefit-risk patient preference studies with sufficient planning and ongoing communication. This article is a call for action for other organizations to engage in sharing of experiences regarding effective partnering in quantifying patient preferences in medical product development.

Identifying protein kinase target preferences using mass spectrometry

PubMed Central

Douglass, Jacqueline; Gunaratne, Ruwan; Bradford, Davis; Saeed, Fahad; Hoffert, Jason D.; Steinbach, Peter J.; Pisitkun, Trairak

2012-01-01

A general question in molecular physiology is how to identify candidate protein kinases corresponding to a known or hypothetical phosphorylation site in a protein of interest. It is generally recognized that the amino acid sequence surrounding the phosphorylation site provides information that is relevant to identification of the cognate protein kinase. Here, we present a mass spectrometry-based method for profiling the target specificity of a given protein kinase as well as a computational tool for the calculation and visualization of the target preferences. The mass spectrometry-based method identifies sites phosphorylated in response to in vitro incubation of protein mixtures with active recombinant protein kinases followed by standard phosphoproteomic methodologies. The computational tool, called “PhosphoLogo,” uses an information-theoretic algorithm to calculate position-specific amino acid preferences and anti-preferences from the mass-spectrometry data (http://helixweb.nih.gov/PhosphoLogo/). The method was tested using protein kinase A (catalytic subunit α), revealing the well-known preference for basic amino acids in positions −2 and −3 relative to the phosphorylated amino acid. It also provides evidence for a preference for amino acids with a branched aliphatic side chain in position +1, a finding compatible with known crystal structures of protein kinase A. The method was also employed to profile target preferences and anti-preferences for 15 additional protein kinases with potential roles in regulation of epithelial transport: CK2, p38, AKT1, SGK1, PKCδ, CaMK2δ, DAPK1, MAPKAPK2, PKD3, PIM1, OSR1, STK39/SPAK, GSK3β, Wnk1, and Wnk4. PMID:22723110

pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC.

PubMed

Jia, Jianhua; Zhang, Liuxia; Liu, Zi; Xiao, Xuan; Chou, Kuo-Chen

2016-10-15

Sumoylation is a post-translational modification (PTM) process, in which small ubiquitin-related modifier (SUMO) is attaching by covalent bonds to substrate protein. It is critical to many different biological processes such as replicating genome, expressing gene, localizing and stabilizing proteins; unfortunately, it is also involved with many major disorders including Alzheimer's and Parkinson's diseases. Therefore, for both basic research and drug development, it is important to identify the sumoylation sites in proteins. To address such a problem, we developed a predictor called pSumo-CD by incorporating the sequence-coupled information into the general pseudo-amino acid composition (PseAAC) and introducing the covariance discriminant (CD) algorithm, in which a bias-adjustment term, which has the function to automatically adjust the errors caused by the bias due to the imbalance of training data, had been incorporated. Rigorous cross-validations indicated that the new predictor remarkably outperformed the existing state-of-the-art prediction method for the same purpose. For the convenience of most experimental scientists, a user-friendly web-server for pSumo-CD has been established at http://www.jci-bioinfo.cn/pSumo-CD, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. jjia@gordonlifescience.org, xxiao@gordonlifescience.org or kcchou@gordonlifescience.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Improved collaborative filtering recommendation algorithm of similarity measure

NASA Astrophysics Data System (ADS)

Zhang, Baofu; Yuan, Baoping

2017-05-01

The Collaborative filtering recommendation algorithm is one of the most widely used recommendation algorithm in personalized recommender systems. The key is to find the nearest neighbor set of the active user by using similarity measure. However, the methods of traditional similarity measure mainly focus on the similarity of user common rating items, but ignore the relationship between the user common rating items and all items the user rates. And because rating matrix is very sparse, traditional collaborative filtering recommendation algorithm is not high efficiency. In order to obtain better accuracy, based on the consideration of common preference between users, the difference of rating scale and score of common items, this paper presents an improved similarity measure method, and based on this method, a collaborative filtering recommendation algorithm based on similarity improvement is proposed. Experimental results show that the algorithm can effectively improve the quality of recommendation, thus alleviate the impact of data sparseness.

Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

PubMed Central

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm. PMID:23737718

Interactive genetic algorithm for user-centered design of distributed conservation practices in a watershed: An examination of user preferences in objective space and user behavior

NASA Astrophysics Data System (ADS)

Piemonti, Adriana Debora; Babbar-Sebens, Meghna; Mukhopadhyay, Snehasis; Kleinberg, Austin

2017-05-01

Interactive Genetic Algorithms (IGA) are advanced human-in-the-loop optimization methods that enable humans to give feedback, based on their subjective and unquantified preferences and knowledge, during the algorithm's search process. While these methods are gaining popularity in multiple fields, there is a critical lack of data and analyses on (a) the nature of interactions of different humans with interfaces of decision support systems (DSS) that employ IGA in water resources planning problems and on (b) the effect of human feedback on the algorithm's ability to search for design alternatives desirable to end-users. In this paper, we present results and analyses of observational experiments in which different human participants (surrogates and stakeholders) interacted with an IGA-based, watershed DSS called WRESTORE to identify plans of conservation practices in a watershed. The main goal of this paper is to evaluate how the IGA adapts its search process in the objective space to a user's feedback, and identify whether any similarities exist in the objective space of plans found by different participants. Some participants focused on the entire watershed, while others focused only on specific local subbasins. Additionally, two different hydrology models were used to identify any potential differences in interactive search outcomes that could arise from differences in the numerical values of benefits displayed to participants. Results indicate that stakeholders, in comparison to their surrogates, were more likely to use multiple features of the DSS interface to collect information before giving feedback, and dissimilarities existed among participants in the objective space of design alternatives.

A Coulomb collision algorithm for weighted particle simulations

NASA Technical Reports Server (NTRS)

Miller, Ronald H.; Combi, Michael R.

1994-01-01

A binary Coulomb collision algorithm is developed for weighted particle simulations employing Monte Carlo techniques. Charged particles within a given spatial grid cell are pair-wise scattered, explicitly conserving momentum and implicitly conserving energy. A similar algorithm developed by Takizuka and Abe (1977) conserves momentum and energy provided the particles are unweighted (each particle representing equal fractions of the total particle density). If applied as is to simulations incorporating weighted particles, the plasma temperatures equilibrate to an incorrect temperature, as compared to theory. Using the appropriate pairing statistics, a Coulomb collision algorithm is developed for weighted particles. The algorithm conserves energy and momentum and produces the appropriate relaxation time scales as compared to theoretical predictions. Such an algorithm is necessary for future work studying self-consistent multi-species kinetic transport.

Men's Preferences for Physical Activity Interventions: An Exploratory Study Using a Factorial Survey Design Created With R Software.

PubMed

Chatfield, Sheryl L; Gamble, Abigail; Hallam, Jeffrey S

2018-03-01

Effective exercise interventions are needed to improve quality of life and decrease the impact of chronic disease. Researchers suggest males have been underrepresented in exercise intervention studies, resulting in less understanding of their exercise practices. Findings from preference survey methods suggest reasonable association between preference and behavior. The purpose of the research described in this article was to use factorial survey, a preference method, to identify the characteristics of exercise interventions most likely to appeal to male participants, so preferences might be incorporated into future intervention research. The research was guided by the framework of Bandura's social cognitive theory, such that variations in individual, environmental, and behavioral factors were incorporated into vignettes. Participants included 53 adult male nonadministrative staff and contract employees at a public university in the Southeastern United States, who each scored 8 vignettes resulting in 423 observations. Multilevel models were used to assess the influence of the factors. Participants scored vignettes that included exercising with a single partner, playing basketball, and exercising in the evening higher than vignettes with other options. Qualitative analysis of an open response item identified additional alternatives in group size, participant desire for coaching support, and interest in programs that incorporate a range of activity alternatives. Findings from this research were consistent with elements of social cognitive theory as applied to health promotion. Factorial surveys potentially provide a resource effective means of identifying participants' preferences for use when planning interventions. The addition of a single qualitative item helped clarify and expand findings from statistical analysis.

Developing a Screening Algorithm for Type II Diabetes Mellitus in the Resource-Limited Setting of Rural Tanzania.

PubMed

West, Caroline; Ploth, David; Fonner, Virginia; Mbwambo, Jessie; Fredrick, Francis; Sweat, Michael

2016-04-01

Noncommunicable diseases are on pace to outnumber infectious disease as the leading cause of death in sub-Saharan Africa, yet many questions remain unanswered with concern toward effective methods of screening for type II diabetes mellitus (DM) in this resource-limited setting. We aim to design a screening algorithm for type II DM that optimizes sensitivity and specificity of identifying individuals with undiagnosed DM, as well as affordability to health systems and individuals. Baseline demographic and clinical data, including hemoglobin A1c (HbA1c), were collected from 713 participants using probability sampling of the general population. We used these data, along with model parameters obtained from the literature, to mathematically model 8 purposed DM screening algorithms, while optimizing the sensitivity and specificity using Monte Carlo and Latin Hypercube simulation. An algorithm that combines risk assessment and measurement of fasting blood glucose was found to be superior for the most resource-limited settings (sensitivity 68%, sensitivity 99% and cost per patient having DM identified as $2.94). Incorporating HbA1c testing improves the sensitivity to 75.62%, but raises the cost per DM case identified to $6.04. The preferred algorithms are heavily biased to diagnose those with more severe cases of DM. Using basic risk assessment tools and fasting blood sugar testing in lieu of HbA1c testing in resource-limited settings could allow for significantly more feasible DM screening programs with reasonable sensitivity and specificity. Copyright © 2016 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

A novel approach based on preference-based index for interval bilevel linear programming problem.

PubMed

Ren, Aihong; Wang, Yuping; Xue, Xingsi

2017-01-01

This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ -optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Patient preferences for diabetes-related complications in Taiwan.

PubMed

Lin, Yi-Ju; Wang, Chin-Yuan; Cheng, Ssu-Wei; Ko, Yu

2018-05-25

As the prevalence of diabetes mellitus (DM) continues to increase rapidly, there has been a rising need not only to assess the clinical outcomes but also the impact of DM on the health-related quality of life (HRQoL) of affected individuals. Most previous studies have found that having complications is strongly associated with decreased HRQoL in DM patients. As such, it is crucial to measure individuals' preferences for DM-related complications in order to assess the magnitude of complications' effect on overall HRQoL. In addition, preference scores are an essential component of cost-utility analyses (CUAs), which studies can incorporate healthcare costs, HRQoL and clinical outcomes of DM into one analysis. The aims of this study were to assess the preference scores of DM-related complications using both the standard gamble (SG), a choice-based method, and visual analogue scale (VAS), a scaling method. We also aimed to assess several possible factors that might be associated with the preference scores of the complications. This is a cross-sectional interview-administered survey, and 213 patients with type 2 DM were interviewed. The respondents' preference scores of eleven DM-related complications were obtained using VAS and SG techniques. Demographic information, clinical characteristics and risk attitudes were also collected to explore factors that may affect patients' preference scores. Nearly one quarter of participants in Taiwan ranked at least one of the complications worse than death. The mean VAS scores ranged from 0.004 (amputation) to 0.47 (nocturnal hypoglycemia) while the mean adjusted SG scores ranged from 0.30 (blindness) to 0.66 (nocturnal hypoglycemia). There were significant differences in all of the complications' preference scores depending on risk attitudes. Both the VAS and SG methods were used to elicit the preference scores of DM-related complications, and the preference scores derived could be useful for future cost utility analyses.

A divide-and-conquer algorithm for large-scale de novo transcriptome assembly through combining small assemblies from existing algorithms.

PubMed

Sze, Sing-Hoi; Parrott, Jonathan J; Tarone, Aaron M

2017-12-06

While the continued development of high-throughput sequencing has facilitated studies of entire transcriptomes in non-model organisms, the incorporation of an increasing amount of RNA-Seq libraries has made de novo transcriptome assembly difficult. Although algorithms that can assemble a large amount of RNA-Seq data are available, they are generally very memory-intensive and can only be used to construct small assemblies. We develop a divide-and-conquer strategy that allows these algorithms to be utilized, by subdividing a large RNA-Seq data set into small libraries. Each individual library is assembled independently by an existing algorithm, and a merging algorithm is developed to combine these assemblies by picking a subset of high quality transcripts to form a large transcriptome. When compared to existing algorithms that return a single assembly directly, this strategy achieves comparable or increased accuracy as memory-efficient algorithms that can be used to process a large amount of RNA-Seq data, and comparable or decreased accuracy as memory-intensive algorithms that can only be used to construct small assemblies. Our divide-and-conquer strategy allows memory-intensive de novo transcriptome assembly algorithms to be utilized to construct large assemblies.

Research on cascading failure in multilayer network with different coupling preference

NASA Astrophysics Data System (ADS)

Zhang, Yong; Jin, Lei; Wang, Xiao Juan

This paper is aimed at constructing robust multilayer networks against cascading failure. Considering link protection strategies in reality, we design a cascading failure model based on load distribution and extend it to multilayer. We use the cascading failure model to deduce the scale of the largest connected component after cascading failure, from which we can find that the performance of four kinds of load distribution strategies associates with the load ratio of the current edge to its adjacent edge. Coupling preference is a typical characteristic in multilayer networks which corresponds to the network robustness. The coupling preference of multilayer networks is divided into two forms: the coupling preference in layers and the coupling preference between layers. To analyze the relationship between the coupling preference and the multilayer network robustness, we design a construction algorithm to generate multilayer networks with different coupling preferences. Simulation results show that the load distribution based on the node betweenness performs the best. When the coupling coefficient in layers is zero, the scale-free network is the most robust. In the random network, the assortative coupling in layers is more robust than the disassortative coupling. For the coupling preference between layers, the assortative coupling between layers is more robust than the disassortative coupling both in the scale free network and the random network.

Patient or physician preferences for decision analysis: the prenatal genetic testing decision.

PubMed

Heckerling, P S; Verp, M S; Albert, N

1999-01-01

The choice between amniocentesis and chorionic villus sampling for prenatal genetic testing involves tradeoffs of the benefits and risks of the tests. Decision analysis is a method of explicitly weighing such tradeoffs. The authors examined the relationship between prenatal test choices made by patients and the choices prescribed by decision-analytic models based on their preferences, and separate models based on the preferences of their physicians. Preferences were assessed using written scenarios describing prenatal testing outcomes, and were recorded on linear rating scales. After adjustment for sociodemographic and obstetric confounders, test choice was significantly associated with the choice of decision models based on patient preferences (odds ratio 4.44; Cl, 2.53 to 7.78), but not with the choice of models based on the preferences of the physicians (odds ratio 1.60; Cl, 0.79 to 3.26). Agreement between decision analyses based on patient preferences and on physician preferences was little better than chance (kappa = 0.085+/-0.063). These results were robust both to changes in the decision-analytic probabilities and to changes in the model structure itself to simulate non-expected utility decision rules. The authors conclude that patient but not physician preferences, incorporated in decision models, correspond to the choice of amniocentesis or chorionic villus sampling made by the patient. Nevertheless, because patient preferences were assessed after referral for genetic testing, prospective preference-assessment studies will be necessary to confirm this association.

INCORPORATING ENVIRONMENTAL AND ECONOMIC CONSIDERATIONS INTO PROCESS DESIGN: THE WASTE REDUCTION (WAR) ALGORITHM

EPA Science Inventory

A general theory known as the WAste Reduction (WASR) algorithm has been developed to describe the flow and the generation of potential environmental impact through a chemical process. This theory integrates environmental impact assessment into chemical process design Potential en...

Guideline attribute and implementation preferences among physicians in multiple health systems.

PubMed

Stone, Tamara T; Schweikhart, Sharon B; Mantese, Annamarie; Sonnad, Seema S

2005-01-01

Although practice guidelines are effective in assisting providers with clinical decision making, ineffective implementation strategies often prevent their use in practice. This study aimed to understand physician preferences for guideline format, placement, content, evidence, and learning strategies in different clinical environments. Semistructured telephone interviews were conducted with 500 randomly selected physicians from 4 major US health systems who were involved in the treatment of patients with acute myocardial infarction or pediatric asthma. Paired sample t tests and Tukey's method of comparisons determined the relative ranking of physicians' guideline implementation preferences. Physicians preferred guidelines located on the front of the patient chart, in palm pilots, or in progress notes and presented as flow charts/flow diagrams, algorithms, or preprinted orders that contain strategies to minimize readmits/encourage self-management and immediate treatment flows. Discussions with colleagues and continuing medical education are the most effective strategies for encouraging guideline use, and randomized controlled trials remain the most persuasive medical evidence. Health care organizations must align guideline implementation efforts with physician preferences to encourage utilization. The results of this study reveal systematic physician preferences for guideline implementation that can be applied to clinical settings to encourage guideline use by physicians.

Medical Decision Algorithm for Pre-Hospital Trauma Care. Phase I.

DTIC Science & Technology

1996-09-01

Algorithm for Pre-Hospital Trauma Care PRINCIPAL INVESTIGATOR: Donald K. Wedding, P.E., Ph.D CONTRACTING ORGANIZATION : Photonics Systems, Incorporated... ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER Photonics Systems, Incorporated Northwood, Ohio 43619 9. SPONSORING...three areas: 1) data acquisition, 2) neural network design, and 3) system architechture design. In the first area of this research, a triage database

A Diagonal-Steering-Based Binaural Beamforming Algorithm Incorporating a Diagonal Speech Localizer for Persons With Bilateral Hearing Impairment.

PubMed

Lee, Jun Chang; Nam, Kyoung Won; Jang, Dong Pyo; Kim, In Young

2015-12-01

Previously suggested diagonal-steering algorithms for binaural hearing support devices have commonly assumed that the direction of the speech signal is known in advance, which is not always the case in many real circumstances. In this study, a new diagonal-steering-based binaural speech localization (BSL) algorithm is proposed, and the performances of the BSL algorithm and the binaural beamforming algorithm, which integrates the BSL and diagonal-steering algorithms, were evaluated using actual speech-in-noise signals in several simulated listening scenarios. Testing sounds were recorded in a KEMAR mannequin setup and two objective indices, improvements in signal-to-noise ratio (SNRi ) and segmental SNR (segSNRi ), were utilized for performance evaluation. Experimental results demonstrated that the accuracy of the BSL was in the 90-100% range when input SNR was -10 to +5 dB range. The average differences between the γ-adjusted and γ-fixed diagonal-steering algorithms (for -15 to +5 dB input SNR) in the talking in the restaurant scenario were 0.203-0.937 dB for SNRi and 0.052-0.437 dB for segSNRi , and in the listening while car driving scenario, the differences were 0.387-0.835 dB for SNRi and 0.259-1.175 dB for segSNRi . In addition, the average difference between the BSL-turned-on and the BSL-turned-off cases for the binaural beamforming algorithm in the listening while car driving scenario was 1.631-4.246 dB for SNRi and 0.574-2.784 dB for segSNRi . In all testing conditions, the γ-adjusted diagonal-steering and BSL algorithm improved the values of the indices more than the conventional algorithms. The binaural beamforming algorithm, which integrates the proposed BSL and diagonal-steering algorithm, is expected to improve the performance of the binaural hearing support devices in noisy situations. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

A hierarchical transition state search algorithm

NASA Astrophysics Data System (ADS)

del Campo, Jorge M.; Köster, Andreas M.

2008-07-01

A hierarchical transition state search algorithm is developed and its implementation in the density functional theory program deMon2k is described. This search algorithm combines the double ended saddle interpolation method with local uphill trust region optimization. A new formalism for the incorporation of the distance constrain in the saddle interpolation method is derived. The similarities between the constrained optimizations in the local trust region method and the saddle interpolation are highlighted. The saddle interpolation and local uphill trust region optimizations are validated on a test set of 28 representative reactions. The hierarchical transition state search algorithm is applied to an intramolecular Diels-Alder reaction with several internal rotors, which makes automatic transition state search rather challenging. The obtained reaction mechanism is discussed in the context of the experimentally observed product distribution.

Realistic Free-Spins Features Increase Preference for Slot Machines.

PubMed

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Subjective preference evaluation of sound fields by performing singers

NASA Astrophysics Data System (ADS)

Noson, Dennis

2003-08-01

A model of the auditory process is proposed for performing singers, which incorporates the added signal from bone conduction, as well as the psychological distance for subjective preference of the performer from the acoustic sound field of the stage. The explanatory power of previous scientific studies of vocal stage acoustics has been limited by a lack of an underlying theory of performer preference. Ando's theory, using the autocorrelation function (ACF) for parametrizing temporal factors, was applied to interpretation of singer sound field preference determined by the pair comparison method. Melisma style singing (no lyrics) was shown to increase the preferred delay time of reflections from a mean of 14 ms with lyrics to 23 ms without (p<0.05). The extent of the shift in preferred time delay was shown to be directly related to minima of the effective duration of the running ACF, (τe)min, calculated from each singer's voice. Voice matching experiments for singers demonstrated a strong overestimate of the voice outside the head compared with the singer's own voice (22.4 dB overestimate, p<0.01). Individual singer melisma singing delay preferences were compared for ``ah'' versus ``hum'' syllables, and the increased delay preference (41 ms) was shown to be correlated with (τe)min (r2<0.68, p<0.01). When the proposed bone conduction model was applied, using the measured overestimate of sound level of the singer's own voice for each singer (9.9 dB mean overestimate difference between ``ah'' and ``hum,'' p<0.01), the relationship of singer preference to (τe)min was improved (r2=0.97, p<0.01). Thesis advisor: Yoichi Ando Copies of this thesis are available from the author by inquiry at BRC Acoustics, 1741 First Avenue South, Seattle, WA 98134 USA. E-mail address: dnoson@brcacoustics.com

TOPSIS-based consensus model for group decision-making with incomplete interval fuzzy preference relations.

PubMed

Liu, Fang; Zhang, Wei-Guo

2014-08-01

Due to the vagueness of real-world environments and the subjective nature of human judgments, it is natural for experts to estimate their judgements by using incomplete interval fuzzy preference relations. In this paper, based on the technique for order preference by similarity to ideal solution method, we present a consensus model for group decision-making (GDM) with incomplete interval fuzzy preference relations. To do this, we first define a new consistency measure for incomplete interval fuzzy preference relations. Second, a goal programming model is proposed to estimate the missing interval preference values and it is guided by the consistency property. Third, an ideal interval fuzzy preference relation is constructed by using the induced ordered weighted averaging operator, where the associated weights of characterizing the operator are based on the defined consistency measure. Fourth, a similarity degree between complete interval fuzzy preference relations and the ideal one is defined. The similarity degree is related to the associated weights, and used to aggregate the experts' preference relations in such a way that more importance is given to ones with the higher similarity degree. Finally, a new algorithm is given to solve the GDM problem with incomplete interval fuzzy preference relations, which is further applied to partnership selection in formation of virtual enterprises.

A chaos wolf optimization algorithm with self-adaptive variable step-size

NASA Astrophysics Data System (ADS)

Zhu, Yong; Jiang, Wanlu; Kong, Xiangdong; Quan, Lingxiao; Zhang, Yongshun

2017-10-01

To explore the problem of parameter optimization for complex nonlinear function, a chaos wolf optimization algorithm (CWOA) with self-adaptive variable step-size was proposed. The algorithm was based on the swarm intelligence of wolf pack, which fully simulated the predation behavior and prey distribution way of wolves. It possessed three intelligent behaviors such as migration, summons and siege. And the competition rule as "winner-take-all" and the update mechanism as "survival of the fittest" were also the characteristics of the algorithm. Moreover, it combined the strategies of self-adaptive variable step-size search and chaos optimization. The CWOA was utilized in parameter optimization of twelve typical and complex nonlinear functions. And the obtained results were compared with many existing algorithms, including the classical genetic algorithm, the particle swarm optimization algorithm and the leader wolf pack search algorithm. The investigation results indicate that CWOA possess preferable optimization ability. There are advantages in optimization accuracy and convergence rate. Furthermore, it demonstrates high robustness and global searching ability.

Depressive symptoms and decision-making preferences in patients with comorbid illnesses.

PubMed

Moise, Nathalie; Ye, Siqin; Alcántara, Carmela; Davidson, Karina W; Kronish, Ian

2017-01-01

Shared decision-making (SDM) is increasingly promoted in the primary care setting, but depressive symptoms, which are associated with cognitive changes, may influence decision-making preferences. We sought to assess whether elevated depressive symptoms are associated with decision-making preference in patients with comorbid chronic illness. We enrolled 195 patients ≥18years old with uncontrolled hypertension from two urban, academic primary care clinics. Depressive symptoms were assessed using the 8-item Patient Health Questionnaire. Clinician-directed decision-making preference was assessed according to the Control Preference Scale. The impact of depressive symptoms on decision-making preference was assessed using generalized linear mixed models adjusted for age, gender, race, ethnicity, education, Medicaid status, Charlson Comorbidity Index, partner status, and clustering within clinicians. The mean age was 64.2years; 72% were women, 77% Hispanic, 38% Black, and 33% had elevated depressive symptoms. Overall, 35% of patients preferred clinician-directed decision-making, 19% mostly clinician-directed, 39% shared, and 7% some or little clinician-input. Patients with (vs. without) elevated depressive symptoms were more likely to prefer clinician-directed decision-making (46% versus 29%; p=0.02; AOR 2.51, 95% CI 1.30-4.85, p=0.005). Remitted depressive symptoms (vs. never depressed) were not associated with preference. Elevated depressive symptoms are associated with preference for clinician-directed decision-making. We suggest that clinicians should be aware of this effect when incorporating preference into their communication styles and take an active role in eliciting patient values and exchanging information about treatment choice, all important components of shared decision-making, particularly when patients are depressed. Copyright © 2015 Elsevier Inc. All rights reserved.

Mode of delivery preferences in a diverse population of pregnant women.

PubMed

Yee, Lynn M; Kaimal, Anjali J; Houston, Kathryn A; Wu, Erica; Thiet, Mari-Paule; Nakagawa, Sanae; Caughey, Aaron B; Firouzian, Atoosa; Kuppermann, Miriam

2015-03-01

The objective of the study was to assess women's preferences for vaginal vs cesarean delivery in 4 contexts: prior cesarean delivery, twins, breech presentation, and absent indication for cesarean. This was a cross-sectional study of pregnant women at 24-40 weeks' gestation. After assessing stated preferences for vaginal or cesarean delivery, we used the standard gamble metric to measure the strength of these preferences and the time tradeoff metric to determine how women value the potential processes and outcomes associated with these 2 delivery approaches. Among the 240 participants, 90.8% had a stated preference for vaginal delivery. Across the 4 contexts, these women indicated that, on average, they would accept a 59-75% chance of an attempted vaginal birth ending in a cesarean delivery before choosing a planned cesarean delivery, indicating strong preferences for spontaneous, uncomplicated vaginal delivery. Variations in preferences for labor processes emerged. Although uncomplicated labor ending in vaginal birth was assigned mean utilities of 0.993 or higher (on a 0-1 scale, with higher scores indicating more preferred outcomes), the need for oxytocin, antibiotics, or operative vaginal delivery resulted in lower mean scores, comparable with those assigned to uncomplicated cesarean delivery. Substantially lower scores (ranging from 0.432 to 0.598) were obtained for scenarios ending in severe maternal or neonatal morbidity. Although most women expressed strong preferences for vaginal delivery, their preferences regarding interventions frequently used to achieve that goal varied. These data underscore the importance of educating patients about the process of labor and delivery to facilitate incorporation of informed patient preferences in shared decision making regarding delivery approach. Copyright © 2015 Elsevier Inc. All rights reserved.

Algorithms for bioluminescence tomography incorporating anatomical information and reconstruction of tissue optical properties

PubMed Central

Naser, Mohamed A.; Patterson, Michael S.

2010-01-01

Reconstruction algorithms are presented for a two-step solution of the bioluminescence tomography (BLT) problem. In the first step, a priori anatomical information provided by x-ray computed tomography or by other methods is used to solve the continuous wave (cw) diffuse optical tomography (DOT) problem. A Taylor series expansion approximates the light fluence rate dependence on the optical properties of each region where first and second order direct derivatives of the light fluence rate with respect to scattering and absorption coefficients are obtained and used for the reconstruction. In the second step, the reconstructed optical properties at different wavelengths are used to calculate the Green’s function of the system. Then an iterative minimization solution based on the L1 norm shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. This provides an efficient BLT reconstruction algorithm with the ability to determine relative source magnitudes and positions in the presence of noise. PMID:21258486

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.

PubMed

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-08-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features.

An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm.

PubMed

Mallayya, Deivamani; Ramachandran, Baskaran; Viswanathan, Suganya

2015-01-01

Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the "quality of service" as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user's request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services.

An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm

PubMed Central

Mallayya, Deivamani; Ramachandran, Baskaran; Viswanathan, Suganya

2015-01-01

Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the “quality of service” as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user's request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services. PMID:26504894

The colour preference control based on two-colour combinations

NASA Astrophysics Data System (ADS)

Hong, Ji Young; Kwak, Youngshin; Park, Du-Sik; Kim, Chang Yeong

2008-02-01

This paper proposes a framework of colour preference control to satisfy the consumer's colour related emotion. A colour harmony algorithm based on two-colour combinations is developed for displaying the images with several complementary colour pairs as the relationship of two-colour combination. The colours of pixels belonging to complementary colour areas in HSV colour space are shifted toward the target hue colours and there is no colour change for the other pixels. According to the developed technique, dynamic emotions by the proposed hue conversion can be improved and the controlled output image shows improved colour emotions in the preference of the human viewer. The psychophysical experiments are conducted to investigate the optimal model parameters to produce the most pleasant image to the users in the respect of colour emotions.

Preferences of colorectal cancer patients for treatment and decision-making: a systematic literature review.

PubMed

Damm, K; Vogel, A; Prenzler, A

2014-11-01

Treatment decisions in life-threatening diseases, like colorectal cancer (CRC), are crucial, since they have a great impact on patient's survival and health-related quality of life. Thereby, the inclusion of patient's preferences becomes more and more important; however, these first need to be identified. Therefore, we conducted a systematic literature review in 12 electronic databases, published between 2000 and 2012, in order to identify patient's preferences concerning treatment preferences and involvement in the decision-making process. Nineteen studies were included and thoroughly analysed. This review shows that CRC patients do have preferences regarding different treatment options and outcomes; however, these preferences are not homogenous and seem to depend on personal factors like age and gender. Despite the existence of these preferences, the majority of patients prefer a passive role in the decision-making process, which in part may be explained by the severity of the disease. Again, subgroup analyses reveal the impact of personal factors like gender and education on the preference. Due to the importance of personal factors in the analysis of patient preferences, we identified an urgent need for larger studies that are suitable for subgroup analyses and incorporate multi-attributive measurement techniques, like discrete choice methods. © 2014 John Wiley & Sons Ltd.

Preferred computer activities among individuals with dementia: a pilot study.

PubMed

Tak, Sunghee H; Zhang, Hongmei; Hong, Song Hee

2015-03-01

Computers offer new activities that are easily accessible, cognitively stimulating, and enjoyable for individuals with dementia. The current descriptive study examined preferred computer activities among nursing home residents with different severity levels of dementia. A secondary data analysis was conducted using activity observation logs from 15 study participants with dementia (severe = 115 logs, moderate = 234 logs, and mild = 124 logs) who participated in a computer activity program. Significant differences existed in preferred computer activities among groups with different severity levels of dementia. Participants with severe dementia spent significantly more time watching slide shows with music than those with both mild and moderate dementia (F [2,12] = 9.72, p = 0.003). Preference in playing games also differed significantly across the three groups. It is critical to consider individuals' interests and functional abilities when computer activities are provided for individuals with dementia. A practice guideline for tailoring computer activities is detailed. Copyright 2015, SLACK Incorporated.

Development of a preference-based index from the National Eye Institute Visual Function Questionnaire-25.

PubMed

Rentz, Anne M; Kowalski, Jonathan W; Walt, John G; Hays, Ron D; Brazier, John E; Yu, Ren; Lee, Paul; Bressler, Neil; Revicki, Dennis A

2014-03-01

Understanding how individuals value health states is central to patient-centered care and to health policy decision making. Generic preference-based measures of health may not effectively capture the impact of ocular diseases. Recently, 6 items from the National Eye Institute Visual Function Questionnaire-25 were used to develop the Visual Function Questionnaire-Utility Index health state classification, which defines visual function health states. To describe elicitation of preferences for health states generated from the Visual Function Questionnaire-Utility Index health state classification and development of an algorithm to estimate health preference scores for any health state. Nonintervention, cross-sectional study of the general community in 4 countries (Australia, Canada, United Kingdom, and United States). A total of 607 adult participants were recruited from local newspaper advertisements. In the United Kingdom, an existing database of participants from previous studies was used for recruitment. Eight of 15,625 possible health states from the Visual Function Questionnaire-Utility Index were valued using time trade-off technique. A θ severity score was calculated for Visual Function Questionnaire-Utility Index-defined health states using item response theory analysis. Regression models were then used to develop an algorithm to assign health state preference values for all potential health states defined by the Visual Function Questionnaire-Utility Index. Health state preference values for the 8 states ranged from a mean (SD) of 0.343 (0.395) to 0.956 (0.124). As expected, preference values declined with worsening visual function. Results indicate that the Visual Function Questionnaire-Utility Index describes states that participants view as spanning most of the continuum from full health to dead. Visual Function Questionnaire-Utility Index health state classification produces health preference scores that can be estimated in vision-related studies that

Student Preferences Regarding Teaching Methods in a Drug-Induced Diseases and Clinical Toxicology Course

PubMed Central

Gim, Suzanna

2013-01-01

Objectives. To determine which teaching method in a drug-induced diseases and clinical toxicology course was preferred by students and whether their preference correlated with their learning of drug-induced diseases. Design. Three teaching methods incorporating active-learning exercises were implemented. A survey instrument was developed to analyze students’ perceptions of the active-learning methods used and how they compared to the traditional teaching method (lecture). Examination performance was then correlated to students’ perceptions of various teaching methods. Assessment. The majority of the 107 students who responded to the survey found traditional lecture significantly more helpful than active-learning methods (p=0.01 for all comparisons). None of the 3 active-learning methods were preferred over the others. No significant correlations were found between students’ survey responses and examination performance. Conclusions. Students preferred traditional lecture to other instructional methods. Learning was not influenced by the teaching method or by preference for a teaching method. PMID:23966726

Kinematics of preferred and non-preferred handballing in Australian football.

PubMed

Parrington, Lucy; Ball, Kevin; MacMahon, Clare

2015-01-01

In Australian football (AF), handballing proficiently with both the preferred and non-preferred arm is important at elite levels; yet, little information is available for handballing on the non-preferred arm. This study compared preferred and non-preferred arm handballing techniques. Optotrak Certus (100 Hz) collected three-dimensional data for 19 elite AF players performing handballs with the preferred and non-preferred arms. Position data, range of motion (ROM), and linear and angular velocities were collected and compared between preferred and non-preferred arms using dependent t-tests. The preferred arm exhibited significantly greater forearm and humerus ROM and angular velocity and significantly greater shoulder angular velocity at ball contact compared to the non-preferred arm. In addition, the preferred arm produced a significantly greater range of lateral bend and maximum lower-trunk speed, maximum strike-side hip speed and hand speed at ball contact than the non-preferred arm. The non-preferred arm exhibited a significantly greater shoulder angle and lower- and upper-trunk orientation angle, but significantly lower support-elbow angle, trunk ROM, and trunk rotation velocity compared to the preferred arm. Reduced ROM and angular velocities found in non-preferred arm handballs indicates a reduction in the degrees of freedom and a less developed skill. Findings have implication for development of handballing on the non-preferred arm.

Genetic Algorithm Approaches for Actuator Placement

NASA Technical Reports Server (NTRS)

Crossley, William A.

2000-01-01

This research investigated genetic algorithm approaches for smart actuator placement to provide aircraft maneuverability without requiring hinged flaps or other control surfaces. The effort supported goals of the Multidisciplinary Design Optimization focus efforts in NASA's Aircraft au program. This work helped to properly identify various aspects of the genetic algorithm operators and parameters that allow for placement of discrete control actuators/effectors. An improved problem definition, including better definition of the objective function and constraints, resulted from this research effort. The work conducted for this research used a geometrically simple wing model; however, an increasing number of potential actuator placement locations were incorporated to illustrate the ability of the GA to determine promising actuator placement arrangements. This effort's major result is a useful genetic algorithm-based approach to assist in the discrete actuator/effector placement problem.

Wildlife tradeoffs based on landscape models of habitat preference

USGS Publications Warehouse

Loehle, C.; Mitchell, M.S.; White, M.

2000-01-01

Wildlife tradeoffs based on landscape models of habitat preference were presented. Multiscale logistic regression models were used and based on these models a spatial optimization technique was utilized to generate optimal maps. The tradeoffs were analyzed by gradually increasing the weighting on a single species in the objective function over a series of simulations. Results indicated that efficiency of habitat management for species diversity could be maximized for small landscapes by incorporating spatial context.

New human-centered linear and nonlinear motion cueing algorithms for control of simulator motion systems

NASA Astrophysics Data System (ADS)

Telban, Robert J.

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input

Algorithms for in-season nutrient management in cereals

USDA-ARS?s Scientific Manuscript database

The demand for improved decision making products for cereal production systems has placed added emphasis on using plant sensors in-season, and that incorporate real-time, site specific, growing environments. The objective of this work was to describe validated in-season sensor based algorithms prese...

Dose calculation accuracy of the Monte Carlo algorithm for CyberKnife compared with other commercially available dose calculation algorithms.

PubMed

Sharma, Subhash; Ott, Joseph; Williams, Jamone; Dickow, Danny

2011-01-01

Monte Carlo dose calculation algorithms have the potential for greater accuracy than traditional model-based algorithms. This enhanced accuracy is particularly evident in regions of lateral scatter disequilibrium, which can develop during treatments incorporating small field sizes and low-density tissue. A heterogeneous slab phantom was used to evaluate the accuracy of several commercially available dose calculation algorithms, including Monte Carlo dose calculation for CyberKnife, Analytical Anisotropic Algorithm and Pencil Beam convolution for the Eclipse planning system, and convolution-superposition for the Xio planning system. The phantom accommodated slabs of varying density; comparisons between planned and measured dose distributions were accomplished with radiochromic film. The Monte Carlo algorithm provided the most accurate comparison between planned and measured dose distributions. In each phantom irradiation, the Monte Carlo predictions resulted in gamma analysis comparisons >97%, using acceptance criteria of 3% dose and 3-mm distance to agreement. In general, the gamma analysis comparisons for the other algorithms were <95%. The Monte Carlo dose calculation algorithm for CyberKnife provides more accurate dose distribution calculations in regions of lateral electron disequilibrium than commercially available model-based algorithms. This is primarily because of the ability of Monte Carlo algorithms to implicitly account for tissue heterogeneities, density scaling functions; and/or effective depth correction factors are not required. Copyright © 2011 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm

PubMed Central

Wang, Jinzhao

2016-01-01

We present a novel algorithm for optimizing the order in which Chinese characters are learned, one that incorporates the benefits of learning them in order of usage frequency and in order of their hierarchal structural relationships. We show that our work outperforms previously published orders and algorithms. Our algorithm is applicable to any scheduling task where nodes have intrinsic differences in importance and must be visited in topological order. PMID:27706234

Update on Development of Mesh Generation Algorithms in MeshKit

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

Jain, Rajeev; Vanderzee, Evan; Mahadevan, Vijay

2015-09-30

MeshKit uses a graph-based design for coding all its meshing algorithms, which includes the Reactor Geometry (and mesh) Generation (RGG) algorithms. This report highlights the developmental updates of all the algorithms, results and future work. Parallel versions of algorithms, documentation and performance results are reported. RGG GUI design was updated to incorporate new features requested by the users; boundary layer generation and parallel RGG support were added to the GUI. Key contributions to the release, upgrade and maintenance of other SIGMA1 libraries (CGM and MOAB) were made. Several fundamental meshing algorithms for creating a robust parallel meshing pipeline in MeshKitmore » are under development. Results and current status of automated, open-source and high quality nuclear reactor assembly mesh generation algorithms such as trimesher, quadmesher, interval matching and multi-sweeper are reported.« less

Automated Method of Frequency Determination in Software Metric Data Through the Use of the Multiple Signal Classification (MUSIC) Algorithm

DTIC Science & Technology

1998-06-26

METHOD OF FREQUENCY DETERMINATION 4 IN SOFTWARE METRIC DATA THROUGH THE USE OF THE 5 MULTIPLE SIGNAL CLASSIFICATION ( MUSIC ) ALGORITHM 6 7 STATEMENT OF...graph showing the estimated power spectral 12 density (PSD) generated by the multiple signal classification 13 ( MUSIC ) algorithm from the data set used...implemented in this module; however, it is preferred to use 1 the Multiple Signal Classification ( MUSIC ) algorithm. The MUSIC 2 algorithm is

Zero-block mode decision algorithm for H.264/AVC.

PubMed

Lee, Yu-Ming; Lin, Yinyi

2009-03-01

In the previous paper , we proposed a zero-block intermode decision algorithm for H.264 video coding based upon the number of zero-blocks of 4 x 4 DCT coefficients between the current macroblock and the co-located macroblock. The proposed algorithm can achieve significant improvement in computation, but the computation performance is limited for high bit-rate coding. To improve computation efficiency, in this paper, we suggest an enhanced zero-block decision algorithm, which uses an early zero-block detection method to compute the number of zero-blocks instead of direct DCT and quantization (DCT/Q) calculation and incorporates two adequate decision methods into semi-stationary and nonstationary regions of a video sequence. In addition, the zero-block decision algorithm is also applied to the intramode prediction in the P frame. The enhanced zero-block decision algorithm brings out a reduction of average 27% of total encoding time compared to the zero-block decision algorithm.

DNA polymerase preference determines PCR priming efficiency.

PubMed

Pan, Wenjing; Byrne-Steele, Miranda; Wang, Chunlin; Lu, Stanley; Clemmons, Scott; Zahorchak, Robert J; Han, Jian

2014-01-30

Polymerase chain reaction (PCR) is one of the most important developments in modern biotechnology. However, PCR is known to introduce biases, especially during multiplex reactions. Recent studies have implicated the DNA polymerase as the primary source of bias, particularly initiation of polymerization on the template strand. In our study, amplification from a synthetic library containing a 12 nucleotide random portion was used to provide an in-depth characterization of DNA polymerase priming bias. The synthetic library was amplified with three commercially available DNA polymerases using an anchored primer with a random 3' hexamer end. After normalization, the next generation sequencing (NGS) results of the amplified libraries were directly compared to the unamplified synthetic library. Here, high throughput sequencing was used to systematically demonstrate and characterize DNA polymerase priming bias. We demonstrate that certain sequence motifs are preferred over others as primers where the six nucleotide sequences at the 3' end of the primer, as well as the sequences four base pairs downstream of the priming site, may influence priming efficiencies. DNA polymerases in the same family from two different commercial vendors prefer similar motifs, while another commercially available enzyme from a different DNA polymerase family prefers different motifs. Furthermore, the preferred priming motifs are GC-rich. The DNA polymerase preference for certain sequence motifs was verified by amplification from single-primer templates. We incorporated the observed DNA polymerase preference into a primer-design program that guides the placement of the primer to an optimal location on the template. DNA polymerase priming bias was characterized using a synthetic library amplification system and NGS. The characterization of DNA polymerase priming bias was then utilized to guide the primer-design process and demonstrate varying amplification efficiencies among three commercially

Sea-ice habitat preference of the Pacific walrus (Odobenus rosmarus divergens) in the Bering Sea: A multiscaled approach

NASA Astrophysics Data System (ADS)

Sacco, Alexander Edward

, walruses were preferentially occupying fragmented pack ice seascapes range 50 -- 89% of the time, when, all throughout the Bering Sea, only range 41 -- 46% of seascapes consisted of fragmented pack ice. Traditional knowledge of a walrus' use of sea ice is investigated through semi-directed interviews conducted with subsistence hunters and elders from Savoonga and Gambell, two Alaskan Native communities on St. Lawrence Island, Alaska. Informants were provided with a large nautical map of the land and ocean surrounding St. Lawrence Island and 45 printed large-format aerial photographs of walruses on sea ice to stimulate discussion as questions were asked to direct the topics of conversation. Informants discussed change in sea ice conditions over time, walrus behaviors during the fall and spring subsistence hunts, and sea-ice characteristics that walruses typically occupy. These observations are compared with ice-patch preferences analyzed from aerial imagery. Floe size was found to agree with remotely-sensed ice-patch analysis results, while floe shape was not distinguishable to informants during the hunt. Ice-patch arrangement descriptors concentration and density generally agreed with ice-patch analysis results. Results include possible preference of ice-patch descriptors at the ice-patch scale and fragmented pack ice preference at the seascape scale. Traditional knowledge suggests large ice ridges are preferential sea-ice features at the ice-patch scale, which are rapidly becoming less common during the fall and spring migration of sea ice through the Bering Sea. Traditional knowledge, combined with a scientific analysis and field work to study species habitat preferences and, ultimately, habitat partitioning, can stem from these results. Future work includes increased sophistication of the synthetic aperture radar classification algorithm, experimentation with various spatial scales to determine the optimal scale for walrus' life-cycle events, and incorporation of

An improved finger-vein recognition algorithm based on template matching

NASA Astrophysics Data System (ADS)

Liu, Yueyue; Di, Si; Jin, Jian; Huang, Daoping

2016-10-01

Finger-vein recognition has became the most popular biometric identify methods. The investigation on the recognition algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein recognition algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.

Definition and Analysis of a System for the Automated Comparison of Curriculum Sequencing Algorithms in Adaptive Distance Learning

ERIC Educational Resources Information Center

Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia

2011-01-01

LS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms…

OGUPSA sensor scheduling architecture and algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhixiong; Hintz, Kenneth J.

1996-06-01

This paper introduces a new architecture for a sensor measurement scheduler as well as a dynamic sensor scheduling algorithm called the on-line, greedy, urgency-driven, preemptive scheduling algorithm (OGUPSA). OGUPSA incorporates a preemptive mechanism which uses three policies, (1) most-urgent-first (MUF), (2) earliest- completed-first (ECF), and (3) least-versatile-first (LVF). The three policies are used successively to dynamically allocate and schedule and distribute a set of arriving tasks among a set of sensors. OGUPSA also can detect the failure of a task to meet a deadline as well as generate an optimal schedule in the sense of minimum makespan for a group of tasks with the same priorities. A side benefit is OGUPSA's ability to improve dynamic load balance among all sensors while being a polynomial time algorithm. Results of a simulation are presented for a simple sensor system.

The design and development of a long-term fall detection system incorporated into a custom vest for the elderly.

PubMed

Bourke, Alan K; van de Ven, Pepijn W J; Chaya, Amy E; OLaighin, Gearóid M; Nelson, John

2008-01-01

A fall detection system and algorithm, incorporated into a custom designed garment has been developed. The developed fall detection system uses a tri-axial accelerometer, microcontroller, battery and Bluetooth module. This sensor is attached to a custom designed vest, designed to be worn by the elderly person under clothing. The fall detection algorithm was developed and incorporates both impact and posture detection capability. The vest and fall algorithm was tested on young healthy subjects performing normal activities of daily living (ADL) and falls onto crash mats, while wearing the best and sensor. Results show that falls can de distinguished from normal activities with a sensitivity >90% and a specificity of >99%, from a total data set of 264 falls and 165 normal ADL. By incorporating the fall-detection sensor into a custom designed garment it is anticipated that greater compliance when wearing a fall-detection system can be achieved and will help reduce the incidence of the long-lie, when falls occur in the elderly population. However further long-term testing using elderly subjects is required to validate the systems performance.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

PubMed Central

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-01-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features. PMID:26705504

An Improved Cuckoo Search Optimization Algorithm for the Problem of Chaotic Systems Parameter Estimation

PubMed Central

Wang, Jun; Zhou, Bihua; Zhou, Shudao

2016-01-01

This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior. PMID:26880874

A Mathematical Model of the Color Preference Scale Construction in Quality Management at the Machine-Building Enterprise

NASA Astrophysics Data System (ADS)

Averchenkov, V. I.; Kondratenko, S. V.; Potapov, L. A.; Spasennikov, V. V.

2017-01-01

In this article, the author consider the basic features of color preferences. The famous scientists’ works confirm their identity and independence of subjective factors. The article examines the method of constructing the respondent’s color preference individual scale on the basis of L Thurstone’s pair election method. The practical example of applying this technique for constructing the respondent’s color preference individual scale is given. The result of this method application is the color preference individual scale with the weight value of each color. The authors also developed and presented the algorithm of applying this method within the program complex to determine the respondents’ attitude to the issues under investigation based on their color preferences. Also, the article considers the possibility of using the software at the industrial enterprises to improve the quality of the consumer quality products.

Object-Oriented Algorithm For Evaluation Of Fault Trees

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Koen, B. V.

1992-01-01

Algorithm for direct evaluation of fault trees incorporates techniques of object-oriented programming. Reduces number of calls needed to solve trees with repeated events. Provides significantly improved software environment for such computations as quantitative analyses of safety and reliability of complicated systems of equipment (e.g., spacecraft or factories).

Community pharmacy-based asthma services--what do patients prefer?

PubMed

Naik Panvelkar, Pradnya; Armour, Carol; Saini, Bandana

2010-12-01

identified. It would be important to identify the strength and magnitude of patient's preferences for different elements of such services. Future pharmacy-based services should incorporate patient preferences and tailor services to patient's needs to ensure their long-term viability.

Evaluation of an Efficient Method for Training Staff to Implement Stimulus Preference Assessments

ERIC Educational Resources Information Center

Roscoe, Eileen M.; Fisher, Wayne W.

2008-01-01

We used a brief training procedure that incorporated feedback and role-play practice to train staff members to conduct stimulus preference assessments, and we used group-comparison methods to evaluate the effects of training. Staff members were trained to implement the multiple-stimulus-without-replacement assessment in a single session and the…

The contingency of patient preferences for involvement in health decision making.

PubMed

Ryan, John; Sysko, James

2007-01-01

Studies indicate that better patient compliance and higher patient satisfaction result when agreement exists between the physician and the patient regarding the medical problem and its treatment. This study will extend previous work by investigating (1) under what conditions patients prefer to be actively involved in their treatment decisions, (2) the underlying theoretical reasons that may account for patient decision-making preferences, and (3) what medical decision-making model can guide physicians and medical policy makers when adapting their medical decision-making styles. A total of 2,765 individuals were surveyed by the National Opinion Research Center as part of the 2002 General Social Survey (GSS). This survey included a one-time topical module on "Doctors and Patients," which incorporated questions on patient preferences concerning the physician-patient relationship. Demographic information (e.g., age, education, and sex) was analyzed against patient preferences for medical decision making. Results support patient preferences for participatory medical decision making, and this is especially true for younger, more educated, and female patients. Common prudence would suggest that the best way to determine a patient's preference for participating in medical decision making is to simply ask them. However, the very asking of this straightforward question is based on the assumption that patients do wish to be actively involved. Results of this study support such an assumption. In the absence of all other knowledge, the results of this national survey support the health care practitioner's belief that U.S. patients, in general, have a preference for being actively involved in medical decision making and that this preference is truer for younger, female, and more educated patients.

Adaptive phase extraction: incorporating the Gabor transform in the matching pursuit algorithm.

PubMed

Wacker, Matthias; Witte, Herbert

2011-10-01

Short-time Fourier transform (STFT), Gabor transform (GT), wavelet transform (WT), and the Wigner-Ville distribution (WVD) are just some examples of time-frequency analysis methods which are frequently applied in biomedical signal analysis. However, all of these methods have their individual drawbacks. The STFT, GT, and WT have a time-frequency resolution that is determined by algorithm parameters and the WVD is contaminated by cross terms. In 1993, Mallat and Zhang introduced the matching pursuit (MP) algorithm that decomposes a signal into a sum of atoms and uses a cross-term free pseudo-WVD to generate a data-adaptive power distribution in the time-frequency space. Thus, it solved some of the problems of the GT and WT but lacks phase information that is crucial e.g., for synchronization analysis. We introduce a new time-frequency analysis method that combines the MP with a pseudo-GT. Therefore, the signal is decomposed into a set of Gabor atoms. Afterward, each atom is analyzed with a Gabor analysis, where the time-domain gaussian window of the analysis matches that of the specific atom envelope. A superposition of the single time-frequency planes gives the final result. This is the first time that a complete analysis of the complex time-frequency plane can be performed in a fully data-adaptive and frequency-selective manner. We demonstrate the capabilities of our approach on a simulation and on real-life magnetoencephalogram data.

Assessment of transport performance index for urban transport development strategies — Incorporating residents' preferences

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

Ambarwati, Lasmini, E-mail: L.Ambarwati@tudelft.nl; Department of Civil Engineering, Brawijaya University; Verhaeghe, Robert, E-mail: R.Verhaeghe@tudelft.nl

The performance of urban transport depends on a variety of factors related to metropolitan structure; in particular, the patterns of commuting, roads and public transport (PT) systems. To evaluate urban transport planning efforts, there is a need for a metric expressing the aggregate performance of the city's transport systems which should relate to residents' preferences. The existing metrics have typically focused on a measure to express the proximity of job locations to residences. A Transport Performance Index (TPI) is proposed in which the total cost of transportation system (operational and environmental costs) is divided by willingness to pay (WTP) formore » transport plus the willingness to accept (WTA) the environmental effects on residents. Transport operational as well as the environmental costs are derived from a simulation of all transport systems, to particular designs of spatial development. Willingness to pay for transport and willingness to accept the environmental effects are derived from surveys among residents. Simulations were modelled of Surabaya's spatial structure and public transport expansion. The results indicate that the current TPI is high, which will double by 2030. With a hypothetical polycentric city structure and adjusted job housing balance, a lower index occurs because of the improvements in urban transport performance. A low index means that the residents obtain much benefit from the alternative proposed. This illustrates the importance of residents' preferences in urban spatial planning in order to achieve efficient urban transport. Applying the index suggests that city authorities should provide fair and equitable public transport systems for suburban residents in the effort to control the phenomenon of urban sprawl. This index is certainly a good tool and prospective benchmark for measuring sustainability in relation to urban development.« less

Interest and preferences for contingency management design among addiction treatment clientele.

PubMed

Hartzler, Bryan; Garrett, Sharon

2016-05-01

Despite strong support for its efficacy, debates persist about how dissemination of contingency management is most effectively undertaken. Currently-promoted contingency management methods are empirically-validated, yet their congruence with interests and preferences of addiction treatment clientele is unknown. Such client input is a foundational support for evidence-based clinical practice. This study documented interest in incentives and preferences for fixed-ratio vs. variable-ratio and immediate vs. distal distribution of earned incentives among clients enrolled at three community programs affiliated with the National Institute on Drug Abuse Clinical Trials Network. This multi-site study included anonymous survey completion by an aggregate sample of 358 treatment enrollees. Analyses first ruled out site differences in survey responses, and then tested age and gender as influences on client interest in financial incentives, and preferences for fixed-ratio vs. variable-ratio reinforcement and immediate vs. distal incentive distribution. Interest in different types of $50 incentives (i.e. retail vouchers, transportation vouchers, cash) was highly inter-correlated, with a mean sample rating of 3.49 (0.83) on a five-point scale. While consistent across client gender, age was an inverse predictor of client interest in incentives. A majority of clients stated preference for fixed-ratio incentive magnitude and distal incentive distribution (67% and 63%, respectively), with these preferences voiced by a larger proportion of females. Sample preferences contradict currently-promoted contingency management design features. Future efforts to disseminate contingency management may be more successful if flexibly undertaken in a manner that incorporates the interests and preferences of local client populations.

Parana Basin Structure from Multi-Objective Inversion of Surface Wave and Receiver Function by Competent Genetic Algorithm

NASA Astrophysics Data System (ADS)

An, M.; Assumpcao, M.

2003-12-01

The joint inversion of receiver function and surface wave is an effective way to diminish the influences of the strong tradeoff among parameters and the different sensitivity to the model parameters in their respective inversions, but the inversion problem becomes more complex. Multi-objective problems can be much more complicated than single-objective inversion in the model selection and optimization. If objectives are involved and conflicting, models can be ordered only partially. In this case, Pareto-optimal preference should be used to select solutions. On the other hand, the inversion to get only a few optimal solutions can not deal properly with the strong tradeoff between parameters, the uncertainties in the observation, the geophysical complexities and even the incompetency of the inversion technique. The effective way is to retrieve the geophysical information statistically from many acceptable solutions, which requires more competent global algorithms. Competent genetic algorithms recently proposed are far superior to the conventional genetic algorithm and can solve hard problems quickly, reliably and accurately. In this work we used one of competent genetic algorithms, Bayesian Optimization Algorithm as the main inverse procedure. This algorithm uses Bayesian networks to draw out inherited information and can use Pareto-optimal preference in the inversion. With this algorithm, the lithospheric structure of Paran"› basin is inverted to fit both the observations of inter-station surface wave dispersion and receiver function.

The Vocational Preference Inventory Scores and Environmental Preferences

ERIC Educational Resources Information Center

Kunce, Joseph T.; Kappes, Bruno Maurice

1976-01-01

This study investigated the relationship between vocational interest measured by the Vocational Preference Inventory (VPI) and preferences of 175 undergraduates for structured or unstructured environments. Males having clear-cut preferences for structured situations had significantly higher Realistic-Conventional scores than those without…

Network-based recommendation algorithms: A review

NASA Astrophysics Data System (ADS)

Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš

2016-06-01

Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

Comparing multiple turbulence restoration algorithms performance on noisy anisoplanatic imagery

NASA Astrophysics Data System (ADS)

Rucci, Michael A.; Hardie, Russell C.; Dapore, Alexander J.

2017-05-01

In this paper, we compare the performance of multiple turbulence mitigation algorithms to restore imagery degraded by atmospheric turbulence and camera noise. In order to quantify and compare algorithm performance, imaging scenes were simulated by applying noise and varying levels of turbulence. For the simulation, a Monte-Carlo wave optics approach is used to simulate the spatially and temporally varying turbulence in an image sequence. A Poisson-Gaussian noise mixture model is then used to add noise to the observed turbulence image set. These degraded image sets are processed with three separate restoration algorithms: Lucky Look imaging, bispectral speckle imaging, and a block matching method with restoration filter. These algorithms were chosen because they incorporate different approaches and processing techniques. The results quantitatively show how well the algorithms are able to restore the simulated degraded imagery.

Applying a Genetic Algorithm to Reconfigurable Hardware

NASA Technical Reports Server (NTRS)

Wells, B. Earl; Weir, John; Trevino, Luis; Patrick, Clint; Steincamp, Jim

2004-01-01

This paper investigates the feasibility of applying genetic algorithms to solve optimization problems that are implemented entirely in reconfgurable hardware. The paper highlights the pe$ormance/design space trade-offs that must be understood to effectively implement a standard genetic algorithm within a modem Field Programmable Gate Array, FPGA, reconfgurable hardware environment and presents a case-study where this stochastic search technique is applied to standard test-case problems taken from the technical literature. In this research, the targeted FPGA-based platform and high-level design environment was the Starbridge Hypercomputing platform, which incorporates multiple Xilinx Virtex II FPGAs, and the Viva TM graphical hardware description language.

Parameter optimization of differential evolution algorithm for automatic playlist generation problem

NASA Astrophysics Data System (ADS)

Alamag, Kaye Melina Natividad B.; Addawe, Joel M.

2017-11-01

With the digitalization of music, the number of collection of music increased largely and there is a need to create lists of music that filter the collection according to user preferences, thus giving rise to the Automatic Playlist Generation Problem (APGP). Previous attempts to solve this problem include the use of search and optimization algorithms. If a music database is very large, the algorithm to be used must be able to search the lists thoroughly taking into account the quality of the playlist given a set of user constraints. In this paper we perform an evolutionary meta-heuristic optimization algorithm, Differential Evolution (DE) using different combination of parameter values and select the best performing set when used to solve four standard test functions. Performance of the proposed algorithm is then compared with normal Genetic Algorithm (GA) and a hybrid GA with Tabu Search. Numerical simulations are carried out to show better results from Differential Evolution approach with the optimized parameter values.

Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Blackmore, James C.; Scharf, Daniel P.

2011-01-01

An enhanced algorithm is developed that builds on a previous innovation of fuel-optimal powered-descent guidance (PDG) for planetary pinpoint landing. The PDG problem is to compute constrained, fuel-optimal trajectories to land a craft at a prescribed target on a planetary surface, starting from a parachute cut-off point and using a throttleable descent engine. The previous innovation showed the minimal-fuel PDG problem can be posed as a convex optimization problem, in particular, as a Second-Order Cone Program, which can be solved to global optimality with deterministic convergence properties, and hence is a candidate for onboard implementation. To increase the speed and robustness of this convex PDG algorithm for possible onboard implementation, the following enhancements are incorporated: 1) Fast detection of infeasibility (i.e., control authority is not sufficient for soft-landing) for subsequent fault response. 2) The use of a piecewise-linear control parameterization, providing smooth solution trajectories and increasing computational efficiency. 3) An enhanced line-search algorithm for optimal time-of-flight, providing quicker convergence and bounding the number of path-planning iterations needed. 4) An additional constraint that analytically guarantees inter-sample satisfaction of glide-slope and non-sub-surface flight constraints, allowing larger discretizations and, hence, faster optimization. 5) Explicit incorporation of Mars rotation rate into the trajectory computation for improved targeting accuracy. These enhancements allow faster convergence to the fuel-optimal solution and, more importantly, remove the need for a "human-in-the-loop," as constraints will be satisfied over the entire path-planning interval independent of step-size (as opposed to just at the discrete time points) and infeasible initial conditions are immediately detected. Finally, while the PDG stage is typically only a few minutes, ignoring the rotation rate of Mars can introduce 10s

Recursive least-squares learning algorithms for neural networks

NASA Astrophysics Data System (ADS)

Lewis, Paul S.; Hwang, Jenq N.

1990-11-01

This paper presents the development of a pair of recursive least squares (ItLS) algorithms for online training of multilayer perceptrons which are a class of feedforward artificial neural networks. These algorithms incorporate second order information about the training error surface in order to achieve faster learning rates than are possible using first order gradient descent algorithms such as the generalized delta rule. A least squares formulation is derived from a linearization of the training error function. Individual training pattern errors are linearized about the network parameters that were in effect when the pattern was presented. This permits the recursive solution of the least squares approximation either via conventional RLS recursions or by recursive QR decomposition-based techniques. The computational complexity of the update is 0(N2) where N is the number of network parameters. This is due to the estimation of the N x N inverse Hessian matrix. Less computationally intensive approximations of the ilLS algorithms can be easily derived by using only block diagonal elements of this matrix thereby partitioning the learning into independent sets. A simulation example is presented in which a neural network is trained to approximate a two dimensional Gaussian bump. In this example RLS training required an order of magnitude fewer iterations on average (527) than did training with the generalized delta rule (6 1 BACKGROUND Artificial neural networks (ANNs) offer an interesting and potentially useful paradigm for signal processing and pattern recognition. The majority of ANN applications employ the feed-forward multilayer perceptron (MLP) network architecture in which network parameters are " trained" by a supervised learning algorithm employing the generalized delta rule (GDIt) [1 2]. The GDR algorithm approximates a fixed step steepest descent algorithm using derivatives computed by error backpropagatiori. The GDII algorithm is sometimes referred to as the

A simple algorithm for sequentially incorporating gravity observations in seismic traveltime tomography

USGS Publications Warehouse

Parsons, T.; Blakely, R.J.; Brocher, T.M.

2001-01-01

The geologic structure of the Earth's upper crust can be revealed by modeling variation in seismic arrival times and in potential field measurements. We demonstrate a simple method for sequentially satisfying seismic traveltime and observed gravity residuals in an iterative 3-D inversion. The algorithm is portable to any seismic analysis method that uses a gridded representation of velocity structure. Our technique calculates the gravity anomaly resulting from a velocity model by converting to density with Gardner's rule. The residual between calculated and observed gravity is minimized by weighted adjustments to the model velocity-depth gradient where the gradient is steepest and where seismic coverage is least. The adjustments are scaled by the sign and magnitude of the gravity residuals, and a smoothing step is performed to minimize vertical streaking. The adjusted model is then used as a starting model in the next seismic traveltime iteration. The process is repeated until one velocity model can simultaneously satisfy both the gravity anomaly and seismic traveltime observations within acceptable misfits. We test our algorithm with data gathered in the Puget Lowland of Washington state, USA (Seismic Hazards Investigation in Puget Sound [SHIPS] experiment). We perform resolution tests with synthetic traveltime and gravity observations calculated with a checkerboard velocity model using the SHIPS experiment geometry, and show that the addition of gravity significantly enhances resolution. We calculate a new velocity model for the region using SHIPS traveltimes and observed gravity, and show examples where correlation between surface geology and modeled subsurface velocity structure is enhanced.

Orientation estimation algorithm applied to high-spin projectiles

NASA Astrophysics Data System (ADS)

Long, D. F.; Lin, J.; Zhang, X. M.; Li, J.

2014-06-01

High-spin projectiles are low cost military weapons. Accurate orientation information is critical to the performance of the high-spin projectiles control system. However, orientation estimators have not been well translated from flight vehicles since they are too expensive, lack launch robustness, do not fit within the allotted space, or are too application specific. This paper presents an orientation estimation algorithm specific for these projectiles. The orientation estimator uses an integrated filter to combine feedback from a three-axis magnetometer, two single-axis gyros and a GPS receiver. As a new feature of this algorithm, the magnetometer feedback estimates roll angular rate of projectile. The algorithm also incorporates online sensor error parameter estimation performed simultaneously with the projectile attitude estimation. The second part of the paper deals with the verification of the proposed orientation algorithm through numerical simulation and experimental tests. Simulations and experiments demonstrate that the orientation estimator can effectively estimate the attitude of high-spin projectiles. Moreover, online sensor calibration significantly enhances the estimation performance of the algorithm.

Digital terrain model generalization incorporating scale, semantic and cognitive constraints

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Papadogiorgaki, Maria

2014-05-01

Cartographic generalization is a well-known process accommodating spatial data compression, visualization and comprehension under various scales. In the last few years, there are several international attempts to construct tangible GIS systems, forming real 3D surfaces using a vast number of mechanical parts along a matrix formation (i.e., bars, pistons, vacuums). Usually, moving bars upon a structured grid push a stretching membrane resulting in a smooth visualization for a given surface. Most of these attempts suffer either in their cost, accuracy, resolution and/or speed. Under this perspective, the present study proposes a surface generalization process that incorporates intrinsic constrains of tangible GIS systems including robotic-motor movement and surface stretching limitations. The main objective is to provide optimized visualizations of 3D digital terrain models with minimum loss of information. That is, to minimize the number of pixels in a raster dataset used to define a DTM, while reserving the surface information. This neighborhood type of pixel relations adheres to the basics of Self Organizing Map (SOM) artificial neural networks, which are often used for information abstraction since they are indicative of intrinsic statistical features contained in the input patterns and provide concise and characteristic representations. Nevertheless, SOM remains more like a black box procedure not capable to cope with possible particularities and semantics of the application at hand. E.g. for coastal monitoring applications, the near - coast areas, surrounding mountains and lakes are more important than other features and generalization should be "biased"-stratified to fulfill this requirement. Moreover, according to the application objectives, we extend the SOM algorithm to incorporate special types of information generalization by differentiating the underlying strategy based on topologic information of the objects included in the application. The final

A Network Selection Algorithm Considering Power Consumption in Hybrid Wireless Networks

NASA Astrophysics Data System (ADS)

Joe, Inwhee; Kim, Won-Tae; Hong, Seokjoon

In this paper, we propose a novel network selection algorithm considering power consumption in hybrid wireless networks for vertical handover. CDMA, WiBro, WLAN networks are candidate networks for this selection algorithm. This algorithm is composed of the power consumption prediction algorithm and the final network selection algorithm. The power consumption prediction algorithm estimates the expected lifetime of the mobile station based on the current battery level, traffic class and power consumption for each network interface card of the mobile station. If the expected lifetime of the mobile station in a certain network is not long enough compared the handover delay, this particular network will be removed from the candidate network list, thereby preventing unnecessary handovers in the preprocessing procedure. On the other hand, the final network selection algorithm consists of AHP (Analytic Hierarchical Process) and GRA (Grey Relational Analysis). The global factors of the network selection structure are QoS, cost and lifetime. If user preference is lifetime, our selection algorithm selects the network that offers longest service duration due to low power consumption. Also, we conduct some simulations using the OPNET simulation tool. The simulation results show that the proposed algorithm provides longer lifetime in the hybrid wireless network environment.

Stochastic characterization of phase detection algorithms in phase-shifting interferometry

DOE PAGES

Munteanu, Florin

2016-11-01

Phase-shifting interferometry (PSI) is the preferred non-contact method for profiling sub-nanometer surfaces. Based on monochromatic light interference, the method computes the surface profile from a set of interferograms collected at separate stepping positions. Errors in the estimated profile are introduced when these positions are not located correctly. In order to cope with this problem, various algorithms that minimize the effects of certain types of stepping errors (linear, sinusoidal, etc.) have been developed. Despite the relatively large number of algorithms suggested in the literature, there is no unified way of characterizing their performance when additional unaccounted random errors are present. Here,more » we suggest a procedure for quantifying the expected behavior of each algorithm in the presence of independent and identically distributed (i.i.d.) random stepping errors, which can occur in addition to the systematic errors for which the algorithm has been designed. As a result, the usefulness of this method derives from the fact that it can guide the selection of the best algorithm for specific measurement situations.« less

A structure preserving Lanczos algorithm for computing the optical absorption spectrum

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

Shao, Meiyue; Jornada, Felipe H. da; Lin, Lin

2016-11-16

We present a new structure preserving Lanczos algorithm for approximating the optical absorption spectrum in the context of solving full Bethe-Salpeter equation without Tamm-Dancoff approximation. The new algorithm is based on a structure preserving Lanczos procedure, which exploits the special block structure of Bethe-Salpeter Hamiltonian matrices. A recently developed technique of generalized averaged Gauss quadrature is incorporated to accelerate the convergence. We also establish the connection between our structure preserving Lanczos procedure with several existing Lanczos procedures developed in different contexts. Numerical examples are presented to demonstrate the effectiveness of our Lanczos algorithm.

Testing of a long-term fall detection system incorporated into a custom vest for the elderly.

PubMed

Bourke, Alan K; van de Ven, Pepijn W J; Chaya, Amy E; OLaighin, Gearóid M; Nelson, John

2008-01-01

A fall detection system and algorithm, incorporated into a custom designed garment has been developed. The developed fall detection system uses a tri-axial accelerometer to detect impacts and monitor posture. This sensor is attached to a custom designed vest, designed to be worn by the elderly person under clothing. The fall detection algorithm was developed and incorporates both impact and posture detection capability. The vest and fall algorithm was tested by two teams of 5 elderly subjects who wore the sensor system in turn for 2 week each and were monitored for 8 hours a day. The system previously achieved sensitivity of >90% and a specificity of >99%, using young healthy subjects performing falls and normal activities of daily living (ADL). In this study, over 833 hours of monitoring was performed over the course of the four weeks from the elderly subjects, during normal daily activity. In this time no actual falls were recorded, however the system registered a total of the 42 fall-alerts however only 9 were received at the care taker site. A fall detection system incorporated into a custom designed garment has been developed which will help reduce the incidence of the long-lie, when falls occur in the elderly population. However further development is required to reduce the number of false-positives and improve the transmission of messages.

Progress on a generalized coordinates tensor product finite element 3DPNS algorithm for subsonic

NASA Technical Reports Server (NTRS)

Baker, A. J.; Orzechowski, J. A.

1983-01-01

A generalized coordinates form of the penalty finite element algorithm for the 3-dimensional parabolic Navier-Stokes equations for turbulent subsonic flows was derived. This algorithm formulation requires only three distinct hypermatrices and is applicable using any boundary fitted coordinate transformation procedure. The tensor matrix product approximation to the Jacobian of the Newton linear algebra matrix statement was also derived. Tne Newton algorithm was restructured to replace large sparse matrix solution procedures with grid sweeping using alpha-block tridiagonal matrices, where alpha equals the number of dependent variables. Numerical experiments were conducted and the resultant data gives guidance on potentially preferred tensor product constructions for the penalty finite element 3DPNS algorithm.

A Scheduling Algorithm for Replicated Real-Time Tasks

NASA Technical Reports Server (NTRS)

Yu, Albert C.; Lin, Kwei-Jay

1991-01-01

We present an algorithm for scheduling real-time periodic tasks on a multiprocessor system under fault-tolerant requirement. Our approach incorporates both the redundancy and masking technique and the imprecise computation model. Since the tasks in hard real-time systems have stringent timing constraints, the redundancy and masking technique are more appropriate than the rollback techniques which usually require extra time for error recovery. The imprecise computation model provides flexible functionality by trading off the quality of the result produced by a task with the amount of processing time required to produce it. It therefore permits the performance of a real-time system to degrade gracefully. We evaluate the algorithm by stochastic analysis and Monte Carlo simulations. The results show that the algorithm is resilient under hardware failures.

Fuel management optimization using genetic algorithms and expert knowledge

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

DeChaine, M.D.; Feltus, M.A.

1996-09-01

The CIGARO fuel management optimization code based on genetic algorithms is described and tested. The test problem optimized the core lifetime for a pressurized water reactor with a penalty function constraint on the peak normalized power. A bit-string genotype encoded the loading patterns, and genotype bias was reduced with additional bits. Expert knowledge about fuel management was incorporated into the genetic algorithm. Regional crossover exchanged physically adjacent fuel assemblies and improved the optimization slightly. Biasing the initial population toward a known priority table significantly improved the optimization.

Evolutionary algorithm for optimization of nonimaging Fresnel lens geometry.

PubMed

Yamada, N; Nishikawa, T

2010-06-21

In this study, an evolutionary algorithm (EA), which consists of genetic and immune algorithms, is introduced to design the optical geometry of a nonimaging Fresnel lens; this lens generates the uniform flux concentration required for a photovoltaic cell. Herein, a design procedure that incorporates a ray-tracing technique in the EA is described, and the validity of the design is demonstrated. The results show that the EA automatically generated a unique geometry of the Fresnel lens; the use of this geometry resulted in better uniform flux concentration with high optical efficiency.

Individualized cost-effectiveness analysis of patient-centered care: a case series of hospitalized patient preferences departing from practice-based guidelines.

PubMed

Padula, William V; Millis, M Andrew; Worku, Aelaf D; Pronovost, Peter J; Bridges, John F P; Meltzer, David O

2017-03-01

To develop cases of preference-sensitive care and analyze the individualized cost-effectiveness of respecting patient preference compared to guidelines. Four cases were analyzed comparing patient preference to guidelines: (a) high-risk cancer patient preferring to forgo colonoscopy; (b) decubitus patient preferring to forgo air-fluidized bed use; (c) anemic patient preferring to forgo transfusion; (d) end-of-life patient requesting all resuscitative measures. Decision trees were modeled to analyze cost-effectiveness of alternative treatments that respect preference compared to guidelines in USD per quality-adjusted life year (QALY) at a $100,000/QALY willingness-to-pay threshold from patient, provider and societal perspectives. Forgoing colonoscopy dominates colonoscopy from patient, provider, and societal perspectives. Forgoing transfusion and air-fluidized bed are cost-effective from all three perspectives. Palliative care is cost-effective from provider and societal perspectives, but not from the patient perspective. Prioritizing incorporation of patient preferences within guidelines holds good value and should be prioritized when developing new guidelines.

Comparing preference assessments: selection- versus duration-based preference assessment procedures.

PubMed

Kodak, Tiffany; Fisher, Wayne W; Kelley, Michael E; Kisamore, April

2009-01-01

In the current investigation, the results of a selection- and a duration-based preference assessment procedure were compared. A Multiple Stimulus With Replacement (MSW) preference assessment [Windsor, J., Piché, L. M., & Locke, P. A. (1994). Preference testing: A comparison of two presentation methods. Research in Developmental Disabilities, 15, 439-455] and a variation of a Free-Operant (FO) preference assessment procedure [Roane, H. S., Vollmer, T. R., Ringdahl, J. E., & Marcus, B. A. (1998). Evaluation of a brief stimulus preference assessment. Journal of Applied Behavior Analysis, 31, 605-620] were conducted with four participants. A reinforcer assessment was conducted to determine which preference assessment procedure identified the item that produced the highest rates of responding. The items identified as most highly preferred were different across preference assessment procedures for all participants. Results of the reinforcer assessment showed that the MSW identified the item that functioned as the most effective reinforcer for two participants.

A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

NASA Technical Reports Server (NTRS)

Delaat, J. C.; Merrill, W. C.

1983-01-01

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.

Analytic TOF PET reconstruction algorithm within DIRECT data partitioning framework

PubMed Central

Matej, Samuel; Daube-Witherspoon, Margaret E.; Karp, Joel S.

2016-01-01

Iterative reconstruction algorithms are routinely used for clinical practice; however, analytic algorithms are relevant candidates for quantitative research studies due to their linear behavior. While iterative algorithms also benefit from the inclusion of accurate data and noise models the widespread use of TOF scanners with less sensitivity to noise and data imperfections make analytic algorithms even more promising. In our previous work we have developed a novel iterative reconstruction approach (Direct Image Reconstruction for TOF) providing convenient TOF data partitioning framework and leading to very efficient reconstructions. In this work we have expanded DIRECT to include an analytic TOF algorithm with confidence weighting incorporating models of both TOF and spatial resolution kernels. Feasibility studies using simulated and measured data demonstrate that analytic-DIRECT with appropriate resolution and regularization filters is able to provide matched bias vs. variance performance to iterative TOF reconstruction with a matched resolution model. PMID:27032968

Analytic TOF PET reconstruction algorithm within DIRECT data partitioning framework

NASA Astrophysics Data System (ADS)

Matej, Samuel; Daube-Witherspoon, Margaret E.; Karp, Joel S.

2016-05-01

Iterative reconstruction algorithms are routinely used for clinical practice; however, analytic algorithms are relevant candidates for quantitative research studies due to their linear behavior. While iterative algorithms also benefit from the inclusion of accurate data and noise models the widespread use of time-of-flight (TOF) scanners with less sensitivity to noise and data imperfections make analytic algorithms even more promising. In our previous work we have developed a novel iterative reconstruction approach (DIRECT: direct image reconstruction for TOF) providing convenient TOF data partitioning framework and leading to very efficient reconstructions. In this work we have expanded DIRECT to include an analytic TOF algorithm with confidence weighting incorporating models of both TOF and spatial resolution kernels. Feasibility studies using simulated and measured data demonstrate that analytic-DIRECT with appropriate resolution and regularization filters is able to provide matched bias versus variance performance to iterative TOF reconstruction with a matched resolution model.

Incorporation of quality updates for JPSS CGS Products

NASA Astrophysics Data System (ADS)

Cochran, S.; Grant, K. D.; Ibrahim, W.; Brueske, K. F.; Smit, P.

2016-12-01

NOAA's next-generation environmental satellite, the Joint Polar Satellite System (JPSS) replaces the current Polar-orbiting Operational Environmental Satellites (POES). JPSS satellites carry sensors which collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The first JPSS satellite was launched in 2011 and is currently NOAA's primary operational polar satellite. The JPSS ground system is the Common Ground System (CGS), and provides command, control, and communications (C3) and data processing (DP). A multi-mission system, CGS provides combinations of C3/DP for numerous NASA, NOAA, DoD, and international missions. In preparation for the next JPSS satellite, CGS improved its multi-mission capabilities to enhance mission operations for larger constellations of earth observing satellites with the added benefit of streamlining mission operations for other NOAA missions. This paper will discuss both the theoretical basis and the actual practices used to date to identify, test and incorporate algorithm updates into the CGS processing baseline. To provide a basis for this support, Raytheon developed a theoretical analysis framework, and the application of derived engineering processes, for the maintenance of consistency and integrity of remote sensing operational algorithm outputs. The framework is an abstraction of the operationalization of the science-grade algorithm (Sci2Ops) process used throughout the JPSS program. By combining software and systems engineering controls, manufacturing disciplines to detect and reduce defects, and a standard process to control analysis, an environment to maintain operational algorithm maturity is achieved. Results of the use of this approach to implement algorithm changes into operations will also be detailed.

Algorithm and Architecture Independent Benchmarking with SEAK

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

Tallent, Nathan R.; Manzano Franco, Joseph B.; Gawande, Nitin A.

2016-05-23

Many applications of high performance embedded computing are limited by performance or power bottlenecks. We have designed the Suite for Embedded Applications & Kernels (SEAK), a new benchmark suite, (a) to capture these bottlenecks in a way that encourages creative solutions; and (b) to facilitate rigorous, objective, end-user evaluation for their solutions. To avoid biasing solutions toward existing algorithms, SEAK benchmarks use a mission-centric (abstracted from a particular algorithm) and goal-oriented (functional) specification. To encourage solutions that are any combination of software or hardware, we use an end-user black-box evaluation that can capture tradeoffs between performance, power, accuracy, size, andmore » weight. The tradeoffs are especially informative for procurement decisions. We call our benchmarks future proof because each mission-centric interface and evaluation remains useful despite shifting algorithmic preferences. It is challenging to create both concise and precise goal-oriented specifications for mission-centric problems. This paper describes the SEAK benchmark suite and presents an evaluation of sample solutions that highlights power and performance tradeoffs.« less

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

PubMed

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

An Adaptive Tradeoff Algorithm for Multi-issue SLA Negotiation

NASA Astrophysics Data System (ADS)

Son, Seokho; Sim, Kwang Mong

Since participants in a Cloud may be independent bodies, mechanisms are necessary for resolving different preferences in leasing Cloud services. Whereas there are currently mechanisms that support service-level agreement negotiation, there is little or no negotiation support for concurrent price and timeslot for Cloud service reservations. For the concurrent price and timeslot negotiation, a tradeoff algorithm to generate and evaluate a proposal which consists of price and timeslot proposal is necessary. The contribution of this work is thus to design an adaptive tradeoff algorithm for multi-issue negotiation mechanism. The tradeoff algorithm referred to as "adaptive burst mode" is especially designed to increase negotiation speed and total utility and to reduce computational load by adaptively generating concurrent set of proposals. The empirical results obtained from simulations carried out using a testbed suggest that due to the concurrent price and timeslot negotiation mechanism with adaptive tradeoff algorithm: 1) both agents achieve the best performance in terms of negotiation speed and utility; 2) the number of evaluations of each proposal is comparatively lower than previous scheme (burst-N).

Preference weights for cost-outcome analyses of schizophrenia treatments: comparison of four stakeholder groups.

PubMed

Shumway, Martha

2003-01-01

This study quantified preferences for schizophrenia outcomes in four stakeholder groups, tested the hypotheses that outcomes differ in importance and stakeholder groups have different preferences, and produced preference weights for seven outcomes for cost-outcome analysis. Fifty patients with schizophrenia, 50 clinicians, 41 family members of patients, and 50 members of the general public rated 16 schizophrenia-related health states, yielding preference weights for seven outcomes: positive symptoms, negative symptoms, extrapyramidal symptoms, tardive dyskinesia, social function, independent living, and vocational function. Outcomes differed in importance (F = 23.4, p < 0.01). All stakeholders rated positive symptoms and social functioning as more important than negative and extrapyramidal symptoms. Stakeholder groups had different preferences (F = 1.9, p = 0.01). Patients rated extrapyramidal symptoms as more important than did other groups (p < 0.01); clinicians rated social functioning as more important than did patients or family members (p < 0.05); and clinicians and family members rated vocational functioning as more important than did patients and the general public (p < 0.05). Results show that schizophrenia outcomes are not equally important and that stakeholder groups value outcomes differently, demonstrating the importance of incorporating stakeholder preferences in cost-outcome analyses and other treatment comparisons.

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

NASA Astrophysics Data System (ADS)

Tang, Jing; Rahmim, Arman

2015-01-01

A promising approach in PET image reconstruction is to incorporate high resolution anatomical information (measured from MR or CT) taking the anato-functional similarity measures such as mutual information or joint entropy (JE) as the prior. These similarity measures only classify voxels based on intensity values, while neglecting structural spatial information. In this work, we developed an anatomy-assisted maximum a posteriori (MAP) reconstruction algorithm wherein the JE measure is supplied by spatial information generated using wavelet multi-resolution analysis. The proposed wavelet-based JE (WJE) MAP algorithm involves calculation of derivatives of the subband JE measures with respect to individual PET image voxel intensities, which we have shown can be computed very similarly to how the inverse wavelet transform is implemented. We performed a simulation study with the BrainWeb phantom creating PET data corresponding to different noise levels. Realistically simulated T1-weighted MR images provided by BrainWeb modeling were applied in the anatomy-assisted reconstruction with the WJE-MAP algorithm and the intensity-only JE-MAP algorithm. Quantitative analysis showed that the WJE-MAP algorithm performed similarly to the JE-MAP algorithm at low noise level in the gray matter (GM) and white matter (WM) regions in terms of noise versus bias tradeoff. When noise increased to medium level in the simulated data, the WJE-MAP algorithm started to surpass the JE-MAP algorithm in the GM region, which is less uniform with smaller isolated structures compared to the WM region. In the high noise level simulation, the WJE-MAP algorithm presented clear improvement over the JE-MAP algorithm in both the GM and WM regions. In addition to the simulation study, we applied the reconstruction algorithms to real patient studies involving DPA-173 PET data and Florbetapir PET data with corresponding T1-MPRAGE MRI images. Compared to the intensity-only JE-MAP algorithm, the WJE

Algorithmic, LOCS and HOCS (chemistry) exam questions: performance and attitudes of college students

NASA Astrophysics Data System (ADS)

Zoller, Uri

2002-02-01

The performance of freshmen biology and physics-mathematics majors and chemistry majors as well as pre- and in-service chemistry teachers in two Israeli universities on algorithmic (ALG), lower-order cognitive skills (LOCS), and higher-order cognitive skills (HOCS) chemistry exam questions were studied. The driving force for the study was an interest in moving science and chemistry instruction from an algorithmic and factual recall orientation dominated by LOCS, to a decision-making, problem-solving and critical system thinking approach, dominated by HOCS. College students' responses to the specially designed ALG, LOCS and HOCS chemistry exam questions were scored and analysed for differences and correlation between the performance means within and across universities by the questions' category. This was followed by a combined student interview - 'speaking aloud' problem solving session for assessing the thinking processes involved in solving these types of questions and the students' attitudes towards them. The main findings were: (1) students in both universities performed consistently in each of the three categories in the order of ALG > LOCS > HOCS; their 'ideological' preference, was HOCS > algorithmic/LOCS, - referred to as 'computational questions', but their pragmatic preference was the reverse; (2) success on algorithmic/LOCS does not imply success on HOCS questions; algorithmic questions constitute a category on its own as far as students success in solving them is concerned. Our study and its results support the effort being made, worldwide, to integrate HOCS-fostering teaching and assessment strategies and, to develop HOCS-oriented science-technology-environment-society (STES)-type curricula within science and chemistry education.

Delivering preference for place of death in a specialist palliative care setting.

PubMed

Oxenham, David; Finucane, Anne; Arnold, Elizabeth; Russell, Papiya

2013-01-01

Over the last 10 years, one of the key themes of public policy in palliative care has been achievement of choice in place of death. In Marie Curie Hospice Edinburgh a baseline audit conducted in 2006 showed that only a small proportion (18%) of patients referred to hospice services died at home. The audit also revealed that only 31% of those who expressed a preference to die at home were able to do so, whereas 91% of those who chose a setting other than home achieved their preference. Overall achievement of preferred place of death was 56%. However a significant number of patients (29%) did not have a recorded preference. A programme of quality improvement has continued over the last 7 years to improve identification, communication and achievement of preferred place of death for all patients. The mechanisms to change practice have been: changes to documentation; changes to clinical systems to support use of documentation; support for clinical staff to recognise the value of discussing preferences; and support for clinical staff to develop new skills. In addition the programme has been incorporated into local clinical strategy and this has enabled gaps in service to be addressed with a new service to support early discharge of those patients who wish to die at home. A recent audit showed that all patients had a recorded preference or a documented reason why their preference was unclarified. One third of patients died at home - nearly double the proportion that died at home in the baseline audit. Seventy one per cent of patients who wished to die at home actually died at home - a substantial increase from 31% at baseline. Achievement of preferred place of death for patients wishing to die in the hospice remained high at 88%. The focus on assessment of preference for place of death has led to substantial improvements in the identification and achievement of preference for patients dying under the care of the hospice. Furthermore, it has been associated with an

On Optimizing H. 264/AVC Rate Control by Improving R-D Model and Incorporating HVS Characteristics

NASA Astrophysics Data System (ADS)

Zhu, Zhongjie; Wang, Yuer; Bai, Yongqiang; Jiang, Gangyi

2010-12-01

The state-of-the-art JVT-G012 rate control algorithm of H.264 is improved from two aspects. First, the quadratic rate-distortion (R-D) model is modified based on both empirical observations and theoretical analysis. Second, based on the existing physiological and psychological research findings of human vision, the rate control algorithm is optimized by incorporating the main characteristics of the human visual system (HVS) such as contrast sensitivity, multichannel theory, and masking effect. Experiments are conducted, and experimental results show that the improved algorithm can simultaneously enhance the overall subjective visual quality and improve the rate control precision effectively.

Reducing preference reversals: The role of preference imprecision and nontransparent methods.

PubMed

Pinto-Prades, José Luis; Sánchez-Martínez, Fernando Ignacio; Abellán-Perpiñán, José María; Martínez-Pérez, Jorge E

2018-05-16

Preferences elicited with matching and choice usually diverge (as characterised by preference reversals), violating a basic rationality requirement, namely, procedure invariance. We report the results of an experiment that shows that preference reversals between matching (Standard Gamble in our case) and choice are reduced when the matching task is conducted using nontransparent methods. Our results suggest that techniques based on nontransparent methods are less influenced by biases (i.e., compatibility effects) than transparent methods. We also observe that imprecision of preferences influences the degree of preference reversals. The preference reversal phenomenon is less strong in subjects with more precise preferences. Copyright © 2018 John Wiley & Sons, Ltd.

The evaluation of the OSGLR algorithm for restructurable controls

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.

1986-01-01

The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.

Technetium incorporation into goethite (α-FeOOH): An atomic-scale investigation

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

Smith, Frances N.; Taylor, Christopher D.; Um, Wooyong

2015-11-17

During the processing of low-activity radioactive waste to generate solid waste forms (e.g., glass), technetium-99 (Tc) is of concern because of its volatility. A variety of materials are under consideration to capture Tc from waste streams, including the iron oxyhydroxide, goethite (α-FeOOH), which was experimentally shown to sequester Tc(IV). This material could ultimately be incorporated into glass or other low-temperature waste form matrices. However, questions remain regarding the incorporation mechanism for Tc(IV) in goethite, which has implications for predicting the long-term stability of Tc in waste forms under changing conditions. Here, quantum-mechanical calculations were used to evaluate the energy ofmore » five different charge-compensated Tc(IV) incorporation scenarios in goethite. The two most stable incorporation mechanisms involve direct substitution of Tc(IV) onto Fe(III) lattice sites and charge balancing either by removing one nearby H+ (i.e., within 5 Å), or by creating an Fe(III) vacancy when substituting 3 Tc(IV) for 4 Fe(III), with the former being preferred over the latter relative to gas-phase ions. When corrections for hydrated references phases are applied, the Fe(III)-vacancy mechanism becomes more energetically competitive. Calculated incorporation energies and optimized bond-lengths are presented. Proton movement is observed to satisfy under-coordinated bonds surrounding vacancies in the goethite structure.« less

A strategy for measuring patient preferences to incorporate in benefit-risk assessment of new ophthalmic devices and procedures

NASA Astrophysics Data System (ADS)

Massof, R. W.; Bradley, C.

2016-11-01

The U.S. Food and Drug Administration recently released guidance documents explaining that measurement of patient preferences should be considered during the pre-market approval process to specify patients’ tolerances for risk and perspectives on benefit when assessing the benefit-risk profile of new medical devices. For ophthalmological patients, the typical primary clinical outcome is a visual impairment measure. Especially for surgically- implanted devices, the benefit a specified improvement in vision measures must be translated to a patient-specific benefit of the improvement in ability to function in everyday life. We developed, and validated with simulations, a strategy for measuring an individual patient's ability to function and the overall benefit to that patient of specified improvements in functional ability. Our strategy employs Rasch analysis to measure changes in functional ability; multidimensional scaling to measure patient-specific benefits of changes in functional ability; and structural equation modeling to cross-walk patient preferences for functional ability changes to changes in visual impairment measures.

Kinematic comparison of the preferred and non-preferred foot punt kick.

PubMed

Ball, Kevin A

2011-11-01

Kicking with the non-preferred leg is important in Australian Football and becoming important in the rugby codes. The aim of this study was to examine differences between preferred and non-preferred leg kicking in the drop punt kick. Seventeen elite Australian Football players performed kicks with the preferred and non-preferred leg. Optotrak Certus collected kinematic data of the kick leg and pelvis (200 Hz) from kick leg toe-off until ball contact. Foot speed, knee and shank angular velocity at ball contact, and pelvis range of motion were significantly larger for the preferred leg (P < 0.05). In contrast, hip and thigh angular velocity at ball contact and hip range of motion were significantly larger for the non-preferred leg. This indicates different movement patterns, with preferred-leg kicks making greater use of the pelvis, knee, and shank while non-preferred leg kicks rely relatively more on the hip and thigh (P < 0.05). Reasons for this difference might be due to locking degrees of freedom or sub-optimal sequencing in the non-preferred leg. The thigh-knee continuum identified by Ball ( 2008 ) was also evident in this study. Findings have implications for training non-preferred leg kicking for performance and injury prevention.

Using patient values and preferences to inform the importance of health outcomes in practice guideline development following the GRADE approach.

PubMed

Zhang, Yuan; Coello, Pablo Alonso; Brożek, Jan; Wiercioch, Wojtek; Etxeandia-Ikobaltzeta, Itziar; Akl, Elie A; Meerpohl, Joerg J; Alhazzani, Waleed; Carrasco-Labra, Alonso; Morgan, Rebecca L; Mustafa, Reem A; Riva, John J; Moore, Ainsley; Yepes-Nuñez, Juan José; Cuello-Garcia, Carlos; AlRayees, Zulfa; Manja, Veena; Falavigna, Maicon; Neumann, Ignacio; Brignardello-Petersen, Romina; Santesso, Nancy; Rochwerg, Bram; Darzi, Andrea; Rojas, Maria Ximena; Adi, Yaser; Bollig, Claudia; Waziry, Reem; Schünemann, Holger J

2017-05-02

There are diverse opinions and confusion about defining and including patient values and preferences (i.e. the importance people place on the health outcomes) in the guideline development processes. This article aims to provide an overview of a process for systematically incorporating values and preferences in guideline development. In 2013 and 2014, we followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to adopt, adapt and develop 226 recommendations in 22 guidelines for the Ministry of Health of the Kingdom of Saudi Arabia. To collect context-specific values and preferences for each recommendation, we performed systematic reviews, asked clinical experts to provide feedback according to their clinical experience, and consulted patient representatives. We found several types of studies addressing the importance of outcomes, including those reporting utilities, non-utility measures of health states based on structured questionnaires or scales, and qualitative studies. Guideline panels used the relative importance of outcomes based on values and preferences to weigh the balance of desirable and undesirable consequences of alternative intervention options. However, we found few studies addressing local values and preferences. Currently there are different but no firmly established processes for integrating patient values and preferences in healthcare decision-making of practice guideline development. With GRADE Evidence-to-Decision (EtD) frameworks, we provide an empirical strategy to find and incorporate values and preferences in guidelines by performing systematic reviews and eliciting information from guideline panel members and patient representatives. However, more research and practical guidance are needed on how to search for relevant studies and grey literature, assess the certainty of this evidence, and best summarize and present the findings.

Pressure algorithm for elliptic flow calculations with the PDF method

NASA Technical Reports Server (NTRS)

Anand, M. S.; Pope, S. B.; Mongia, H. C.

1991-01-01

An algorithm to determine the mean pressure field for elliptic flow calculations with the probability density function (PDF) method is developed and applied. The PDF method is a most promising approach for the computation of turbulent reacting flows. Previous computations of elliptic flows with the method were in conjunction with conventional finite volume based calculations that provided the mean pressure field. The algorithm developed and described here permits the mean pressure field to be determined within the PDF calculations. The PDF method incorporating the pressure algorithm is applied to the flow past a backward-facing step. The results are in good agreement with data for the reattachment length, mean velocities, and turbulence quantities including triple correlations.

Chimpanzees’ socially maintained food preferences indicate both conservatism and conformity

PubMed Central

Hopper, Lydia M.; Schapiro, Steven J.; Lambeth, Susan P.; Brosnan, Sarah F.

2015-01-01

Chimpanzees remain fixed on a single strategy, even if a novel, more efficient, strategy is introduced. Previous studies reporting such findings have incorporated paradigms in which chimpanzees learn one behavioural method and then are shown a new one that the chimpanzees invariably do not adopt. This study provides the first evidence that chimpanzees show such conservatism even when the new method employs the identical required behaviour as the first, but for a different reward. Groups of chimpanzees could choose to exchange one of two types of inedible tokens, with each token type being associated with a different food reward: one type was rewarded with a highly preferred food (grape) and the other type was rewarded with a less preferred food (carrot). Individuals first observed a model chimpanzee from their social group trained to choose one of the two types of tokens. In one group, this token earned a carrot, while in the other, control, group the token earned a grape. In both groups, chimpanzees conformed to the trained model’s choice. This was especially striking for those gaining the pieces of carrot, the less favoured reward. This resulted in a population-level trend of food choices, even when counter to their original, individual, preferences. Moreover, the chimpanzees’ food preferences did not change over time, demonstrating that these results were not due to a simple shift in preferences. We discuss social factors apparent in the interactions and suggest that, despite seeming to be inefficient, in chimpanzees, conformity may benefit them, possibly by assisting with the maintenance of group relations. PMID:27011390

Applying a multi-criteria genetic algorithm framework for brownfield reuse optimization: improving redevelopment options based on stakeholder preferences.

PubMed

Morio, Maximilian; Schädler, Sebastian; Finkel, Michael

2013-11-30

The reuse of underused or abandoned contaminated land, so-called brownfields, is increasingly seen as an important means for reducing the consumption of land and natural resources. Many existing decision support systems are not appropriate because they focus mainly on economic aspects, while neglecting sustainability issues. To fill this gap, we present a framework for spatially explicit, integrated planning and assessment of brownfield redevelopment options. A multi-criteria genetic algorithm allows us to determine optimal land use configurations with respect to assessment criteria and given constraints on the composition of land use classes, according to, e.g., stakeholder preferences. Assessment criteria include sustainability indicators as well as economic aspects, including remediation costs and land value. The framework is applied to a case study of a former military site near Potsdam, Germany. Emphasis is placed on the trade-off between possibly conflicting objectives (e.g., economic goals versus the need for sustainable development in the regional context of the brownfield site), which may represent different perspectives of involved stakeholders. The economic analysis reveals the trade-off between the increase in land value due to reuse and the costs for remediation required to make reuse possible. We identify various reuse options, which perform similarly well although they exhibit different land use patterns. High-cost high-value options dominated by residential land use and low-cost low-value options with less sensitive land use types may perform equally well economically. The results of the integrated analysis show that the quantitative integration of sustainability may change optimal land use patterns considerably. Copyright © 2013 Elsevier Ltd. All rights reserved.

How Are Preferences Revealed?

PubMed Central

Beshears, John; Choi, James J.; Laibson, David; Madrian, Brigitte C.

2009-01-01

Revealed preferences are tastes that rationalize an economic agent’s observed actions. Normative preferences represent the agent’s actual interests. It sometimes makes sense to assume that revealed preferences are identical to normative preferences. But there are many cases where this assumption is violated. We identify five factors that increase the likelihood of a disparity between revealed preferences and normative preferences: passive choice, complexity, limited personal experience, third-party marketing, and intertemporal choice. We then discuss six approaches that jointly contribute to the identification of normative preferences: structural estimation, active decisions, asymptotic choice, aggregated revealed preferences, reported preferences, and informed preferences. Each of these approaches uses consumer behavior to infer some property of normative preferences without equating revealed and normative preferences. We illustrate these issues with evidence from savings and investment outcomes. PMID:24761048

Competitive Incorporation of Perrhenate and Nitrate into Sodalite

DOE PAGES

Dickson, Johnbull O.; Harsh, James B.; Flury, Markus; ...

2014-10-03

Nuclear waste storage tanks at the Hanford site in southeastern Washington have released highly alkaline solutions, containing radioactive and other contaminants, into subsurface sediments. When this waste reacts with subsurface sediments, feldspathoid minerals (sodalite, cancrinite) can form, sequestering pertechnetate ( 99TcO 4 –) and other ions. This study investigates the potential for incorporation of perrhenate (ReO 4 –), a chemical surrogate for 99TcO 4 –, into mixed perrhenate/nitrate (ReO 4 –/NO 3 –) sodalite. Mixed-anion sodalites were hydrothermally synthesized in the laboratory from zeolite A in sodium hydroxide, nitrate, and perrhenate solutions at 90 °C for 24 h. The resultingmore » solids were characterized by bulk chemical analysis, X-ray diffraction, scanning electron microscopy, and X-ray absorption near edge structure spectroscopy (XANES) to determine the products’ chemical composition, structure, morphology, and Re oxidation state. The XANES data indicated that nearly all rhenium (Re) was incorporated as Re(VII)O 4 –. The nonlinear increase of the unit cell parameter with ReO 4 –/NO 3 – ratios suggests formation of two separate sodalite phases in lieu of a mixed-anion sodalite. The results reveal that the sodalite cage is highly selective toward NO 3 – over ReO 4 –. Calculated enthalpy and Gibbs free energy of formation at 298 K for NO 3 - and ReO 4 -sodalite suggest that NO 3 – incorporation into the cage is favored over the incorporation of the larger ReO 4 –, due to the smaller ionic radius of NO 3 –. In conclusion, based on these results, it is expected that NO 3 –, which is present at significantly higher concentrations in alkaline waste solutions than 99TcO 4 –, will be strongly preferred for incorporation into the sodalite cage.« less

Sustainability assessment in forest management based on individual preferences.

PubMed

Martín-Fernández, Susana; Martinez-Falero, Eugenio

2018-01-15

This paper presents a methodology to elicit the preferences of any individual in the assessment of sustainable forest management at the stand level. The elicitation procedure was based on the comparison of the sustainability of pairs of forest locations. A sustainability map of the whole territory was obtained according to the individual's preferences. Three forest sustainability indicators were pre-calculated for each point in a study area in a Scots pine forest in the National Park of Sierra de Guadarrama in the Madrid Region in Spain to obtain the best management plan with the sustainability map. We followed a participatory process involving fifty people to assess the sustainability of the forest management and the methodology. The results highlighted the demand for conservative forest management, the usefulness of the methodology for managers, and the importance and necessity of incorporating stakeholders into forestry decision-making processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transitivity of Preferences

ERIC Educational Resources Information Center

Regenwetter, Michel; Dana, Jason; Davis-Stober, Clintin P.

2011-01-01

Transitivity of preferences is a fundamental principle shared by most major contemporary rational, prescriptive, and descriptive models of decision making. To have transitive preferences, a person, group, or society that prefers choice option "x" to "y" and "y" to "z" must prefer "x" to…

To IMPRES or to EXPRES? Exploiting comparative judgments to measure and visualize implicit and explicit preferences.

PubMed

Everaert, Tom; Spruyt, Adriaan; De Houwer, Jan

2018-01-01

We introduce an adaptation of the affect misattribution procedure (AMP), called the implicit preference scale (IMPRES). Participants who complete the IMPRES indicate their preference for one of two, simultaneously presented Chinese ideographs. Each ideograph is preceded by a briefly presented prime stimulus that is irrelevant to the task. Participants are hypothesized to prefer the ideograph that is preceded by the prime they prefer. In the present research, the IMPRES was designed to capture racial attitudes (preferences for white versus black faces) and age-related attitudes (preferences for young versus old faces). Results suggest that (a) the reliability of the IMPRES is similar (or even better) than the reliability of the AMP and (b) that the IMPRES and the AMP correlate significantly. However, neither the AMP nor the IMPRES were found to predict attitude-related outcome behavior (i.e., the preparedness to donate money to a charity benefiting ethnic minorities vs. the elderly). Further research is thus necessary to establish the validity of the IMPRES. Finally, we demonstrated that, unlike the AMP, the IMPRES allows for an in-depth assessment of unanticipated response patterns and/or extreme observations using multidimensional scaling algorithms.

Optimal spiral phase modulation in Gerchberg-Saxton algorithm for wavefront reconstruction and correction

NASA Astrophysics Data System (ADS)

Baránek, M.; Běhal, J.; Bouchal, Z.

2018-01-01

In the phase retrieval applications, the Gerchberg-Saxton (GS) algorithm is widely used for the simplicity of implementation. This iterative process can advantageously be deployed in the combination with a spatial light modulator (SLM) enabling simultaneous correction of optical aberrations. As recently demonstrated, the accuracy and efficiency of the aberration correction using the GS algorithm can be significantly enhanced by a vortex image spot used as the target intensity pattern in the iterative process. Here we present an optimization of the spiral phase modulation incorporated into the GS algorithm.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem.

PubMed

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA.

Algorithm integration using ADL (Algorithm Development Library) for improving CrIMSS EDR science product quality

NASA Astrophysics Data System (ADS)

Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.

2013-05-01

Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.

A Hybrid Cellular Genetic Algorithm for Multi-objective Crew Scheduling Problem

NASA Astrophysics Data System (ADS)

Jolai, Fariborz; Assadipour, Ghazal

Crew scheduling is one of the important problems of the airline industry. This problem aims to cover a number of flights by crew members, such that all the flights are covered. In a robust scheduling the assignment should be so that the total cost, delays, and unbalanced utilization are minimized. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimization method. The proposed algorithm provides the decision maker with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Evaluating the performance of the proposed algorithm, three metrics are suggested, and the diversity and the convergence of the achieved Pareto front are appraised. Finally a comparison is made between CellDE and PAES, another meta-heuristic algorithm. The results show the superiority of CellDE.

[Tachycardia detection in implantable cardioverter-defibrillators by Sorin/LivaNova : Algorithms, pearls and pitfalls].

PubMed

Kolb, Christof; Ocklenburg, Rolf

2016-09-01

For physicians involved in the treatment of patients with implantable cardioverter-defibrillators (ICDs) the knowledge of tachycardia detection algorithms is of paramount importance. This knowledge is essential for adequate device selection during de-novo implantation, ICD replacement, and for troubleshooting during follow-up. This review describes tachycardia detection algorithms incorporated in ICDs by Sorin/LivaNova and analyses their strengths and weaknesses.

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

NASA Astrophysics Data System (ADS)

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Baillet, Clio; Vermandel, Maximilien

2015-12-01

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians’ manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

PubMed

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Baillet, Clio; Vermandel, Maximilien

2015-12-21

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians' manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.

BootGraph: probabilistic fiber tractography using bootstrap algorithms and graph theory.

PubMed

Vorburger, Robert S; Reischauer, Carolin; Boesiger, Peter

2013-02-01

Bootstrap methods have recently been introduced to diffusion-weighted magnetic resonance imaging to estimate the measurement uncertainty of ensuing diffusion parameters directly from the acquired data without the necessity to assume a noise model. These methods have been previously combined with deterministic streamline tractography algorithms to allow for the assessment of connection probabilities in the human brain. Thereby, the local noise induced disturbance in the diffusion data is accumulated additively due to the incremental progression of streamline tractography algorithms. Graph based approaches have been proposed to overcome this drawback of streamline techniques. For this reason, the bootstrap method is in the present work incorporated into a graph setup to derive a new probabilistic fiber tractography method, called BootGraph. The acquired data set is thereby converted into a weighted, undirected graph by defining a vertex in each voxel and edges between adjacent vertices. By means of the cone of uncertainty, which is derived using the wild bootstrap, a weight is thereafter assigned to each edge. Two path finding algorithms are subsequently applied to derive connection probabilities. While the first algorithm is based on the shortest path approach, the second algorithm takes all existing paths between two vertices into consideration. Tracking results are compared to an established algorithm based on the bootstrap method in combination with streamline fiber tractography and to another graph based algorithm. The BootGraph shows a very good performance in crossing situations with respect to false negatives and permits incorporating additional constraints, such as a curvature threshold. By inheriting the advantages of the bootstrap method and graph theory, the BootGraph method provides a computationally efficient and flexible probabilistic tractography setup to compute connection probability maps and virtual fiber pathways without the drawbacks of

Some aspects of algorithm performance and modeling in transient analysis of structures

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

1981-01-01

The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit algorithms with variable time steps, known as the GEAR package, is described. Four test problems, used for evaluating and comparing various algorithms, were selected and finite-element models of the configurations are described. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system, and a model of the wing of the space shuttle orbiter. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures).

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

A hierarchical word-merging algorithm with class separability measure.

PubMed

Wang, Lei; Zhou, Luping; Shen, Chunhua; Liu, Lingqiao; Liu, Huan

2014-03-01

In image recognition with the bag-of-features model, a small-sized visual codebook is usually preferred to obtain a low-dimensional histogram representation and high computational efficiency. Such a visual codebook has to be discriminative enough to achieve excellent recognition performance. To create a compact and discriminative codebook, in this paper we propose to merge the visual words in a large-sized initial codebook by maximally preserving class separability. We first show that this results in a difficult optimization problem. To deal with this situation, we devise a suboptimal but very efficient hierarchical word-merging algorithm, which optimally merges two words at each level of the hierarchy. By exploiting the characteristics of the class separability measure and designing a novel indexing structure, the proposed algorithm can hierarchically merge 10,000 visual words down to two words in merely 90 seconds. Also, to show the properties of the proposed algorithm and reveal its advantages, we conduct detailed theoretical analysis to compare it with another hierarchical word-merging algorithm that maximally preserves mutual information, obtaining interesting findings. Experimental studies are conducted to verify the effectiveness of the proposed algorithm on multiple benchmark data sets. As shown, it can efficiently produce more compact and discriminative codebooks than the state-of-the-art hierarchical word-merging algorithms, especially when the size of the codebook is significantly reduced.

An approach to decision-making with triangular fuzzy reciprocal preference relations and its application

NASA Astrophysics Data System (ADS)

Meng, Fanyong

2018-02-01

Triangular fuzzy reciprocal preference relations (TFRPRs) are powerful tools to denoting decision-makers' fuzzy judgments, which permit the decision-makers to apply triangular fuzzy ratio rather than real numbers to express their judgements. Consistency analysis is one of the most crucial issues in preference relations that can guarantee the reasonable ranking order. However, all previous consistency concepts cannot well address this type of preference relations. Based on the operational laws on triangular fuzzy numbers, this paper introduces an additive consistency concept for TFRPRs by using quasi TFRPRs, which can be seen as a natural extension of the crisp case. Using this consistency concept, models to judging the additive consistency of TFRPRs and to estimating missing values in complete TFRPRs are constructed. Then, an algorithm to decision-making with TFRPRs is developed. Finally, two numerical examples are offered to illustrate the application of the proposed procedure, and comparison analysis is performed.

Automated measurement of spatial preference in the open field test with transmitted lighting.

PubMed

Kulikov, Alexander V; Tikhonova, Maria A; Kulikov, Victor A

2008-05-30

New modification of the open field was designed to improve automation of the test. The main innovations were: (1) transmitted lighting and (2) estimation of probability to find pixels associated with an animal in the selected region of arena as an objective index of spatial preference. Transmitted (inverted) lighting significantly ameliorated the contrast between an animal and arena and allowed to track white animals with similar efficacy as colored ones. Probability as a measure of preference of selected region was mathematically proved and experimentally verified. A good correlation between probability and classic indices of spatial preference (number of region entries and time spent therein) was shown. The algorithm of calculation of probability to find pixels associated with an animal in the selected region was implemented in the EthoStudio software. Significant interstrain differences in locomotion and the central zone preference (index of anxiety) were shown using the inverted lighting and the EthoStudio software in mice of six inbred strains. The effects of arena shape (circle or square) and a novel object presence in the center of arena on the open field behavior in mice were studied.

Conformational Preferences of β– and γ–Aminated Proline Analogues

PubMed Central

Flores-Ortega, Alejandra; Casanovas, Jordi; Nussinov, Ruth; Alemán, Carlos

2010-01-01

Quantum mechanical calculations have been used to investigate how the incorporation of an amino group to the Cβ- or Cγ-positions of the pyrrolidine ring affects the intrinsic conformational properties of the proline. Specifically, a conformational study of the N-acetyl-N′-methylamide derivatives of four isomers of aminoproline, which differ not only in the β- or γ-position of the substituent but also in its cis or trans relative disposition, has been performed. In order to further understand the role of the intramolecular hydrogen bonds between the backbone carbonyl groups and the amino side group, a conformational study was also performed on the corresponding four analogues of dimethylaminoproline. In addition, the effects of solvation on aminoproline and dimethylaminoproline dipeptides have been evaluated using a Self Consistent Reaction Field model, and considering four different solvents (carbon tetrachloride, chloroform, methanol and water). Results indicate that the incorporation of the amino substituent into the pyrrolidine ring affects the conformational properties, with backbone⋯side chain intramolecular hydrogen bonds detected when it is incorporated in a cis relative disposition. In general, the incorporation of the amino side group tends to stabilize those structures where the peptide bond involving the pyrrolidine nitrogen is arranged in cis. The aminoproline isomer with the substituent attached to the Cγ-position with a cis relative disposition is the most stable in the gas-phase and in chloroform, methanol and water solutions. Replacement of the amino side group by the dimethylamino substituent produces significant changes in the potential energy surfaces of the four investigated dimethylaminoproline-containing dipeptides. Thus, these changes affect not only the number of minima, which increases considerably, but also the backbone and pseudorotational preferences. In spite of these effects, comparison of the conformational preferences, i

An item-oriented recommendation algorithm on cold-start problem

NASA Astrophysics Data System (ADS)

Qiu, Tian; Chen, Guang; Zhang, Zi-Ke; Zhou, Tao

2011-09-01

Based on a hybrid algorithm incorporating the heat conduction and probability spreading processes (Proc. Natl. Acad. Sci. U.S.A., 107 (2010) 4511), in this letter, we propose an improved method by introducing an item-oriented function, focusing on solving the dilemma of the recommendation accuracy between the cold and popular items. Differently from previous works, the present algorithm does not require any additional information (e.g., tags). Further experimental results obtained in three real datasets, RYM, Netflix and MovieLens, show that, compared with the original hybrid method, the proposed algorithm significantly enhances the recommendation accuracy of the cold items, while it keeps the recommendation accuracy of the overall and the popular items. This work might shed some light on both understanding and designing effective methods for long-tailed online applications of recommender systems.

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

NASA Technical Reports Server (NTRS)

Karr, C. L.; Freeman, L. M.; Meredith, D. L.

1990-01-01

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

An efficient robust sound classification algorithm for hearing aids.

PubMed

Nordqvist, Peter; Leijon, Arne

2004-06-01

An efficient robust sound classification algorithm based on hidden Markov models is presented. The system would enable a hearing aid to automatically change its behavior for differing listening environments according to the user's preferences. This work attempts to distinguish between three listening environment categories: speech in traffic noise, speech in babble, and clean speech, regardless of the signal-to-noise ratio. The classifier uses only the modulation characteristics of the signal. The classifier ignores the absolute sound pressure level and the absolute spectrum shape, resulting in an algorithm that is robust against irrelevant acoustic variations. The measured classification hit rate was 96.7%-99.5% when the classifier was tested with sounds representing one of the three environment categories included in the classifier. False-alarm rates were 0.2%-1.7% in these tests. The algorithm is robust and efficient and consumes a small amount of instructions and memory. It is fully possible to implement the classifier in a DSP-based hearing instrument.

Young women's contraceptive microbicide preferences: associations with contraceptive behavior and sexual relationship characteristics.

PubMed

Best, Candace; Tanner, Amanda E; Hensel, Devon J; Fortenberry, J Dennis; Zimet, Gregory D

2014-03-01

In time, microbicides may provide women with dual prevention against pregnancy and STDs. Although several microbicide dimensions have been evaluated, little is known about women's preferences for contraceptive microbicides and correlates of these preferences. Acceptability of a hypothetical contraceptive microbicide cream or jelly was examined among a -clinic-based sample of 266 women in Indianapolis from 2004 (when participants were aged 14-22) to 2008. Group conjoint analyses and individual conjoint analyses were used to compare preferences with respect to four microbicide -dimensions: contraceptive ability, efficacy in relation to condoms, timing of use and texture. Pearson's product moment correlations were used to examine the relationship between preferences for a contraceptive microbicide and selected characteristics of the women. Overall, the top-rated microbicide dimensions were efficacy in relation to that of condoms and contraceptive ability (importance scores, 40.0 and 35.4 out of 100.0, respectively). When all dimension levels were compared, contraceptive ability was the most strongly preferred (part-worth utility score, 8.9), and lower efficacy than that of -condoms was the least strongly preferred (-11.9). Preference for contraceptive microbicides was positively -associated with current contraceptive use, sexual agency, partner communication, commitment to avoiding pregnancy and -perceived partner agreement about avoiding pregnancy (coefficients, 0.07-0.18). It was negatively associated with current or past nonuse of contraceptives, seeking pregnancy and perceived partner agreement about seeking -pregnancy (-0.08 to -0.14). Microbicides with dual prevention properties may be attractive to young women. Microbicide development and subsequent clinical trials should incorporate contraceptive microbicides. Copyright © 2013 by the Guttmacher Institute.

Application of Particle Swarm Optimization Algorithm in the Heating System Planning Problem

PubMed Central

Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

2013-01-01

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem. PMID:23935429

Modeling the Effect of Enlarging Seating Room on Passengers' Preference of Taiwan's Domestic Airlines

NASA Technical Reports Server (NTRS)

Lu, Jin-Long; Tsai, Li-Non

2003-01-01

This study addresses the need for measuring the effect of enlarging seating room in airplane on passengers' preferences of airline in Taiwan. The results can assist Taiwan's domestic air carriers in better understanding their customers' expectations. Stated choice experiment is used to incorporate passengers' trade-offs in the preferred measurement, and three major attributes are taken into account in the stated choice experiment: (1) type of seat (enlarged or not), (2) price, and (3) brand names of airlines. Furthermore, a binary logit model is used to model the choice behavior of air passengers. The findings show that the type of seat is a major significant variable; price and airline's brand are also significant as well. It concludes that air carriers should put more emphasis on the issue of improving the quality of seat comfort. Keywords: Passengers' preference, Enlarged seating room, Stated choice experiment, Binary logit model.

Patient preferences versus physicians' judgement: does it make a difference in healthcare decision making?

PubMed

Mühlbacher, Axel C; Juhnke, Christin

2013-06-01

and the patient. This in turn may keep physicians from fully appreciating the impact of certain medical conditions on patient preferences. Because differences exist between physicians' judgement and patient preferences, it is important to incorporate the needs and wants of the patient into treatment decisions.

[High resolution reconstruction of PET images using the iterative OSEM algorithm].

PubMed

Doll, J; Henze, M; Bublitz, O; Werling, A; Adam, L E; Haberkorn, U; Semmler, W; Brix, G

2004-06-01

Improvement of the spatial resolution in positron emission tomography (PET) by incorporation of the image-forming characteristics of the scanner into the process of iterative image reconstruction. All measurements were performed at the whole-body PET system ECAT EXACT HR(+) in 3D mode. The acquired 3D sinograms were sorted into 2D sinograms by means of the Fourier rebinning (FORE) algorithm, which allows the usage of 2D algorithms for image reconstruction. The scanner characteristics were described by a spatially variant line-spread function (LSF), which was determined from activated copper-64 line sources. This information was used to model the physical degradation processes in PET measurements during the course of 2D image reconstruction with the iterative OSEM algorithm. To assess the performance of the high-resolution OSEM algorithm, phantom measurements performed at a cylinder phantom, the hotspot Jaszczack phantom, and the 3D Hoffmann brain phantom as well as different patient examinations were analyzed. Scanner characteristics could be described by a Gaussian-shaped LSF with a full-width at half-maximum increasing from 4.8 mm at the center to 5.5 mm at a radial distance of 10.5 cm. Incorporation of the LSF into the iteration formula resulted in a markedly improved resolution of 3.0 and 3.5 mm, respectively. The evaluation of phantom and patient studies showed that the high-resolution OSEM algorithm not only lead to a better contrast resolution in the reconstructed activity distributions but also to an improved accuracy in the quantification of activity concentrations in small structures without leading to an amplification of image noise or even the occurrence of image artifacts. The spatial and contrast resolution of PET scans can markedly be improved by the presented image restauration algorithm, which is of special interest for the examination of both patients with brain disorders and small animals.

Factors Influencing Parents' Preferences and Parents' Perceptions of Child Preferences of Picturebooks

PubMed Central

Wagner, Laura

2017-01-01

This study examined factors influencing parents' preferences and their perceptions of their children's preferences for picturebooks. First, a content analysis was conducted on a set of picturebooks (N = 87) drawn from the sample described in Wagner (2013); Then, parents (N = 149) rated the books and several content properties were examined for their ability to predict parents' preferences and their perception of their children's preferences. The initial content analysis found correlated clusters of disparate measures of complexity (linguistic, cognitive, narrative) and identified a distinctive sub-genre of modern books featuring female protagonists. The experimental preference analysis found that parents' own preferences were most influenced by the books' age and status; parents' perceptions of their children's preferences were influenced by gender, with parents perceiving their sons (but not daughters) as dis-preferring books with female protagnoists. In addition, influences of the child's reading ability and the linguistic complexity of the book on preferences suggested a sensitivity to the cultural practice of joint book-reading. PMID:28919869

Association of health literacy with health information-seeking preference in older people: A correlational, descriptive study.

PubMed

Kim, Su Hyun; Utz, Sonja

2018-02-28

Low health literacy has been recognized as a potential barrier to obtaining knowledge and maintaining self-care in older people. However, little is known about information-seeking preference in relation to health literacy among older people. The aim of the present study was to understand the influence of health literacy on the information-seeking preference of older people. A total of 129 community-residing Korean older people completed a survey in 2016. The findings revealed that health literacy was a significant predictor of information-seeking preference in older people after controlling for demographic and illness variables. Our study highlights the important need to incorporate strategies to increase the desire for information seeking in older people, in addition to adopting communication strategies that address low health literacy. © 2018 John Wiley & Sons Australia, Ltd.

Genetic Algorithm Design of a 3D Printed Heat Sink

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

Wu, Tong; Ozpineci, Burak; Ayers, Curtis William

2016-01-01

In this paper, a genetic algorithm- (GA-) based approach is discussed for designing heat sinks based on total heat generation and dissipation for a pre-specified size andshape. This approach combines random iteration processesand genetic algorithms with finite element analysis (FEA) to design the optimized heat sink. With an approach that prefers survival of the fittest , a more powerful heat sink can bedesigned which can cool power electronics more efficiently. Some of the resulting designs can only be 3D printed due totheir complexity. In addition to describing the methodology, this paper also includes comparisons of different cases to evaluate themore » performance of the newly designed heat sinkcompared to commercially available heat sinks.« less

Automatic Regionalization Algorithm for Distributed State Estimation in Power Systems

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

Wang, Dexin; Yang, Liuqing; Florita, Anthony

The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the helpmore » of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.« less

A dynamically adaptive multigrid algorithm for the incompressible Navier-Stokes equations: Validation and model problems

NASA Technical Reports Server (NTRS)

Thompson, C. P.; Leaf, G. K.; Vanrosendale, J.

1991-01-01

An algorithm is described for the solution of the laminar, incompressible Navier-Stokes equations. The basic algorithm is a multigrid based on a robust, box-based smoothing step. Its most important feature is the incorporation of automatic, dynamic mesh refinement. This algorithm supports generalized simple domains. The program is based on a standard staggered-grid formulation of the Navier-Stokes equations for robustness and efficiency. Special grid transfer operators were introduced at grid interfaces in the multigrid algorithm to ensure discrete mass conservation. Results are presented for three models: the driven-cavity, a backward-facing step, and a sudden expansion/contraction.

Preferences and beliefs in ingroup favoritism.

PubMed

Everett, Jim A C; Faber, Nadira S; Crockett, Molly

2015-01-01

Ingroup favoritism-the tendency to favor members of one's own group over those in other groups-is well documented, but the mechanisms driving this behavior are not well understood. In particular, it is unclear to what extent ingroup favoritism is driven by preferences concerning the welfare of ingroup over outgroup members, vs. beliefs about the behavior of ingroup and outgroup members. In this review we analyze research on ingroup favoritism in economic games, identifying key gaps in the literature and providing suggestions on how future work can incorporate these insights to shed further light on when, why, and how ingroup favoritism occurs. In doing so, we demonstrate how social psychological theory and research can be integrated with findings from behavioral economics, providing new theoretical and methodological directions for future research.

Preferences and beliefs in ingroup favoritism

PubMed Central

Everett, Jim A. C.; Faber, Nadira S.; Crockett, Molly

2015-01-01

Ingroup favoritism—the tendency to favor members of one’s own group over those in other groups—is well documented, but the mechanisms driving this behavior are not well understood. In particular, it is unclear to what extent ingroup favoritism is driven by preferences concerning the welfare of ingroup over outgroup members, vs. beliefs about the behavior of ingroup and outgroup members. In this review we analyze research on ingroup favoritism in economic games, identifying key gaps in the literature and providing suggestions on how future work can incorporate these insights to shed further light on when, why, and how ingroup favoritism occurs. In doing so, we demonstrate how social psychological theory and research can be integrated with findings from behavioral economics, providing new theoretical and methodological directions for future research. PMID:25762906

Growth Inhibition of Sporomusa ovata by Incorporation of Benzimidazole Bases into Cobamides

PubMed Central

Mok, Kenny C.

2013-01-01

Phenolyl cobamides are unique members of a class of cobalt-containing cofactors that includes vitamin B12 (cobalamin). Cobamide cofactors facilitate diverse reactions in prokaryotes and eukaryotes. Phenolyl cobamides are structurally and chemically distinct from the more commonly used benzimidazolyl cobamides such as cobalamin, as the lower axial ligand is a phenolic group rather than a benzimidazole. The functional significance of this difference is not well understood. Here we show that in the bacterium Sporomusa ovata, the only organism known to synthesize phenolyl cobamides, several cobamide-dependent acetogenic metabolisms have a requirement or preference for phenolyl cobamides. The addition of benzimidazoles to S. ovata cultures results in a decrease in growth rate when grown on methanol, 3,4-dimethoxybenzoate, H2 plus CO2, or betaine. Suppression of native p-cresolyl cobamide synthesis and production of benzimidazolyl cobamides occur upon the addition of benzimidazoles, indicating that benzimidazolyl cobamides are not functionally equivalent to the phenolyl cobamide cofactors produced by S. ovata. We further show that S. ovata is capable of incorporating other phenolic compounds into cobamides that function in methanol metabolism. These results demonstrate that S. ovata can incorporate a wide range of compounds as cobamide lower ligands, despite its preference for phenolyl cobamides in the metabolism of certain energy substrates. To our knowledge, S. ovata is unique among cobamide-dependent organisms in its preferential utilization of phenolyl cobamides. PMID:23417488

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem

PubMed Central

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA. PMID:26167171

Investigating country-specific music preferences and music recommendation algorithms with the LFM-1b dataset.

PubMed

Schedl, Markus

2017-01-01

Recently, the LFM-1b dataset has been proposed to foster research and evaluation in music retrieval and music recommender systems, Schedl (Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR). New York, 2016). It contains more than one billion music listening events created by more than 120,000 users of Last.fm. Each listening event is characterized by artist, album, and track name, and further includes a timestamp. Basic demographic information and a selection of more elaborate listener-specific descriptors are included as well, for anonymized users. In this article, we reveal information about LFM-1b's acquisition and content and we compare it to existing datasets. We furthermore provide an extensive statistical analysis of the dataset, including basic properties of the item sets, demographic coverage, distribution of listening events (e.g., over artists and users), and aspects related to music preference and consumption behavior (e.g., temporal features and mainstreaminess of listeners). Exploiting country information of users and genre tags of artists, we also create taste profiles for populations and determine similar and dissimilar countries in terms of their populations' music preferences. Finally, we illustrate the dataset's usage in a simple artist recommendation task, whose results are intended to serve as baseline against which more elaborate techniques can be assessed.

USE OF POPULATION VIABILITY ANALYSIS AND RESERVE SELECTION ALGORITHMS IN REGIONAL CONSERVATION PLANS

EPA Science Inventory

Current reserve selection algorithms have difficulty evaluating connectivity and other factors
necessary to conserve wide-ranging species in developing landscapes. Conversely, population viability analyses may incorporate detailed demographic data but often lack sufficient spa...

Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.

PubMed

Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A

2012-02-01

Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method.

Self-Love or Other-Love? Explicit Other-Preference but Implicit Self-Preference

PubMed Central

Gebauer, Jochen E.; Göritz, Anja S.; Hofmann, Wilhelm; Sedikides, Constantine

2012-01-01

Do humans prefer the self even over their favorite other person? This question has pervaded philosophy and social-behavioral sciences. Psychology’s distinction between explicit and implicit preferences calls for a two-tiered solution. Our evolutionarily-based Dissociative Self-Preference Model offers two hypotheses. Other-preferences prevail at an explicit level, because they convey caring for others, which strengthens interpersonal bonds–a major evolutionary advantage. Self-preferences, however, prevail at an implicit level, because they facilitate self-serving automatic behavior, which favors the self in life-or-die situations–also a major evolutionary advantage. We examined the data of 1,519 participants, who completed an explicit measure and one of five implicit measures of preferences for self versus favorite other. The results were consistent with the Dissociative Self-Preference Model. Explicitly, participants preferred their favorite other over the self. Implicitly, however, they preferred the self over their favorite other (be it their child, romantic partner, or best friend). Results are discussed in relation to evolutionary theorizing on self-deception. PMID:22848605

Algorithms and Application of Sparse Matrix Assembly and Equation Solvers for Aeroacoustics

NASA Technical Reports Server (NTRS)

Watson, W. R.; Nguyen, D. T.; Reddy, C. J.; Vatsa, V. N.; Tang, W. H.

2001-01-01

An algorithm for symmetric sparse equation solutions on an unstructured grid is described. Efficient, sequential sparse algorithms for degree-of-freedom reordering, supernodes, symbolic/numerical factorization, and forward backward solution phases are reviewed. Three sparse algorithms for the generation and assembly of symmetric systems of matrix equations are presented. The accuracy and numerical performance of the sequential version of the sparse algorithms are evaluated over the frequency range of interest in a three-dimensional aeroacoustics application. Results show that the solver solutions are accurate using a discretization of 12 points per wavelength. Results also show that the first assembly algorithm is impractical for high-frequency noise calculations. The second and third assembly algorithms have nearly equal performance at low values of source frequencies, but at higher values of source frequencies the third algorithm saves CPU time and RAM. The CPU time and the RAM required by the second and third assembly algorithms are two orders of magnitude smaller than that required by the sparse equation solver. A sequential version of these sparse algorithms can, therefore, be conveniently incorporated into a substructuring for domain decomposition formulation to achieve parallel computation, where different substructures are handles by different parallel processors.

Continuing Education Preferences, Facilitators, and Barriers for Nursing Home Nurses.

PubMed

Dyck, Mary J; Kim, Myoung Jin

2018-01-01

The purpose of the study was to determine the continuing education needs for nursing home nurses in rural central Illinois and to determine any potential facilitators or barriers to obtaining continuing education. Data were collected using the Educational Needs Assessment questionnaire. Descriptive statistics were computed to examine continuing education preferences, facilitators, and barriers among nursing home nurses. Independent samples t tests were used to compare preferences between administrative and staff nurses. The sample included 317 nurses from 34 facilities. The five top needs were related to clinical problems. Administrative nurses had greater needs for professional issues, managerial skills, and quality improvement than staff nurses. Barriers included rural settings, need for vacation time for programs, and inadequate staffing. Continuing education needs of nursing home nurses in Illinois are similar to previous studies conducted in Arizona and North Carolina. Continuing education barriers were mostly organizational, rather than personal. J Contin Nurs Educ. 2018;49(1):26-33. Copyright 2018, SLACK Incorporated.

Simulated annealing algorithm for solving chambering student-case assignment problem

NASA Astrophysics Data System (ADS)

Ghazali, Saadiah; Abdul-Rahman, Syariza

2015-12-01

The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.

Eliciting women's cervical screening preferences: a mixed methods systematic review protocol.

PubMed

Wood, Brianne; Van Katwyk, Susan Rogers; El-Khatib, Ziad; McFaul, Susan; Taljaard, Monica; Wright, Erica; Graham, Ian D; Little, Julian

2016-08-11

quantitative study designs). The strength of the synthesized findings will be assessed using the validated GRADE and CERQual tool. This review will inform the development of a tool to elicit women's cervical screening preferences. Understanding the methods used to elicit women's preferences and what is known about women's cervical screening preferences will be useful for guideline developers who wish to incorporate a woman-centered approach specifically for cervical screening guidelines. PROSPERO CRD42016035737.

Automated characterization of perceptual quality of clinical chest radiographs: Validation and calibration to observer preference

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

Samei, Ehsan, E-mail: samei@duke.edu; Lin, Yuan; Choudhury, Kingshuk R.

Purpose: The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking. Methods: Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual qualitymore » assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib–lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm–lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable

TITRATION: A Randomized Study to Assess 2 Treatment Algorithms with New Insulin Glargine 300 units/mL.

PubMed

Yale, Jean-François; Berard, Lori; Groleau, Mélanie; Javadi, Pasha; Stewart, John; Harris, Stewart B

2017-10-01

It was uncertain whether an algorithm that involves increasing insulin dosages by 1 unit/day may cause more hypoglycemia with the longer-acting insulin glargine 300 units/mL (GLA-300). The objective of this study was to compare safety and efficacy of 2 titration algorithms, INSIGHT and EDITION, for GLA-300 in people with uncontrolled type 2 diabetes mellitus, mainly in a primary care setting. This was a 12-week, open-label, randomized, multicentre pilot study. Participants were randomly assigned to 1 of 2 algorithms: they either increased their dosage by 1 unit/day (INSIGHT, n=108) or the dose was adjusted by the investigator at least once weekly, but no more often than every 3 days (EDITION, n=104). The target fasting self-monitored blood glucose was in the range of 4.4 to 5.6 mmol/L. The percentages of participants reaching the primary endpoint of fasting self-monitored blood glucose ≤5.6 mmol/L without nocturnal hypoglycemia were 19.4% (INSIGHT) and 18.3% (EDITION). At week 12, 26.9% (INSIGHT) and 28.8% (EDITION) of participants achieved a glycated hemoglobin value of ≤7%. No differences in the incidence of hypoglycemia of any category were noted between algorithms. Participants in both arms of the study were much more satisfied with their new treatment as assessed by the Diabetes Treatment Satisfaction Questionnaire. Most health-care professionals (86%) preferred the INSIGHT over the EDITION algorithm. The frequency of adverse events was similar between algorithms. A patient-driven titration algorithm of 1 unit/day with GLA-300 is effective and comparable to the previously tested EDITION algorithm and is preferred by health-care professionals. Copyright © 2017 Diabetes Canada. Published by Elsevier Inc. All rights reserved.

Characterizing outcome preferences in patients with psychotic disorders: a discrete choice conjoint experiment.

PubMed

Zipursky, Robert B; Cunningham, Charles E; Stewart, Bailey; Rimas, Heather; Cole, Emily; Vaz, Stephanie McDermid

2017-07-01

The majority of individuals with schizophrenia will achieve a remission of psychotic symptoms, but few will meet criteria for recovery. Little is known about what outcomes are important to patients. We carried out a discrete choice experiment to characterize the outcome preferences of patients with psychotic disorders. Participants (N=300) were recruited from two clinics specializing in psychotic disorders. Twelve outcomes were each defined at three levels and incorporated into a computerized survey with 15 choice tasks. Utility values and importance scores were calculated for each outcome level. Latent class analysis was carried out to determine whether participants were distributed into segments with different preferences. Multinomial logistic regression was used to identify predictors of segment membership. Latent class analysis revealed three segments of respondents. The first segment (48%), which we labeled "Achievement-focused," preferred to have a full-time job, to live independently, to be in a long-term relationship, and to have no psychotic symptoms. The second segment (29%), labeled "Stability-focused," preferred to not have a job, to live independently, and to have some ongoing psychotic symptoms. The third segment (23%), labeled "Health-focused," preferred to not have a job, to live in supervised housing, and to have no psychotic symptoms. Segment membership was predicted by education, socioeconomic status, psychotic symptom severity, and work status. This study has revealed that patients with psychotic disorders are distributed between segments with different outcome preferences. New approaches to improve outcomes for patients with psychotic disorders should be informed by a greater understanding of patient preferences and priorities. Copyright © 2016 Elsevier B.V. All rights reserved.

The development of PubMed search strategies for patient preferences for treatment outcomes.

PubMed

van Hoorn, Ralph; Kievit, Wietske; Booth, Andrew; Mozygemba, Kati; Lysdahl, Kristin Bakke; Refolo, Pietro; Sacchini, Dario; Gerhardus, Ansgar; van der Wilt, Gert Jan; Tummers, Marcia

2016-07-29

The importance of respecting patients' preferences when making treatment decisions is increasingly recognized. Efficiently retrieving papers from the scientific literature reporting on the presence and nature of such preferences can help to achieve this goal. The objective of this study was to create a search filter for PubMed to help retrieve evidence on patient preferences for treatment outcomes. A total of 27 journals were hand-searched for articles on patient preferences for treatment outcomes published in 2011. Selected articles served as a reference set. To develop optimal search strategies to retrieve this set, all articles in the reference set were randomly split into a development and a validation set. MeSH-terms and keywords retrieved using PubReMiner were tested individually and as combinations in PubMed and evaluated for retrieval performance (e.g. sensitivity (Se) and specificity (Sp)). Of 8238 articles, 22 were considered to report empirical evidence on patient preferences for specific treatment outcomes. The best search filters reached Se of 100 % [95 % CI 100-100] with Sp of 95 % [94-95 %] and Sp of 97 % [97-98 %] with 75 % Se [74-76 %]. In the validation set these queries reached values of Se of 90 % [89-91 %] with Sp 94 % [93-95 %] and Se of 80 % [79-81 %] with Sp of 97 % [96-96 %], respectively. Narrow and broad search queries were developed which can help in retrieving literature on patient preferences for treatment outcomes. Identifying such evidence may in turn enhance the incorporation of patient preferences in clinical decision making and health technology assessment.

About the algorithm for construction of coordinated university timetables

NASA Astrophysics Data System (ADS)

Dobrynin, A. S.; Kulakov, S. M.; Taraborina, E. N.

2018-05-01

The factual description of the task and an algorithm for drawing up a coordinated timetable of academic work of the faculty and students at the level of department (local timetable) is presented, as well as the procedure for integrating private schedules, i.e. the formation of a university-wide timetable. Coordination of the latter has not only spatio-temporal in nature, but also takes into account the preferences (interests) of agents (users and performers of works).

Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations.

PubMed

Tang, Ming; Liao, Huchang; Li, Zongmin; Xu, Zeshui

2018-04-13

Because the natural disaster system is a very comprehensive and large system, the disaster reduction scheme must rely on risk analysis. Experts' knowledge and experiences play a critical role in disaster risk assessment. The hesitant fuzzy linguistic preference relation is an effective tool to express experts' preference information when comparing pairwise alternatives. Owing to the lack of knowledge or a heavy workload, information may be missed in the hesitant fuzzy linguistic preference relation. Thus, an incomplete hesitant fuzzy linguistic preference relation is constructed. In this paper, we firstly discuss some properties of the additive consistent hesitant fuzzy linguistic preference relation. Next, the incomplete hesitant fuzzy linguistic preference relation, the normalized hesitant fuzzy linguistic preference relation, and the acceptable hesitant fuzzy linguistic preference relation are defined. Afterwards, three procedures to estimate the missing information are proposed. The first one deals with the situation in which there are only n-1 known judgments involving all the alternatives; the second one is used to estimate the missing information of the hesitant fuzzy linguistic preference relation with more known judgments; while the third procedure is used to deal with ignorance situations in which there is at least one alternative with totally missing information. Furthermore, an algorithm for group decision making with incomplete hesitant fuzzy linguistic preference relations is given. Finally, we illustrate our model with a case study about flood disaster risk evaluation. A comparative analysis is presented to testify the advantage of our method.

Optimal platform design using non-dominated sorting genetic algorithm II and technique for order of preference by similarity to ideal solution; application to automotive suspension system

NASA Astrophysics Data System (ADS)

Shojaeefard, Mohammad Hassan; Khalkhali, Abolfazl; Faghihian, Hamed; Dahmardeh, Masoud

2018-03-01

Unlike conventional approaches where optimization is performed on a unique component of a specific product, optimum design of a set of components for employing in a product family can cause significant reduction in costs. Increasing commonality and performance of the product platform simultaneously is a multi-objective optimization problem (MOP). Several optimization methods are reported to solve these MOPs. However, what is less discussed is how to find the trade-off points among the obtained non-dominated optimum points. This article investigates the optimal design of a product family using non-dominated sorting genetic algorithm II (NSGA-II) and proposes the employment of technique for order of preference by similarity to ideal solution (TOPSIS) method to find the trade-off points among the obtained non-dominated results while compromising all objective functions together. A case study for a family of suspension systems is presented, considering performance and commonality. The results indicate the effectiveness of the proposed method to obtain the trade-off points with the best possible performance while maximizing the common parts.

The effects of stochastic demand and expense preference behaviour on public hospital costs and excess capacity.

PubMed

Lovell, C A Knox; Rodríguez-Alvarez, Ana; Wall, Alan

2009-02-01

The literature to date on the effect of demand uncertainty on public hospital costs and excess capacity has not taken into account the role of expense preference behaviour. Similarly, the research on expense preference behaviour has not taken demand uncertainty into account. In this paper, we argue that both demand uncertainty and expense preference behaviour may affect public hospital costs and excess capacity and that ignoring either of these effects may lead to biased parameter estimates and misleading inference. To show this, we extend the analysis of Rodríguez-Alvarez and Lovell (Health Econ. 2004; 13: 157-169) by incorporating demand uncertainty into the technology to account for the hospital activity of providing standby capacity or insurance against the unexpected demand. We find that demand uncertainty in Spanish public hospitals affects hospital production decisions and increases costs. Our results also show that overcapitalization in these hospitals can be explained by hospitals providing insurance demand when faced with demand uncertainty. We also find evidence of expense preference behaviour. We conclude that both stochastic demand and expense preference behaviour should be taken into account when analysing hospital costs and production. Copyright (c) 2008 John Wiley & Sons, Ltd.

Going direct to the consumer: Examining treatment preferences for veterans with insomnia, PTSD, and depression.

PubMed

Gutner, Cassidy A; Pedersen, Eric R; Drummond, Sean P A

2018-05-01

Inclusion of consumer preferences to disseminate evidence-based psychosocial treatment (EBPT) is crucial to effectively bridge the science-to-practice quality chasm. We examined this treatment gap for insomnia, posttraumatic stress disorder (PTSD), depression, and comorbid symptoms in a sample of 622 young adult veterans through preference in symptom focus, treatment modality, and related gender differences among those screening positive for each problem. Data were collected from veteran drinkers recruited through targeted Facebook advertisements as part of a brief online alcohol intervention. Analyses demonstrated that veterans reported greater willingness to seek insomnia-focused treatment over PTSD- or depression-focused care. Notably, even when participants screened negative for insomnia, they preferred sleep-focused care to PTSD- or depression-focused care. Although one in five veterans with a positive screen would not consider care, veterans screening for both insomnia and PTSD who would consider care had a preference for in-person counseling, and those screening for both insomnia and depression had similar preferences for in-person and mobile app-based/computer self-help treatment. Marginal gender differences were found. Incorporating direct-to-consumer methods into research can help educate stakeholders about methods to expand EBPT access. Though traditional in-person counseling was often preferred, openness to app-based/computer interventions offers alternative methods to provide veterans with EBPTs. Published by Elsevier B.V.

A new algorithm for modeling friction in dynamic mechanical systems

NASA Technical Reports Server (NTRS)

Hill, R. E.

1988-01-01

A method of modeling friction forces that impede the motion of parts of dynamic mechanical systems is described. Conventional methods in which the friction effect is assumed a constant force, or torque, in a direction opposite to the relative motion, are applicable only to those cases where applied forces are large in comparison to the friction, and where there is little interest in system behavior close to the times of transitions through zero velocity. An algorithm is described that provides accurate determination of friction forces over a wide range of applied force and velocity conditions. The method avoids the simulation errors resulting from a finite integration interval used in connection with a conventional friction model, as is the case in many digital computer-based simulations. The algorithm incorporates a predictive calculation based on initial conditions of motion, externally applied forces, inertia, and integration step size. The predictive calculation in connection with an external integration process provides an accurate determination of both static and Coulomb friction forces and resulting motions in dynamic simulations. Accuracy of the results is improved over that obtained with conventional methods and a relatively large integration step size is permitted. A function block for incorporation in a specific simulation program is described. The general form of the algorithm facilitates implementation with various programming languages such as FORTRAN or C, as well as with other simulation programs.

Happy faces are preferred regardless of familiarity--sad faces are preferred only when familiar.

PubMed

Liao, Hsin-I; Shimojo, Shinsuke; Yeh, Su-Ling

2013-06-01

Familiarity leads to preference (e.g., the mere exposure effect), yet it remains unknown whether it is objective familiarity, that is, repetitive exposure, or subjective familiarity that contributes to preference. In addition, it is unexplored whether and how different emotions influence familiarity-related preference. The authors investigated whether happy or sad faces are preferred or perceived as more familiar and whether this subjective familiarity judgment correlates with preference for different emotional faces. An emotional face--happy or sad--was paired with a neutral face, and participants rated the relative preference and familiarity of each of the paired faces. For preference judgment, happy faces were preferred and sad faces were less preferred, compared with neutral faces. For familiarity judgment, happy faces did not show any bias, but sad faces were perceived as less familiar than neutral faces. Item-by-item correlational analyses show preference for sad faces--but not happy faces--positively correlate with familiarity. These results suggest a direct link between positive emotion and preference, and argue at least partly against a common cause for familiarity and preference. Instead, facial expression of different emotional valence modulates the link between familiarity and preference.

Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies

PubMed Central

Edwards, Hannah; Abeln, Sanne; Deane, Charlotte M.

2013-01-01

The evolution of proteins is one of the fundamental processes that has delivered the diversity and complexity of life we see around ourselves today. While we tend to define protein evolution in terms of sequence level mutations, insertions and deletions, it is hard to translate these processes to a more complete picture incorporating a polypeptide's structure and function. By considering how protein structures change over time we can gain an entirely new appreciation of their long-term evolutionary dynamics. In this work we seek to identify how populations of proteins at different stages of evolution explore their possible structure space. We use an annotation of superfamily age to this space and explore the relationship between these ages and a diverse set of properties pertaining to a superfamily's sequence, structure and function. We note several marked differences between the populations of newly evolved and ancient structures, such as in their length distributions, secondary structure content and tertiary packing arrangements. In particular, many of these differences suggest a less elaborate structure for newly evolved superfamilies when compared with their ancient counterparts. We show that the structural preferences we report are not a residual effect of a more fundamental relationship with function. Furthermore, we demonstrate the robustness of our results, using significant variation in the algorithm used to estimate the ages. We present these age estimates as a useful tool to analyse protein populations. In particularly, we apply this in a comparison of domains containing greek key or jelly roll motifs. PMID:24244135

Improving Socialization for High School Students with ASD by Using their Preferred Interests

PubMed Central

Koegel, Robert; Kim, Sunny; Koegel, Lynn; Schwartzman, Ben

2013-01-01

There has been a paucity of research on effective social interventions for adolescents with ASD in inclusive high school settings. The literature, however, suggests that incorporating the student with ASD’s special interests into activities may help improve their socialization with typical peers. Within the context of a multiple baseline across participants design, we implemented lunchtime activities incorporating the adolescent with ASD’s preferred interests that were similar to ongoing activities already available at the schools. Results showed this increased both level of engagement and their rate of initiations made to typical peers. Social validation measures suggest that both adolescents with ASD and typical peers enjoyed participating in these activities and that the results generalized to other similar activities. PMID:23361918

Quantifying patient preferences for symptomatic breast clinic referral: a decision analysis study.

PubMed

Quinlan, Aisling; O'Brien, Kirsty K; Galvin, Rose; Hardy, Colin; McDonnell, Ronan; Joyce, Doireann; McDowell, Ronald D; Aherne, Emma; Keogh, Claire; O'Sullivan, Katriona; Fahey, Tom

2018-05-31

Decision analysis study that incorporates patient preferences and probability estimates to investigate the impact of women's preferences for referral or an alternative strategy of watchful waiting if faced with symptoms that could be due to breast cancer. Community-based study. Asymptomatic women aged 30-60 years. Participants were presented with 11 health scenarios that represent the possible consequences of symptomatic breast problems. Participants were asked the risk of death that they were willing to take in order to avoid the health scenario using the standard gamble utility method. This process was repeated for all 11 health scenarios. Formal decision analysis for the preferred individual decision was then estimated for each participant. The preferred diagnostic strategy was either watchful waiting or referral to a breast clinic. Sensitivity analysis was used to examine how each varied according to changes in the probabilities of the health scenarios. A total of 35 participants completed the interviews, with a median age 41 years (IQR 35-47 years). The majority of the study sample was employed (n=32, 91.4%), with a third-level (university) education (n=32, 91.4%) and with knowledge of someone with breast cancer (n=30, 85.7%). When individual preferences were accounted for, 25 (71.4%) patients preferred watchful waiting to referral for triple assessment as their preferred initial diagnostic strategy. Sensitivity analysis shows that referral for triple assessment becomes the dominant strategy at the upper probability estimate (18%) of breast cancer in the community. Watchful waiting is an acceptable strategy for most women who present to their general practitioner (GP) with breast symptoms. These findings suggest that current referral guidelines should take more explicit account of women's preferences in relation to their GPs initial management strategy. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All

A similarity based agglomerative clustering algorithm in networks

NASA Astrophysics Data System (ADS)

Liu, Zhiyuan; Wang, Xiujuan; Ma, Yinghong

2018-04-01

The detection of clusters is benefit for understanding the organizations and functions of networks. Clusters, or communities, are usually groups of nodes densely interconnected but sparsely linked with any other clusters. To identify communities, an efficient and effective community agglomerative algorithm based on node similarity is proposed. The proposed method initially calculates similarities between each pair of nodes, and form pre-partitions according to the principle that each node is in the same community as its most similar neighbor. After that, check each partition whether it satisfies community criterion. For the pre-partitions who do not satisfy, incorporate them with others that having the biggest attraction until there are no changes. To measure the attraction ability of a partition, we propose an attraction index that based on the linked node's importance in networks. Therefore, our proposed method can better exploit the nodes' properties and network's structure. To test the performance of our algorithm, both synthetic and empirical networks ranging in different scales are tested. Simulation results show that the proposed algorithm can obtain superior clustering results compared with six other widely used community detection algorithms.

Artificial immune system algorithm in VLSI circuit configuration

NASA Astrophysics Data System (ADS)

Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

2017-08-01

In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

Comparison of selected dose calculation algorithms in radiotherapy treatment planning for tissues with inhomogeneities

NASA Astrophysics Data System (ADS)

Woon, Y. L.; Heng, S. P.; Wong, J. H. D.; Ung, N. M.

2016-03-01

Inhomogeneity correction is recommended for accurate dose calculation in radiotherapy treatment planning since human body are highly inhomogeneous with the presence of bones and air cavities. However, each dose calculation algorithm has its own limitations. This study is to assess the accuracy of five algorithms that are currently implemented for treatment planning, including pencil beam convolution (PBC), superposition (SP), anisotropic analytical algorithm (AAA), Monte Carlo (MC) and Acuros XB (AXB). The calculated dose was compared with the measured dose using radiochromic film (Gafchromic EBT2) in inhomogeneous phantoms. In addition, the dosimetric impact of different algorithms on intensity modulated radiotherapy (IMRT) was studied for head and neck region. MC had the best agreement with the measured percentage depth dose (PDD) within the inhomogeneous region. This was followed by AXB, AAA, SP and PBC. For IMRT planning, MC algorithm is recommended for treatment planning in preference to PBC and SP. The MC and AXB algorithms were found to have better accuracy in terms of inhomogeneity correction and should be used for tumour volume within the proximity of inhomogeneous structures.

Evolution of Inbreeding Avoidance and Inbreeding Preference through Mate Choice among Interacting Relatives.

PubMed

Duthie, A Bradley; Reid, Jane M

2016-12-01

While extensive population genetic theory predicts conditions favoring evolution of self-fertilization versus outcrossing, there is no analogous theory that predicts conditions favoring evolution of inbreeding avoidance or inbreeding preference enacted through mate choice given obligate biparental reproduction. Multiple interacting processes complicate the dynamics of alleles underlying such inbreeding strategies, including sexual conflict, distributions of kinship, genetic drift, purging of mutation load, direct costs, and restricted kin discrimination. We incorporated these processes into an individual-based model to predict conditions where selection should increase or decrease frequencies of alleles causing inbreeding avoidance or inbreeding preference when females or males controlled mating. Selection for inbreeding avoidance occurred given strong inbreeding depression when either sex chose mates, while selection for inbreeding preference occurred given very weak inbreeding depression when females chose but never occurred when males chose. Selection for both strategies was constrained by direct costs and restricted kin discrimination. Purging was negligible, but allele frequencies were strongly affected by drift in small populations, while selection for inbreeding avoidance was weak in larger populations because inbreeding risk decreased. Therefore, while selection sometimes favored alleles underlying inbreeding avoidance or preference, evolution of such strategies may be much more restricted and stochastic than is commonly presumed.

Analysis of Factors for Incorporating User Preferences in Air Traffic Management: A system Perspective

NASA Technical Reports Server (NTRS)

Sheth, Kapil S.; Gutierrez-Nolasco, Sebastian

2010-01-01

This paper presents an analysis of factors that impact user flight schedules during air traffic congestion. In pre-departure flight planning, users file one route per flight, which often leads to increased delays, inefficient airspace utilization, and exclusion of user flight preferences. In this paper, first the idea of filing alternate routes and providing priorities on each of those routes is introduced. Then, the impact of varying planning interval and system imposed departure delay increment is discussed. The metrics of total delay and equity are used for analyzing the impact of these factors on increased traffic and on different users. The results are shown for four cases, with and without the optional routes and priority assignments. Results demonstrate that adding priorities to optional routes further improves system performance compared to filing one route per flight and using first-come first-served scheme. It was also observed that a two-hour planning interval with a five-minute system imposed departure delay increment results in highest delay reduction. The trend holds for a scenario with increased traffic.

Intelligent decision support algorithm for distribution system restoration.

PubMed

Singh, Reetu; Mehfuz, Shabana; Kumar, Parmod

2016-01-01

Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network's parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network.

Developments in Human Centered Cueing Algorithms for Control of Flight Simulator Motion Systems

NASA Technical Reports Server (NTRS)

Houck, Jacob A.; Telban, Robert J.; Cardullo, Frank M.

1997-01-01

The authors conducted further research with cueing algorithms for control of flight simulator motion systems. A variation of the so-called optimal algorithm was formulated using simulated aircraft angular velocity input as a basis. Models of the human vestibular sensation system, i.e. the semicircular canals and otoliths, are incorporated within the algorithm. Comparisons of angular velocity cueing responses showed a significant improvement over a formulation using angular acceleration input. Results also compared favorably with the coordinated adaptive washout algorithm, yielding similar results for angular velocity cues while eliminating false cues and reducing the tilt rate for longitudinal cues. These results were confirmed in piloted tests on the current motion system at NASA-Langley, the Visual Motion Simulator (VMS). Proposed future developments by the authors in cueing algorithms are revealed. The new motion system, the Cockpit Motion Facility (CMF), where the final evaluation of the cueing algorithms will be conducted, is also described.

Automatic Regionalization Algorithm for Distributed State Estimation in Power Systems: Preprint

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

Wang, Dexin; Yang, Liuqing; Florita, Anthony

The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the helpmore » of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.« less

The Six-Legged Subject: A Survey of Secondary Science Teachers’ Incorporation of Insects into U.S. Life Science Instruction

PubMed Central

Ingram, Erin

2018-01-01

To improve students’ understanding and appreciation of insects, entomology education efforts have supported insect incorporation in formal education settings. While several studies have explored student ideas about insects and the incorporation of insects in elementary and middle school classrooms, the topic of how and why insects are incorporated in secondary science classrooms remains relatively unexplored. Using survey research methods, this study addresses the gap in the literature by (1) describing in-service secondary science teachers’ incorporation of insects in science classrooms; (2) identifying factors that support or deter insect incorporation and (3) identifying teachers’ preferred resources to support future entomology education efforts. Findings indicate that our sample of U.S. secondary science teachers commonly incorporate various insects in their classrooms, but that incorporation is infrequent throughout the academic year. Insect-related lesson plans are commonly used and often self-created to meet teachers’ need for standards-aligned curriculum materials. Obstacles to insect incorporation include a perceived lack of alignment of insect education materials to state or national science standards and a lack of time and professional training to teach about insects. Recommendations are provided for entomology and science education organizations to support teachers in overcoming these obstacles. PMID:29538297

The Six-Legged Subject: A Survey of Secondary Science Teachers' Incorporation of Insects into U.S. Life Science Instruction.

PubMed

Ingram, Erin; Golick, Douglas

2018-03-14

To improve students' understanding and appreciation of insects, entomology education efforts have supported insect incorporation in formal education settings. While several studies have explored student ideas about insects and the incorporation of insects in elementary and middle school classrooms, the topic of how and why insects are incorporated in secondary science classrooms remains relatively unexplored. Using survey research methods, this study addresses the gap in the literature by (1) describing in-service secondary science teachers' incorporation of insects in science classrooms; (2) identifying factors that support or deter insect incorporation and (3) identifying teachers' preferred resources to support future entomology education efforts. Findings indicate that our sample of U.S. secondary science teachers commonly incorporate various insects in their classrooms, but that incorporation is infrequent throughout the academic year. Insect-related lesson plans are commonly used and often self-created to meet teachers' need for standards-aligned curriculum materials. Obstacles to insect incorporation include a perceived lack of alignment of insect education materials to state or national science standards and a lack of time and professional training to teach about insects. Recommendations are provided for entomology and science education organizations to support teachers in overcoming these obstacles.

FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm.

PubMed

Tuo, Shouheng; Zhang, Junying; Yuan, Xiguo; Zhang, Yuanyuan; Liu, Zhaowen

2016-01-01

Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS). Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models. In this study, two scoring functions (Bayesian network based K2-score and Gini-score) are used for characterizing two SNP locus as a candidate model, the two criteria are adopted simultaneously for improving identification power and tackling the preference problem to disease models. Harmony search algorithm (HSA) is improved for quickly finding the most likely candidate models among all two-locus models, in which a local search algorithm with two-dimensional tabu table is presented to avoid repeatedly evaluating some disease models that have strong marginal effect. Finally G-test statistic is used to further test the candidate models. We investigate our method named FHSA-SED on 82 simulated datasets and a real AMD dataset, and compare it with two typical methods (MACOED and CSE) which have been developed recently based on swarm intelligent search algorithm. The results of simulation experiments indicate that our method outperforms the two compared algorithms in terms of detection power, computation time, evaluation times, sensitivity (TPR), specificity (SPC), positive predictive value (PPV) and accuracy (ACC). Our method has identified two SNPs (rs3775652 and rs10511467) that may be also associated with disease in AMD dataset.

FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm

PubMed Central

Tuo, Shouheng; Zhang, Junying; Yuan, Xiguo; Zhang, Yuanyuan; Liu, Zhaowen

2016-01-01

Motivation Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS). Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models. Method In this study, two scoring functions (Bayesian network based K2-score and Gini-score) are used for characterizing two SNP locus as a candidate model, the two criteria are adopted simultaneously for improving identification power and tackling the preference problem to disease models. Harmony search algorithm (HSA) is improved for quickly finding the most likely candidate models among all two-locus models, in which a local search algorithm with two-dimensional tabu table is presented to avoid repeatedly evaluating some disease models that have strong marginal effect. Finally G-test statistic is used to further test the candidate models. Results We investigate our method named FHSA-SED on 82 simulated datasets and a real AMD dataset, and compare it with two typical methods (MACOED and CSE) which have been developed recently based on swarm intelligent search algorithm. The results of simulation experiments indicate that our method outperforms the two compared algorithms in terms of detection power, computation time, evaluation times, sensitivity (TPR), specificity (SPC), positive predictive value (PPV) and accuracy (ACC). Our method has identified two SNPs (rs3775652 and rs10511467) that may be also associated with disease in AMD dataset. PMID:27014873

A new collaborative recommendation approach based on users clustering using artificial bee colony algorithm.

PubMed

Ju, Chunhua; Xu, Chonghuan

2013-01-01

Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

PubMed Central

Ju, Chunhua

2013-01-01

Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods. PMID:24381525

Comparison of algorithms to generate event times conditional on time-dependent covariates.

PubMed

Sylvestre, Marie-Pierre; Abrahamowicz, Michal

2008-06-30

The Cox proportional hazards model with time-dependent covariates (TDC) is now a part of the standard statistical analysis toolbox in medical research. As new methods involving more complex modeling of time-dependent variables are developed, simulations could often be used to systematically assess the performance of these models. Yet, generating event times conditional on TDC requires well-designed and efficient algorithms. We compare two classes of such algorithms: permutational algorithms (PAs) and algorithms based on a binomial model. We also propose a modification of the PA to incorporate a rejection sampler. We performed a simulation study to assess the accuracy, stability, and speed of these algorithms in several scenarios. Both classes of algorithms generated data sets that, once analyzed, provided virtually unbiased estimates with comparable variances. In terms of computational efficiency, the PA with the rejection sampler reduced the time necessary to generate data by more than 50 per cent relative to alternative methods. The PAs also allowed more flexibility in the specification of the marginal distributions of event times and required less calibration.

Risk Preference and Diagnosticity.

ERIC Educational Resources Information Center

Rocklin, Thomas

Researchers have suggested two models of risk preference to account for subjects' preference for tasks of moderate difficulty. The affective model proposes that pride of success and shame of failure are responsible for the observed preference. The cognitive model suggests preference for tasks of moderate difficulty because they are the most…

Patient preferences for cardiac rehabilitation and desired program elements.

PubMed

Filip, J; McGillen, C; Mosca, L

1999-01-01

Data evaluating the efficacy of traditional cardiac rehabilitation programs to meet patient needs are limited. The authors studied patient-perceived preferences in cardiac rehabilitation programs and desired program elements to evaluate differences by gender or age. The authors surveyed 199 patients (136 men, 60.0 +/- 11.6 years; 63 women, 63.7 +/- 12.7 years; P = 0.045) discharged from a tertiary referral hospital with acute myocardial infarction. Participants completed a standardized questionnaire regarding enrollment in rehabilitation and preferences for six program types on a 10-point scale (1 = little or no agreement, 10 = strongly agree). In this study, 54.3% of subjects enrolled in cardiac rehabilitation. Older patients (> or = 65 years) were more likely to enroll in home-based programs compared with younger patients (< 65 years) (11.8% versus 1.4%, P = 0.02). Younger patients preferred a short-term rehabilitation facility more than older patients (7.4 +/- 3.5 versus 5.1 +/- 4.1 units on the 10-point scale, P = 0.001), and rated the following more favorably than older patients: local health club programs (6.2 +/- 3.7 versus 4.5 +/- 4.0, P = 0.01), long-term programs (6.5 +/- 3.8 versus 4.9 +/- 4.2, P = 0.02), and comprehensive programs (6.6 +/- 3.7 versus 4.9 +/- 2.2, P = 0.02). Younger patients rated the following program elements more favorably compared with older patients: stress management (7.0 +/- 3.5 versus 5.7 +/- 4.1, P = 0.04), vocational counseling (5.1 +/- 3.9 versus 1.9 +/- 2.4, P = 0.001), and smoking cessation (4.9 +/- 4.4 versus 2.7 +/- 3.4, P = 0.001). Program preferences differed significantly by age, but not gender. Older patients enrolled in home-based programs over clinic-based programs. Younger patients rated stress management, vocational counseling, and smoking cessation more favorably than older patients. Strategies to enhance patient participation in cardiac rehabilitation should incorporate patient age and preferences for program

Surface hopping with a manifold of electronic states. I. Incorporating surface-leaking to capture lifetimes

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

Ouyang, Wenjun; Dou, Wenjie; Subotnik, Joseph E., E-mail: subotnik@sas.upenn.edu

2015-02-28

We investigate the incorporation of the surface-leaking (SL) algorithm into Tully’s fewest-switches surface hopping (FSSH) algorithm to simulate some electronic relaxation induced by an electronic bath in conjunction with some electronic transitions between discrete states. The resulting SL-FSSH algorithm is benchmarked against exact quantum scattering calculations for three one-dimensional model problems. The results show excellent agreement between SL-FSSH and exact quantum dynamics in the wide band limit, suggesting the potential for a SL-FSSH algorithm. Discrepancies and failures are investigated in detail to understand the factors that will limit the reliability of SL-FSSH, especially the wide band approximation. Considering the easinessmore » of implementation and the low computational cost, we expect this method to be useful in studying processes involving both a continuum of electronic states (where electronic dynamics are probabilistic) and processes involving only a few electronic states (where non-adiabatic processes cannot ignore short-time coherence)« less

Improved Passive Microwave Algorithms for North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, James; Chang, Alfred; Hall, Dorothy

1997-01-01

Microwave algorithms simplify complex physical processes in order to estimate geophysical parameters such as snow cover and snow depth. The microwave radiances received at the satellite sensor and expressed as brightness temperatures are a composite of contributions from the Earth's surface, the Earth's atmosphere and from space. Owing to the coarse resolution inherent to passive microwave sensors, each pixel value represents a mixture of contributions from different surface types including deep snow, shallow snow, forests and open areas. Algorithms are generated in order to resolve these mixtures. The accuracy of the retrieved information is affected by uncertainties in the assumptions used in the radiative transfer equation (Steffen et al., 1992). One such uncertainty in the Chang et al., (1987) snow algorithm is that the snow grain radius is 0.3 mm for all layers of the snowpack and for all physiographic regions. However, this is not usually the case. The influence of larger grain sizes appears to be of more importance for deeper snowpacks in the interior of Eurasia. Based on this consideration and the effects of forests, a revised SMMR snow algorithm produces more realistic snow mass values. The purpose of this study is to present results of the revised algorithm (referred to for the remainder of this paper as the GSFC 94 snow algorithm) which incorporates differences in both fractional forest cover and snow grain size. Results from the GSFC 94 algorithm will be compared to the original Chang et al. (1987) algorithm and to climatological snow depth data as well.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators

Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

2000-01-01

This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

A Machine Learning Recommender System to Tailor Preference Assessments to Enhance Person-Centered Care Among Nursing Home Residents.

PubMed

Gannod, Gerald C; Abbott, Katherine M; Van Haitsma, Kimberly; Martindale, Nathan; Heppner, Alexandra

2018-05-21

Nursing homes (NHs) using the Preferences for Everyday Living Inventory (PELI-NH) to assess important preferences and provide person-centered care find the number of items (72) to be a barrier to using the assessment. Using a sample of n = 255 NH resident responses to the PELI-NH, we used the 16 preference items from the MDS 3.0 Section F to develop a machine learning recommender system to identify additional PELI-NH items that may be important to specific residents. Much like the Netflix recommender system, our system is based on the concept of collaborative filtering whereby insights and predictions (e.g., filters) are created using the interests and preferences of many users. The algorithm identifies multiple sets of "you might also like" patterns called association rules, based upon responses to the 16 MDS preferences that recommends an additional set of preferences with a high likelihood of being important to a specific resident. In the evaluation of the combined apriori and logistic regression approach, we obtained a high recall performance (i.e., the ratio of correctly predicted preferences compared with all predicted preferences and nonpreferences) and high precision (i.e., the ratio of correctly predicted rules with respect to the rules predicted to be true) of 80.2% and 79.2%, respectively. The recommender system successfully provides guidance on how to best tailor the preference items asked of residents and can support preference capture in busy clinical environments, contributing to the feasibility of delivering person-centered care.

Therapeutic mode preferences and associated factors among Norwegian undergraduate occupational therapy students: A cross-sectional exploratory study.

PubMed

Yazdani, Farzaneh; Carstensen, Tove; Bonsaksen, Tore

2017-03-01

The Intentional Relationship Model is specifically focused on the relational aspect of therapy. The model describes six therapeutic modes; these represent different types of interaction for the therapist. However, preferences for therapeutic mode use are under researched. This study aims to describe preferences for therapeutic modes in undergraduate occupational therapy students, as well as to explore factors associated to each of the therapeutic modes. A sample of 96 occupational therapy students, based at two different Norwegian universities, participated in the study. They completed the Norwegian Self-Assessment of Modes Questionnaire along with sociodemographic information. Descriptive analysis, bivariate correlation and linear regression analysis were employed. The problem-solving mode was most frequently endorsed. There were generally weak associations between the variables, but female sex and being a student in the education program in Trondheim were associated with higher preference for collaboration. There is diversity in students' preferences for the modes, but the problem-solving mode was the most preferred. Students need to be aware of the mode they feel more comfortable with and make sure they use modes that fit with the specific client. The occupational therapy education programs need to incorporate raising awareness about therapeutic modes.

New Parallel Algorithms for Structural Analysis and Design of Aerospace Structures

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.

1998-01-01

Subspace and Lanczos iterations have been developed, well documented, and widely accepted as efficient methods for obtaining p-lowest eigen-pair solutions of large-scale, practical engineering problems. The focus of this paper is to incorporate recent developments in vectorized sparse technologies in conjunction with Subspace and Lanczos iterative algorithms for computational enhancements. Numerical performance, in terms of accuracy and efficiency of the proposed sparse strategies for Subspace and Lanczos algorithm, is demonstrated by solving for the lowest frequencies and mode shapes of structural problems on the IBM-R6000/590 and SunSparc 20 workstations.

Women's Contraceptive Preference-Use Mismatch

PubMed Central

He, Katherine; Dalton, Vanessa K.; Zochowski, Melissa K.

2017-01-01

Abstract Background: Family planning research has not adequately addressed women's preferences for different contraceptive methods and whether women's contraceptive experiences match their preferences. Methods: Data were drawn from the Women's Healthcare Experiences and Preferences Study, an Internet survey of 1,078 women aged 18–55 randomly sampled from a national probability panel. Survey items assessed women's preferences for contraceptive methods, match between methods preferred and used, and perceived reasons for mismatch. We estimated predictors of contraceptive preference with multinomial logistic regression models. Results: Among women at risk for pregnancy who responded with their preferred method (n = 363), hormonal methods (non-LARC [long-acting reversible contraception]) were the most preferred method (34%), followed by no method (23%) and LARC (18%). Sociodemographic differences in contraception method preferences were noted (p-values <0.05), generally with minority, married, and older women having higher rates of preferring less effective methods, compared to their counterparts. Thirty-six percent of women reported preference-use mismatch, with the majority preferring more effective methods than those they were using. Rates of match between preferred and usual methods were highest for LARC (76%), hormonal (non-LARC) (65%), and no method (65%). The most common reasons for mismatch were cost/insurance (41%), lack of perceived/actual need (34%), and method-specific preference concerns (19%). Conclusion: While preference for effective contraception was common among this sample of women, we found substantial mismatch between preferred and usual methods, notably among women of lower socioeconomic status and women using less effective methods. Findings may have implications for patient-centered contraceptive interventions. PMID:27710196

Effects of stress on human mating preferences: stressed individuals prefer dissimilar mates

PubMed Central

Lass-Hennemann, Johanna; Deuter, Christian E.; Kuehl, Linn K.; Schulz, André; Blumenthal, Terry D.; Schachinger, Hartmut

2010-01-01

Although humans usually prefer mates that resemble themselves, mating preferences can vary with context. Stress has been shown to alter mating preferences in animals, but the effects of stress on human mating preferences are unknown. Here, we investigated whether stress alters men's preference for self-resembling mates. Participants first underwent a cold-pressor test (stress induction) or a control procedure. Then, participants viewed either neutral pictures or pictures of erotic female nudes whose facial characteristics were computer-modified to resemble either the participant or another participant, or were not modified, while startle eyeblink responses were elicited by noise probes. Erotic pictures were rated as being pleasant, and reduced startle magnitude compared with neutral pictures. In the control group, startle magnitude was smaller during foreground presentation of photographs of self-resembling female nudes compared with other-resembling female nudes and non-manipulated female nudes, indicating a higher approach motivation to self-resembling mates. In the stress group, startle magnitude was larger during foreground presentation of self-resembling female nudes compared with other-resembling female nudes and non-manipulated female nudes, indicating a higher approach motivation to dissimilar mates. Our findings show that stress affects human mating preferences: unstressed individuals showed the expected preference for similar mates, but stressed individuals seem to prefer dissimilar mates. PMID:20219732

The Goals and Effects of Music Listening and Their Relationship to the Strength of Music Preference.

PubMed

Schäfer, Thomas

2016-01-01

Individual differences in the strength of music preference are among the most intricate psychological phenomena. While one person gets by very well without music, another person needs to listen to music every day and spends a lot of temporal and financial resources on listening to music, attending concerts, or buying concert tickets. Where do these differences come from? The hypothesis presented in this article is that the strength of music preference is mainly informed by the functions that music fulfills in people's lives (e.g., to regulate emotions, moods, or physiological arousal; to promote self-awareness; to foster social relatedness). Data were collected with a diary study, in which 121 respondents documented the goals they tried to attain and the effects that actually occurred for up to 5 music-listening episodes per day for 10 successive days. As expected, listeners reporting more intense experience of the functional use of music in the past (1) had a stronger intention to listen to music to attain specific goals in specific situations and (2) showed a larger overall strength of music preference. It is concluded that the functional effectiveness of music listening should be incorporated in existing models and frameworks of music preference to produce better predictions of interindividual differences in the strength of music preference. The predictability of musical style/genre preferences is also discussed with regard to the present results.

Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.

PubMed

Li, Dong; Pan, Zhisong; Hu, Guyu; Zhu, Zexuan; He, Shan

2017-03-14

Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.

Preferred and Actual Relative Height among Homosexual Male Partners Vary with Preferred Dominance and Sex Role

PubMed Central

Valentova, Jaroslava Varella; Stulp, Gert; Třebický, Vít; Havlíček, Jan

2014-01-01

Previous research has shown repeatedly that human stature influences mate preferences and mate choice in heterosexuals. In general, it has been shown that tall men and average height women are most preferred by the opposite sex, and that both sexes prefer to be in a relationship where the man is taller than the woman. However, little is known about such partner preferences in homosexual individuals. Based on an online survey of a large sample of non-heterosexual men (N = 541), we found that the majority of men prefer a partner slightly taller than themselves. However, these preferences were dependent on the participant’s own height, such that taller men preferred shorter partners, whereas shorter men preferred taller partners. We also examined whether height preferences predicted the preference for dominance and the adoption of particular sexual roles within a couple. Although a large proportion of men preferred to be in an egalitarian relationship with respect to preferred dominance (although not with respect to preferred sexual role), men that preferred a more dominant and more “active” sexual role preferred shorter partners, whereas those that preferred a more submissive and more “passive” sexual role preferred taller partners. Our results indicate that preferences for relative height in homosexual men are modulated by own height, preferred dominance and sex role, and do not simply resemble those of heterosexual women or men. PMID:24466136

Preferred and actual relative height among homosexual male partners vary with preferred dominance and sex role.

PubMed

Valentova, Jaroslava Varella; Stulp, Gert; Třebický, Vít; Havlíček, Jan

2014-01-01

Previous research has shown repeatedly that human stature influences mate preferences and mate choice in heterosexuals. In general, it has been shown that tall men and average height women are most preferred by the opposite sex, and that both sexes prefer to be in a relationship where the man is taller than the woman. However, little is known about such partner preferences in homosexual individuals. Based on an online survey of a large sample of non-heterosexual men (N = 541), we found that the majority of men prefer a partner slightly taller than themselves. However, these preferences were dependent on the participant's own height, such that taller men preferred shorter partners, whereas shorter men preferred taller partners. We also examined whether height preferences predicted the preference for dominance and the adoption of particular sexual roles within a couple. Although a large proportion of men preferred to be in an egalitarian relationship with respect to preferred dominance (although not with respect to preferred sexual role), men that preferred a more dominant and more "active" sexual role preferred shorter partners, whereas those that preferred a more submissive and more "passive" sexual role preferred taller partners. Our results indicate that preferences for relative height in homosexual men are modulated by own height, preferred dominance and sex role, and do not simply resemble those of heterosexual women or men.

Implementation of an algorithm for cylindrical object identification using range data

NASA Technical Reports Server (NTRS)

Bozeman, Sylvia T.; Martin, Benjamin J.

1989-01-01

One of the problems in 3-D object identification and localization is addressed. In robotic and navigation applications the vision system must be able to distinguish cylindrical or spherical objects as well as those of other geometric shapes. An algorithm was developed to identify cylindrical objects in an image when range data is used. The algorithm incorporates the Hough transform for line detection using edge points which emerge from a Sobel mask. Slices of the data are examined to locate arcs of circles using the normal equations of an over-determined linear system. Current efforts are devoted to testing the computer implementation of the algorithm. Refinements are expected to continue in order to accommodate cylinders in various positions. A technique is sought which is robust in the presence of noise and partial occlusions.

Model Predictive Control Based Motion Drive Algorithm for a Driving Simulator

NASA Astrophysics Data System (ADS)

Rehmatullah, Faizan

In this research, we develop a model predictive control based motion drive algorithm for the driving simulator at Toronto Rehabilitation Institute. Motion drive algorithms exploit the limitations of the human vestibular system to formulate a perception of motion within the constrained workspace of a simulator. In the absence of visual cues, the human perception system is unable to distinguish between acceleration and the force of gravity. The motion drive algorithm determines control inputs to displace the simulator platform, and by using the resulting inertial forces and angular rates, creates the perception of motion. By using model predictive control, we can optimize the use of simulator workspace for every maneuver while simulating the vehicle perception. With the ability to handle nonlinear constraints, the model predictive control allows us to incorporate workspace limitations.

Value redefined for inflammatory bowel disease patients: a choice-based conjoint analysis of patients' preferences.

PubMed

van Deen, Welmoed K; Nguyen, Dominic; Duran, Natalie E; Kane, Ellen; van Oijen, Martijn G H; Hommes, Daniel W

2017-02-01

Value-based healthcare is an upcoming field. The core idea is to evaluate care based on achieved outcomes divided by the costs. Unfortunately, the optimal way to evaluate outcomes is ill-defined. In this study, we aim to develop a single, preference based, outcome metric, which can be used to quantify overall health value in inflammatory bowel disease (IBD). IBD patients filled out a choice-based conjoint (CBC) questionnaire in which patients chose preferable outcome scenarios with different levels of disease control (DC), quality of life (QoL), and productivity (Pr). A CBC analysis was performed to estimate the relative value of DC, QoL, and Pr. A patient-centered composite score was developed which was weighted based on the stated preferences. We included 210 IBD patients. Large differences in stated preferences were observed. Increases from low to intermediate outcome levels were valued more than increases from intermediate to high outcome levels. Overall, QoL was more important to patients than DC or Pr. Individual outcome scores were calculated based on the stated preferences. This score was significantly different from a score not weighted based on patient preferences in patients with active disease. We showed the feasibility of creating a single outcome metric in IBD which incorporates patients' values using a CBC. Because this metric changes significantly when weighted according to patients' values, we propose that success in healthcare should be measured accordingly.

Genetic algorithms for multicriteria shape optimization of induction furnace

NASA Astrophysics Data System (ADS)

Kůs, Pavel; Mach, František; Karban, Pavel; Doležel, Ivo

2012-09-01

In this contribution we deal with a multi-criteria shape optimization of an induction furnace. We want to find shape parameters of the furnace in such a way, that two different criteria are optimized. Since they cannot be optimized simultaneously, instead of one optimum we find set of partially optimal designs, so called Pareto front. We compare two different approaches to the optimization, one using nonlinear conjugate gradient method and second using variation of genetic algorithm. As can be seen from the numerical results, genetic algorithm seems to be the right choice for this problem. Solution of direct problem (coupled problem consisting of magnetic and heat field) is done using our own code Agros2D. It uses finite elements of higher order leading to fast and accurate solution of relatively complicated coupled problem. It also provides advanced scripting support, allowing us to prepare parametric model of the furnace and simply incorporate various types of optimization algorithms.

Enhancements and Algorithms for Avionic Information Processing System Design Methodology.

DTIC Science & Technology

1982-06-16

programming algorithm is enhanced by incorporating task precedence constraints and hardware failures. Stochastic network methods are used to analyze...allocations in the presence of random fluctuations. Graph theoretic methods are used to analyze hardware designs, and new designs are constructed with...There, spatial dynamic programming (SDP) was used to solve a static, deterministic software allocation problem. Under the current contract the SDP

Performance characterization of a combined material identification and screening algorithm

NASA Astrophysics Data System (ADS)

Green, Robert L.; Hargreaves, Michael D.; Gardner, Craig M.

2013-05-01

Portable analytical devices based on a gamut of technologies (Infrared, Raman, X-Ray Fluorescence, Mass Spectrometry, etc.) are now widely available. These tools have seen increasing adoption for field-based assessment by diverse users including military, emergency response, and law enforcement. Frequently, end-users of portable devices are non-scientists who rely on embedded software and the associated algorithms to convert collected data into actionable information. Two classes of problems commonly encountered in field applications are identification and screening. Identification algorithms are designed to scour a library of known materials and determine whether the unknown measurement is consistent with a stored response (or combination of stored responses). Such algorithms can be used to identify a material from many thousands of possible candidates. Screening algorithms evaluate whether at least a subset of features in an unknown measurement correspond to one or more specific substances of interest and are typically configured to detect from a small list potential target analytes. Thus, screening algorithms are much less broadly applicable than identification algorithms; however, they typically provide higher detection rates which makes them attractive for specific applications such as chemical warfare agent or narcotics detection. This paper will present an overview and performance characterization of a combined identification/screening algorithm that has recently been developed. It will be shown that the combined algorithm provides enhanced detection capability more typical of screening algorithms while maintaining a broad identification capability. Additionally, we will highlight how this approach can enable users to incorporate situational awareness during a response.

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

Design of long-endurance unmanned airplanes incorporating solar and fuel cell propulsion

NASA Technical Reports Server (NTRS)

Youngblood, J. W.; Talay, T. A.; Pegg, R. J.

1984-01-01

Attention is given to the design features and operational capabilities of a class of unmanned flight vehicles possessing multiday mission endurance capabilities, based on the use of a mixed-mode electric power system which incorporates solar cells for diurnal energy production and a nonregenerative H2-O2 fuel cell for nocturnal energy supply. Energy is thereby provided for not only propulsion, but also the operation of the payload and the vehicle's avionics. The excess solar energy available during high insolation portions of the diurnal period may be used for climb/maneuvering or payload-related functions. Empirical structure scaling algorithms are combined with low Reynolds number aerodynamics algorithms to estimate requisite size and geometry for the chosen mission. Wing loadings will be of the order of 0.9-1.3 lb/sq ft.

GASPACHO: a generic automatic solver using proximal algorithms for convex huge optimization problems

NASA Astrophysics Data System (ADS)

Goossens, Bart; Luong, Hiêp; Philips, Wilfried

2017-08-01

Many inverse problems (e.g., demosaicking, deblurring, denoising, image fusion, HDR synthesis) share various similarities: degradation operators are often modeled by a specific data fitting function while image prior knowledge (e.g., sparsity) is incorporated by additional regularization terms. In this paper, we investigate automatic algorithmic techniques for evaluating proximal operators. These algorithmic techniques also enable efficient calculation of adjoints from linear operators in a general matrix-free setting. In particular, we study the simultaneous-direction method of multipliers (SDMM) and the parallel proximal algorithm (PPXA) solvers and show that the automatically derived implementations are well suited for both single-GPU and multi-GPU processing. We demonstrate this approach for an Electron Microscopy (EM) deconvolution problem.

Genetic algorithm-based improved DOA estimation using fourth-order cumulants

NASA Astrophysics Data System (ADS)

Ahmed, Ammar; Tufail, Muhammad

2017-05-01

Genetic algorithm (GA)-based direction of arrival (DOA) estimation is proposed using fourth-order cumulants (FOC) and ESPRIT principle which results in Multiple Invariance Cumulant ESPRIT algorithm. In the existing FOC ESPRIT formulations, only one invariance is utilised to estimate DOAs. The unused multiple invariances (MIs) must be exploited simultaneously in order to improve the estimation accuracy. In this paper, a fitness function based on a carefully designed cumulant matrix is developed which incorporates MIs present in the sensor array. Better DOA estimation can be achieved by minimising this fitness function. Moreover, the effectiveness of Newton's method as well as GA for this optimisation problem has been illustrated. Simulation results show that the proposed algorithm provides improved estimation accuracy compared to existing algorithms, especially in the case of low SNR, less number of snapshots, closely spaced sources and high signal and noise correlation. Moreover, it is observed that the optimisation using Newton's method is more likely to converge to false local optima resulting in erroneous results. However, GA-based optimisation has been found attractive due to its global optimisation capability.

Traffic Noise Ground Attenuation Algorithm Evaluation

NASA Astrophysics Data System (ADS)

Herman, Lloyd Allen

The Federal Highway Administration traffic noise prediction program, STAMINA 2.0, was evaluated for its accuracy. In addition, the ground attenuation algorithm used in the Ontario ORNAMENT method was evaluated to determine its potential to improve these predictions. Field measurements of sound levels were made at 41 sites on I-440 in Nashville, Tennessee in order to both study noise barrier effectiveness and to evaluate STAMINA 2.0 and the performance of the ORNAMENT ground attenuation algorithm. The measurement sites, which contain large variations in terrain, included several cross sections. Further, all sites contain some type of barrier, natural or constructed, which could more fully expose the strength and weaknesses of the ground attenuation algorithms. The noise barrier evaluation was accomplished in accordance with American National Standard Methods for Determination of Insertion Loss of Outdoor Noise Barriers which resulted in an evaluation of this standard. The entire 7.2 mile length of I-440 was modeled using STAMINA 2.0. A multiple run procedure was developed to emulate the results that would be obtained if the ORNAMENT algorithm was incorporated into STAMINA 2.0. Finally, the predicted noise levels based on STAMINA 2.0 and STAMINA with the ORNAMENT ground attenuation algorithm were compared with each other and with the field measurements. It was found that STAMINA 2.0 overpredicted noise levels by an average of over 2 dB for the receivers on I-440, whereas, the STAMINA with ORNAMENT ground attenuation algorithm overpredicted noise levels by an average of less than 0.5 dB. The mean errors for the two predictions were found to be statistically different from each other, and the mean error for the prediction with the ORNAMENT ground attenuation algorithm was not found to be statistically different from zero. The STAMINA 2.0 program predicts little, if any, ground attenuation for receivers at typical first-row distances from highways where noise barriers

Hybrid genetic algorithm in the Hopfield network for maximum 2-satisfiability problem

NASA Astrophysics Data System (ADS)

Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

2017-08-01

Heuristic method was designed for finding optimal solution more quickly compared to classical methods which are too complex to comprehend. In this study, a hybrid approach that utilizes Hopfield network and genetic algorithm in doing maximum 2-Satisfiability problem (MAX-2SAT) was proposed. Hopfield neural network was used to minimize logical inconsistency in interpretations of logic clauses or program. Genetic algorithm (GA) has pioneered the implementation of methods that exploit the idea of combination and reproduce a better solution. The simulation incorporated with and without genetic algorithm will be examined by using Microsoft Visual 2013 C++ Express software. The performance of both searching techniques in doing MAX-2SAT was evaluate based on global minima ratio, ratio of satisfied clause and computation time. The result obtained form the computer simulation demonstrates the effectiveness and acceleration features of genetic algorithm in doing MAX-2SAT in Hopfield network.

ecode - Electron Transport Algorithm Testing v. 1.0

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

Franke, Brian C.; Olson, Aaron J.; Bruss, Donald Eugene

2016-10-05

ecode is a Monte Carlo code used for testing algorithms related to electron transport. The code can read basic physics parameters, such as energy-dependent stopping powers and screening parameters. The code permits simple planar geometries of slabs or cubes. Parallelization consists of domain replication, with work distributed at the start of the calculation and statistical results gathered at the end of the calculation. Some basic routines (such as input parsing, random number generation, and statistics processing) are shared with the Integrated Tiger Series codes. A variety of algorithms for uncertainty propagation are incorporated based on the stochastic collocation and stochasticmore » Galerkin methods. These permit uncertainty only in the total and angular scattering cross sections. The code contains algorithms for simulating stochastic mixtures of two materials. The physics is approximate, ranging from mono-energetic and isotropic scattering to screened Rutherford angular scattering and Rutherford energy-loss scattering (simple electron transport models). No production of secondary particles is implemented, and no photon physics is implemented.« less

A new full-field digital mammography system with and without the use of an advanced post-processing algorithm: comparison of image quality and diagnostic performance.

PubMed

Ahn, Hye Shin; Kim, Sun Mi; Jang, Mijung; Yun, Bo La; Kim, Bohyoung; Ko, Eun Sook; Han, Boo-Kyung; Chang, Jung Min; Yi, Ann; Cho, Nariya; Moon, Woo Kyung; Choi, Hye Young

2014-01-01

To compare new full-field digital mammography (FFDM) with and without use of an advanced post-processing algorithm to improve image quality, lesion detection, diagnostic performance, and priority rank. During a 22-month period, we prospectively enrolled 100 cases of specimen FFDM mammography (Brestige®), which was performed alone or in combination with a post-processing algorithm developed by the manufacturer: group A (SMA), specimen mammography without application of "Mammogram enhancement ver. 2.0"; group B (SMB), specimen mammography with application of "Mammogram enhancement ver. 2.0". Two sets of specimen mammographies were randomly reviewed by five experienced radiologists. Image quality, lesion detection, diagnostic performance, and priority rank with regard to image preference were evaluated. Three aspects of image quality (overall quality, contrast, and noise) of the SMB were significantly superior to those of SMA (p < 0.05). SMB was significantly superior to SMA for visualizing calcifications (p < 0.05). Diagnostic performance, as evaluated by cancer score, was similar between SMA and SMB. SMB was preferred to SMA by four of the five reviewers. The post-processing algorithm may improve image quality with better image preference in FFDM than without use of the software.

Finite element solution for energy conservation using a highly stable explicit integration algorithm

NASA Technical Reports Server (NTRS)

Baker, A. J.; Manhardt, P. D.

1972-01-01

Theoretical derivation of a finite element solution algorithm for the transient energy conservation equation in multidimensional, stationary multi-media continua with irregular solution domain closure is considered. The complete finite element matrix forms for arbitrarily irregular discretizations are established, using natural coordinate function representations. The algorithm is embodied into a user-oriented computer program (COMOC) which obtains transient temperature distributions at the node points of the finite element discretization using a highly stable explicit integration procedure with automatic error control features. The finite element algorithm is shown to posses convergence with discretization for a transient sample problem. The condensed form for the specific heat element matrix is shown to be preferable to the consistent form. Computed results for diverse problems illustrate the versatility of COMOC, and easily prepared output subroutines are shown to allow quick engineering assessment of solution behavior.

Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy.

PubMed

Tang, Jing; Kuwabara, Hiroto; Wong, Dean F; Rahmim, Arman

2010-08-07

We developed an anatomy-guided 4D closed-form algorithm to directly reconstruct parametric images from projection data for (nearly) irreversible tracers. Conventional methods consist of individually reconstructing 2D/3D PET data, followed by graphical analysis on the sequence of reconstructed image frames. The proposed direct reconstruction approach maintains the simplicity and accuracy of the expectation-maximization (EM) algorithm by extending the system matrix to include the relation between the parametric images and the measured data. A closed-form solution was achieved using a different hidden complete-data formulation within the EM framework. Furthermore, the proposed method was extended to maximum a posterior reconstruction via incorporation of MR image information, taking the joint entropy between MR and parametric PET features as the prior. Using realistic simulated noisy [(11)C]-naltrindole PET and MR brain images/data, the quantitative performance of the proposed methods was investigated. Significant improvements in terms of noise versus bias performance were demonstrated when performing direct parametric reconstruction, and additionally upon extending the algorithm to its Bayesian counterpart using the MR-PET joint entropy measure.

Incorporation of a two metre long PET scanner in STIR

NASA Astrophysics Data System (ADS)

Tsoumpas, C.; Brain, C.; Dyke, T.; Gold, D.

2015-09-01

The Explorer project aims to investigate the potential benefits of a total-body 2 metre long PET scanner. The following investigation incorporates this scanner in STIR library and demonstrates the capabilities and weaknesses of existing reconstruction (FBP and OSEM) and single scatter simulation algorithms. It was found that sensible images are reconstructed but at the expense of high memory and processing time demands. FBP requires 4 hours on a core; OSEM: 2 hours per iteration if ran in parallel on 15-cores of a high performance computer. The single scatter simulation algorithm shows that on a short scale, up to a fifth of the scanner length, the assumption that the scatter between direct rings is similar to the scatter between the oblique rings is approximately valid. However, for more extreme cases this assumption is not longer valid, which illustrates that consideration of the oblique rings within the single scatter simulation will be necessary, if this scatter correction is the method of choice.

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

High performance genetic algorithm for VLSI circuit partitioning

NASA Astrophysics Data System (ADS)

Dinu, Simona

2016-12-01

Partitioning is one of the biggest challenges in computer-aided design for VLSI circuits (very large-scale integrated circuits). This work address the min-cut balanced circuit partitioning problem- dividing the graph that models the circuit into almost equal sized k sub-graphs while minimizing the number of edges cut i.e. minimizing the number of edges connecting the sub-graphs. The problem may be formulated as a combinatorial optimization problem. Experimental studies in the literature have shown the problem to be NP-hard and thus it is important to design an efficient heuristic algorithm to solve it. The approach proposed in this study is a parallel implementation of a genetic algorithm, namely an island model. The information exchange between the evolving subpopulations is modeled using a fuzzy controller, which determines an optimal balance between exploration and exploitation of the solution space. The results of simulations show that the proposed algorithm outperforms the standard sequential genetic algorithm both in terms of solution quality and convergence speed. As a direction for future study, this research can be further extended to incorporate local search operators which should include problem-specific knowledge. In addition, the adaptive configuration of mutation and crossover rates is another guidance for future research.

Relations among Spontaneous Preferences, Familiarized Preferences, and Novelty Effects: Measurements with Forced-Choice Techniques

ERIC Educational Resources Information Center

Civan, Andrea; Teller, Davida Y.; Palmer, John

2005-01-01

We here describe a discrete trial, forced-choice, combined spontaneous preference and novelty preference technique. In this technique, spontaneous preferences and familiarized (postfamiliarization) preferences are measured with the same stimulus pairs under closely parallel conditions. A variety of systematic stimulus variations were used in…

Design of a fast echo matching algorithm to reduce crosstalk with Doppler shifts in ultrasonic ranging

NASA Astrophysics Data System (ADS)

Liu, Lei; Guo, Rui; Wu, Jun-an

2017-02-01

Crosstalk is a main factor for wrong distance measurement by ultrasonic sensors, and this problem becomes more difficult to deal with under Doppler effects. In this paper, crosstalk reduction with Doppler shifts on small platforms is focused on, and a fast echo matching algorithm (FEMA) is proposed on the basis of chaotic sequences and pulse coding technology, then verified through applying it to match practical echoes. Finally, we introduce how to select both better mapping methods for chaotic sequences, and algorithm parameters for higher achievable maximum of cross-correlation peaks. The results indicate the following: logistic mapping is preferred to generate good chaotic sequences, with high autocorrelation even when the length is very limited; FEMA can not only match echoes and calculate distance accurately with an error degree mostly below 5%, but also generates nearly the same calculation cost level for static or kinematic ranging, much lower than that by direct Doppler compensation (DDC) with the same frequency compensation step; The sensitivity to threshold value selection and performance of FEMA depend significantly on the achievable maximum of cross-correlation peaks, and a higher peak is preferred, which can be considered as a criterion for algorithm parameter optimization under practical conditions.

Zombie algorithms: a timesaving remote sensing systems engineering tool

NASA Astrophysics Data System (ADS)

Ardanuy, Philip E.; Powell, Dylan C.; Marley, Stephen

2008-08-01

In modern horror fiction, zombies are generally undead corpses brought back from the dead by supernatural or scientific means, and are rarely under anyone's direct control. They typically have very limited intelligence, and hunger for the flesh of the living [1]. Typical spectroradiometric or hyperspectral instruments providess calibrated radiances for a number of remote sensing algorithms. The algorithms typically must meet specified latency and availability requirements while yielding products at the required quality. These systems, whether research, operational, or a hybrid, are typically cost constrained. Complexity of the algorithms can be high, and may evolve and mature over time as sensor characterization changes, product validation occurs, and areas of scientific basis improvement are identified and completed. This suggests the need for a systems engineering process for algorithm maintenance that is agile, cost efficient, repeatable, and predictable. Experience on remote sensing science data systems suggests the benefits of "plug-n-play" concepts of operation. The concept, while intuitively simple, can be challenging to implement in practice. The use of zombie algorithms-empty shells that outwardly resemble the form, fit, and function of a "complete" algorithm without the implemented theoretical basis-provides the ground systems advantages equivalent to those obtained by integrating sensor engineering models onto the spacecraft bus. Combined with a mature, repeatable process for incorporating the theoretical basis, or scientific core, into the "head" of the zombie algorithm, along with associated scripting and registration, provides an easy "on ramp" for the rapid and low-risk integration of scientific applications into operational systems.

Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm.

PubMed

Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

2016-10-01

Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.

Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm

PubMed Central

Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

2016-01-01

Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses. PMID:27706086

What are colorectal cancer survivors' preferences for dietary advice? A best-worst discrete choice experiment.

PubMed

Wright, Stuart J; Gibson, Debbie; Eden, Martin; Lal, Simon; Todd, Chris; Ness, Andy; Burden, Sorrel

2017-12-01

Studies on healthy lifestyle interventions in survivors of colorectal cancer have been disappointing, demonstrating only modest changes. This study aims to quantify people's preferences for different aspects of dietary intervention. A best-worst discrete choice experiment was designed and incorporated into a questionnaire including participants' characteristics and a self-assessment of lifestyle. The response rate was 68% and 179 questionnaires were analysed. When analysing aggregate preferences, the modes of information provision selected as the most preferred were "face-to-face" (willingness to pay (WTP) £63.97, p ≤ 0.001) and "telephone" (WTP £62.36, p < 0.001) discussions whereas group discussions were preferred least (WTP -£118.96, p ≤ 0.001). Scenarios that included hospitals were most preferred (WTP £17.94, p = 0.031), and the favoured provider was bowel cancer nurses (WTP £75.11, p ≤ 0.001). When investigating preference heterogeneity, three sub-groups were identified: Firstly, "technophiles" preferring email (WTP £239.60, p ≤ 0.001) were male, were younger and had fewer risk factors. Secondly, a "one-to-one" group had strong preference for interventions over the telephone or at their local doctors and were older (WTP £642.13, p ≤ 0.001). Finally, a "person-centred" group preferred face-to-face individual or group sessions (WTP £358.79, p < 0.001) and had a high risk lifestyle. For survivors of colorectal cancer, there is not one approach that suits all when it comes to providing dietary advice. This is important information to consider when planning healthy lifestyle interventions which include dietary advice for survivors of colorectal cancer. Aligning services to individuals' preferences has the potential to improve patient experience and outcomes by increasing uptake of healthy lifestyle advice services and promoting a more tailored approach to dietary modifications, acknowledging sub-groups of people within the total

Mass Conservation and Positivity Preservation with Ensemble-type Kalman Filter Algorithms

NASA Technical Reports Server (NTRS)

Janjic, Tijana; McLaughlin, Dennis B.; Cohn, Stephen E.; Verlaan, Martin

2013-01-01

Maintaining conservative physical laws numerically has long been recognized as being important in the development of numerical weather prediction (NWP) models. In the broader context of data assimilation, concerted efforts to maintain conservation laws numerically and to understand the significance of doing so have begun only recently. In order to enforce physically based conservation laws of total mass and positivity in the ensemble Kalman filter, we incorporate constraints to ensure that the filter ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. We show that the analysis steps of ensemble transform Kalman filter (ETKF) algorithm and ensemble Kalman filter algorithm (EnKF) can conserve the mass integral, but do not preserve positivity. Further, if localization is applied or if negative values are simply set to zero, then the total mass is not conserved either. In order to ensure mass conservation, a projection matrix that corrects for localization effects is constructed. In order to maintain both mass conservation and positivity preservation through the analysis step, we construct a data assimilation algorithms based on quadratic programming and ensemble Kalman filtering. Mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate constraints. Some simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. The results show clear improvements in both analyses and forecasts, particularly in the presence of localized features. Behavior of the algorithm is also tested in presence of model error.

The convergence analysis of SpikeProp algorithm with smoothing L1∕2 regularization.

PubMed

Zhao, Junhong; Zurada, Jacek M; Yang, Jie; Wu, Wei

2018-07-01

Unlike the first and the second generation artificial neural networks, spiking neural networks (SNNs) model the human brain by incorporating not only synaptic state but also a temporal component into their operating model. However, their intrinsic properties require expensive computation during training. This paper presents a novel algorithm to SpikeProp for SNN by introducing smoothing L 1∕2 regularization term into the error function. This algorithm makes the network structure sparse, with some smaller weights that can be eventually removed. Meanwhile, the convergence of this algorithm is proved under some reasonable conditions. The proposed algorithms have been tested for the convergence speed, the convergence rate and the generalization on the classical XOR-problem, Iris problem and Wisconsin Breast Cancer classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impact of whey protein coating incorporated with Bifidobacterium and Lactobacillus on sliced ham properties.

PubMed

Odila Pereira, Joana; Soares, José; J P Monteiro, Maria; Gomes, Ana; Pintado, Manuela

2018-05-01

Edible coatings/films with functional ingredients may be a solution to consumers' demands for high-quality food products and an extended shelf-life. The aim of this work was to evaluate the antimicrobial efficiency of edible coatings incorporated with probiotics on sliced ham preservation. Coatings was developed based on whey protein isolates with incorporation of Bifidobacterium animalis Bb-12® or Lactobacillus casei-01. The physicochemical analyses showed that coating decreased water and weight loss on the ham. Furthermore, color analysis showed that coated sliced ham, exhibited no color change, comparatively to uncoated slices. The edible coatings incorporating the probiotic strains inhibited detectable growth of Staphylococcus spp., Pseudomonas spp., Enterobacteriaceae and yeasts/molds, at least, for 45days of storage at 4°C. The sensory evaluation demonstrated that there was a preference for the sliced coated ham. Probiotic bacteria viable cell numbers were maintained at ca. 10 8 CFU/g throughout storage time, enabling the slice of ham to act as a suitable carrier for the beneficial bacteria. Copyright © 2018 Elsevier Ltd. All rights reserved.

WAM: an improved algorithm for modelling antibodies on the WEB.

PubMed

Whitelegg, N R; Rees, A R

2000-12-01

An improved antibody modelling algorithm has been developed which incorporates significant improvements to the earlier versions developed by Martin et al. (1989, 1991), Pedersen et al. (1992) and Rees et al. (1996) and known as AbM (Oxford Molecular). The new algorithm, WAM (for Web Antibody Modelling), has been launched as an online modelling service and is located at URL http://antibody.bath.ac.uk. Here we provide a summary only of the important features of WAM. Readers interested in further details are directed to the website, which gives extensive background information on the methods employed. A brief description of the rationale behind some of the newer methodology (specifically, the knowledge-based screens) is also given.

Color preferences are not universal.

PubMed

Taylor, Chloe; Clifford, Alexandra; Franklin, Anna

2013-11-01

Claims of universality pervade color preference research. It has been argued that there are universal preferences for some colors over others (e.g., Eysenck, 1941), universal sex differences (e.g., Hurlbert & Ling, 2007), and universal mechanisms or dimensions that govern these preferences (e.g., Palmer & Schloss, 2010). However, there have been surprisingly few cross-cultural investigations of color preference and none from nonindustrialized societies that are relatively free from the common influence of global consumer culture. Here, we compare the color preferences of British adults to those of Himba adults who belong to a nonindustrialized culture in rural Namibia. British and Himba color preferences are found to share few characteristics, and Himba color preferences display none of the so-called "universal" patterns or sex differences. Several significant predictors of color preference are identified, such as cone-contrast between stimulus and background (Hurlbert & Ling, 2007), the valence of color-associated objects (Palmer & Schloss, 2010), and the colorfulness of the color. However, the relationship of these predictors to color preference was strikingly different for the two cultures. No one model of color preference is able to account for both British and Himba color preferences. We suggest that not only do patterns of color preference vary across individuals and groups but the underlying mechanisms and dimensions of color preference vary as well. The findings have implications for broader debate on the extent to which our perception and experience of color is culturally relative or universally constrained. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks

PubMed Central

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806

Decomposition-based multiobjective evolutionary algorithm for community detection in dynamic social networks.

PubMed

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.

Clinical effectiveness of a Bayesian algorithm for the diagnosis and management of heparin-induced thrombocytopenia.

PubMed

Raschke, R A; Gallo, T; Curry, S C; Whiting, T; Padilla-Jones, A; Warkentin, T E; Puri, A

2017-08-01

Essentials We previously published a diagnostic algorithm for heparin-induced thrombocytopenia (HIT). In this study, we validated the algorithm in an independent large healthcare system. The accuracy was 98%, sensitivity 82% and specificity 99%. The algorithm has potential to improve accuracy and efficiency in the diagnosis of HIT. Background Heparin-induced thrombocytopenia (HIT) is a life-threatening drug reaction caused by antiplatelet factor 4/heparin (anti-PF4/H) antibodies. Commercial tests to detect these antibodies have suboptimal operating characteristics. We previously developed a diagnostic algorithm for HIT that incorporated 'four Ts' (4Ts) scoring and a stratified interpretation of an anti-PF4/H enzyme-linked immunosorbent assay (ELISA) and yielded a discriminant accuracy of 0.97 (95% confidence interval [CI], 0.93-1.00). Objectives The purpose of this study was to validate the algorithm in an independent patient population and quantitate effects that algorithm adherence could have on clinical care. Methods A retrospective cohort comprised patients who had undergone anti-PF4/H ELISA and serotonin release assay (SRA) testing in our healthcare system from 2010 to 2014. We determined the algorithm recommendation for each patient, compared recommendations with the clinical care received, and enumerated consequences of discrepancies. Operating characteristics were calculated for algorithm recommendations using SRA as the reference standard. Results Analysis was performed on 181 patients, 10 of whom were ruled in for HIT. The algorithm accurately stratified 98% of patients (95% CI, 95-99%), ruling out HIT in 158, ruling in HIT in 10 and recommending an SRA in 13 patients. Algorithm adherence would have obviated 165 SRAs and prevented 30 courses of unnecessary antithrombotic therapy for HIT. Diagnostic sensitivity was 0.82 (95% CI, 0.48-0.98), specificity 0.99 (95% CI, 0.97-1.00), PPV 0.90 (95% CI, 0.56-0.99) and NPV 0.99 (95% CI, 0.96-1.00). Conclusions An

Practical application of contrast-enhanced magnetic resonance mammography [CE-MRM] by an algorithm combining morphological and enhancement patterns.

PubMed

Potente, Giuseppe; Messineo, Daniela; Maggi, Claudia; Savelli, Sara

2009-03-01

The purpose of this article is to report our practical utilization of dynamic contrast-enhanced magnetic resonance mammography [DCE-MRM] in the diagnosis of breast lesions. In many European centers, was preferred a high-temporal acquisition of both breasts simultaneously in a large FOV. We preferred to scan single breasts, with the aim to combine the analysis of the contrast intake and washout with the morphological evaluation of breast lesions. We followed an interpretation model, based upon a diagnostic algorithm, which combined contrast enhancement with morphological evaluation, in order to increase our confidence in diagnosis. DCE-MRM with our diagnostic algorithm has identified 179 malignant and 41 benign lesions; final outcome has identified 178 malignant and 42 benign lesions, 3 false positives and 2 false negatives. Sensitivity of CE-MRM was 98.3%; specificity, 95.1%; positive predictive value, 98.9%; negative predictive value, 92.8% and accuracy, 97.7%.

Preferred Methods of Learning for Nursing Students in an On-Line Degree Program.

PubMed

Hampton, Debra; Pearce, Patricia F; Moser, Debra K

more effective for learning (P<.0167) than did Baby Boomer and Generation X students. In conclusion, the results of this study demonstrate that there are distinct student preferences and generational differences in preferred teaching/learning methods for on-line students. Faculty need to incorporate various teaching methodologies within on-line courses to include both synchronous and asynchronous activities and interactive and passive methodologies. Copyright © 2016 Elsevier Inc. All rights reserved.

Fire behavior simulation in Mediterranean forests using the minimum travel time algorithm

Treesearch

Kostas Kalabokidis; Palaiologos Palaiologou; Mark A. Finney

2014-01-01

Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap's version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the...

Single-Spot Yellow Laser Versus Conventional Green Laser on Panretinal Photocoagulation: Patient Pain Scores and Preferences.

PubMed

González-Saldivar, Gerardo; Rojas-Juárez, Sergio; Espinosa-Soto, Itzel; Sánchez-Ramos, Jorge; Jaurieta-Hinojosa, Noel; Ramírez-Estudillo, Abel

2017-11-01

Panretinal photocoagulation (PRP) is the mainstay therapy for proliferative diabetic retinopathy. Pain during and after its application is a complication that affects patients' therapeutic adherence. This study aimed to compare pain perception and patient preference for the 577-nm yellow laser (YL-577) (LIGHTL as 577; LIGHTMED, San Clemente, CA) and the conventional 532-nm green laser (GL-532) (Purepoint Laser; Alcon, Fort Worth, TX) with PRP. A total of 92 patient eyes with proliferative diabetic retinopathy treated with PRP were randomly assigned to receive both GL-532 and YL-577 (184 eyes) - one on each eye, with the order of application randomized, as well. Afterward, verbal rapid answer and visual analogue scale (VAS) scores for pain perception and patient preference were evaluated. VAS score was 7 ± 2 for the GL-532 group compared to 5 ± 3 in the YL-577 group (P = .001). Overall, 75% of the patients preferred YL-577 therapy if they were to receive a second PRP session. The use of YL-577 as an alternative approach for PRP reduces pain perception and is preferred by patients. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:902-905.]. Copyright 2017, SLACK Incorporated.

Issues related to incorporating northern peatlands into global climate models

NASA Astrophysics Data System (ADS)

Frolking, Steve; Roulet, Nigel; Lawrence, David

Northern peatlands cover ˜3-4 million km2 (˜10% of the land north of 45°N) and contain ˜200-400 Pg carbon (˜10-20% of total global soil carbon), almost entirely as peat (organic soil). Recent developments in global climate models have included incorporation of the terrestrial carbon cycle and representation of several terrestrial ecosystem types and processes in their land surface modules. Peatlands share many general properties with upland, mineral-soil ecosystems, and general ecosystem carbon, water, and energy cycle functions (productivity, decomposition, water infiltration, evapotranspiration, runoff, latent, sensible, and ground heat fluxes). However, northern peatlands also have several unique characteristics that will require some rethinking or revising of land surface algorithms in global climate models. Here we review some of these characteristics, deep organic soils, a significant fraction of bryophyte vegetation, shallow water tables, spatial heterogeneity, anaerobic biogeochemistry, and disturbance regimes, in the context of incorporating them into global climate models. With the incorporation of peatlands, global climate models will be able to simulate the fate of northern peatland carbon under climate change, and estimate the magnitude and strength of any climate system feedbacks associated with the dynamics of this large carbon pool.

A parallel algorithm for switch-level timing simulation on a hypercube multiprocessor

NASA Technical Reports Server (NTRS)

Rao, Hariprasad Nannapaneni

1989-01-01

The parallel approach to speeding up simulation is studied, specifically the simulation of digital LSI MOS circuitry on the Intel iPSC/2 hypercube. The simulation algorithm is based on RSIM, an event driven switch-level simulator that incorporates a linear transistor model for simulating digital MOS circuits. Parallel processing techniques based on the concepts of Virtual Time and rollback are utilized so that portions of the circuit may be simulated on separate processors, in parallel for as large an increase in speed as possible. A partitioning algorithm is also developed in order to subdivide the circuit for parallel processing.

Embedded assessment algorithms within home-based cognitive computer game exercises for elders.

PubMed

Jimison, Holly; Pavel, Misha

2006-01-01

With the recent consumer interest in computer-based activities designed to improve cognitive performance, there is a growing need for scientific assessment algorithms to validate the potential contributions of cognitive exercises. In this paper, we present a novel methodology for incorporating dynamic cognitive assessment algorithms within computer games designed to enhance cognitive performance. We describe how this approach works for variety of computer applications and describe cognitive monitoring results for one of the computer game exercises. The real-time cognitive assessments also provide a control signal for adapting the difficulty of the game exercises and providing tailored help for elders of varying abilities.

Preference assessments in the zoo: Keeper and staff predictions of enrichment preferences across species.

PubMed

Mehrkam, Lindsay R; Dorey, Nicole R

2015-01-01

Environmental enrichment is widely used in the management of zoo animals, and is an essential strategy for increasing the behavioral welfare of these populations. It may be difficult, however, to identify potentially effective enrichment strategies that are also cost-effective and readily available. An animal's preference for a potential enrichment item may be a reliable predictor of whether that individual will reliably interact with that item, and subsequently enable staff to evaluate the effects of that enrichment strategy. The aim of the present study was to assess the utility of preference assessments for identifying potential enrichment items across six different species--each representing a different taxonomic group. In addition, we evaluated the agreement between zoo personnel's predictions of animals' enrichment preferences and stimuli selected via a preference assessment. Five out of six species (nine out of 11 individuals) exhibited clear, systematic preferences for specific stimuli. Similarities in enrichment preferences were observed among all individuals of primates, whereas individuals within ungulate and avian species displayed individual differences in enrichment preferences. Overall, zoo personnel, regardless of experience level, were significantly more accurate at predicting least-preferred stimuli than most-preferred stimuli across species, and tended to make the same predictions for all individuals within a species. Preference assessments may therefore be a useful, efficient husbandry strategy for identifying viable enrichment items at both the individual and species levels. © 2015 Wiley Periodicals, Inc.

Multi-scale graph-cut algorithm for efficient water-fat separation.

PubMed

Berglund, Johan; Skorpil, Mikael

2017-09-01

To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Assessing Women's Preferences and Preference Modeling for Breast Reconstruction Decision-Making.

PubMed

Sun, Clement S; Cantor, Scott B; Reece, Gregory P; Crosby, Melissa A; Fingeret, Michelle C; Markey, Mia K

2014-03-01

Women considering breast reconstruction must make challenging trade-offs amongst issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using nine different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual wellbeing as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants' rankings. The median amount of time required to assess preferences was 34 minutes. Agreement among the nine preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best performing risk averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the seven attributes. We recommend the risk averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study.

Evaluation of a multi-channel algorithm for reducing transient sounds.

PubMed

Keshavarzi, Mahmoud; Baer, Thomas; Moore, Brian C J

2018-05-15

The objective was to evaluate and select appropriate parameters for a multi-channel transient reduction (MCTR) algorithm for detecting and attenuating transient sounds in speech. In each trial, the same sentence was played twice. A transient sound was presented in both sentences, but its level varied across the two depending on whether or not it had been processed by the MCTR and on the "strength" of the processing. The participant indicated their preference for which one was better and by how much in terms of the balance between the annoyance produced by the transient and the audibility of the transient (they were told that the transient should still be audible). Twenty English-speaking participants were tested, 10 with normal hearing and 10 with mild-to-moderate hearing-impairment. Frequency-dependent linear amplification was provided for the latter. The results for both participant groups indicated that sounds processed using the MCTR were preferred over the unprocessed sounds. For the hearing-impaired participants, the medium and strong settings of the MCTR were preferred over the weak setting. The medium and strong settings of the MCTR reduced the annoyance produced by the transients while maintaining their audibility.

Providing health information for culturally and linguistically diverse women: priorities and preferences of new migrants and refugees.

PubMed

Lee, Susan K; Sulaiman-Hill, Cheryl M R; Thompson, Sandra C

2013-08-01

Preferences for topics and means of access to health information among newly arrived, culturally and linguistically diverse women in Perth, Western Australia, were explored. A mixed-methods approach was adopted. Qualitative material obtained from focus groups and interviews with 22 service providers and 26 migrant women was used to develop a questionnaire, which was then administered to 268 newly arrived migrant and refugee women from 50 countries. Participants' information and support priorities were ascertained from a ranking exercise conducted in a non-threatening context. Responses of migrant and refugee women were compared quantitatively. Women's top priorities for information and support included employment advice, as well as information regarding mental health issues, women's health, exercise and nutrition, family violence and alcohol and other drug issues. Their preferred methods for receiving information were interactive talks or presentations, with written material support. Audiovisual and Web-based material were also considered useful. There were differences between refugee women's and other migrants' preferences for means of receiving information and topics of most concern. The use of a non-threatening ranking process encouraged women to prioritise sensitive topics, such as family violence, and revealed a need for such topics to be incorporated within general health information presentations. Internet-based technologies are becoming increasingly important methods for disseminating information to migrant women. SO WHAT? Differences between migrant and refugee women's priority health issues and their preferred methods for receiving information highlight the desirability of tailoring information to particular groups. Although advice on employment pathways and mental health concerns were top priorities, the study revealed a need for more discussion on other sensitive topics, such as family violence and alcohol-related issues, and that ideally these should

The Goals and Effects of Music Listening and Their Relationship to the Strength of Music Preference

PubMed Central

Schäfer, Thomas

2016-01-01

Individual differences in the strength of music preference are among the most intricate psychological phenomena. While one person gets by very well without music, another person needs to listen to music every day and spends a lot of temporal and financial resources on listening to music, attending concerts, or buying concert tickets. Where do these differences come from? The hypothesis presented in this article is that the strength of music preference is mainly informed by the functions that music fulfills in people’s lives (e.g., to regulate emotions, moods, or physiological arousal; to promote self-awareness; to foster social relatedness). Data were collected with a diary study, in which 121 respondents documented the goals they tried to attain and the effects that actually occurred for up to 5 music-listening episodes per day for 10 successive days. As expected, listeners reporting more intense experience of the functional use of music in the past (1) had a stronger intention to listen to music to attain specific goals in specific situations and (2) showed a larger overall strength of music preference. It is concluded that the functional effectiveness of music listening should be incorporated in existing models and frameworks of music preference to produce better predictions of interindividual differences in the strength of music preference. The predictability of musical style/genre preferences is also discussed with regard to the present results. PMID:26985998

Plasticity of preferred body temperatures as means of coping with climate change?

PubMed Central

Gvoždík, Lumír

2012-01-01

Thermoregulatory behaviour represents an important component of ectotherm non-genetic adaptive capacity that mitigates the impact of ongoing climate change. The buffering role of behavioural thermoregulation has been attributed solely to the ability to maintain near optimal body temperature for sufficiently extended periods under altered thermal conditions. The widespread occurrence of plastic modification of target temperatures that an ectotherm aims to achieve (preferred body temperatures) has been largely overlooked. I argue that plasticity of target temperatures may significantly contribute to an ectotherm's adaptive capacity. Its contribution to population persistence depends on both the effectiveness of acute thermoregulatory adjustments (reactivity) in buffering selection pressures in a changing thermal environment, and the total costs of thermoregulation (i.e. reactivity and plasticity) in a given environment. The direction and magnitude of plastic shifts in preferred body temperatures can be incorporated into mechanistic models, to improve predictions of the impact of global climate change on ectotherm populations. PMID:22072284

Plasticity of preferred body temperatures as means of coping with climate change?

PubMed

Gvozdík, Lumír

2012-04-23

Thermoregulatory behaviour represents an important component of ectotherm non-genetic adaptive capacity that mitigates the impact of ongoing climate change. The buffering role of behavioural thermoregulation has been attributed solely to the ability to maintain near optimal body temperature for sufficiently extended periods under altered thermal conditions. The widespread occurrence of plastic modification of target temperatures that an ectotherm aims to achieve (preferred body temperatures) has been largely overlooked. I argue that plasticity of target temperatures may significantly contribute to an ectotherm's adaptive capacity. Its contribution to population persistence depends on both the effectiveness of acute thermoregulatory adjustments (reactivity) in buffering selection pressures in a changing thermal environment, and the total costs of thermoregulation (i.e. reactivity and plasticity) in a given environment. The direction and magnitude of plastic shifts in preferred body temperatures can be incorporated into mechanistic models, to improve predictions of the impact of global climate change on ectotherm populations.

Application of an enhanced fuzzy algorithm for MR brain tumor image segmentation

NASA Astrophysics Data System (ADS)

Hemanth, D. Jude; Vijila, C. Kezi Selva; Anitha, J.

2010-02-01

Image segmentation is one of the significant digital image processing techniques commonly used in the medical field. One of the specific applications is tumor detection in abnormal Magnetic Resonance (MR) brain images. Fuzzy approaches are widely preferred for tumor segmentation which generally yields superior results in terms of accuracy. But most of the fuzzy algorithms suffer from the drawback of slow convergence rate which makes the system practically non-feasible. In this work, the application of modified Fuzzy C-means (FCM) algorithm to tackle the convergence problem is explored in the context of brain image segmentation. This modified FCM algorithm employs the concept of quantization to improve the convergence rate besides yielding excellent segmentation efficiency. This algorithm is experimented on real time abnormal MR brain images collected from the radiologists. A comprehensive feature vector is extracted from these images and used for the segmentation technique. An extensive feature selection process is performed which reduces the convergence time period and improve the segmentation efficiency. After segmentation, the tumor portion is extracted from the segmented image. Comparative analysis in terms of segmentation efficiency and convergence rate is performed between the conventional FCM and the modified FCM. Experimental results show superior results for the modified FCM algorithm in terms of the performance measures. Thus, this work highlights the application of the modified algorithm for brain tumor detection in abnormal MR brain images.

Taste preference and psychopathology.

PubMed

Aguayo, G A; Vaillant, M T; Arendt, C; Bachim, S; Pull, C B

2012-01-01

Excessive food intake has been linked to many factors including taste preference and the presence of psychopathology. The purpose of this study was to investigate the association between sweet and salty taste preference and psychopathology in patients with severe obesity. A consecutive series of patients applying for bariatric surgery was recruited for the study. Taste preference was self-reported. Psychopathology was assessed using the revised version of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). 190 patients were included in the study. In comparison with patients who had salty taste preference, patients with sweet taste preference had significantly higher elevations on the depression (OD: 4.090, p = 0.010) and the hysteria (OD: 2.951, p = 0.026) clinical scales of the MMPI-2. The results suggest the presence of an association between taste preference and psychopathology. The findings may be of interest for clinicians who are involved in the treatment of obesity. In particular, they may wish to pay increased attention to patients with sweet taste preference or who have a strong attraction for both sweet and salty foods, in order to detect psychopathology and to adapt the treatment.

Control optimization, stabilization and computer algorithms for aircraft applications

NASA Technical Reports Server (NTRS)

1975-01-01

Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.

A novel global Harmony Search method based on Ant Colony Optimisation algorithm

NASA Astrophysics Data System (ADS)

Fouad, Allouani; Boukhetala, Djamel; Boudjema, Fares; Zenger, Kai; Gao, Xiao-Zhi

2016-03-01

The Global-best Harmony Search (GHS) is a stochastic optimisation algorithm recently developed, which hybridises the Harmony Search (HS) method with the concept of swarm intelligence in the particle swarm optimisation (PSO) to enhance its performance. In this article, a new optimisation algorithm called GHSACO is developed by incorporating the GHS with the Ant Colony Optimisation algorithm (ACO). Our method introduces a novel improvisation process, which is different from that of the GHS in the following aspects. (i) A modified harmony memory (HM) representation and conception. (ii) The use of a global random switching mechanism to monitor the choice between the ACO and GHS. (iii) An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The proposed GHSACO algorithm has been applied to various benchmark functions and constrained optimisation problems. Simulation results demonstrate that it can find significantly better solutions when compared with the original HS and some of its variants.

Optimizing conservation practices in watersheds: Do community preferences matter?

NASA Astrophysics Data System (ADS)

Piemonti, Adriana D.; Babbar-Sebens, Meghna; Jane Luzar, E.

2013-10-01

This paper focuses on investigating (a) how landowner tenure and attitudes of farming communities affect the preference of individual conservation practices in agricultural watersheds, (b) how spatial distribution of landowner tenure affects the spatial optimization of conservation practices on a watershed scale, and (c) how the different attitudes and preferences of stakeholders can modify the effectiveness of alternatives obtained via classic optimization approaches that do not include the influence of existing social attitudes in a watershed during the search process. Results show that for Eagle Creek Watershed in central Indiana, USA, the most optimal alternatives (i.e., highest benefits for minimum economic costs) are for a scenario when the watershed consists of landowners who operate as farmers on their own land. When a different land-tenure scenario was used for the watershed (e.g., share renters and cash renters), the optimized alternatives had similar nitrate reduction benefits and sediment reduction benefits, but at higher economic costs. Our experiments also demonstrated that social attitudes can lead to alteration of optimized alternatives found via typical optimization approaches. For example, when certain practices were rejected by landowner operators whose attitudes toward practices were driven by economic profits, removal of these practices from the optimized alternatives led to a setback of nitrates reduction by 2-50%, peak flow reductions by 11-98 %, and sediments reduction by 20-77%. In conclusion, this study reveals the potential loss in optimality of optimized alternatives possible, when socioeconomic data on farmer preferences and land tenure are not incorporated within watershed optimization investigations.

Geomagnetic field models incorporating physical constraints on the secular variation

NASA Technical Reports Server (NTRS)

Constable, Catherine; Parker, Robert L.

1993-01-01

This proposal has been concerned with methods for constructing geomagnetic field models that incorporate physical constraints on the secular variation. The principle goal that has been accomplished is the development of flexible algorithms designed to test whether the frozen flux approximation is adequate to describe the available geomagnetic data and their secular variation throughout this century. These have been applied to geomagnetic data from both the early and middle part of this century and convincingly demonstrate that there is no need to invoke violations of the frozen flux hypothesis in order to satisfy the available geomagnetic data.

SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters

NASA Technical Reports Server (NTRS)

McKinna, Lachlan I. W.; Werdell, P. Jeremy; Fearns, Peter R. C. S.; Weeks, Scarla J.; Reichstetter, Martina; Franz, Bryan A.; Shea, Donald M.; Feldman, Gene C.

2014-01-01

Ocean color remote sensing provides synoptic-scale, near-daily observations of marine inherent optical properties (IOPs). Whilst contemporary ocean color algorithms are known to perform well in deep oceanic waters, they have difficulty operating in optically clear, shallow marine environments where light reflected from the seafloor contributes to the water-leaving radiance. The effect of benthic reflectance in optically shallow waters is known to adversely affect algorithms developed for optically deep waters [1, 2]. Whilst adapted versions of optically deep ocean color algorithms have been applied to optically shallow regions with reasonable success [3], there is presently no approach that directly corrects for bottom reflectance using existing knowledge of bathymetry and benthic albedo.To address the issue of optically shallow waters, we have developed a semi-analytical ocean color inversion algorithm: the Shallow Water Inversion Model (SWIM). SWIM uses existing bathymetry and a derived benthic albedo map to correct for bottom reflectance using the semi-analytical model of Lee et al [4]. The algorithm was incorporated into the NASA Ocean Biology Processing Groups L2GEN program and tested in optically shallow waters of the Great Barrier Reef, Australia. In-lieu of readily available in situ matchup data, we present a comparison between SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Property Algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA).

Automated Pressure Injury Risk Assessment System Incorporated Into an Electronic Health Record System.

PubMed

Jin, Yinji; Jin, Taixian; Lee, Sun-Mi

Pressure injury risk assessment is the first step toward preventing pressure injuries, but traditional assessment tools are time-consuming, resulting in work overload and fatigue for nurses. The objectives of the study were to build an automated pressure injury risk assessment system (Auto-PIRAS) that can assess pressure injury risk using data, without requiring nurses to collect or input additional data, and to evaluate the validity of this assessment tool. A retrospective case-control study and a system development study were conducted in a 1,355-bed university hospital in Seoul, South Korea. A total of 1,305 pressure injury patients and 5,220 nonpressure injury patients participated for the development of a risk scoring algorithm: 687 and 2,748 for the validation of the algorithm and 237 and 994 for validation after clinical implementation, respectively. A total of 4,211 pressure injury-related clinical variables were extracted from the electronic health record (EHR) systems to develop a risk scoring algorithm, which was validated and incorporated into the EHR. That program was further evaluated for predictive and concurrent validity. Auto-PIRAS, incorporated into the EHR system, assigned a risk assessment score of high, moderate, or low and displayed this on the Kardex nursing record screen. Risk scores were updated nightly according to 10 predetermined risk factors. The predictive validity measures of the algorithm validation stage were as follows: sensitivity = .87, specificity = .90, positive predictive value = .68, negative predictive value = .97, Youden index = .77, and the area under the receiver operating characteristic curve = .95. The predictive validity measures of the Braden Scale were as follows: sensitivity = .77, specificity = .93, positive predictive value = .72, negative predictive value = .95, Youden index = .70, and the area under the receiver operating characteristic curve = .85. The kappa of the Auto-PIRAS and Braden Scale risk

CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

2014-12-01

Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

Incorporation of Fixed Installation Costs into Optimization of Groundwater Remediation with a New Efficient Surrogate Nonlinear Mixed Integer Optimization Algorithm

NASA Astrophysics Data System (ADS)

Shoemaker, Christine; Wan, Ying

2016-04-01

Optimization of nonlinear water resources management issues which have a mixture of fixed (e.g. construction cost for a well) and variable (e.g. cost per gallon of water pumped) costs has been not well addressed because prior algorithms for the resulting nonlinear mixed integer problems have required many groundwater simulations (with different configurations of decision variable), especially when the solution space is multimodal. In particular heuristic methods like genetic algorithms have often been used in the water resources area, but they require so many groundwater simulations that only small systems have been solved. Hence there is a need to have a method that reduces the number of expensive groundwater simulations. A recently published algorithm for nonlinear mixed integer programming using surrogates was shown in this study to greatly reduce the computational effort for obtaining accurate answers to problems involving fixed costs for well construction as well as variable costs for pumping because of a substantial reduction in the number of groundwater simulations required to obtain an accurate answer. Results are presented for a US EPA hazardous waste site. The nonlinear mixed integer surrogate algorithm is general and can be used on other problems arising in hydrology with open source codes in Matlab and python ("pySOT" in Bitbucket).

Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

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

Sheng, Zheng, E-mail: 19994035@sina.com; Wang, Jun; Zhou, Bihua

2014-03-15

This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented tomore » tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.« less

An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, D.; Zhang, W. Y.

2017-08-01

Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

Real-time depth camera tracking with geometrically stable weight algorithm

NASA Astrophysics Data System (ADS)

Fu, Xingyin; Zhu, Feng; Qi, Feng; Wang, Mingming

2017-03-01

We present an approach for real-time camera tracking with depth stream. Existing methods are prone to drift in sceneries without sufficient geometric information. First, we propose a new weight method for an iterative closest point algorithm commonly used in real-time dense mapping and tracking systems. By detecting uncertainty in pose and increasing weight of points that constrain unstable transformations, our system achieves accurate and robust trajectory estimation results. Our pipeline can be fully parallelized with GPU and incorporated into the current real-time depth camera tracking system seamlessly. Second, we compare the state-of-the-art weight algorithms and propose a weight degradation algorithm according to the measurement characteristics of a consumer depth camera. Third, we use Nvidia Kepler Shuffle instructions during warp and block reduction to improve the efficiency of our system. Results on the public TUM RGB-D database benchmark demonstrate that our camera tracking system achieves state-of-the-art results both in accuracy and efficiency.

Classification and characterization of Japanese consumers' beef preferences by external preference mapping.

PubMed

Sasaki, Keisuke; Ooi, Motoki; Nagura, Naoto; Motoyama, Michiyo; Narita, Takumi; Oe, Mika; Nakajima, Ikuyo; Hagi, Tatsuro; Ojima, Koichi; Kobayashi, Miho; Nomura, Masaru; Muroya, Susumu; Hayashi, Takeshi; Akama, Kyoko; Fujikawa, Akira; Hokiyama, Hironao; Kobayashi, Kuniyuki; Nishimura, Takanori

2017-08-01

Over the past few decades, beef producers in Japan have improved marbling in their beef products. It was recently reported that marbling is not well correlated with palatability as rated by Japanese consumers. This study sought to identify the consumer segments in Japan that prefer sensory characteristics of beef other than high marbling. Three Wagyu beef, one Holstein beef and two lean imported beef longissimus samples were subjected to a descriptive sensory test, physicochemical analysis and a consumer (n = 307) preference test. According to consumer classification and external preference mapping, four consumer segments were identified as 'gradual high-fat likers', 'moderate-fat and distinctive taste likers', 'Wagyu likers' and 'distinctive texture likers'. Although the major trend of Japanese consumers' beef preference was 'marbling liking', 16.9% of the consumers preferred beef samples that had moderate marbling and distinctive taste. The consumers' attitudes expressed in a questionnaire survey were in good agreement with the preference for marbling among the 'moderate-fat and distinctive taste likers'. These results indicate that moderately marbled beef is a potent category in the Japanese beef market. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state

Targeted physical activity messages for parents of children with disabilities: A qualitative investigation of parents' informational needs and preferences.

PubMed

Bassett-Gunter, R L; Ruscitti, R J; Latimer-Cheung, A E; Fraser-Thomas, J L

2017-05-01

Physical activity (PA) has myriad benefits for children with disabilities (CWD). Information and messaging campaigns can promote PA among CWD. The overall purpose of the study was to gain an understanding of the development of PA information and messages targeting parents of CWD. The specific objectives were to identify parents' preferences regarding PA information and messaging content and preferred methods and sources of communication. Focus groups were conducted with parents of CWD (N=28). Qualitative data were collected and transcribed. Inductive content analyses were employed to identify key themes. Three key thematic areas were identified: 1) Preferred content (e.g., targeted information, self-regulatory strategies, inclusive images), 2) Challenges (e.g., lack of information and language clarity), 3) Preferred sources (e.g., other parents, reliable organizations, central information hub). Parents' needs and preferences regarding PA information could be incorporated into campaigns to enhance parent PA support and PA among CWD. Stakeholders (e.g., PA organizations, programs and practitioners) can employ these strategies in campaigns and resources targeting parents of CWD. Research is necessary to empirically develop and evaluate PA information and messaging campaigns targeting parents of CWD. Copyright © 2017 Elsevier Ltd. All rights reserved.

A computationally efficient method for incorporating spike waveform information into decoding algorithms.

PubMed

Ventura, Valérie; Todorova, Sonia

2015-05-01

Spike-based brain-computer interfaces (BCIs) have the potential to restore motor ability to people with paralysis and amputation, and have shown impressive performance in the lab. To transition BCI devices from the lab to the clinic, decoding must proceed automatically and in real time, which prohibits the use of algorithms that are computationally intensive or require manual tweaking. A common choice is to avoid spike sorting and treat the signal on each electrode as if it came from a single neuron, which is fast, easy, and therefore desirable for clinical use. But this approach ignores the kinematic information provided by individual neurons recorded on the same electrode. The contribution of this letter is a linear decoding model that extracts kinematic information from individual neurons without spike-sorting the electrode signals. The method relies on modeling sample averages of waveform features as functions of kinematics, which is automatic and requires minimal data storage and computation. In offline reconstruction of arm trajectories of a nonhuman primate performing reaching tasks, the proposed method performs as well as decoders based on expertly manually and automatically sorted spikes.

Model and algorithmic framework for detection and correction of cognitive errors.

PubMed

Feki, Mohamed Ali; Biswas, Jit; Tolstikov, Andrei

2009-01-01

This paper outlines an approach that we are taking for elder-care applications in the smart home, involving cognitive errors and their compensation. Our approach involves high level modeling of daily activities of the elderly by breaking down these activities into smaller units, which can then be automatically recognized at a low level by collections of sensors placed in the homes of the elderly. This separation allows us to employ plan recognition algorithms and systems at a high level, while developing stand-alone activity recognition algorithms and systems at a low level. It also allows the mixing and matching of multi-modality sensors of various kinds that go to support the same high level requirement. Currently our plan recognition algorithms are still at a conceptual stage, whereas a number of low level activity recognition algorithms and systems have been developed. Herein we present our model for plan recognition, providing a brief survey of the background literature. We also present some concrete results that we have achieved for activity recognition, emphasizing how these results are incorporated into the overall plan recognition system.

Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH.

PubMed

Volk, Jochen; Herrmann, Torsten; Wüthrich, Kurt

2008-07-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness.

Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm

NASA Astrophysics Data System (ADS)

Sun, Xiuqiao; Wang, Jian

2018-07-01

Freeway service patrol (FSP), is considered to be an effective method for incident management and can help transportation agency decision-makers alter existing route coverage and fleet allocation. This paper investigates the FSP problem of patrol routing design and fleet allocation, with the objective of minimizing the overall average incident response time. While the simulated annealing (SA) algorithm and its improvements have been applied to solve this problem, they often become trapped in local optimal solution. Moreover, the issue of searching efficiency remains to be further addressed. In this paper, we employ the genetic algorithm (GA) and SA to solve the FSP problem. To maintain population diversity and avoid premature convergence, niche strategy is incorporated into the traditional genetic algorithm. We also employ elitist strategy to speed up the convergence. Numerical experiments have been conducted with the help of the Sioux Falls network. Results show that the GA slightly outperforms the dual-based greedy (DBG) algorithm, the very large-scale neighborhood searching (VLNS) algorithm, the SA algorithm and the scenario algorithm.

Evaluation of an Agricultural Meteorological Disaster Based on Multiple Criterion Decision Making and Evolutionary Algorithm

PubMed Central

Yu, Xiaobing; Yu, Xianrui; Lu, Yiqun

2018-01-01

The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which includes the disaster rate, the inundated rate, and the complete loss rate. Following this, the relative weights of the three criteria are acquired using a novel proposed evolutionary algorithm. The proposed algorithm consists of a differential evolution algorithm and an evolution strategy. Finally, a novel evaluation model, based on the proposed algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is presented to estimate the agricultural meteorological disaster of 2008 in China. The geographic information system (GIS) technique is employed to depict the disaster. The experimental results demonstrated that the agricultural meteorological disaster of 2008 was very serious, especially in Hunan and Hubei provinces. Some useful suggestions are provided to relieve agriculture meteorological disasters. PMID:29597243

Using data mining to segment healthcare markets from patients' preference perspectives.

PubMed

Liu, Sandra S; Chen, Jie

2009-01-01

This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic characteristics. Data were derived from a number of individuals who received in-patient care at a health network in 2006. Data mining and conventional hierarchical clustering with average linkage and Pearson correlation procedures are employed and compared to show how each procedure best determines segmentation variables. Data mining tools identified three differentiable segments by means of cluster analysis. These three clusters have significantly different demographic profiles. The study reveals, when compared with traditional statistical methods, that data mining provides an efficient and effective tool for market segmentation. When there are numerous cluster variables involved, researchers and practitioners need to incorporate factor analysis for reducing variables to clearly and meaningfully understand clusters. Interests and applications in data mining are increasing in many businesses. However, this technology is seldom applied to healthcare customer experience management. The paper shows that efficient and effective application of data mining methods can aid the understanding of patient healthcare preferences.

Explicit symplectic algorithms based on generating functions for relativistic charged particle dynamics in time-dependent electromagnetic field

NASA Astrophysics Data System (ADS)

Zhang, Ruili; Wang, Yulei; He, Yang; Xiao, Jianyuan; Liu, Jian; Qin, Hong; Tang, Yifa

2018-02-01

Relativistic dynamics of a charged particle in time-dependent electromagnetic fields has theoretical significance and a wide range of applications. The numerical simulation of relativistic dynamics is often multi-scale and requires accurate long-term numerical simulations. Therefore, explicit symplectic algorithms are much more preferable than non-symplectic methods and implicit symplectic algorithms. In this paper, we employ the proper time and express the Hamiltonian as the sum of exactly solvable terms and product-separable terms in space-time coordinates. Then, we give the explicit symplectic algorithms based on the generating functions of orders 2 and 3 for relativistic dynamics of a charged particle. The methodology is not new, which has been applied to non-relativistic dynamics of charged particles, but the algorithm for relativistic dynamics has much significance in practical simulations, such as the secular simulation of runaway electrons in tokamaks.

Adaptation of a Hyperspectral Atmospheric Correction Algorithm for Multi-spectral Ocean Color Data in Coastal Waters. Chapter 3

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Montes, Marcos J.; Davis, Curtiss O.

2003-01-01

This SIMBIOS contract supports several activities over its three-year time-span. These include certain computational aspects of atmospheric correction, including the modification of our hyperspectral atmospheric correction algorithm Tafkaa for various multi-spectral instruments, such as SeaWiFS, MODIS, and GLI. Additionally, since absorbing aerosols are becoming common in many coastal areas, we are making the model calculations to incorporate various absorbing aerosol models into tables used by our Tafkaa atmospheric correction algorithm. Finally, we have developed the algorithms to use MODIS data to characterize thin cirrus effects on aerosol retrieval.

Preferences for prenatal testing among pregnant women, partners and health professionals.

PubMed

Lund, Ida Charlotte Bay; Becher, Naja; Petersen, Olav Bjørn; Hill, Melissa; Chitty, Lyn; Vogel, Ida

2018-05-01

Cell-free DNA testing (cfDNA testing) in maternal plasma has recently been implemented in Danish healthcare. Prior to that we wanted to evaluate the preferences among pregnant women, partners and health professionals regarding cfDNA testing compared with invasive prenatal diagnostics. Responders were recruited at public hospitals in the Central and North Denmark Regions. Stated preferences for prenatal testing were obtained through an online questionnaire incorporating a discrete choice experiment. Test choices differed according to attributes such as risk of miscarriage (none or small) and genetic information provided by the test; simple (Down syndrome only) or comprehensive (chromosomal abnormalities beyond Down syndrome). No risk of miscarriage was the key attribute affecting the preferences of women (n = 315) and partners (n = 102). However, women with experiences of invasive testing placed more emphasis on comprehensive genetic information and less on risk of miscarriage compared with other women. Likewise, foetal medicine experts, obstetricians and sonographers (n = 57) had a greater preference for comprehensive genetic information than midwives who were not directly involved in counselling for prenatal testing (n = 48). As safety seems to affect the majority of pregnant couples' choice behaviour, thorough pre-test counselling by trained health professionals is of paramount importance. Aarhus University and The Foundation of 17-12-1981. This study was registered with the Danish Data Protection Agency (1-16-02-586-13/ 2007-58-0010). Articles published in the DMJ are “open access”. This means that the articles are distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits any non-commercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis.

PubMed

Bousquet, Jean; Schünemann, Holger J; Hellings, Peter W; Arnavielhe, Sylvie; Bachert, Claus; Bedbrook, Anna; Bergmann, Karl-Christian; Bosnic-Anticevich, Sinthia; Brozek, Jan; Calderon, Moises; Canonica, G Walter; Casale, Thomas B; Chavannes, Niels H; Cox, Linda; Chrystyn, Henry; Cruz, Alvaro A; Dahl, Ronald; De Carlo, Giuseppe; Demoly, Pascal; Devillier, Phillipe; Dray, Gérard; Fletcher, Monica; Fokkens, Wytske J; Fonseca, Joao; Gonzalez-Diaz, Sandra N; Grouse, Lawrence; Keil, Thomas; Kuna, Piotr; Larenas-Linnemann, Désirée; Lodrup Carlsen, Karin C; Meltzer, Eli O; Mullol, Jaoquim; Muraro, Antonella; Naclerio, Robert N; Palkonen, Susanna; Papadopoulos, Nikolaos G; Passalacqua, Giovanni; Price, David; Ryan, Dermot; Samolinski, Boleslaw; Scadding, Glenis K; Sheikh, Aziz; Spertini, François; Valiulis, Arunas; Valovirta, Erkka; Walker, Samantha; Wickman, Magnus; Yorgancioglu, Arzu; Haahtela, Tari; Zuberbier, Torsten

2016-08-01

The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Work and retirement preferences of practicing radiologists as a predictor of workforce needs.

PubMed

Moriarity, Andrew K; Brown, Manuel L; Schultz, Lonni R

2014-08-01

The radiology job market has been described as highly variable, and recent practice hiring surveys predict that the number of available jobs will remain flat. Radiologists may be working more hours and retiring later than desired, activities that influence overall job availability. A national survey was performed to determine the desired work rate and retirement preferences of practicing radiologists, and the responses are used to estimate current and potential future work output and future workforce needs. Practicing radiologists were surveyed regarding current and preferred work level and desired and expected retirement age. A model incorporating these preferences and stratified by age was developed using survey responses and American Medical Association full-time equivalent (FTE) estimates. Available FTE radiologists are estimated under four scenarios from 2016 to 2031 in 5-year intervals. The model predicts a total of 26,362 FTE radiologists available in 2011, which corresponds to previous estimates. Participants reported working more hours and expecting to retire later than desired, with younger radiologists and women reporting the greatest desired decrease in FTE hours worked. Under each scenario, there is an initial FTE availability in 2016 ranging from 21,156 to 24,537, which increases to between 27,753 and 31,435 FTE by 2031 depending on work rate and retirement patterns. Practicing radiologists report that they currently work more hours than desired and expect to retire later than they would prefer. If radiologists changed current personal work rate and expected retirement age to meet these preferences, there would be an immediate shortage of FTE radiologists continuing until at least 2020 assuming no other workforce needs changes. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing

PubMed Central

Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

2017-01-01

Remote sensing technologies have been widely applied in urban environments’ monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the “salt and pepper” phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive. PMID:28604641

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

PubMed

Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

2017-06-12

Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

Heightened sour preferences during childhood.

PubMed

Liem, Djin Gie; Mennella, Julie A

2003-02-01

Basic research has revealed that the chemical sensory world of children is different from that of adults, as evidenced by their heightened preferences for sweet and salty tastes. However, little is known about the ontogeny of sour taste preferences, despite the growing market of extreme sour candies. The present study investigated whether the level of sourness most preferred in a food matrix and the ability to discriminate differences in sour intensity differed between 5- to 9-year-old children and their mothers, by using a rank-by-elimination procedure embedded in the context of a game. Mothers also completed a variety of questionnaires and children were asked several questions to assess whether children's temperament and food preferences and habits related to sour preferences. The results indicated that, although every mother and all but two of the children (92%) were able to rank the gelatins from most to least sour, more than one-third (35%) of the children, but virtually none of the adults, preferred the high levels of sour taste (0.25 M citric acid) in gelatin. Those children who preferred the extreme sour tastes were significantly less food neophobic (P < 0.05) and tended to experience a greater variety of fruits when compared with the remaining children (P = 0.11). Moreover, the children's preference for sour tastes generalized to other foods, such as candies and lemons, as reported by both children and mothers. These findings are the first experimental evidence to demonstrate that sour taste preferences are heightened during childhood and that such preferences are related to children's food habits and preferences. Further research is needed to unfold the relationship between the level of sour taste preferred and the actual consumption of sour-tasting foods and flavors in children.

Heightened Sour Preferences During Childhood

PubMed Central

Liem, Djin Gie; Mennella, Julie A.

2009-01-01

Basic research has revealed that the chemical sensory world of children is different from that of adults, as evidenced by their heightened preferences for sweet and salty tastes. However, little is known about the ontogeny of sour taste preferences, despite the growing market of extreme sour candies. The present study investigated whether the level of sourness most preferred in a food matrix and the ability to discriminate differences in sour intensity differed between 5- to 9-year-old children and their mothers, by using a rank-by-elimination procedure embedded in the context of a game. Mothers also completed a variety of questionnaires and children were asked several questions to assess whether children’s temperament and food preferences and habits related to sour preferences. The results indicated that, although every mother and all but two of the children (92%) were able to rank the gelatins from most to least sour, more than one-third (35%) of the children, but virtually none of the adults, preferred the high levels of sour taste (0.25 M citric acid) in gelatin. Those children who preferred the extreme sour tastes were significantly less food neophobic (P < 0.05) and tended to experience a greater variety of fruits when compared with the remaining children (P = 0.11). Moreover, the children’s preference for sour tastes generalized to other foods, such as candies and lemons, as reported by both children and mothers. These findings are the first experimental evidence to demonstrate that sour taste preferences are heightened during childhood and that such preferences are related to children’s food habits and preferences. Further research is needed to unfold the relationship between the level of sour taste preferred and the actual consumption of sour-tasting foods and flavors in children. PMID:12588738

Characterization of active paper packaging incorporated with ginger pulp oleoresin

NASA Astrophysics Data System (ADS)

Wiastuti, T.; Khasanah, L. U.; Atmaka Kawiji, W.; Manuhara, G. J.; Utami, R.

2016-02-01

Utilization of ginger pulp waste from herbal medicine and instant drinks industry in Indonesia currently used for fertilizer and fuel, whereas the ginger pulp still contains high oleoresin. Active paper packaging were developed incorporated with ginger pulp oleoresin (0%, 2%, 4%, and 6% w/w). Physical (thickness, tensile strength, and folding endurance, moisture content), sensory characteristics and antimicrobial activity of the active paper were evaluated. Selected active paper then were chemically characterized (functional groups). The additional of ginger pulp oleoresin levels are reduced tensile strength, folding endurance and sensory characteristic (color, texture and overall) and increased antimicrobial activity. Due to physical, sensory characteristic and antimicrobial activity, active paper with 2% ginger pulp oleoresin incorporation was selected. Characteristics of selected paper were 9.93% of water content; 0.81 mm of thickness; 0.54 N / mm of tensile strength; 0.30 of folding endurance; 8.43 mm inhibits the growth of Pseudomonas fluorescence and 27.86 mm inhibits the growth of Aspergillus niger (antimicrobial activity) and neutral preference response for sensory properties. For chemical characteristic, selected paper had OH functional group of ginger in 3422.83 cm-1 of wave number and indicated contain red ginger active compounds.

Great apes prefer cooked food.

PubMed

Wobber, Victoria; Hare, Brian; Wrangham, Richard

2008-08-01

The cooking hypothesis proposes that a diet of cooked food was responsible for diverse morphological and behavioral changes in human evolution. However, it does not predict whether a preference for cooked food evolved before or after the control of fire. This question is important because the greater the preference shown by a raw-food-eating hominid for the properties present in cooked food, the more easily cooking should have been adopted following the control of fire. Here we use great apes to model food preferences by Paleolithic hominids. We conducted preference tests with various plant and animal foods to determine whether great apes prefer food items raw or cooked. We found that several populations of captive apes tended to prefer their food cooked, though with important exceptions. These results suggest that Paleolithic hominids would likewise have spontaneously preferred cooked food to raw, exapting a pre-existing preference for high-quality, easily chewed foods onto these cooked items. The results, therefore, challenge the hypothesis that the control of fire preceded cooking by a significant period.

An innovative artificial bee colony algorithm and its application to a practical intercell scheduling problem

NASA Astrophysics Data System (ADS)

Li, Dongni; Guo, Rongtao; Zhan, Rongxin; Yin, Yong

2018-06-01

In this article, an innovative artificial bee colony (IABC) algorithm is proposed, which incorporates two mechanisms. On the one hand, to provide the evolutionary process with a higher starting level, genetic programming (GP) is used to generate heuristic rules by exploiting the elements that constitute the problem. On the other hand, to achieve a better balance between exploration and exploitation, a leading mechanism is proposed to attract individuals towards a promising region. To evaluate the performance of IABC in solving practical and complex problems, it is applied to the intercell scheduling problem with limited transportation capacity. It is observed that the GP-generated rules incorporate the elements of the most competing human-designed rules, and they are more effective than the human-designed ones. Regarding the leading mechanism, the strategies of the ageing leader and multiple challengers make the algorithm less likely to be trapped in local optima.

Runway Operations Planning: A Two-Stage Heuristic Algorithm

NASA Technical Reports Server (NTRS)

Anagnostakis, Ioannis; Clarke, John-Paul

2003-01-01

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, can also be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. This paper introduces a two stage heuristic algorithm for solving the Runway Operations Planning (ROP) problem. In the first stage, sequences of departure class slots and runway crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program with a Branch & Bound algorithm implementation. Preliminary results from this implementation of the two-stage algorithm on real-world traffic data are presented.

Fast Adapting Ensemble: A New Algorithm for Mining Data Streams with Concept Drift

PubMed Central

Ortíz Díaz, Agustín; Ramos-Jiménez, Gonzalo; Frías Blanco, Isvani; Caballero Mota, Yailé; Morales-Bueno, Rafael

2015-01-01

The treatment of large data streams in the presence of concept drifts is one of the main challenges in the field of data mining, particularly when the algorithms have to deal with concepts that disappear and then reappear. This paper presents a new algorithm, called Fast Adapting Ensemble (FAE), which adapts very quickly to both abrupt and gradual concept drifts, and has been specifically designed to deal with recurring concepts. FAE processes the learning examples in blocks of the same size, but it does not have to wait for the batch to be complete in order to adapt its base classification mechanism. FAE incorporates a drift detector to improve the handling of abrupt concept drifts and stores a set of inactive classifiers that represent old concepts, which are activated very quickly when these concepts reappear. We compare our new algorithm with various well-known learning algorithms, taking into account, common benchmark datasets. The experiments show promising results from the proposed algorithm (regarding accuracy and runtime), handling different types of concept drifts. PMID:25879051

Time discounting and time preference in animals: A critical review.

PubMed

Hayden, Benjamin Y

2016-02-01

Animals are an important model for studies of impulsivity and self-control. Many studies have made use of the intertemporal choice task, which pits small rewards available sooner against larger rewards available later (typically several seconds), repeated over many trials. Preference for the sooner reward is often taken to indicate impulsivity and/or a failure of self-control. This review shows that very little evidence supports this assumption; on the contrary, ostensible discounting behavior may reflect a boundedly rational but not necessarily impulsive reward-maximizing strategy. Specifically, animals may discount weakly, or even adopt a long-term rate-maximizing strategy, but fail to fully incorporate postreward delays into their choices. This failure may reflect learning biases. Consequently, tasks that measure animal discounting may greatly overestimate the true discounting and may be confounded by processes unrelated to time preferences. If so, animals may be much more patient than is widely believed; human and animal intertemporal choices may reflect unrelated mental operations; and the shared hyperbolic shape of the human and animal discount curves, which is used to justify cross-species comparisons, may be coincidental. The discussion concludes with a consideration of alternative ways to measure self-control in animals.

Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

PubMed

Moore, J H

1995-06-01

A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

An on-line modified least-mean-square algorithm for training neurofuzzy controllers.

PubMed

Tan, Woei Wan

2007-04-01

The problem hindering the use of data-driven modelling methods for training controllers on-line is the lack of control over the amount by which the plant is excited. As the operating schedule determines the information available on-line, the knowledge of the process may degrade if the setpoint remains constant for an extended period. This paper proposes an identification algorithm that alleviates "learning interference" by incorporating fuzzy theory into the normalized least-mean-square update rule. The ability of the proposed methodology to achieve faster learning is examined by employing the algorithm to train a neurofuzzy feedforward controller for controlling a liquid level process. Since the proposed identification strategy has similarities with the normalized least-mean-square update rule and the recursive least-square estimator, the on-line learning rates of these algorithms are also compared.

Factors Influencing Radiology Residents' Fellowship Training and Practice Preferences in Canada.

PubMed

Mok, Philip S; Probyn, Linda; Finlay, Karen

2016-05-01

The study aimed to examine the postresidency plans of Canadian radiology residents and factors influencing their fellowship choices and practice preferences, including interest in teaching and research. Institutional ethics approval was obtained at McMaster University. Electronic surveys were sent to second to fifth-year residents at all 16 radiology residency programs across Canada. Each survey assessed factors influencing fellowship choices and practice preferences. A total of 103 (31%) Canadian radiology residents responded to the online survey. Over 89% from English-speaking programs intended to pursue fellowship training compared to 55% of residents from French-speaking programs. The most important factors influencing residents' decision to pursue fellowship training were enhanced employability (46%) and personal interest (47%). Top fellowship choices were musculoskeletal imaging (19%), body imaging (17%), vascular or interventional (14%), neuroradiology (8%), and women's imaging (7%). Respondents received the majority of their fellowship information from peers (68%), staff radiologists (61%), and university websites (58%). Approximately 59% planned on practicing at academic institutions and stated that lifestyle (43%), job prospects (29%), and teaching opportunities (27%) were the most important factors influencing their decisions. A total of 89% were interested in teaching but only 46% were interested in incorporating research into their future practice. The majority of radiology residents plan on pursuing fellowship training and often receive their fellowship information from informal sources such as peers and staff radiologists. Fellowship directors can incorporate recruitment strategies such as mentorship programs and improving program websites. There is a need to increase resident participation in research to advance the future of radiology. Copyright © 2016 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

An adaptive DPCM algorithm for predicting contours in NTSC composite video signals

NASA Astrophysics Data System (ADS)

Cox, N. R.

An adaptive DPCM algorithm is proposed for encoding digitized National Television Systems Committee (NTSC) color video signals. This algorithm essentially predicts picture contours in the composite signal without resorting to component separation. The contour parameters (slope thresholds) are optimized using four 'typical' television frames that have been sampled at three times the color subcarrier frequency. Three variations of the basic predictor are simulated and compared quantitatively with three non-adaptive predictors of similar complexity. By incorporating a dual-word-length coder and buffer memory, high quality color pictures can be encoded at 4.0 bits/pel or 42.95 Mbit/s. The effect of channel error propagation is also investigated.

Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making

PubMed Central

Sun, Clement S.; Cantor, Scott B.; Reece, Gregory P.; Crosby, Melissa A.; Fingeret, Michelle C.

2014-01-01

Background: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. Methods: In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings. Results: The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes. Conclusions: We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study. PMID:25105083

An Algorithm to Automate Yeast Segmentation and Tracking

PubMed Central

Doncic, Andreas; Eser, Umut; Atay, Oguzhan; Skotheim, Jan M.

2013-01-01

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation. PMID:23520484

XtalOpt  version r9: An open-source evolutionary algorithm for crystal structure prediction

DOE PAGES

Falls, Zackary; Lonie, David C.; Avery, Patrick; ...

2015-10-23

This is a new version of XtalOpt, an evolutionary algorithm for crystal structure prediction available for download from the CPC library or the XtalOpt website, http://xtalopt.github.io. XtalOpt is published under the Gnu Public License (GPL), which is an open source license that is recognized by the Open Source Initiative. We have detailed the new version incorporates many bug-fixes and new features here and predict the crystal structure of a system from its stoichiometry alone, using evolutionary algorithms.

Load flow and state estimation algorithms for three-phase unbalanced power distribution systems

NASA Astrophysics Data System (ADS)

Madvesh, Chiranjeevi

Distribution load flow and state estimation are two important functions in distribution energy management systems (DEMS) and advanced distribution automation (ADA) systems. Distribution load flow analysis is a tool which helps to analyze the status of a power distribution system under steady-state operating conditions. In this research, an effective and comprehensive load flow algorithm is developed to extensively incorporate the distribution system components. Distribution system state estimation is a mathematical procedure which aims to estimate the operating states of a power distribution system by utilizing the information collected from available measurement devices in real-time. An efficient and computationally effective state estimation algorithm adapting the weighted-least-squares (WLS) method has been developed in this research. Both the developed algorithms are tested on different IEEE test-feeders and the results obtained are justified.

Color preference in red-green dichromats.

PubMed

Álvaro, Leticia; Moreira, Humberto; Lillo, Julio; Franklin, Anna

2015-07-28

Around 2% of males have red-green dichromacy, which is a genetic disorder of color vision where one type of cone photoreceptor is missing. Here we investigate the color preferences of dichromats. We aim (i) to establish whether the systematic and reliable color preferences of normal trichromatic observers (e.g., preference maximum at blue, minimum at yellow-green) are affected by dichromacy and (ii) to test theories of color preference with a dichromatic sample. Dichromat and normal trichromat observers named and rated how much they liked saturated, light, dark, and focal colors twice. Trichromats had the expected pattern of preference. Dichromats had a reliable pattern of preference that was different to trichromats, with a preference maximum rather than minimum at yellow and a much weaker preference for blue than trichromats. Color preference was more affected in observers who lacked the cone type sensitive to long wavelengths (protanopes) than in those who lacked the cone type sensitive to medium wavelengths (deuteranopes). Trichromats' preferences were summarized effectively in terms of cone-contrast between color and background, and yellow-blue cone-contrast could account for dichromats' pattern of preference, with some evidence for residual red-green activity in deuteranopes' preference. Dichromats' color naming also could account for their color preferences, with colors named more accurately and quickly being more preferred. This relationship between color naming and preference also was present for trichromat males but not females. Overall, the findings provide novel evidence on how dichromats experience color, advance the understanding of why humans like some colors more than others, and have implications for general theories of aesthetics.

Color preference in red–green dichromats

PubMed Central

Álvaro, Leticia; Moreira, Humberto; Lillo, Julio; Franklin, Anna

2015-01-01

Around 2% of males have red–green dichromacy, which is a genetic disorder of color vision where one type of cone photoreceptor is missing. Here we investigate the color preferences of dichromats. We aim (i) to establish whether the systematic and reliable color preferences of normal trichromatic observers (e.g., preference maximum at blue, minimum at yellow-green) are affected by dichromacy and (ii) to test theories of color preference with a dichromatic sample. Dichromat and normal trichromat observers named and rated how much they liked saturated, light, dark, and focal colors twice. Trichromats had the expected pattern of preference. Dichromats had a reliable pattern of preference that was different to trichromats, with a preference maximum rather than minimum at yellow and a much weaker preference for blue than trichromats. Color preference was more affected in observers who lacked the cone type sensitive to long wavelengths (protanopes) than in those who lacked the cone type sensitive to medium wavelengths (deuteranopes). Trichromats’ preferences were summarized effectively in terms of cone-contrast between color and background, and yellow-blue cone-contrast could account for dichromats’ pattern of preference, with some evidence for residual red–green activity in deuteranopes’ preference. Dichromats’ color naming also could account for their color preferences, with colors named more accurately and quickly being more preferred. This relationship between color naming and preference also was present for trichromat males but not females. Overall, the findings provide novel evidence on how dichromats experience color, advance the understanding of why humans like some colors more than others, and have implications for general theories of aesthetics. PMID:26170287

On the inclusion of mass source terms in a single-relaxation-time lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Aursjø, Olav; Jettestuen, Espen; Vinningland, Jan Ludvig; Hiorth, Aksel

2018-05-01

We present a lattice Boltzmann algorithm for incorporating a mass source in a fluid flow system. The proposed mass source/sink term, included in the lattice Boltzmann equation, maintains the Galilean invariance and the accuracy of the overall method, while introducing a mass source/sink term in the fluid dynamical equations. The method can, for instance, be used to inject or withdraw fluid from any preferred lattice node in a system. This suggests that injection and withdrawal of fluid does not have to be introduced through cumbersome, and sometimes less accurate, boundary conditions. The method also suggests that, through a chosen equation of state relating mass density to pressure, the proposed mass source term will render it possible to set a preferred pressure at any lattice node in a system. We demonstrate how this model handles injection and withdrawal of a fluid. And we show how it can be used to incorporate pressure boundaries. The accuracy of the algorithm is identified through a Chapman-Enskog expansion of the model and supported by the numerical simulations.

Ab initio modeling of point defects, self-diffusion, and incorporation of impurities in thorium

NASA Astrophysics Data System (ADS)

Daroca, D. Pérez

2017-02-01

Research on Generation-IV nuclear reactors has boosted the investigation of thorium as nuclear fuel. By means of first-principles calculations within the framework of density functional theory, structural properties and phonon dispersion curves of Th are obtained. These results agreed very well with previous ones. The stability and formation energies of vacancies, interstitial and divacancies are studied. It is found that vacancies are the energetically preferred defects. The incorporation energies of He, Xe, and Kr atoms in Th defects are analyzed. Self-diffusion, migration paths and activation energies are also calculated.

Covalent Incorporation of Selenium into Oligonucleotides for X-ray Crystal Structure Determination via MAD: Proof of Principle

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

Teplova, M.; Wilds, C.J.; Wawrzak, Z.

2010-03-08

Selenium was incorporated into an oligodeoxynucleotide in the form of 2'-methylseleno-uridine (U{sub Se}). The X-ray crystal structure of the duplex d(GCGTA)U{sub Se}d(ACGC){sub 2} was determined by the multiwavelength anomalous dispersion (MAD) technique and refined to a resolution of 1.3 {angstrom}, demonstrating that selenium can selectively substitute oxygen in DNA and that the resulting compounds are chemically stable. Since derivatization at the 2'-{alpha}-position with selenium does not affect the preference of the sugar for the C3'-endo conformation, this strategy is suitable for incorporating selenium into RNA. The availability of selenium-containing nucleic acids for crystallographic phasing offers an attractive alternative to themore » commonly used halogenated pyrimidines.« less

Tears or Fears? Comparing Gender Stereotypes about Movie Preferences to Actual Preferences.

PubMed

Wühr, Peter; Lange, Benjamin P; Schwarz, Sascha

2017-01-01

This study investigated the accuracy of gender-specific stereotypes about movie-genre preferences for 17 genres. In Study 1, female and male participants rated the extent to which 17 movie genres are preferred by women or men. In Study 2, another sample of female and male participants rated their own preference for each genre. There were three notable results. First, Study 1 revealed the existence of gender stereotypes for the majority of genres (i.e., for 15 of 17 genres). Second, Study 2 revealed the existence of actual gender differences in preferences for the majority of genres (i.e., for 11 of 17 genres). Third, in order to assess the accuracy of gender stereotypes on movie preferences, we compared the results of both studies and found that the majority of gender stereotypes were accurate in direction, but inaccurate in size. In particular, the stereotypes overestimated actual gender differences for the majority of movie genres (i.e., 10 of 17). Practical and theoretical implications of these findings are discussed.

Tears or Fears? Comparing Gender Stereotypes about Movie Preferences to Actual Preferences

PubMed Central

Wühr, Peter; Lange, Benjamin P.; Schwarz, Sascha

2017-01-01

This study investigated the accuracy of gender-specific stereotypes about movie-genre preferences for 17 genres. In Study 1, female and male participants rated the extent to which 17 movie genres are preferred by women or men. In Study 2, another sample of female and male participants rated their own preference for each genre. There were three notable results. First, Study 1 revealed the existence of gender stereotypes for the majority of genres (i.e., for 15 of 17 genres). Second, Study 2 revealed the existence of actual gender differences in preferences for the majority of genres (i.e., for 11 of 17 genres). Third, in order to assess the accuracy of gender stereotypes on movie preferences, we compared the results of both studies and found that the majority of gender stereotypes were accurate in direction, but inaccurate in size. In particular, the stereotypes overestimated actual gender differences for the majority of movie genres (i.e., 10 of 17). Practical and theoretical implications of these findings are discussed. PMID:28392774

On the suitability of different representations of solid catalysts for combinatorial library design by genetic algorithms.

PubMed

Gobin, Oliver C; Schüth, Ferdi

2008-01-01

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Beverage intake preference and bowel preparation laxative taste preference for colonoscopy

PubMed Central

Laiyemo, Adeyinka O; Burnside, Clinton; Laiyemo, Maryam A; Kwagyan, John; Williams, Carla D; Idowu, Kolapo A; Ashktorab, Hassan; Kibreab, Angesom; Scott, Victor F; Sanderson, Andrew K

2015-01-01

AIM: To examine whether non-alcoholic beverage intake preferences can guide polyethylene glycol (PEG)-based bowel laxative preparation selection for patients. METHODS: We conducted eight public taste test sessions using commercially procured (A) unflavored PEG, (B) citrus flavored PEG and (C) PEG with ascorbate (Moviprep). We collected characteristics of volunteers including their beverage intake preferences. The volunteers tasted the laxatives in randomly assigned orders and ranked the laxatives as 1st, 2nd, and 3rd based on their taste preferences. Our primary outcome is the number of 1st place rankings for each preparation. RESULTS: A total of 777 volunteers completed the study. Unflavored PEG was ranked as 1st by 70 (9.0%), flavored PEG by 534 (68.7%) and PEG with ascorbate by 173 (22.3%) volunteers. Demographic, lifestyle characteristics and beverage intake patterns for coffee, tea, and carbonated drinks did not predict PEG-based laxative preference. CONCLUSION: Beverage intake pattern was not a useful guide for PEG-based laxative preference. It is important to develop more tolerable and affordable bowel preparation laxatives for colonoscopy. Also, patients should taste their PEG solution with and without flavoring before flavoring the entire gallon as this may give them more opportunity to pick a pattern that may be more tolerable. PMID:26261736

Beverage intake preference and bowel preparation laxative taste preference for colonoscopy.

PubMed

Laiyemo, Adeyinka O; Burnside, Clinton; Laiyemo, Maryam A; Kwagyan, John; Williams, Carla D; Idowu, Kolapo A; Ashktorab, Hassan; Kibreab, Angesom; Scott, Victor F; Sanderson, Andrew K

2015-08-06

To examine whether non-alcoholic beverage intake preferences can guide polyethylene glycol (PEG)-based bowel laxative preparation selection for patients. We conducted eight public taste test sessions using commercially procured (A) unflavored PEG, (B) citrus flavored PEG and (C) PEG with ascorbate (Moviprep). We collected characteristics of volunteers including their beverage intake preferences. The volunteers tasted the laxatives in randomly assigned orders and ranked the laxatives as 1(st), 2(nd), and 3(rd) based on their taste preferences. Our primary outcome is the number of 1(st) place rankings for each preparation. A total of 777 volunteers completed the study. Unflavored PEG was ranked as 1(st) by 70 (9.0%), flavored PEG by 534 (68.7%) and PEG with ascorbate by 173 (22.3%) volunteers. Demographic, lifestyle characteristics and beverage intake patterns for coffee, tea, and carbonated drinks did not predict PEG-based laxative preference. Beverage intake pattern was not a useful guide for PEG-based laxative preference. It is important to develop more tolerable and affordable bowel preparation laxatives for colonoscopy. Also, patients should taste their PEG solution with and without flavoring before flavoring the entire gallon as this may give them more opportunity to pick a pattern that may be more tolerable.

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

Observational study to calculate addictive risk to opioids: a validation study of a predictive algorithm to evaluate opioid use disorder.

PubMed

Brenton, Ashley; Richeimer, Steven; Sharma, Maneesh; Lee, Chee; Kantorovich, Svetlana; Blanchard, John; Meshkin, Brian

2017-01-01

Opioid abuse in chronic pain patients is a major public health issue, with rapidly increasing addiction rates and deaths from unintentional overdose more than quadrupling since 1999. This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated single-nucleotide polymorphisms (SNPs). The Proove Opioid Risk (POR) algorithm determines the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated SNPs. In a validation study with 258 subjects with diagnosed opioid use disorder (OUD) and 650 controls who reported using opioids, the POR successfully categorized patients at high and moderate risks of opioid misuse or abuse with 95.7% sensitivity. Regardless of changes in the prevalence of opioid misuse or abuse, the sensitivity of POR remained >95%. The POR correctly stratifies patients into low-, moderate-, and high-risk categories to appropriately identify patients at need for additional guidance, monitoring, or treatment changes.

A general tool for the evaluation of spiral CT interpolation algorithms: revisiting the effect of pitch in multislice CT.

PubMed

Bricault, Ivan; Ferretti, Gilbert

2005-01-01

While multislice spiral computed tomography (CT) scanners are provided by all major manufacturers, their specific interpolation algorithms have been rarely evaluated. Because the results published so far relate to distinct particular cases and differ significantly, there are contradictory recommendations about the choice of pitch in clinical practice. In this paper, we present a new tool for the evaluation of multislice spiral CT z-interpolation algorithms, and apply it to the four-slice case. Our software is based on the computation of a "Weighted Radiation Profile" (WRP), and compares WRP to an expected ideal profile in terms of widening and heterogeneity. It provides a unique scheme for analyzing a large variety of spiral CT acquisition procedures. Freely chosen parameters include: number of detector rows, detector collimation, nominal slice width, helical pitch, and interpolation algorithm with any filter shape and width. Moreover, it is possible to study any longitudinal and off-isocenter positions. Theoretical and experimental results show that WRP, more than Slice Sensitivity Profile (SSP), provides a comprehensive characterization of interpolation algorithms. WRP analysis demonstrates that commonly "preferred helical pitches" are actually nonoptimal regarding the formerly distinguished z-sampling gap reduction criterion. It is also shown that "narrow filter" interpolation algorithms do not enable a general preferred pitch discussion, since they present poor properties with large longitudinal and off-center variations. In the more stable case of "wide filter" interpolation algorithms, SSP width or WRP widening are shown to be almost constant. Therefore, optimal properties should no longer be sought in terms of these criteria. On the contrary, WRP heterogeneity is related to variable artifact phenomena and can pertinently characterize optimal pitches. In particular, the exemplary interpolation properties of pitch = 1 "wide filter" mode are demonstrated.

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

2007-01-01

Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.

Static vs. dynamic decoding algorithms in a non-invasive body-machine interface

PubMed Central

Seáñez-González, Ismael; Pierella, Camilla; Farshchiansadegh, Ali; Thorp, Elias B.; Abdollahi, Farnaz; Pedersen, Jessica; Mussa-Ivaldi, Ferdinando A.

2017-01-01

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a high-dimensional body-signal vector into a lower dimensional control vector on 6 subjects with high-level SCI and 8 controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter. SCI and control participants performed straighter and smoother cursor movements with the Kalman algorithm during center-out reaching, but their movements were faster and more precise when using PCA. All participants were able to use the BMI’s continuous, two-dimensional control to type on a virtual keyboard and play pong, and performance with both algorithms was comparable. However, seven of eight control participants preferred PCA as their method of virtual wheelchair control. The unsupervised PCA algorithm was easier to train and seemed sufficient to achieve a higher degree of learnability and perceived ease of use. PMID:28092564

Prefer feeling bad? Subcultural differences in emotional preferences between Han Chinese and Mongolian Chinese.

PubMed

Deng, Xinmei; Cheng, Chen; Chow, Hiu Mei; Ding, Xuechen

2018-03-01

As a multi-ethnic country that is comprised of diverse cultural systems, there has been little research on the subcultural differences in emotional preferences in China. Also, little attention has been paid to examine how explicit and implicit attitudes towards emotions influence emotional preferences interactively. In this study, we manipulated explicit attitudes towards emotions among Han (N = 62) and Mongolian Chinese individuals (N = 70). We assessed participants' implicit attitudes towards emotions to explore their contributions to emotional preferences. (a) Han Chinese had lower preferences for pleasant emotions than Mongolian Chinese after inducing contra-hedonic attitudes towards emotions, and (b) after priming contra-hedonic attitudes towards emotions, the more Han Chinese participants evaluated pleasant emotions as negative implicitly, the less they preferred to engage in pleasant emotional activities. These findings contribute to the growing literature of subcultural differences and demonstrate that explicit and implicit attitudes towards emotions interactively influence individuals' emotional preferences between different subculture groups. © 2018 International Union of Psychological Science.

Use of preferred music to decrease agitated behaviours in older people with dementia: a review of the literature.

PubMed

Sung, Huei-Chuan; Chang, Anne M

2005-10-01

This paper reviews study findings of preferred music on agitated behaviours for older people with dementia and provides implications for future research and practice. Music has been suggested as a feasible and less costly intervention to manage agitated behaviours in older people with dementia. However, no review of the literature focusing on study findings of preferred music on agitated behaviours in older people with dementia had been reported. A review was undertaken using electronic databases with specified search terms for the period of 1993-2005. The references listed in the publications selected were also searched for additional studies. Eight research-based articles met the inclusion criteria and were included in the review. The preferred music intervention demonstrated positive outcomes in reducing the occurrence of some types of agitated behaviours in older people with dementia. The findings from these studies were relatively consistent in finding improvement in agitated behaviours although the findings in one study did not reach statistical significance. The small sample sizes and some variations in the application of the preferred music intervention mean that caution is needed in drawing conclusions from these studies. This review highlights that preferred music has positive effects on decreasing agitated behaviours in older people with dementia; however, the methodological limitations indicate the need for further research. Findings from the review highlight the beneficial outcomes of preferred music in reducing agitated behaviours for older people with dementia. The incorporation of preferred music has the potential to provide a therapeutic approach to the care of older people with dementia.

Cloud detection algorithm comparison and validation for operational Landsat data products

USGS Publications Warehouse

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

nonthermal-based algorithm. We give preference to CFMask for operational cloud and cloud shadow detection, as it is derived from a priori knowledge of physical phenomena and is operable without geographic restriction, making it useful for current and future land imaging missions without having to be retrained in a machine-learning environment.

Do Italian women prefer cesarean section? Results from a survey on mode of delivery preferences

PubMed Central

2013-01-01

Background About 20 million cesareans occur each year in the world and rates have steadily increased in almost all middle- and high-income countries over the last decades. Maternal request is often argued as one of the key forces driving this increase. Italy has the highest cesarean rate of Europe, yet there are no national surveys on the views of Italian women about their preferences on route of delivery. This study aimed to assess Italian women´s preference for mode of delivery, as well as reasons and factors associated with this preference, in a nationally representative sample of women. Methods This cross sectional survey was conducted between December 2010-March 2011. An anonymous structured questionnaire asked participants what was their preferred mode of delivery and explored the reasons for this preference by assessing their agreement to a series of statements. Participants were also asked to what extent their preference was influenced by a series of possible sources. The 1st phase of the study was carried out among readers of a popular Italian women´s magazine (Io Donna). In a 2nd phase, the study was complemented by a structured telephone interview. Results A total of 1000 Italian women participated in the survey and 80% declared they would prefer to deliver vaginally if they could opt. The preference for vaginal delivery was significantly higher among older (84.7%), more educated (87.6%), multiparous women (82.3%) and especially among those without any previous cesareans (94.2%). The main reasons for preferring a vaginal delivery were not wanting to be separated from the baby during the first hours of life, a shorter hospital stay and a faster postpartum recovery. The main reasons for preferring a cesarean were fear of pain, convenience to schedule the delivery and because it was perceived as being less traumatic for the baby. The source which most influenced the preference of these Italian women was their obstetrician, followed by friends or relatives

Algorithm for Wavefront Sensing Using an Extended Scene

NASA Technical Reports Server (NTRS)

Sidick, Erkin; Green, Joseph; Ohara, Catherine

2008-01-01

A recently conceived algorithm for processing image data acquired by a Shack-Hartmann (SH) wavefront sensor is not subject to the restriction, previously applicable in SH wavefront sensing, that the image be formed from a distant star or other equivalent of a point light source. That is to say, the image could be of an extended scene. (One still has the option of using a point source.) The algorithm can be implemented in commercially available software on ordinary computers. The steps of the algorithm are the following: 1. Suppose that the image comprises M sub-images. Determine the x,y Cartesian coordinates of the centers of these sub-images and store them in a 2xM matrix. 2. Within each sub-image, choose an NxN-pixel cell centered at the coordinates determined in step 1. For the ith sub-image, let this cell be denoted as si(x,y). Let the cell of another subimage (preferably near the center of the whole extended-scene image) be designated a reference cell, denoted r(x,y). 3. Calculate the fast Fourier transforms of the sub-sub-images in the central NxN portions (where N < N and both are preferably powers of 2) of r(x,y) and si(x,y). 4. Multiply the two transforms to obtain a cross-correlation function Ci(u,v), in the Fourier domain. Then let the phase of Ci(u, v) constitute a phase function, phi(u,v). 5. Fit u and v slopes to phi (u,v) over a small u,v subdomain. 6. Compute the fast Fourier transform, Si(u,v) of the full NxN cell si(x,y). Multiply this transform by the u and phase slopes obtained in step 4. Then compute the inverse fast Fourier transform of the product. 7. Repeat steps 4 through 6 in an iteration loop, cumulating the u and slopes, until a maximum iteration number is reached or the change in image shift becomes smaller than a predetermined tolerance. 8. Repeat steps 4 through 7 for the cells of all other sub-images.

Automated spike sorting algorithm based on Laplacian eigenmaps and k-means clustering.

PubMed

Chah, E; Hok, V; Della-Chiesa, A; Miller, J J H; O'Mara, S M; Reilly, R B

2011-02-01

This study presents a new automatic spike sorting method based on feature extraction by Laplacian eigenmaps combined with k-means clustering. The performance of the proposed method was compared against previously reported algorithms such as principal component analysis (PCA) and amplitude-based feature extraction. Two types of classifier (namely k-means and classification expectation-maximization) were incorporated within the spike sorting algorithms, in order to find a suitable classifier for the feature sets. Simulated data sets and in-vivo tetrode multichannel recordings were employed to assess the performance of the spike sorting algorithms. The results show that the proposed algorithm yields significantly improved performance with mean sorting accuracy of 73% and sorting error of 10% compared to PCA which combined with k-means had a sorting accuracy of 58% and sorting error of 10%.A correction was made to this article on 22 February 2011. The spacing of the title was amended on the abstract page. No changes were made to the article PDF and the print version was unaffected.

Recommendations for incorporating biologicals into management of moderate to severe plaque psoriasis: individualized patient approaches.

PubMed

Langley, Richard G; Ho, Vincent; Lynde, Charles; Papp, Kim A; Poulin, Yves; Shear, Neil; Toole, Jack; Zip, Catherine

2006-01-01

Psoriasis is a T-cell mediated skin disease that affects approximately 2% of the population worldwide. Despite the prevalence of the disease and long-standing efforts to develop strategies to treat it, there is a need for safe and effective therapies to treat psoriasis, particularly the more severe forms. Biological agents such as alefacept, efalizumab, etanercept, and infliximab have been recognized as a class of treatment distinct from other forms of therapy in the treatment algorithm of psoriasis. Recent national and international consensus meetings have developed statements that position biological agents as an important addition to the treatment armamentarium for moderate to severe psoriasis, along with phototherapy and traditional systemic agents. There has been consensus that treatment should be individualized to each patient's needs and circumstances. Biological agents offer the hope of safe, effective, long-term management of moderate to severe psoriasis. As new agents receive approval from Health Canada, the available range of therapeutic options for treating this chronic disease will broaden. A Canadian Psoriasis Expert Panel recently convened in February 2005 to analyze, based on a series of clinical case scenarios, the indications, contraindications, and considerations for and against each of the four biological agents, derived from product labelling, where available, and from the efficacy and safety data from phase 3 and earlier clinical trials, as well as post-marketing reports. The Panel has formulated a set of recommendations for incorporating these biological agents into the current treatment paradigm of moderate to severe plaque psoriasis and has identified the preferred biological agents for each patient based on individual needs and circumstances.

Difference in plantar pressure between the preferred and non‐preferred feet in four soccer‐related movements

PubMed Central

Wong, Pui‐lam; Chamari, Karim; Chaouachi, Anis; De Wei Mao; Wisløff, Ulrik; Hong, Youlian

2007-01-01

Objective and participants The present study measured the difference in plantar pressure between the preferred and non‐preferred foot in four soccer‐related movements in 15 male university soccer players (mean (SD) age 20.9 (1.3) years, mean (SD) height 173 (4) cm and mean (SD) weight 61.7 (3.6) kg). Design To record plantar pressure distribution, players randomly wore three types of soccer shoes (classical 6‐stud and 12‐stud, and specially designed 12‐stud) embedded with an insole pressure recorder device with 99 sensors, divided into 10 areas for analysis. Plantar pressure was recorded in five successful trials in each of the four soccer‐related movements: running (at 3.3 m/s), sideward cutting, 45° cutting and landing from a vertical jump. Results Plantar pressures of the preferred and non‐preferred foot were different in 115 of 120 comparisons. The overall plantar pressure of the preferred foot was higher than that of the non‐preferred foot. Specifically, in each of the four movements, higher pressure was found in the preferred foot during the take‐off phase, whereas this was found in the non‐preferred foot during the landing phase. This would suggest a tendency of the preferred foot for higher motion force and of the non‐preferred foot for a greater role in body stabilisation. Conclusions The data indicate that the preferred and non‐preferred foot should be treated independently with regard to strength/power training to avoid unnecessary injuries. Different shoes/insoles and different muscular strengthening programmes are thus suggested for each of the soccer player's feet. PMID:17138639

Adaptive inversion algorithm for 1 . 5 μm visibility lidar incorporating in situ Angstrom wavelength exponent

NASA Astrophysics Data System (ADS)

Shang, Xiang; Xia, Haiyun; Dou, Xiankang; Shangguan, Mingjia; Li, Manyi; Wang, Chong

2018-07-01

An eye-safe 1 . 5 μm visibility lidar is presented in this work considering in situ particle size distribution, which can be deployed in crowded places like airports. In such a case, the measured extinction coefficient at 1 . 5 μm should be converted to that at 0 . 55 μm for visibility retrieval. Although several models have been established since 1962, the accurate wavelength conversion remains a challenge. An adaptive inversion algorithm for 1 . 5 μm visibility lidar is proposed and demonstrated by using the in situ Angstrom wavelength exponent, which is derived from an aerosol spectrometer. The impact of the particle size distribution of atmospheric aerosols and the Rayleigh backscattering of atmospheric molecules are taken into account. Using the 1 . 5 μm visibility lidar, the visibility with a temporal resolution of 5 min is detected over 48 h in Hefei (31 . 83∘ N, 117 . 25∘ E). The average visibility error between the new method and a visibility sensor (Vaisala, PWD52) is 5.2% with the R-square value of 0.96, while the relative error between another reference visibility lidar at 532 nm and the visibility sensor is 6.7% with the R-square value of 0.91. All results agree with each other well, demonstrating the accuracy and stability of the algorithm.

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.