CTN summary of DSREDS, EDCARS, EDMICS CALS readiness testing. [Computer-aided Acquisition and Logistic Support (CALS) CALS Test Network (CTN), Digital Storage Retrieval Eng. Data System (DSREDS), Eng. Data Computer Assisted Retrieval System (EDCARS), Eng. Data Management Information and Control System (EDMICS)

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

Mitschkowetz, N.; Vickers, D.L.

This report provides a summary of the Computer-aided Acquisition and Logistic Support (CALS) Test Network (CTN) Laboratory Acceptance Test (LAT) and User Application Test (UAT) activities undertaken to evaluate the CALS capabilities being implemented as part of the Department of Defense (DOD) engineering repositories. Although the individual testing activities provided detailed reports for each repository, a synthesis of the results, conclusions, and recommendations is offered to provide a more concise presentation of the issues and the strategies, as viewed from the CTN perspective.

Transport spatial model for the definition of green routes for city logistics centers

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

Pamučar, Dragan, E-mail: dpamucar@gmail.com; Gigović, Ljubomir, E-mail: gigoviclj@gmail.com; Ćirović, Goran, E-mail: cirovic@sezampro.rs

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas.more » The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.« less

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

PubMed

Zhang, Xingyu; Kim, Joyce; Patzer, Rachel E; Pitts, Stephen R; Patzer, Aaron; Schrager, Justin D

2017-10-26

To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements. Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed several predictive models with the outcome being admission to the hospital or transfer vs. discharge home. We included patient characteristics immediately available after the patient has presented to the ED and undergone a triage process. We used this information to construct logistic regression (LR) and multilayer neural network models (MLNN) which included natural language processing (NLP) and principal component analysis from the patient's reason for visit. Ten-fold cross validation was used to test the predictive capacity of each model and receiver operating curves (AUC) were then calculated for each model. Of the 47,200 ED visits from 642 hospitals, 6,335 (13.42%) resulted in hospital admission (or transfer). A total of 48 principal components were extracted by NLP from the reason for visit fields, which explained 75% of the overall variance for hospitalization. In the model including only structured variables, the AUC was 0.824 (95% CI 0.818-0.830) for logistic regression and 0.823 (95% CI 0.817-0.829) for MLNN. Models including only free-text information generated AUC of 0.742 (95% CI 0.731- 0.753) for logistic regression and 0.753 (95% CI 0.742-0.764) for MLNN. When both structured variables and free text variables were included, the AUC reached 0.846 (95% CI 0.839-0.853) for logistic regression and 0.844 (95% CI 0.836-0.852) for MLNN. The predictive accuracy of hospital admission or transfer for patients who presented to ED triage overall was good, and was improved with the inclusion of free text data from a patient's reason for visit regardless of modeling approach. Natural language processing and neural networks that incorporate patient-reported outcome free text may increase predictive accuracy for hospital admission.

Risk assessment of logistics outsourcing based on BP neural network

NASA Astrophysics Data System (ADS)

Liu, Xiaofeng; Tian, Zi-you

The purpose of this article is to evaluate the risk of the enterprises logistics outsourcing. To get this goal, the paper first analysed he main risks existing in the logistics outsourcing, and then set up a risk evaluation index system of the logistics outsourcing; second applied BP neural network into the logistics outsourcing risk evaluation and used MATLAB to the simulation. It proved that the network error is small and has strong practicability. And this method can be used by enterprises to evaluate the risks of logistics outsourcing.

32 CFR 161.5 - Responsibilities.

Code of Federal Regulations, 2014 CFR

2014-07-01

... telephone center support, and telecommunications engineering and network control center assistance. (7) In... Acquisition, Technology, and Logistics (USD(AT&L)), and the DoD Chief Information Officer (DoD CIO) establish..., printer consumables, and electromagnetically opaque sleeves to Defense Manpower Data Center (DMDC). (7...

Effect of Biodiesel on Diesel Engine Nitrogen Oxide and Other Regulated Emissions

DTIC Science & Technology

2006-05-01

DENIX Defense Environmental Network & Information Exchange DLA Defense Logistics Agency DNPH Dinitrophenylhydrazine DoD Department of... Dinitrophenylhydrazine (DNPH) cartridges and analyzed using a high-performance liquid chromatograph with ultraviolet detection, as per an AO/AQIRP method (Reference

Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty.

PubMed

Qiu, Bao-Jian; Zhang, Jiang-Hua; Qi, Yuan-Tao; Liu, Yang

2015-01-01

Natural disasters occur frequently in recent years, causing huge casualties and property losses. Nowadays, people pay more and more attention to the emergency logistics problems. This paper studies the emergency logistics problem with multi-center, multi-commodity, and single-affected-point. Considering that the path near the disaster point may be damaged, the information of the state of the paths is not complete, and the travel time is uncertainty, we establish the nonlinear programming model that objective function is the maximization of time-satisfaction degree. To overcome these drawbacks: the incomplete information and uncertain time, this paper firstly evaluates the multiple roads of transportation network based on grey theory and selects the reliable and optimal path. Then simplify the original model under the scenario that the vehicle only follows the optimal path from the emergency logistics center to the affected point, and use Lingo software to solve it. The numerical experiments are presented to show the feasibility and effectiveness of the proposed method.

Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty

PubMed Central

Qiu, Bao-Jian; Zhang, Jiang-Hua; Qi, Yuan-Tao; Liu, Yang

2015-01-01

Natural disasters occur frequently in recent years, causing huge casualties and property losses. Nowadays, people pay more and more attention to the emergency logistics problems. This paper studies the emergency logistics problem with multi-center, multi-commodity, and single-affected-point. Considering that the path near the disaster point may be damaged, the information of the state of the paths is not complete, and the travel time is uncertainty, we establish the nonlinear programming model that objective function is the maximization of time-satisfaction degree. To overcome these drawbacks: the incomplete information and uncertain time, this paper firstly evaluates the multiple roads of transportation network based on grey theory and selects the reliable and optimal path. Then simplify the original model under the scenario that the vehicle only follows the optimal path from the emergency logistics center to the affected point, and use Lingo software to solve it. The numerical experiments are presented to show the feasibility and effectiveness of the proposed method. PMID:26417946

Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

PubMed Central

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy. PMID:22163641

Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

PubMed

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

Representativeness-based sampling network design for the State of Alaska

Treesearch

Forrest M. Hoffman; Jitendra Kumar; Richard T. Mills; William W. Hargrove

2013-01-01

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection,...

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

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

Zhang, Dezhi; Zhan, Qingwen; Chen, Yuche

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed modelmore » is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.« less

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

DOE PAGES

Zhang, Dezhi; Zhan, Qingwen; Chen, Yuche; ...

2016-03-14

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed modelmore » is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.« less

Association of childhood abuse with homeless women's social networks.

PubMed

Green, Harold D; Tucker, Joan S; Wenzel, Suzanne L; Golinelli, Daniela; Kennedy, David P; Ryan, Gery W; Zhou, Annie J

2012-01-01

Childhood abuse has been linked to negative sequelae for women later in life including drug and alcohol use and violence as victim or perpetrator and may also affect the development of women's social networks. Childhood abuse is prevalent among at-risk populations of women (such as the homeless) and thus may have a stronger impact on their social networks. We conducted a study to: (a) develop a typology of sheltered homeless women's social networks; (b) determine whether childhood abuse was associated with the social networks of sheltered homeless women; and (c) determine whether those associations remained after accounting for past-year substance abuse and recent intimate partner abuse. A probability sample of 428 homeless women from temporary shelter settings in Los Angeles County completed a personal network survey that provided respondent information as well as information about their network members' demographics and level of interaction with each other. Cluster analyses identified groups of women who shared specific social network characteristics. Multinomial logistic regressions revealed variables associated with group membership. We identified three groups of women with differing social network characteristics: low-risk networks, densely connected risky networks (dense, risky), and sparsely connected risky networks (sparse, risky). Multinomial logistic regressions indicated that membership in the sparse, risky network group, when compared to the low-risk group, was associated with history of childhood physical abuse (but not sexual or emotional abuse). Recent drug abuse was associated with membership in both risky network groups; however, the association of childhood physical abuse with sparse, risky network group membership remained. Although these findings support theories proposing that the experience of childhood abuse can shape women's social networks, they suggest that it may be childhood physical abuse that has the most impact among homeless women. The effects of childhood physical abuse should be more actively investigated in clinical settings, especially those frequented by homeless women, particularly with respect to the formation of social networks in social contexts that may expose these women to greater risks. Copyright © 2012. Published by Elsevier Ltd.

Computational Systems Toxicology: recapitulating the logistical dynamics of cellular response networks in virtual tissue models (Eurotox_2017)

EPA Science Inventory

Translating in vitro data and biological information into a predictive model for human toxicity poses a significant challenge. This is especially true for complex adaptive systems such as the embryo where cellular dynamics are precisely orchestrated in space and time. Computer ce...

[Treatment of acute ST Elevation myocardial infarction in a regional network ("Drip & Ship Network Rostock")].

PubMed

Schneider, Henrik; Ince, Hüseyin; Rehders, Tim; Körber, Thomas; Weber, Frank; Kische, Stephan; Chatterjee, Tuchaar; Nienaber, Christoph A

2007-12-01

Management of acute ST elevation myocardial infarction (STEMI) demands rapid and complete reperfusion of the infarct-related artery (IRA). With postinfarction prognosis depending on time delay from onset of symptoms to complete reperfusion (TIMI 3 flow) of the IRA, primary percutaneous coronary intervention (PPCI) performed by an experienced team has been shown to be superior to thrombolytic therapy with lower mortality, less frequent occurrence of nonfatal reinfarction and stroke, and thus represents the preferred treatment strategy according to the national and international guidelines. For regional implementation of PPCI, particularly in rural areas, information and transfer logistics within networks of care and direct transport of an infarction patient to a PCI hospital rather than to the closest hospital are a challenge. With successful implementation of network logistics and standardized therapeutic pathways, current guidelines and requested timelines versus thrombolysis could be met. The implemented logistics comprised 24 h/7 days stand-by services of an experienced PCI team, direct telephone hotline contact between rescue service/emergency physician and interventional cardiologist on call, and direct open access to a catheterization laboratory at any time. Within the Drip&Ship network Rostock, to date (July 2007) 1,022 consecutive patients with PCI for STEMI were documented and analyzed over 5 years; of these, 490 patients were transferred from a community hospital to the PCI center and 532 patients were admitted directly to the interventional center. In 95.1% of all transferred and in 94.8% of all directly admitted patients, PCI was successfully accomplished upon arrival. A normalized flow to the IRA after PCI was documented in 96% of both groups, no patient was subjected to thrombolytic therapy. At 12-month follow-up, there were no differences between both groups with respect to infarct size and mortality. Moreover, there was no evidence of differences in left ventricular ejection fraction between groups. Thus, transportation of STEMI patients within an established PCI network did not result in any prognostic disadvantage. Efficient network logistics with transportation for PPCI in acute STEMI ensure both safety and outcome profiles similar to patients treated by PCI in metropolitan areas.

Gathering Information from Transport Systems for Processing in Supply Chains

NASA Astrophysics Data System (ADS)

Kodym, Oldřich; Unucka, Jakub

2016-12-01

Paper deals with complex system for processing information from means of transport acting as parts of train (rail or road). It focuses on automated information gathering using AutoID technology, information transmission via Internet of Things networks and information usage in information systems of logistic firms for support of selected processes on MES and ERP levels. Different kinds of gathered information from whole transport chain are discussed. Compliance with existing standards is mentioned. Security of information in full life cycle is integral part of presented system. Design of fully equipped system based on synthesized functional nodes is presented.

Improvement of logistics education from the point of view environmental management

NASA Astrophysics Data System (ADS)

Bányai, Á.

2009-04-01

The paper briefly presents the influence of environmental management on the improvement of the logistics education and research structure of the Department of Materials Handling and Logistics at the University of Miskolc, Hungary. The logistics, as an integrated science offers a very good possibility to demonstrate the effect of new innovative knowledge on the migration of the priorities of education and research of sciences. The importance of logistics in the field of recycling (or in wider sense in the field of environmental management) can be justified by the high proportion of logistic costs (as investment and operation costs) and these costs show that optimum logistic solutions are able to decrease the financial outcomes and lead to the establishment of a profitable system. Technological change constantly creates new demands on both education and research. The most important objective of the department is to create a unique logistics education in the country. For this reason the department offered up-to-date integrated knowledge at all level: undergraduate, master degree and PhD education. The integration of logistics means traditionally the joint use of technology of material handling, method of material flow, technology method of traffic, information technology, management sciences, production technology, marketing, market research, technology of services, mathematics and optimization, communication technology, system engineering, electronics and automation, mechatronics [1, 3]. The education and research portfolio of the department followed this tradition till 1993. The new lectures in the field of sustainability (logistics of recycling, logistics of quality management and recycling, closed loop economy, EU logistics or global logistics) became more and more important in the logistics education. The results of fast developments in closed loop economy, recycling, waste management, environmental protection are more and more used in the industry and this effected a revolutionary change in the education and research structure of logistics [2]. The European Community policy in the environment sectors aims at a high level of protection. Four principles were defined: the precautionary principle, the principle that preventive action should be taken, that environmental damages should as a priority be rectified at source and that the polluter should pay. All of these four principles have a very strong logistics background, especially in the field of import/export operations, traffic/transportation, inventory control, materials handling, fleet operations, customer service, supply chain management, distribution, strategic planning, warehousing, information systems of logistics, purchasing. These facts effect the development of different topics of logistics in each field of the education of the department: collection logistics of used products (especially WEEE), optimization of collection systems, design and control of disassembly systems, distribution of fractions of disassembled used products, design and control of recycling parks, possibilities of virtual networks in the field of recycling logistics, integration of logistics, recycling and total quality management, identification systems and recycling, etc. Within the framework of different supports our department has the opportunity to take part in European networks and research projects in the field of sustainability, environmental protection, recycling and closed loop economy. One of the biggest networks was developed within the framework of a Brite-Euram project entitled ‘Closing the loop from the product design to the end of life technologies'. The importance of logistics is certified by the fact, that this network defined the milestones of the improvement of an economically beneficial closed loop economy as quality aspects, communication and marketing, logistics and qualification. Within the frame of this project the logistics focused on the improvement of technologies (disassembly, reuse, refurbishment, remanufacturing and recycling), collection systems, and development of the concept for collection logistics and pre-disassembly, market survey in waste management. The Regional Knowledge Centre of Mechatronics and Logistics Systems was established in 2005. The overall objective of Knowledge Centre is to develop knowledge-intensive mechatronics and logistics systems in the leading edge of the world and to integrate the results in the economy and society through utilising the knowledge. The realisation of the objective requires the establishment and operation of a networking system of relations between those involved in sciences, the economy and society. The knowledge centre is a "knowledge integration tool" of the university in the field of mechanical engineering, and plays an important part in the intensification of the integration of the philosophy of sustainability into the related sciences. The program of the knowledge centre is focused on three well definable strategic fields, which are the vertical elements of the model. These are the R&D programs: world of products, materials and technologies, and integrated systems. The programs cover the implementation of seven, internationally competitive, application-oriented part tasks. These seven part tasks and the sustainability are closely related. The realisation of the part tasks through networking offers considerable results and economical-ecological benefits, forth for the participants and the region. The activities include basic and applied research, experimental development, technology transfer, as well as education and training and preparing the new scientific generation. The horizontal elements of the model are given by the utilisation of knowledge that can be interpreted in different dimensions: technical/engineering, legal, sustainability, economic, and social. The program relies on the continuation of existing relations in networks, and its regional nature is embodied in the cooperation of the higher education institutes and companies of the three counties. This publication was supported by the National Office for Research and Technology within the frame of Pázmány Péter programme. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Office for Research and Technology. Literature: [1] J. Cselényi, Gy. Fischer, J. Murvai, B. Mang: Typical models of the recycling logistics of worn out product. Proceedings of XIV. International Conference on Material Handling and Warehousing in Belgrade, 1996. pp. 138-143. [2] R. Knoth, M. Hoffmann, B. Kopacek, P. Kopacek: A logistic concept to improve the re-usability of electric and electronic equipment, Electronics and the Environment, 2001. Proceedings of the 2001 IEEE International Symposium. 2001. pp. 115 - 118. [3] L. Cser, B. Mang: Cleaner Technologies and Recycling in Hungary. Proceedings of Int. Workshop on Environmental Conscious Manufacturing in Hertogenbosch, The Netherlands, 1997. pp. 48-56.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Network-based regularization for matched case-control analysis of high-dimensional DNA methylation data.

PubMed

Sun, Hokeun; Wang, Shuang

2013-05-30

The matched case-control designs are commonly used to control for potential confounding factors in genetic epidemiology studies especially epigenetic studies with DNA methylation. Compared with unmatched case-control studies with high-dimensional genomic or epigenetic data, there have been few variable selection methods for matched sets. In an earlier paper, we proposed the penalized logistic regression model for the analysis of unmatched DNA methylation data using a network-based penalty. However, for popularly applied matched designs in epigenetic studies that compare DNA methylation between tumor and adjacent non-tumor tissues or between pre-treatment and post-treatment conditions, applying ordinary logistic regression ignoring matching is known to bring serious bias in estimation. In this paper, we developed a penalized conditional logistic model using the network-based penalty that encourages a grouping effect of (1) linked Cytosine-phosphate-Guanine (CpG) sites within a gene or (2) linked genes within a genetic pathway for analysis of matched DNA methylation data. In our simulation studies, we demonstrated the superiority of using conditional logistic model over unconditional logistic model in high-dimensional variable selection problems for matched case-control data. We further investigated the benefits of utilizing biological group or graph information for matched case-control data. We applied the proposed method to a genome-wide DNA methylation study on hepatocellular carcinoma (HCC) where we investigated the DNA methylation levels of tumor and adjacent non-tumor tissues from HCC patients by using the Illumina Infinium HumanMethylation27 Beadchip. Several new CpG sites and genes known to be related to HCC were identified but were missed by the standard method in the original paper. Copyright © 2012 John Wiley & Sons, Ltd.

Research on reverse logistics location under uncertainty environment based on grey prediction

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Congwei, Zhu; Yuqin, Zhao; Quanke, Pan

This article constructs reverse logistic network based on uncertain environment, integrates the reverse logistics network and distribution network, and forms a closed network. An optimization model based on cost is established to help intermediate center, manufacturing center and remanufacturing center make location decision. A gray model GM (1, 1) is used to predict the product holdings of the collection points, and then prediction results are carried into the cost optimization model and a solution is got. Finally, an example is given to verify the effectiveness and feasibility of the model.

A FRAMEWORK FOR ATTRIBUTE-BASED COMMUNITY DETECTION WITH APPLICATIONS TO INTEGRATED FUNCTIONAL GENOMICS.

PubMed

Yu, Han; Hageman Blair, Rachael

2016-01-01

Understanding community structure in networks has received considerable attention in recent years. Detecting and leveraging community structure holds promise for understanding and potentially intervening with the spread of influence. Network features of this type have important implications in a number of research areas, including, marketing, social networks, and biology. However, an overwhelming majority of traditional approaches to community detection cannot readily incorporate information of node attributes. Integrating structural and attribute information is a major challenge. We propose a exible iterative method; inverse regularized Markov Clustering (irMCL), to network clustering via the manipulation of the transition probability matrix (aka stochastic flow) corresponding to a graph. Similar to traditional Markov Clustering, irMCL iterates between "expand" and "inflate" operations, which aim to strengthen the intra-cluster flow, while weakening the inter-cluster flow. Attribute information is directly incorporated into the iterative method through a sigmoid (logistic function) that naturally dampens attribute influence that is contradictory to the stochastic flow through the network. We demonstrate advantages and the exibility of our approach using simulations and real data. We highlight an application that integrates breast cancer gene expression data set and a functional network defined via KEGG pathways reveal significant modules for survival.

Centralized versus decentralized decision-making for recycled material flows.

PubMed

Hong, I-Hsuan; Ammons, Jane C; Realff, Matthew J

2008-02-15

A reverse logistics system is a network of transportation logistics and processing functions that collect, consolidate, refurbish, and demanufacture end-of-life products. This paper examines centralized and decentralized models of decision-making for material flows and associated transaction prices in reverse logistics networks. We compare the application of a centralized model for planning reverse production systems, where a single planner is acquainted with all of the system information and has the authority to determine decision variables for the entire system, to a decentralized approach. In the decentralized approach, the entities coordinate between tiers of the system using a parametrized flow function and compete within tiers based on reaching a price equilibrium. We numerically demonstrate the increase in the total net profit of the centralized system relative to the decentralized one. This implies that one may overestimate the system material flows and profit if the system planner utilizes a centralized viewto predict behaviors of independent entities in the system and that decentralized contract mechanisms will require careful design to avoid losses in the efficiency and scope of these systems.

Using Teradata University Network (TUN), a Free Internet Resource for Teaching and Learning

ERIC Educational Resources Information Center

Winter, Robert; Gericke, Anke; Bucher, Tobias

2008-01-01

Business intelligence and information logistics have become an important part of teaching curricula in recent years due to the increased demand for adequately trained graduates. Since these fields are characterized by a high amount of software and methodology innovations, teaching materials and teaching aids require constant updating. Teradata has…

Use of Informal Networks to Resolve Logistics-related Issues in Humanitarian Assistance Disaster Response

DTIC Science & Technology

2011-06-01

efforts and the situation objectively and were not tempted to cast themselves in a favorable light ( Podsakoff & Organ, 1986). The AARs and CDRs were...Management.13(3), 146-156. doi: 10.1108/ 13673270910962932. Podsakoff , P.M., & Organ, D.W. (1986). Self-Reports in Organizational Research: Problems

Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

NASA Astrophysics Data System (ADS)

Lin, Yi-Kuei; Yeh, Cheng-Ta

2013-05-01

From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.

Bifurcation behaviors of synchronized regions in logistic map networks with coupling delay

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

Tang, Longkun, E-mail: tomlk@hqu.edu.cn, E-mail: xqwu@whu.edu.cn; Wu, Xiaoqun, E-mail: tomlk@hqu.edu.cn, E-mail: xqwu@whu.edu.cn; Lu, Jun-an, E-mail: jalu@whu.edu.cn

2015-03-15

Network synchronized regions play an extremely important role in network synchronization according to the master stability function framework. This paper focuses on network synchronous state stability via studying the effects of nodal dynamics, coupling delay, and coupling way on synchronized regions in Logistic map networks. Theoretical and numerical investigations show that (1) network synchronization is closely associated with its nodal dynamics. Particularly, the synchronized region bifurcation points through which the synchronized region switches from one type to another are in good agreement with those of the uncoupled node system, and chaotic nodal dynamics can greatly impede network synchronization. (2) Themore » coupling delay generally impairs the synchronizability of Logistic map networks, which is also dominated by the parity of delay for some nodal parameters. (3) A simple nonlinear coupling facilitates network synchronization more than the linear one does. The results found in this paper will help to intensify our understanding for the synchronous state stability in discrete-time networks with coupling delay.« less

Application studies of RFID technology in the process of coal logistics transport

NASA Astrophysics Data System (ADS)

Qiao, Bingqin; Chang, Xiaoming; Hao, Meiyan; Kong, Dejin

2012-04-01

For quality control problems in coal transport, RFID technology has been proposed to be applied to coal transportation process. The whole process RFID traceability system from coal production to consumption has been designed and coal supply chain logistics tracking system integration platform has been built, to form the coal supply chain traceability and transport tracking system and providing more and more transparent tracking and monitoring of coal quality information for consumers of coal. Currently direct transport and combined transport are the main forms of coal transportation in China. The means of transport are cars, trains and ships. In the booming networking environment of RFID technology, the RFID technology will be applied to coal logistics and provide opportunity for the coal transportation tracking in the process transportation.

Structure-preserving model reduction of large-scale logistics networks. Applications for supply chains

NASA Astrophysics Data System (ADS)

Scholz-Reiter, B.; Wirth, F.; Dashkovskiy, S.; Makuschewitz, T.; Schönlein, M.; Kosmykov, M.

2011-12-01

We investigate the problem of model reduction with a view to large-scale logistics networks, specifically supply chains. Such networks are modeled by means of graphs, which describe the structure of material flow. An aim of the proposed model reduction procedure is to preserve important features within the network. As a new methodology we introduce the LogRank as a measure for the importance of locations, which is based on the structure of the flows within the network. We argue that these properties reflect relative importance of locations. Based on the LogRank we identify subgraphs of the network that can be neglected or aggregated. The effect of this is discussed for a few motifs. Using this approach we present a meta algorithm for structure-preserving model reduction that can be adapted to different mathematical modeling frameworks. The capabilities of the approach are demonstrated with a test case, where a logistics network is modeled as a Jackson network, i.e., a particular type of queueing network.

Radio frequency identification enabled wireless sensing for intelligent food logistics.

PubMed

Zou, Zhuo; Chen, Qiang; Chen, Qing; Uysal, Ismail; Zheng, Lirong

2014-06-13

Future technologies and applications for the Internet of Things (IoT) will evolve the process of the food supply chain and create added value of business. Radio frequency identifications (RFIDs) and wireless sensor networks (WSNs) have been considered as the key technological enablers. Intelligent tags, powered by autonomous energy, are attached on objects, networked by short-range wireless links, allowing the physical parameters such as temperatures and humidities as well as the location information to seamlessly integrate with the enterprise information system over the Internet. In this paper, challenges, considerations and design examples are reviewed from system, implementation and application perspectives, particularly with focus on intelligent packaging and logistics for the fresh food tracking and monitoring service. An IoT platform with a two-layer network architecture is introduced consisting of an asymmetric tag-reader link (RFID layer) and an ad-hoc link between readers (WSN layer), which are further connected to the Internet via cellular or Wi-Fi. Then, we provide insights into the enabling technology of RFID with sensing capabilities. Passive, semi-passive and active RFID solutions are discussed. In particular, we describe ultra-wideband radio RFID which has been considered as one of the most promising techniques for ultra-low-power and low-cost wireless sensing. Finally, an example is provided in the form of an application in fresh food tracking services and corresponding field testing results.

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

PubMed Central

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-01-01

In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies. PMID:26184252

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming.

PubMed

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-07-09

In order to recycle and dispose of all people's expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

An online expert network for high quality information on occupational safety and health: cross-sectional study of user satisfaction and impact

PubMed Central

2011-01-01

Background Many people have difficulties finding information on health questions, including occupational safety and health (OSH) issues. One solution to alleviate these difficulties could be to offer questioners free-of-charge, online access to a network of OSH experts who provide tailored, high-quality information. The aim of this study was to assess whether network quality, respectively information quality, as perceived by the questioners, is associated with questioners' overall satisfaction and to explore the impact of the information received on questioners' knowledge, work and work functioning. Methods We evaluated the experiences of OSH questioners with the online network ArboAntwoord.com over a two-year period. In this network, approximately 80 qualified experts are available to answer OSH questions. By means of a questionnaire, we assessed questioners' overall satisfaction with the network, whether the network was user-friendly, easily accessible and easy to handle and whether the information provided was complete, applicable and received in a timely manner. The impact of the information on questioners' knowledge, work or work functioning was explored with seven questions. In the study period, 460 unique OSH questioners asked 851 OSH questions. In total, 205 of the 460 questioners completed the questionnaire (response rate 45%). Results Of the responders, 71% were satisfied with the ArboAntwoord network. Multiple logistic regression analysis showed that the applicability of the information had a positive influence on the questioners' overall satisfaction (OR = 16.0, 95% CI: 7.0-36.4). Also, user friendliness of the network (OR = 3.3, 95% CI: 1.3-8.6) and completeness of the information provided (OR = 3.0, 95% CI: 1.3-6.8) were positively related to the questioners' satisfaction. For 74% of the questioners, the information helped to increase their knowledge and understanding. Overall, 25% of the questioners indicated that the received information improved their work, work functioning or health. Conclusions A free-of-charge, online expert network in the field of OSH can be a useful strategy to provide OSH questioners with applicable, complete and timely information that may help improve safety and health at work. This study provides more insight in how to satisfy network questioners and about the potential impact of provided information on OSH. PMID:22111587

An online expert network for high quality information on occupational safety and health: cross-sectional study of user satisfaction and impact.

PubMed

Rhebergen, Martijn D F; Lenderink, Annet F; van Dijk, Frank J H; Hulshof, Carel T J

2011-11-23

Many people have difficulties finding information on health questions, including occupational safety and health (OSH) issues. One solution to alleviate these difficulties could be to offer questioners free-of-charge, online access to a network of OSH experts who provide tailored, high-quality information. The aim of this study was to assess whether network quality, respectively information quality, as perceived by the questioners, is associated with questioners' overall satisfaction and to explore the impact of the information received on questioners' knowledge, work and work functioning. We evaluated the experiences of OSH questioners with the online network ArboAntwoord.com over a two-year period. In this network, approximately 80 qualified experts are available to answer OSH questions. By means of a questionnaire, we assessed questioners' overall satisfaction with the network, whether the network was user-friendly, easily accessible and easy to handle and whether the information provided was complete, applicable and received in a timely manner. The impact of the information on questioners' knowledge, work or work functioning was explored with seven questions. In the study period, 460 unique OSH questioners asked 851 OSH questions. In total, 205 of the 460 questioners completed the questionnaire (response rate 45%). Of the responders, 71% were satisfied with the ArboAntwoord network. Multiple logistic regression analysis showed that the applicability of the information had a positive influence on the questioners' overall satisfaction (OR = 16.0, 95% CI: 7.0-36.4). Also, user friendliness of the network (OR = 3.3, 95% CI: 1.3-8.6) and completeness of the information provided (OR = 3.0, 95% CI: 1.3-6.8) were positively related to the questioners' satisfaction. For 74% of the questioners, the information helped to increase their knowledge and understanding. Overall, 25% of the questioners indicated that the received information improved their work, work functioning or health. A free-of-charge, online expert network in the field of OSH can be a useful strategy to provide OSH questioners with applicable, complete and timely information that may help improve safety and health at work. This study provides more insight in how to satisfy network questioners and about the potential impact of provided information on OSH.

An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

PubMed Central

Zhang, Dezhi; Li, Shuangyan

2014-01-01

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

PubMed

Zhang, Dezhi; Li, Shuangyan; Qin, Jin

2014-01-01

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

Reverse logistics in the Brazilian construction industry.

PubMed

Nunes, K R A; Mahler, C F; Valle, R A

2009-09-01

In Brazil most Construction and Demolition Waste (C&D waste) is not recycled. This situation is expected to change significantly, since new federal regulations oblige municipalities to create and implement sustainable C&D waste management plans which assign an important role to recycling activities. The recycling organizational network and its flows and components are fundamental to C&D waste recycling feasibility. Organizational networks, flows and components involve reverse logistics. The aim of this work is to introduce the concepts of reverse logistics and reverse distribution channel networks and to study the Brazilian C&D waste case.

Reverse logistics network for municipal solid waste management: The inclusion of waste pickers as a Brazilian legal requirement.

PubMed

Ferri, Giovane Lopes; Chaves, Gisele de Lorena Diniz; Ribeiro, Glaydston Mattos

2015-06-01

This study proposes a reverse logistics network involved in the management of municipal solid waste (MSW) to solve the challenge of economically managing these wastes considering the recent legal requirements of the Brazilian Waste Management Policy. The feasibility of the allocation of MSW material recovery facilities (MRF) as intermediate points between the generators of these wastes and the options for reuse and disposal was evaluated, as well as the participation of associations and cooperatives of waste pickers. This network was mathematically modelled and validated through a scenario analysis of the municipality of São Mateus, which makes the location model more complete and applicable in practice. The mathematical model allows the determination of the number of facilities required for the reverse logistics network, their location, capacities, and product flows between these facilities. The fixed costs of installation and operation of the proposed MRF were balanced with the reduction of transport costs, allowing the inclusion of waste pickers to the reverse logistics network. The main contribution of this study lies in the proposition of a reverse logistics network for MSW simultaneously involving legal, environmental, economic and social criteria, which is a very complex goal. This study can guide practices in other countries that have realities similar to those in Brazil of accelerated urbanisation without adequate planning for solid waste management, added to the strong presence of waste pickers that, through the characteristic of social vulnerability, must be included in the system. In addition to the theoretical contribution to the reverse logistics network problem, this study aids in decision-making for public managers who have limited technical and administrative capacities for the management of solid wastes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Recovering time-varying networks of dependencies in social and biological studies.

PubMed

Ahmed, Amr; Xing, Eric P

2009-07-21

A plausible representation of the relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network that is topologically rewiring and semantically evolving over time. Although there is a rich literature in modeling static or temporally invariant networks, little has been done toward recovering the network structure when the networks are not observable in a dynamic context. In this article, we present a machine learning method called TESLA, which builds on a temporally smoothed l(1)-regularized logistic regression formalism that can be cast as a standard convex-optimization problem and solved efficiently by using generic solvers scalable to large networks. We report promising results on recovering simulated time-varying networks and on reverse engineering the latent sequence of temporally rewiring political and academic social networks from longitudinal data, and the evolving gene networks over >4,000 genes during the life cycle of Drosophila melanogaster from a microarray time course at a resolution limited only by sample frequency.

Supporting Regularized Logistic Regression Privately and Efficiently.

PubMed

Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei

2016-01-01

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

Supporting Regularized Logistic Regression Privately and Efficiently

PubMed Central

Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei

2016-01-01

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738

Genetic prediction of type 2 diabetes using deep neural network.

PubMed

Kim, J; Kim, J; Kwak, M J; Bajaj, M

2018-04-01

Type 2 diabetes (T2DM) has strong heritability but genetic models to explain heritability have been challenging. We tested deep neural network (DNN) to predict T2DM using the nested case-control study of Nurses' Health Study (3326 females, 45.6% T2DM) and Health Professionals Follow-up Study (2502 males, 46.5% T2DM). We selected 96, 214, 399, and 678 single-nucleotide polymorphism (SNPs) through Fisher's exact test and L1-penalized logistic regression. We split each dataset randomly in 4:1 to train prediction models and test their performance. DNN and logistic regressions showed better area under the curve (AUC) of ROC curves than the clinical model when 399 or more SNPs included. DNN was superior than logistic regressions in AUC with 399 or more SNPs in male and 678 SNPs in female. Addition of clinical factors consistently increased AUC of DNN but failed to improve logistic regressions with 214 or more SNPs. In conclusion, we show that DNN can be a versatile tool to predict T2DM incorporating large numbers of SNPs and clinical information. Limitations include a relatively small number of the subjects mostly of European ethnicity. Further studies are warranted to confirm and improve performance of genetic prediction models using DNN in different ethnic groups. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Toward the establishment of design guidelines for effective 3D perspective interfaces

NASA Astrophysics Data System (ADS)

Fitzhugh, Elisabeth; Dixon, Sharon; Aleva, Denise; Smith, Eric; Ghrayeb, Joseph; Douglas, Lisa

2009-05-01

The propagation of information operation technologies, with correspondingly vast amounts of complex network information to be conveyed, significantly impacts operator workload. Information management research is rife with efforts to develop schemes to aid operators to identify, review, organize, and retrieve the wealth of available data. Data may take on such distinct forms as intelligence libraries, logistics databases, operational environment models, or network topologies. Increased use of taxonomies and semantic technologies opens opportunities to employ network visualization as a display mechanism for diverse information aggregations. The broad applicability of network visualizations is still being tested, but in current usage, the complexity of densely populated abstract networks suggests the potential utility of 3D. Employment of 2.5D in network visualization, using classic perceptual cues, creates a 3D experience within a 2D medium. It is anticipated that use of 3D perspective (2.5D) will enhance user ability to visually inspect large, complex, multidimensional networks. Current research for 2.5D visualizations demonstrates that display attributes, including color, shape, size, lighting, atmospheric effects, and shadows, significantly impact operator experience. However, guidelines for utilization of attributes in display design are limited. This paper discusses pilot experimentation intended to identify potential problem areas arising from these cues and determine how best to optimize perceptual cue settings. Development of optimized design guidelines will ensure that future experiments, comparing network displays with other visualizations, are not confounded or impeded by suboptimal attribute characterization. Current experimentation is anticipated to support development of cost-effective, visually effective methods to implement 3D in military applications.

Computational approaches for predicting biomedical research collaborations.

PubMed

Zhang, Qing; Yu, Hong

2014-01-01

Biomedical research is increasingly collaborative, and successful collaborations often produce high impact work. Computational approaches can be developed for automatically predicting biomedical research collaborations. Previous works of collaboration prediction mainly explored the topological structures of research collaboration networks, leaving out rich semantic information from the publications themselves. In this paper, we propose supervised machine learning approaches to predict research collaborations in the biomedical field. We explored both the semantic features extracted from author research interest profile and the author network topological features. We found that the most informative semantic features for author collaborations are related to research interest, including similarity of out-citing citations, similarity of abstracts. Of the four supervised machine learning models (naïve Bayes, naïve Bayes multinomial, SVMs, and logistic regression), the best performing model is logistic regression with an ROC ranging from 0.766 to 0.980 on different datasets. To our knowledge we are the first to study in depth how research interest and productivities can be used for collaboration prediction. Our approach is computationally efficient, scalable and yet simple to implement. The datasets of this study are available at https://github.com/qingzhanggithub/medline-collaboration-datasets.

A multimodal logistics service network design with time windows and environmental concerns

PubMed Central

Zhang, Dezhi; He, Runzhong; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained. PMID:28934272

A multimodal logistics service network design with time windows and environmental concerns.

PubMed

Zhang, Dezhi; He, Runzhong; Li, Shuangyan; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained.

Reverse logistics network for municipal solid waste management: The inclusion of waste pickers as a Brazilian legal requirement

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

Ferri, Giovane Lopes, E-mail: giovane.ferri@aluno.ufes.br; Diniz Chaves, Gisele de Lorena, E-mail: gisele.chaves@ufes.br; Ribeiro, Glaydston Mattos, E-mail: glaydston@pet.coppe.ufrj.br

Highlights: • We propose a reverse logistics network for MSW involving waste pickers. • A generic facility location mathematical model was validated in a Brazilian city. • The results enable to predict the capacity for screening and storage centres (SSC). • We minimise the costs for transporting MSW with screening and storage centres. • The use of SSC can be a potential source of revenue and a better use of MSW. - Abstract: This study proposes a reverse logistics network involved in the management of municipal solid waste (MSW) to solve the challenge of economically managing these wastes considering themore » recent legal requirements of the Brazilian Waste Management Policy. The feasibility of the allocation of MSW material recovery facilities (MRF) as intermediate points between the generators of these wastes and the options for reuse and disposal was evaluated, as well as the participation of associations and cooperatives of waste pickers. This network was mathematically modelled and validated through a scenario analysis of the municipality of São Mateus, which makes the location model more complete and applicable in practice. The mathematical model allows the determination of the number of facilities required for the reverse logistics network, their location, capacities, and product flows between these facilities. The fixed costs of installation and operation of the proposed MRF were balanced with the reduction of transport costs, allowing the inclusion of waste pickers to the reverse logistics network. The main contribution of this study lies in the proposition of a reverse logistics network for MSW simultaneously involving legal, environmental, economic and social criteria, which is a very complex goal. This study can guide practices in other countries that have realities similar to those in Brazil of accelerated urbanisation without adequate planning for solid waste management, added to the strong presence of waste pickers that, through the characteristic of social vulnerability, must be included in the system. In addition to the theoretical contribution to the reverse logistics network problem, this study aids in decision-making for public managers who have limited technical and administrative capacities for the management of solid wastes.« less

Reverse logistics system planning for recycling computers hardware: A case study

NASA Astrophysics Data System (ADS)

Januri, Siti Sarah; Zulkipli, Faridah; Zahari, Siti Meriam; Shamsuri, Siti Hajar

2014-09-01

This paper describes modeling and simulation of reverse logistics networks for collection of used computers in one of the company in Selangor. The study focuses on design of reverse logistics network for used computers recycling operation. Simulation modeling, presented in this work allows the user to analyze the future performance of the network and to understand the complex relationship between the parties involved. The findings from the simulation suggest that the model calculates processing time and resource utilization in a predictable manner. In this study, the simulation model was developed by using Arena simulation package.

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple dynamic system-level trades over time and give recommendation of the optimal strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.

Family health history communication networks of older adults: importance of social relationships and disease perceptions.

PubMed

Ashida, Sato; Kaphingst, Kimberly A; Goodman, Melody; Schafer, Ellen J

2013-10-01

Older individuals play a critical role in disseminating family health history (FHH) information that can facilitate disease prevention among younger family members. This study evaluated the characteristics of older adults and their familial networks associated with two types of communication (have shared and intend to share new FHH information with family members) to inform public health efforts to facilitate FHH dissemination. Information on 970 social network members enumerated by 99 seniors (aged 57 years and older) at 3 senior centers in Memphis, Tennessee, through face-to-face interviews was analyzed. Participants shared FHH information with 27.5% of the network members; 54.7% of children and 24.4% of siblings. Two-level logistic regression models showed that participants had shared FHH with those to whom they provided emotional support (odds ratio [OR] = 1.836) and felt close to (OR = 1.757). Network-members were more likely to have received FHH from participants with a cancer diagnosis (OR = 2.617) and higher familiarity with (OR = 1.380) and importance of sharing FHH with family (OR = 1.474). Participants intended to share new FHH with those who provide tangible support to (OR = 1.804) and were very close to them (OR = 2.112). Members with whom participants intend to share new FHH were more likely to belong to the network of participants with higher perceived severity if family members encountered heart disease (OR = 1.329). Many first-degree relatives were not informed of FHH. Perceptions about FHH and disease risk as well as quality of social relationships may play roles in whether seniors communicate FHH with their families. Future studies may consider influencing these perceptions and relationships.

Information Assurance Study

DTIC Science & Technology

1998-01-01

usually written up by Logistics or Maintenance (4790 is the Maintenance “ Bible ”). If need be, and if resources are available, one could collect all...Public domain) SATAN (System Administration Tool for Analyzing Networks) (Public Domain) STAT ( Security Test and Analysis Tool) (Harris Corporation...Service-Filtering Tools 1. TCP/IP wrapper program • Tools to Scan Hosts for Known Vulnerabilities 1. ISS (Internet Security Scanner) 2. SATAN (Security

An analysis of respondent-driven sampling with injecting drug users in a high HIV prevalent state of India.

PubMed

Phukan, Sanjib Kumar; Medhi, Gajendra Kumar; Mahanta, Jagadish; Adhikary, Rajatashuvra; Thongamba, Gay; Paranjape, Ramesh S; Akoijam, Brogen S

2017-07-03

Personal networks are significant social spaces to spread of HIV or other blood-borne infections among hard-to-reach population, viz., injecting drug users, female sex workers, etc. Sharing of infected needles or syringes among drug users is one of the major routes of HIV transmission in Manipur, a high HIV prevalence state in India. This study was carried out to describe the network characteristics and recruitment patterns of injecting drug users and to assess the association of personal network with injecting risky behaviors in Manipur. A total of 821 injecting drug users were recruited into the study using respondent-driven sampling (RDS) from Bishnupur and Churachandpur districts of Manipur; data on demographic characteristics, HIV risk behaviors, and network size were collected from them. Transition probability matrices and homophily indices were used to describe the network characteristics, and recruitment patterns of injecting drug users. Univariate and multivariate binary logistic regression models were performed to analyze the association between the personal networks and sharing of needles or syringes. The average network size was similar in both the districts. Recruitment analysis indicates injecting drug users were mostly engaged in mixed age group setting for injecting practice. Ever married and new injectors showed lack of in-group ties. Younger injecting drug users had mainly recruited older injecting drug users from their personal network. In logistic regression analysis, higher personal network was found to be significantly associated with increased likelihood of injecting risky behaviors. Because of mixed personal network of new injectors and higher network density associated with HIV exposure, older injecting drug users may act as a link for HIV transmission or other blood-borne infections to new injectors and also to their sexual partners. The information from this study may be useful to understanding the network pattern of injecting drug users for enriching the HIV prevention in this region.

Osm-Oriented Method of Multimodal Route Planning

NASA Astrophysics Data System (ADS)

Li, X.; Wu, Q.; Chen, L.; Xiong, W.; Jing, N.

2015-07-01

With the increasing pervasiveness of basic facilitate of transportation and information, the need of multimodal route planning is becoming more essential in the fields of communication and transportation, urban planning, logistics management, etc. This article mainly described an OSM-oriented method of multimodal route planning. Firstly, it introduced how to extract the information we need from OSM data and build proper network model and storage model; then it analysed the accustomed cost standard adopted by most travellers; finally, we used shortest path algorithm to calculate the best route with multiple traffic means.

Leveraging socially networked mobile ICT platforms for the last-mile delivery problem.

PubMed

Suh, Kyo; Smith, Timothy; Linhoff, Michelle

2012-09-04

Increasing numbers of people are managing their social networks on mobile information and communication technology (ICT) platforms. This study materializes these social relationships by leveraging spatial and networked information for sharing excess capacity to reduce the environmental impacts associated with "last-mile" package delivery systems from online purchases, particularly in low population density settings. Alternative package pickup location systems (PLS), such as a kiosk on a public transit platform or in a grocery store, have been suggested as effective strategies for reducing package travel miles and greenhouse gas emissions, compared to current door-to-door delivery models (CDS). However, our results suggest that a pickup location delivery system operating in a suburban setting may actually increase travel miles and emissions. Only once a social network is employed to assist in package pickup (SPLS) are significant reductions in the last-mile delivery distance and carbon emissions observed across both urban and suburban settings. Implications for logistics management's decades-long focus on improving efficiencies of dedicated distribution systems through specialization, as well as for public policy targeting carbon emissions of the transport sector are discussed.

Phase-synchronisation in continuous flow models of production networks

NASA Astrophysics Data System (ADS)

Scholz-Reiter, Bernd; Tervo, Jan Topi; Freitag, Michael

2006-04-01

To improve their position at the market, many companies concentrate on their core competences and hence cooperate with suppliers and distributors. Thus, between many independent companies strong linkages develop and production and logistics networks emerge. These networks are characterised by permanently increasing complexity, and are nowadays forced to adapt to dynamically changing markets. This factor complicates an enterprise-spreading production planning and control enormously. Therefore, a continuous flow model for production networks will be derived regarding these special logistic problems. Furthermore, phase-synchronisation effects will be presented and their dependencies to the set of network parameters will be investigated.

Resilience in the face of post-election violence in Kenya: the mediating role of social networks on wellbeing among older people in the Korogocho informal settlement, Nairobi.

PubMed

Bennett, Rachel; Chepngeno-Langat, Gloria; Evandrou, Maria; Falkingham, Jane

2015-03-01

Older people in slum settings are a vulnerable sub-group during crises, yet have received minimal attention in the development discourse. This paper examines the protective role of different types of social networks for older slum dwellers' wellbeing during adversity by investigating the relationship between social networks, the Kenyan 2007/08 post-election violence, and dimensions of wellbeing namely self-rated health, life satisfaction and happiness amongst older people in the Korogocho slum, Nairobi. The analyses are based on conditional change logistic regression models using data from a unique longitudinal survey of the health and wellbeing of older people. The results show that maintaining or increasing formal local networks reduced the detrimental effects of the post-election violence for older people's wellbeing, whilst household environment and informal local and non-local networks did not influence the relationship. Consequently, the paper provides evidence that supporting inclusive community organisations which are accessible to older people can be valuable in promoting the resilience of this population group. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Comparing models for quantitative risk assessment: an application to the European Registry of foreign body injuries in children.

PubMed

Berchialla, Paola; Scarinzi, Cecilia; Snidero, Silvia; Gregori, Dario

2016-08-01

Risk Assessment is the systematic study of decisions subject to uncertain consequences. An increasing interest has been focused on modeling techniques like Bayesian Networks since their capability of (1) combining in the probabilistic framework different type of evidence including both expert judgments and objective data; (2) overturning previous beliefs in the light of the new information being received and (3) making predictions even with incomplete data. In this work, we proposed a comparison among Bayesian Networks and other classical Quantitative Risk Assessment techniques such as Neural Networks, Classification Trees, Random Forests and Logistic Regression models. Hybrid approaches, combining both Classification Trees and Bayesian Networks, were also considered. Among Bayesian Networks, a clear distinction between purely data-driven approach and combination of expert knowledge with objective data is made. The aim of this paper consists in evaluating among this models which best can be applied, in the framework of Quantitative Risk Assessment, to assess the safety of children who are exposed to the risk of inhalation/insertion/aspiration of consumer products. The issue of preventing injuries in children is of paramount importance, in particular where product design is involved: quantifying the risk associated to product characteristics can be of great usefulness in addressing the product safety design regulation. Data of the European Registry of Foreign Bodies Injuries formed the starting evidence for risk assessment. Results showed that Bayesian Networks appeared to have both the ease of interpretability and accuracy in making prediction, even if simpler models like logistic regression still performed well. © The Author(s) 2013.

An assessment of the barriers to the consumers' uptake of genetically modified foods: a neural network analysis.

PubMed

Rodríguez-Entrena, Macario; Salazar-Ordóñez, Melania; Becerra-Alonso, David

2016-03-30

This paper studies which of the attitudinal, cognitive and socio-economic factors determine the willingness to purchase genetically modified (GM) food, enabling the forecasting of consumers' behaviour in Andalusia, southern Spain. This classification has been made by a standard multilayer perceptron neural network trained with extreme learning machine. Later, an ordered logistic regression was applied to determine whether the neural network can outperform this traditional econometric approach. The results show that the highest relative contributions lie in the variables related to perceived risks of GM food, while the perceived benefits have a lower influence. In addition, an innovative attitude towards food presents a strong link, as does the perception of food safety. The variables with the least relative contribution are subjective knowledge about GM food and the consumers' age. The neural network approach outperforms the correct classification percentage from the ordered logistic regression. The perceived risks must be considered as a critical factor. A strategy to improve the GM food acceptance is to develop a transparent and balanced information framework that makes the potential risk understandable by society, and make them aware of the risk assessments for GM food in the EU. For its success, it is essential to improve the trust in EU institutions and scientific regulatory authorities. © 2015 Society of Chemical Industry.

Chimera states in networks of logistic maps with hierarchical connectivities

NASA Astrophysics Data System (ADS)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

Maintenance and Logistics Support for the International Monitoring System Network of the CTBTO

NASA Astrophysics Data System (ADS)

Haslinger, F.; Brely, N.; Akrawy, M.

2007-05-01

The global network of the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), once completed, will consist of 321 monitoring facilities of four different technologies: hydroacoustic, seismic, infrasonic, and radionuclide. As of today, about 65% of the installations are completed and contribute data to the products issued by the International Data Centre (IDC) of the CTBTO. In order to accomplish the task to reliably collect evidence for any potential nuclear test explosion anywhere on the planet, all stations are required to perform to very high data availability requirements (at least 98% data availability over a 12-month period). To enable reaching this requirement, a three-layer concept has been developed to allow efficient support of the IMS stations: Operations, Maintenance and Logistics, and Engineering. Within this concept Maintenance and Logistics provide second level support of the stations, whereby problems arising at the station are assigned through the IMS ticket system to Maintenance if they cannot be resolved on the Operations level. Maintenance will then activate the required resources to appropriately address and ultimately resolve the problem. These resources may be equipment support contracts, other third party contracts, or the dispatch of a maintenance team. Engineering Support will be activated if the problem requires redesign of the station or after catastrophic failures when a total rebuild of a station may be necessary. In this model, Logistics Support is responsible for parts replenishment and support contract management. Logistics Support also collects and analyzes relevant failure mode and effect information, develops supportability models, and has the responsibility for document management, obsolescence, risk & quality, and configuration management, which are key elements for efficient station support. Maintenance Support in addition is responsible for maintenance strategies, for planning and oversight of the execution of preventive maintenance programs by the Station Operators, and for review of operational troubleshooting procedures used in first level support. Particular challenges for the efficient and successful Maintenance and Logistics Support of the IMS network lie in the specific political boundary conditions regulating its implementation, in the fact that all IMS facilities and their equipment are owned by the respective host countries, and in finding the appropriate balance between outsourcing services and retaining essential in-house expertise.

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

A Multi-Stage Reverse Logistics Network Problem by Using Hybrid Priority-Based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu

Today remanufacturing problem is one of the most important problems regarding to the environmental aspects of the recovery of used products and materials. Therefore, the reverse logistics is gaining become power and great potential for winning consumers in a more competitive context in the future. This paper considers the multi-stage reverse Logistics Network Problem (m-rLNP) while minimizing the total cost, which involves reverse logistics shipping cost and fixed cost of opening the disassembly centers and processing centers. In this study, we first formulate the m-rLNP model as a three-stage logistics network model. Following for solving this problem, we propose a Genetic Algorithm pri (GA) with priority-based encoding method consisting of two stages, and introduce a new crossover operator called Weight Mapping Crossover (WMX). Additionally also a heuristic approach is applied in the 3rd stage to ship of materials from processing center to manufacturer. Finally numerical experiments with various scales of the m-rLNP models demonstrate the effectiveness and efficiency of our approach by comparing with the recent researches.

Developing weighted criteria to evaluate lean reverse logistics through analytical network process

NASA Astrophysics Data System (ADS)

Zagloel, Teuku Yuri M.; Hakim, Inaki Maulida; Krisnawardhani, Rike Adyartie

2017-11-01

Reverse logistics is a part of supply chain that bring materials from consumers back to manufacturer in order to gain added value or do a proper disposal. Nowadays, most companies are still facing several problems on reverse logistics implementation which leads to high waste along reverse logistics processes. In order to overcome this problem, Madsen [Framework for Reverse Lean Logistics to Enable Green Manufacturing, Eco Design 2009: 6th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Sapporo, 2009] has developed a lean reverse logistics framework as a step to eliminate waste by implementing lean on reverse logistics. However, the resulted framework sets aside criteria used to evaluate its performance. This research aims to determine weighted criteria that can be used as a base on reverse logistics evaluation by considering lean principles. The resulted criteria will ensure reverse logistics are kept off from waste, thus implemented efficiently. Analytical Network Process (ANP) is used in this research to determine the weighted criteria. The result shows that criteria used for evaluation lean reverse logistics are Innovation and Learning (35%), Economic (30%), Process Flow Management (14%), Customer Relationship Management (13%), Environment (6%), and Social (2%).

A Predictive Analysis of the Department of Defense Distribution System Utilizing Random Forests

DTIC Science & Technology

2016-06-01

resources capable of meeting both customer and individual resource constraints and goals while also maximizing the global benefit to the supply...and probability rules to determine the optimal red wine distribution network for an Italian-based wine producer. The decision support model for...combinations of factors that will result in delivery of the highest quality wines . The model’s first stage inputs basic logistics information to look

Blackmail propagation on small-world networks

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Jian-Ping Sang; Zou, Xian-Wu; Tan, Zhi-Jie; Jin, Zhun-Zhi

2005-06-01

The dynamics of the blackmail propagation model based on small-world networks is investigated. It is found that for a given transmitting probability λ the dynamical behavior of blackmail propagation transits from linear growth type to logistical growth one with the network randomness p increases. The transition takes place at the critical network randomness pc=1/N, where N is the total number of nodes in the network. For a given network randomness p the dynamical behavior of blackmail propagation transits from exponential decrease type to logistical growth one with the transmitting probability λ increases. The transition occurs at the critical transmitting probability λc=1/, where is the average number of the nearest neighbors. The present work will be useful for understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Scenario analysis and disaster preparedness for port and maritime logistics risk management.

PubMed

Kwesi-Buor, John; Menachof, David A; Talas, Risto

2016-08-01

System Dynamics (SD) modelling is used to investigate the impacts of policy interventions on industry actors' preparedness to mitigate risks and to recover from disruptions along the maritime logistics and supply chain network. The model suggests a bi-directional relation between regulation and industry actors' behaviour towards Disaster Preparedness (DP) in maritime logistics networks. The model also showed that the level of DP is highly contingent on forecast accuracy, technology change, attitude to risk prevention, port activities, and port environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Social network and individual correlates of sexual risk behavior among homeless young men who have sex with men.

PubMed

Tucker, Joan S; Hu, Jianhui; Golinelli, Daniela; Kennedy, David P; Green, Harold D; Wenzel, Suzanne L

2012-10-01

There is growing interest in network-based interventions to reduce HIV sexual risk behavior among both homeless youth and men who have sex with men. The goal of this study was to better understand the social network and individual correlates of sexual risk behavior among homeless young men who have sex with men (YMSM) to inform these HIV prevention efforts. A multistage sampling design was used to recruit a probability sample of 121 homeless YMSM (ages: 16-24 years) from shelters, drop-in centers, and street venues in Los Angeles County. Face-to-face interviews were conducted. Because of the different distributions of the three outcome variables, three distinct regression models were needed: ordinal logistic regression for unprotected sex, zero-truncated Poisson regression for number of sex partners, and logistic regression for any sex trade. Homeless YMSM were less likely to engage in unprotected sex and had fewer sex partners if their networks included platonic ties to peers who regularly attended school, and had fewer sex partners if most of their network members were not heavy drinkers. Most other aspects of network composition were unrelated to sexual risk behavior. Individual predictors of sexual risk behavior included older age, Hispanic ethnicity, lower education, depressive symptoms, less positive condom attitudes, and sleeping outdoors because of nowhere else to stay. HIV prevention programs for homeless YMSM may warrant a multipronged approach that helps these youth strengthen their ties to prosocial peers, develop more positive condom attitudes, and access needed mental health and housing services. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

NASA Astrophysics Data System (ADS)

Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

75 FR 76037 - HAVI Logistics, North America a Subsidiary of HAVI Group, LP Including On-Site Leased Workers of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-07

... Logistics, North America a Subsidiary of HAVI Group, LP Including On-Site Leased Workers of Express Personnel Services and the La Salle Network, Bloomingdale, IL; Havi Logistics, North America, Lisle, IL..., applicable to workers of HAVI Logistics, North America, a subsidiary of HAVI Group, LP, including on-site...

Demand Analysis of Logistics Information Matching Platform: A Survey from Highway Freight Market in Zhejiang Province

NASA Astrophysics Data System (ADS)

Chen, Daqiang; Shen, Xiahong; Tong, Bing; Zhu, Xiaoxiao; Feng, Tao

With the increasing competition in logistics industry and promotion of lower logistics costs requirements, the construction of logistics information matching platform for highway transportation plays an important role, and the accuracy of platform design is the key to successful operation or not. Based on survey results of logistics service providers, customers and regulation authorities to access to information and in-depth information demand analysis of logistics information matching platform for highway transportation in Zhejiang province, a survey analysis for framework of logistics information matching platform for highway transportation is provided.

Using Timely Survey-Based Information Networks to Collect Data on Best Practices for Public Health Emergency Preparedness and Response: Illustrative Case From the American College of Emergency Physicians' Ebola Surveys.

PubMed

Abir, Mahshid; Moore, Melinda; Chamberlin, Margaret; Koenig, Kristi L; Hirshon, Jon Mark; Singh, Cynthia; Schneider, Sandra; Cantrill, Stephen

2016-08-01

Using the example of surveys conducted by the American College of Emergency Physicians (ACEP) regarding the management of Ebola cases in the United States, we aimed to demonstrate how survey-based information networks can provide timely data to inform best practices in responding to public health emergencies. ACEP conducted 3 surveys among its members in October to November 2014 to assess the state of Ebola preparedness in emergency departments. We analyzed the surveys to illustrate the types of information that can be gleaned from such surveys. We analyzed qualitative data through theme extraction and collected quantitative results through cross-tabulations and logistic regression examining associations between outcomes and potential contributing factors. In the first survey, most respondents perceived their hospital as being reasonably prepared for Ebola. The second survey revealed significant associations between a hospital's preparedness and its perceived ability to admit Ebola patients. The third survey identified 3 hospital characteristics that were significantly and independently associated with perceived ability to admit Ebola patients: large size, previous Ebola screening experience, and physician- and nurse-led hospital preparedness. Professional associations can use their member networks to collect timely survey data to inform best practices during and immediately after public health emergencies. (Disaster Med Public Health Preparedness. 2016;10:681-690).

An exploration of the Facebook social networks of smokers and non-smokers.

PubMed

Fu, Luella; Jacobs, Megan A; Brookover, Jody; Valente, Thomas W; Cobb, Nathan K; Graham, Amanda L

2017-01-01

Social networks influence health behavior, including tobacco use and cessation. To date, little is known about whether and how the networks of online smokers and non-smokers may differ, or the potential implications of such differences with regards to intervention efforts. Understanding how social networks vary by smoking status could inform public health efforts to accelerate cessation or slow the adoption of tobacco use. These secondary analyses explore the structure of ego networks of both smokers and non-smokers collected as part of a randomized control trial conducted within Facebook. During the trial, a total of 14,010 individuals installed a Facebook smoking cessation app: 9,042 smokers who were randomized in the trial, an additional 2,881 smokers who did not meet full eligibility criteria, and 2,087 non-smokers. The ego network for all individuals was constructed out to second-degree connections. Four kinds of networks were constructed: friendship, family, photo, and group networks. From these networks we measured edges, isolates, density, mean betweenness, transitivity, and mean closeness. We also measured diameter, clustering, and modularity without ego and isolates. Logistic regressions were performed with smoking status as the response and network metrics as the primary independent variables and demographics and Facebook utilization metrics as covariates. The four networks had different characteristics, indicated by different multicollinearity issues and by logistic regression output. Among Friendship networks, the odds of smoking were higher in networks with lower betweenness (p = 0.00), lower transitivity (p = 0.00), and larger diameter (p = 0.00). Among Family networks, the odds of smoking were higher in networks with more vertices (p = .01), less transitivity (p = .04), and fewer isolates (p = .01). Among Photo networks, none of the network metrics were predictive of smoking status. Among Group networks, the odds of smoking were higher when diameter was smaller (p = .04). Together, these findings suggested that compared to non-smokers, smokers in this sample had less connected, more dispersed Facebook Friendship networks; larger but more fractured Family networks with fewer isolates; more compact Group networks; and Photo networks that were similar in network structure to those of non-smokers. This study illustrates the importance of examining structural differences in online social networks as a critical component for network-based interventions and lays the foundation for future research that examines the ways that social networks differ based on individual health behavior. Interventions that seek to target the behavior of individuals in the context of their social environment would be well served to understand social network structures of participants.

An exploration of the Facebook social networks of smokers and non-smokers

PubMed Central

2017-01-01

Background Social networks influence health behavior, including tobacco use and cessation. To date, little is known about whether and how the networks of online smokers and non-smokers may differ, or the potential implications of such differences with regards to intervention efforts. Understanding how social networks vary by smoking status could inform public health efforts to accelerate cessation or slow the adoption of tobacco use. Objectives These secondary analyses explore the structure of ego networks of both smokers and non-smokers collected as part of a randomized control trial conducted within Facebook. Methods During the trial, a total of 14,010 individuals installed a Facebook smoking cessation app: 9,042 smokers who were randomized in the trial, an additional 2,881 smokers who did not meet full eligibility criteria, and 2,087 non-smokers. The ego network for all individuals was constructed out to second-degree connections. Four kinds of networks were constructed: friendship, family, photo, and group networks. From these networks we measured edges, isolates, density, mean betweenness, transitivity, and mean closeness. We also measured diameter, clustering, and modularity without ego and isolates. Logistic regressions were performed with smoking status as the response and network metrics as the primary independent variables and demographics and Facebook utilization metrics as covariates. Results The four networks had different characteristics, indicated by different multicollinearity issues and by logistic regression output. Among Friendship networks, the odds of smoking were higher in networks with lower betweenness (p = 0.00), lower transitivity (p = 0.00), and larger diameter (p = 0.00). Among Family networks, the odds of smoking were higher in networks with more vertices (p = .01), less transitivity (p = .04), and fewer isolates (p = .01). Among Photo networks, none of the network metrics were predictive of smoking status. Among Group networks, the odds of smoking were higher when diameter was smaller (p = .04). Together, these findings suggested that compared to non-smokers, smokers in this sample had less connected, more dispersed Facebook Friendship networks; larger but more fractured Family networks with fewer isolates; more compact Group networks; and Photo networks that were similar in network structure to those of non-smokers. Conclusions This study illustrates the importance of examining structural differences in online social networks as a critical component for network-based interventions and lays the foundation for future research that examines the ways that social networks differ based on individual health behavior. Interventions that seek to target the behavior of individuals in the context of their social environment would be well served to understand social network structures of participants. PMID:29095958

Optimization of Location-Routing Problem for Cold Chain Logistics Considering Carbon Footprint.

PubMed

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-06

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location-routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network.

Dynamic Network Logistic Regression: A Logistic Choice Analysis of Inter- and Intra-Group Blog Citation Dynamics in the 2004 US Presidential Election

PubMed Central

2013-01-01

Methods for analysis of network dynamics have seen great progress in the past decade. This article shows how Dynamic Network Logistic Regression techniques (a special case of the Temporal Exponential Random Graph Models) can be used to implement decision theoretic models for network dynamics in a panel data context. We also provide practical heuristics for model building and assessment. We illustrate the power of these techniques by applying them to a dynamic blog network sampled during the 2004 US presidential election cycle. This is a particularly interesting case because it marks the debut of Internet-based media such as blogs and social networking web sites as institutionally recognized features of the American political landscape. Using a longitudinal sample of all Democratic National Convention/Republican National Convention–designated blog citation networks, we are able to test the influence of various strategic, institutional, and balance-theoretic mechanisms as well as exogenous factors such as seasonality and political events on the propensity of blogs to cite one another over time. Using a combination of deviance-based model selection criteria and simulation-based model adequacy tests, we identify the combination of processes that best characterizes the choice behavior of the contending blogs. PMID:24143060

A support network typology for application in older populations with a preponderance of multigenerational households.

PubMed

Burholt, Vanessa; Dobbs, Christine

2014-08-01

This paper considers the support networks of older people in populations with a preponderance of multigenerational households and examines the most vulnerable network types in terms of loneliness and isolation. Current common typologies of support networks may not be sensitive to differences within and between different cultures. This paper uses cross-sectional data drawn from 590 elders (Gujaratis, Punjabis and Sylhetis) living in the United Kingdom and South Asia. Six variables were used in K-means cluster analysis to establish a new network typology. Two logistic regression models using loneliness and isolation as dependent variables assessed the contribution of the new network type to wellbeing. Four support networks were identified: 'Multigenerational Households: Older Integrated Networks', 'Multigenerational Households: Younger Family Networks', 'Family and Friends Integrated Networks' and 'Non-kin Restricted Networks'. Older South Asians with 'Non-kin Restricted Networks' were more likely to be lonely and isolated compared to others. Using network typologies developed with individualistically oriented cultures, distributions are skewed towards more robust network types and could underestimate the support needs of older people from familistic cultures, who may be isolated and lonely and with limited informal sources of help. The new typology identifies different network types within multigenerational households, identifies a greater proportion of older people with vulnerable networks and could positively contribute to service planning.

Using ROC curves to compare neural networks and logistic regression for modeling individual noncatastrophic tree mortality

Treesearch

Susan L. King

2003-01-01

The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...

Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

PubMed

Fei, Y; Hu, J; Li, W-Q; Wang, W; Zong, G-Q

2017-03-01

Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicting PSMVT. Additional predictive factors may be incorporated into artificial neural networks. Objective To construct and validate artificial neural networks (ANNs) for predicting the occurrence of portosplenomesenteric venous thrombosis (PSMVT) and compare the predictive ability of the ANNs with that of logistic regression. Methods The ANNs and logistic regression modeling were constructed using simple clinical and laboratory data of 72 acute pancreatitis (AP) patients. The ANNs and logistic modeling were first trained on 48 randomly chosen patients and validated on the remaining 24 patients. The accuracy and the performance characteristics were compared between these two approaches by SPSS17.0 software. Results The training set and validation set did not differ on any of the 11 variables. After training, the back propagation network training error converged to 1 × 10 -20 , and it retained excellent pattern recognition ability. When the ANNs model was applied to the validation set, it revealed a sensitivity of 80%, specificity of 85.7%, a positive predictive value of 77.6% and negative predictive value of 90.7%. The accuracy was 83.3%. Differences could be found between ANNs modeling and logistic regression modeling in these parameters (10.0% [95% CI, -14.3 to 34.3%], 14.3% [95% CI, -8.6 to 37.2%], 15.7% [95% CI, -9.9 to 41.3%], 11.8% [95% CI, -8.2 to 31.8%], 22.6% [95% CI, -1.9 to 47.1%], respectively). When ANNs modeling was used to identify PSMVT, the area under receiver operating characteristic curve was 0.849 (95% CI, 0.807-0.901), which demonstrated better overall properties than logistic regression modeling (AUC = 0.716) (95% CI, 0.679-0.761). Conclusions ANNs modeling was a more accurate tool than logistic regression in predicting the occurrence of PSMVT following AP. More clinical factors or biomarkers may be incorporated into ANNs modeling to improve its predictive ability. © 2016 International Society on Thrombosis and Haemostasis.

The Real Time Mission Monitor: A Situational Awareness Tool For Managing Experiment Assets

NASA Technical Reports Server (NTRS)

Blakeslee, Richard; Hall, John; Goodman, Michael; Parker, Philip; Freudinger, Larry; He, Matt

2007-01-01

The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, airborne and surface data sets; weather information; model and forecast outputs; and vehicle state data (e.g., aircraft navigation, satellite tracks and instrument field-of-views) for field experiment management RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses experiment during summer 2006 in Cape Verde, Africa. The integration and delivery of this information is made possible through data acquisition systems, network communication links and network server resources built and managed by collaborators at NASA Dryden Flight Research Center (DFRC) and Marshall Space Flight Center (MSFC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols.

Regional Logistics Information Resources Integration Patterns and Countermeasures

NASA Astrophysics Data System (ADS)

Wu, Hui; Shangguan, Xu-ming

Effective integration of regional logistics information resources can provide collaborative services in information flow, business flow and logistics for regional logistics enterprises, which also can reduce operating costs and improve market responsiveness. First, this paper analyzes the realistic significance on the integration of regional logistics information. Second, this paper brings forward three feasible patterns on the integration of regional logistics information resources, These three models have their own strengths and the scope of application and implementation, which model is selected will depend on the specific business and the regional distribution of enterprises. Last, this paper discusses the related countermeasures on the integration of regional logistics information resources, because the integration of regional logistics information is a systems engineering, when the integration is advancing, the countermeasures should pay close attention to the current needs and long-term development of regional enterprises.

Artificial Neural Network for the Prediction of Chromosomal Abnormalities in Azoospermic Males.

PubMed

Akinsal, Emre Can; Haznedar, Bulent; Baydilli, Numan; Kalinli, Adem; Ozturk, Ahmet; Ekmekçioğlu, Oğuz

2018-02-04

To evaluate whether an artifical neural network helps to diagnose any chromosomal abnormalities in azoospermic males. The data of azoospermic males attending to a tertiary academic referral center were evaluated retrospectively. Height, total testicular volume, follicle stimulating hormone, luteinising hormone, total testosterone and ejaculate volume of the patients were used for the analyses. In artificial neural network, the data of 310 azoospermics were used as the education and 115 as the test set. Logistic regression analyses and discriminant analyses were performed for statistical analyses. The tests were re-analysed with a neural network. Both logistic regression analyses and artificial neural network predicted the presence or absence of chromosomal abnormalities with more than 95% accuracy. The use of artificial neural network model has yielded satisfactory results in terms of distinguishing patients whether they have any chromosomal abnormality or not.

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

Science of Test Research Consortium: Year Two Final Report

DTIC Science & Technology

2012-10-02

July 2012. Analysis of an Intervention for Small Unmanned Aerial System ( SUAS ) Accidents, submitted to Quality Engineering, LQEN-2012-0056. Stone... Systems Engineering. Wolf, S. E., R. R. Hill, and J. J. Pignatiello. June 2012. Using Neural Networks and Logistic Regression to Model Small Unmanned ...Human Retina. 6. Wolf, S. E. March 2012. Modeling Small Unmanned Aerial System Mishaps using Logistic Regression and Artificial Neural Networks. 7

Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.

PubMed

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-08-01

Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this review was to assess machine learning alternatives to logistic regression, which may accomplish the same goals but with fewer assumptions or greater accuracy. We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (classification and regression trees [CART]), and meta-classifiers (in particular, boosting). Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint

PubMed Central

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-01

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location–routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network. PMID:29316639

78 FR 57845 - Notice of Availability (NOA) for Strategic Network Optimization (SNO) Program Environmental...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... (NOA) for Strategic Network Optimization (SNO) Program Environmental Assessment AGENCY: Defense Logistics Agency, DoD. ACTION: Notice of Availability (NOA) for Strategic Network Optimization (SNO) Program... implement the SNO initiative for improvements to material distribution network for the Department of Defense...

The Dropout Learning Algorithm

PubMed Central

Baldi, Pierre; Sadowski, Peter

2014-01-01

Dropout is a recently introduced algorithm for training neural network by randomly dropping units during training to prevent their co-adaptation. A mathematical analysis of some of the static and dynamic properties of dropout is provided using Bernoulli gating variables, general enough to accommodate dropout on units or connections, and with variable rates. The framework allows a complete analysis of the ensemble averaging properties of dropout in linear networks, which is useful to understand the non-linear case. The ensemble averaging properties of dropout in non-linear logistic networks result from three fundamental equations: (1) the approximation of the expectations of logistic functions by normalized geometric means, for which bounds and estimates are derived; (2) the algebraic equality between normalized geometric means of logistic functions with the logistic of the means, which mathematically characterizes logistic functions; and (3) the linearity of the means with respect to sums, as well as products of independent variables. The results are also extended to other classes of transfer functions, including rectified linear functions. Approximation errors tend to cancel each other and do not accumulate. Dropout can also be connected to stochastic neurons and used to predict firing rates, and to backpropagation by viewing the backward propagation as ensemble averaging in a dropout linear network. Moreover, the convergence properties of dropout can be understood in terms of stochastic gradient descent. Finally, for the regularization properties of dropout, the expectation of the dropout gradient is the gradient of the corresponding approximation ensemble, regularized by an adaptive weight decay term with a propensity for self-consistent variance minimization and sparse representations. PMID:24771879

From disaster to development: a systematic review of community-driven humanitarian logistics.

PubMed

Bealt, Jennifer; Mansouri, S Afshin

2018-01-01

A plethora of untapped resources exist within disaster-affected communities that can be used to address relief and development concerns. A systematic review of the literature relating to community participation in humanitarian logistics activities revealed that communities are able to form ad hoc networks that have the ability to meet a wide range of disaster management needs. These structures, characterised as Collaborative Aid Networks (CANs), have demonstrated efficient logistical capabilities exclusive of humanitarian organisations. This study proposes that CANs, as a result of their unique characteristics, present alternatives to established humanitarian approaches to logistics, while also mitigating the challenges commonly faced by traditional humanitarian organisations. Furthermore, CANs offer a more holistic, long-term approach to disaster management, owing to their impact on development through their involvement in humanitarian logistics. This research provides the foundation for further theoretical analysis of effective and efficient disaster management, and details opportunities for policy and practice. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

Evaluation of Deep Learning Representations of Spatial Storm Data

NASA Astrophysics Data System (ADS)

Gagne, D. J., II; Haupt, S. E.; Nychka, D. W.

2017-12-01

The spatial structure of a severe thunderstorm and its surrounding environment provide useful information about the potential for severe weather hazards, including tornadoes, hail, and high winds. Statistics computed over the area of a storm or from the pre-storm environment can provide descriptive information but fail to capture structural information. Because the storm environment is a complex, high-dimensional space, identifying methods to encode important spatial storm information in a low-dimensional form should aid analysis and prediction of storms by statistical and machine learning models. Principal component analysis (PCA), a more traditional approach, transforms high-dimensional data into a set of linearly uncorrelated, orthogonal components ordered by the amount of variance explained by each component. The burgeoning field of deep learning offers two potential approaches to this problem. Convolutional Neural Networks are a supervised learning method for transforming spatial data into a hierarchical set of feature maps that correspond with relevant combinations of spatial structures in the data. Generative Adversarial Networks (GANs) are an unsupervised deep learning model that uses two neural networks trained against each other to produce encoded representations of spatial data. These different spatial encoding methods were evaluated on the prediction of severe hail for a large set of storm patches extracted from the NCAR convection-allowing ensemble. Each storm patch contains information about storm structure and the near-storm environment. Logistic regression and random forest models were trained using the PCA and GAN encodings of the storm data and were compared against the predictions from a convolutional neural network. All methods showed skill over climatology at predicting the probability of severe hail. However, the verification scores among the methods were very similar and the predictions were highly correlated. Further evaluations are being performed to determine how the choice of input variables affects the results.

Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

PubMed

Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

2018-04-17

The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

Design of cold chain logistics remote monitoring system based on ZigBee and GPS location

NASA Astrophysics Data System (ADS)

Zong, Xiaoping; Shao, Heling

2017-03-01

This paper designed a remote monitoring system based on Bee Zig wireless sensor network and GPS positioning, according to the characteristics of cold chain logistics. The system consisted of the ZigBee network, gateway and monitoring center. ZigBee network temperature acquisition modules and GPS positioning acquisition module were responsible for data collection, and then send the data to the host computer through the GPRS network and Internet to realize remote monitoring of vehicle with functions of login permissions, temperature display, latitude and longitude display, historical data, real-time alarm and so on. Experiments showed that the system is stable, reliable and effective to realize the real-time remote monitoring of the vehicle in the process of cold chain transport.

Logistics Distribution Center Location Evaluation Based on Genetic Algorithm and Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Shao, Yuxiang; Chen, Qing; Wei, Zhenhua

Logistics distribution center location evaluation is a dynamic, fuzzy, open and complicated nonlinear system, which makes it difficult to evaluate the distribution center location by the traditional analysis method. The paper proposes a distribution center location evaluation system which uses the fuzzy neural network combined with the genetic algorithm. In this model, the neural network is adopted to construct the fuzzy system. By using the genetic algorithm, the parameters of the neural network are optimized and trained so as to improve the fuzzy system’s abilities of self-study and self-adaptation. At last, the sampled data are trained and tested by Matlab software. The simulation results indicate that the proposed identification model has very small errors.

Systems for the Intermodal Routing of Spent Nuclear Fuel

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

Peterson, Steven K; Liu, Cheng

The safe and secure movement of spent nuclear fuel from shutdown and active reactor facilities to intermediate or long term storage sites may, in some instances, require the use of several modes of transportation to accomplish the move. To that end, a fully operable multi-modal routing system is being developed within Oak Ridge National Laboratory s (ORNL) WebTRAGIS (Transportation Routing Analysis Geographic Information System). This study aims to provide an overview of multi-modal routing, the existing state of the TRAGIS networks, the source data needs, and the requirements for developing structural relationships between various modes to create a suitable systemmore » for modeling the transport of spent nuclear fuel via a multimodal network. Modern transportation systems are comprised of interconnected, yet separate, modal networks. Efficient transportation networks rely upon the smooth transfer of cargoes at junction points that serve as connectors between modes. A key logistical impediment to the shipment of spent nuclear fuel is the absence of identified or designated transfer locations between transport modes. Understanding the potential network impacts on intermodal transportation of spent nuclear fuel is vital for planning transportation routes from origin to destination. By identifying key locations where modes intersect, routing decisions can be made to prioritize cost savings, optimize transport times and minimize potential risks to the population and environment. In order to facilitate such a process, ORNL began the development of a base intermodal network and associated routing code. The network was developed using previous intermodal networks and information from publicly available data sources to construct a database of potential intermodal transfer locations with likely capability to handle spent nuclear fuel casks. The coding development focused on modifying the existing WebTRAGIS routing code to accommodate intermodal transfers and the selection of prioritization constraints and modifiers to determine route selection. The limitations of the current model and future directions for development are discussed, including the current state of information on possible intermodal transfer locations for spent fuel.« less

Building a Decision Support System for Inpatient Admission Prediction With the Manchester Triage System and Administrative Check-in Variables.

PubMed

Zlotnik, Alexander; Alfaro, Miguel Cuchí; Pérez, María Carmen Pérez; Gallardo-Antolín, Ascensión; Martínez, Juan Manuel Montero

2016-05-01

The usage of decision support tools in emergency departments, based on predictive models, capable of estimating the probability of admission for patients in the emergency department may give nursing staff the possibility of allocating resources in advance. We present a methodology for developing and building one such system for a large specialized care hospital using a logistic regression and an artificial neural network model using nine routinely collected variables available right at the end of the triage process.A database of 255.668 triaged nonobstetric emergency department presentations from the Ramon y Cajal University Hospital of Madrid, from January 2011 to December 2012, was used to develop and test the models, with 66% of the data used for derivation and 34% for validation, with an ordered nonrandom partition. On the validation dataset areas under the receiver operating characteristic curve were 0.8568 (95% confidence interval, 0.8508-0.8583) for the logistic regression model and 0.8575 (95% confidence interval, 0.8540-0. 8610) for the artificial neural network model. χ Values for Hosmer-Lemeshow fixed "deciles of risk" were 65.32 for the logistic regression model and 17.28 for the artificial neural network model. A nomogram was generated upon the logistic regression model and an automated software decision support system with a Web interface was built based on the artificial neural network model.

Logistic growth for the Nuzi cuneiform tablets: Analyzing family networks in ancient Mesopotamia

NASA Astrophysics Data System (ADS)

Ueda, Sumie; Makino, Kumi; Itoh, Yoshiaki; Tsuchiya, Takashi

2015-03-01

We reconstruct the published year of each cuneiform tablet of the Nuzi society in ancient Mesopotamia. The tablets are on land transaction, marriage, loan, slavery contracts, etc. The number of tablets seems to increase by logistic growth. It may show the dynamics of concentration of lands or other properties into few powerful families in a period of about sixty years and most of them are in about thirty years. We reconstruct family trees and social networks of Nuzi and estimate the published years of cuneiform tablets consistently with the trees and networks, formulating least squares problems with linear inequality constraints.

USAREUR LOGISTIC MANAGEMENT INFORMATION SYSTEM - 360 DAY BRIEFING.

DTIC Science & Technology

Information System . This report is the 360 Day Briefing presented to the DCSLOG and his Logistic Management Information System Committee at the conclusion of the study. (Author)...objective of the study was to provide for the Deputy Chief of Staff for Logistics, Headquarters USAREUR and Seventh Army, a Logistic Management

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

PubMed

Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Specifications of a Simulation Model for a Local Area Network Design in Support of Stock Point Logistics Integrated Communications Environment (SPLICE).

DTIC Science & Technology

1982-10-01

class queueing system with a preemptive -resume priority service discipline, as depicted in Figure 4.2. Concerning a SPLICLAN configuration a node can...processor can be modeled as a single resource, multi-class queueing system with a preemptive -resume priority structure as the one given in Figure 4.2. An...LOCAL AREA NETWORK DESIGN IN SUPPORT OF STOCK POINT LOGISTICS INTEGRATED COMMUNICATIONS ENVIRONMENT (SPLICE) by Ioannis Th. Mastrocostopoulos October

Solving a bi-objective mathematical model for location-routing problem with time windows in multi-echelon reverse logistics using metaheuristic procedure

NASA Astrophysics Data System (ADS)

Ghezavati, V. R.; Beigi, M.

2016-12-01

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among established facilities and existing demand points. In this paper, the location-routing problem with time window (LRPTW) and homogeneous fleet type and designing a multi-echelon, and capacitated reverse logistics network, are considered which may arise in many real-life situations in logistics management. Our proposed RL network consists of hybrid collection/inspection centers, recovery centers and disposal centers. Here, we present a new bi-objective mathematical programming (BOMP) for LRPTW in reverse logistic. Since this type of problem is NP-hard, the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to obtain the Pareto frontier for the given problem. Several numerical examples are presented to illustrate the effectiveness of the proposed model and algorithm. Also, the present work is an effort to effectively implement the ɛ-constraint method in GAMS software for producing the Pareto-optimal solutions in a BOMP. The results of the proposed algorithm have been compared with the ɛ-constraint method. The computational results show that the ɛ-constraint method is able to solve small-size instances to optimality within reasonable computing times, and for medium-to-large-sized problems, the proposed NSGA-II works better than the ɛ-constraint.

Detecting Anomalies in Process Control Networks

NASA Astrophysics Data System (ADS)

Rrushi, Julian; Kang, Kyoung-Don

This paper presents the estimation-inspection algorithm, a statistical algorithm for anomaly detection in process control networks. The algorithm determines if the payload of a network packet that is about to be processed by a control system is normal or abnormal based on the effect that the packet will have on a variable stored in control system memory. The estimation part of the algorithm uses logistic regression integrated with maximum likelihood estimation in an inductive machine learning process to estimate a series of statistical parameters; these parameters are used in conjunction with logistic regression formulas to form a probability mass function for each variable stored in control system memory. The inspection part of the algorithm uses the probability mass functions to estimate the normalcy probability of a specific value that a network packet writes to a variable. Experimental results demonstrate that the algorithm is very effective at detecting anomalies in process control networks.

Encrypted data stream identification using randomness sparse representation and fuzzy Gaussian mixture model

NASA Astrophysics Data System (ADS)

Zhang, Hong; Hou, Rui; Yi, Lei; Meng, Juan; Pan, Zhisong; Zhou, Yuhuan

2016-07-01

The accurate identification of encrypted data stream helps to regulate illegal data, detect network attacks and protect users' information. In this paper, a novel encrypted data stream identification algorithm is introduced. The proposed method is based on randomness characteristics of encrypted data stream. We use a l1-norm regularized logistic regression to improve sparse representation of randomness features and Fuzzy Gaussian Mixture Model (FGMM) to improve identification accuracy. Experimental results demonstrate that the method can be adopted as an effective technique for encrypted data stream identification.

Young people's comfort receiving sexual health information via social media and other sources.

PubMed

Lim, Megan Sc; Vella, Alyce; Sacks-Davis, Rachel; Hellard, Margaret E

2014-12-01

Social media are growing in popularity and will play a key role in future sexual health promotion initiatives. We asked 620 survey participants aged 16 to 29 years about their time spent using social media and their comfort in receiving information about sexual health via different channels. Median hours per day spent using social network sites was two; 36% spent more than 2 hours per day using social network sites. In multivariable logistic regression, being aged less than 20 years and living in a major city (compared to rural/regional Australia) were associated with use of social media more than 2 hours per day. Most participants reported being comfortable or very comfortable accessing sexual health information from websites (85%), followed by a doctor (81%), school (73%), and the mainstream media (67%). Fewer reported being comfortable getting information from social media; Facebook (52%), apps (51%), SMS (44%), and Twitter (36%). Several health promotion programmes via social media have demonstrated efficacy; however, we have shown that many young people are not comfortable with accessing sexual health information through these channels. Further research is needed to determine how to best take advantage of these novel opportunities for health promotion. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Variations in Social Network Type Membership Among Older African Americans, Caribbean Blacks, and Non-Hispanic Whites

PubMed Central

2017-01-01

Abstract Objectives: This study examined race differences in the probability of belonging to a specific social network typology of family, friends, and church members. Method: Samples of African Americans, Caribbean blacks, and non-Hispanic whites aged 55+ were drawn from the National Survey of American Life. Typology indicators related to social integration and negative interactions with family, friendship, and church networks were used. Latent class analysis was used to identify typologies, and latent class multinomial logistic regression was used to assess the influence of race, and interactions between race and age, and race and education on typology membership. Results: Four network typologies were identified: optimal (high social integration, low negative interaction), family-centered (high social integration within primarily the extended family network, low negative interaction), strained (low social integration, high negative interaction), and ambivalent (high social integration and high negative interaction). Findings for race and age and race and education interactions indicated that the effects of education and age on typology membership varied by race. Discussion: Overall, the findings demonstrate how race interacts with age and education to influence the probability of belonging to particular network types. A better understanding of the influence of race, education, and age on social network typologies will inform future research and theoretical developments in this area. PMID:28329871

Information logistics: A production-line approach to information services

NASA Technical Reports Server (NTRS)

Adams, Dennis; Lee, Chee-Seng

1991-01-01

Logistics can be defined as the process of strategically managing the acquisition, movement, and storage of materials, parts, and finished inventory (and the related information flow) through the organization and its marketing channels in a cost effective manner. It is concerned with delivering the right product to the right customer in the right place at the right time. The logistics function is composed of inventory management, facilities management, communications unitization, transportation, materials management, and production scheduling. The relationship between logistics and information systems is clear. Systems such as Electronic Data Interchange (EDI), Point of Sale (POS) systems, and Just in Time (JIT) inventory management systems are important elements in the management of product development and delivery. With improved access to market demand figures, logisticians can decrease inventory sizes and better service customer demand. However, without accurate, timely information, little, if any, of this would be feasible in today's global markets. Information systems specialists can learn from logisticians. In a manner similar to logistics management, information logistics is concerned with the delivery of the right data, to the ring customer, at the right time. As such, information systems are integral components of the information logistics system charged with providing customers with accurate, timely, cost-effective, and useful information. Information logistics is a management style and is composed of elements similar to those associated with the traditional logistics activity: inventory management (data resource management), facilities management (distributed, centralized and decentralized information systems), communications (participative design and joint application development methodologies), unitization (input/output system design, i.e., packaging or formatting of the information), transportations (voice, data, image, and video communication systems), materials management (data acquisition, e.g., EDI, POS, external data bases, data entry) and production scheduling (job, staff, and project scheduling).

An Organizational Knowledge Ontology for Automotive Supply Chains

NASA Astrophysics Data System (ADS)

Hellingrath, Bernd; Witthaut, Markus; Böhle, Carsten; Brügger, Stephan

The currently completed ILIPT (Intelligent Logistics for Innovative Product Technologies) project was concerned with the concept of the “5 day car” (a customized car that is delivered within five days after its ordering) and encompassed extensive research on the required production and logistics network structures and processes. As car manufacturers in the automotive industry (commonly referred to as OEMs) rely heavily on their suppliers, the major challenge lies in the organization of inter-enterprise cooperation supported by information systems (IS) in an efficient manner. A common understanding of supply chain concepts is indispensable for this. Ontologies as formal representations of concepts can be used as a semantic basis for cooperation. Relevant results from ILIPT are presented followed by a concept as well as a prototype of how to transfer the theoretical findings to a practical implementation, in this case a multi-agent system.

Organization of a tumor bank: the experience of the National Cancer Institute of Mexico.

PubMed

Ruíz-Godoy, L; Meneses-García, A; Suárez-Roa, L; Enriquez, V; Lechuga-Rojas, R; Reyes-Lira, E

2010-01-01

A tumor bank (TB) is an ordered collection of neoplastic samples, normal tissue, and/or fluids preserved under optimal conditions, as well as storing patients' clinical information. The objective of this article is to outline the planning and logistics necessary for the functioning of the Instituto Nacional de Cancerología (INCan) TB in Mexico City. For the planning and logistics of a TB, several technical, legal, medical, structural, and physical aspects were considered, which can be grouped under four headings: (1) design and structure, (2) equipping the area and informatics, (3) ethical-legal aspects, and (4) sample collection, preservation, and quality control. One crucial element of interinstitutional interest will be the transfer of these concepts to the different oncological centers, integrating in this manner a network that enables the exploration of the different pathologies from therapeutic, epidemiological, and molecular points of view. 2010 S. Karger AG, Basel.

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network

PubMed Central

Pamučar, Dragan; Vasin, Ljubislav; Atanasković, Predrag; Miličić, Milica

2016-01-01

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone. PMID:27195005

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

PubMed

Pamučar, Dragan; Vasin, Ljubislav; Atanasković, Predrag; Miličić, Milica

2016-01-01

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.

Gender, Social Networks, and Stroke Preparedness in the Stroke Warning Information and Faster Treatment Study.

PubMed

Madsen, Tracy E; Roberts, Eric T; Kuczynski, Heather; Goldmann, Emily; Parikh, Nina S; Boden-Albala, Bernadette

2017-12-01

The study aimed to investigate the effect of gender on the association between social networks and stroke preparedness as measured by emergency department (ED) arrival within 3 hours of symptom onset. As part of the Stroke Warning Information and Faster Treatment study, baseline data on demographics, social networks, and time to ED arrival were collected from 1193 prospectively enrolled stroke/transient ischemic attack (TIA) patients at Columbia University Medical Center. Logistic regression was conducted with arrival to the ED ≤3 hours as the outcome, social network characteristics as explanatory variables, and gender as a potential effect modifier. Men who lived alone or were divorced were significantly less likely to arrive ≤3 hours than men who lived with a spouse (adjusted odds ratio [aOR]: .31, 95% confidence interval [CI]: .15-0.64) or were married (aOR: .45, 95% CI: .23-0.86). Among women, those who lived alone or were divorced had similar odds of arriving ≤3 hours compared with those who lived with a spouse (aOR: 1.25, 95% CI: .63-2.49) or were married (aOR: .73, 95% CI: .4-1.35). In patients with stroke/TIA, living with someone or being married improved time to arrival in men only. Behavioral interventions to improve stroke preparedness should incorporate gender differences in how social networks affect arrival times. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Depression, Smoking, and Ego-Centric Social Network Characteristics in Ohio Appalachian Women.

PubMed

Lam, Jeffrey; Lu, Bo; Doogan, Nate; Thomson, Tiffany; Ferketich, Amy; Paskett, Electra D; Wewers, Mary Ellen

2017-01-01

Depression is a serious, costly, and debilitating disorder that is understudied in rural women. Studies show that depression is associated with low social integration and support, but few studies investigate the relationship between depression and social network characteristics. This study examined the associations among women from three Ohio Appalachian counties enrolled in a health study, which aimed to collect information for a future social network smoking cessation intervention. An address-based sampling method was used to randomly select and recruit 404 women. A cross-sectional survey and interview were used to collect information about demographic, psychosocial, behavioral factors, and ego-centric social network characteristics, which are variables derived from an individual (ego) and her first degree contacts (alters). The CES-D scale assessed depressive symptoms. A multivariable logistic regression analysis described the association between these factors and participants with depression (defined as CES-D≥16). Higher network density, or greater number of relationships among alters divided by the total amount of alters, reduced the risk for depression (OR = 0.84, 95% confidence interval [CI] 0.73-0.95). Additionally, women with a high percentage of smoking alters were at greater risk for depression (OR = 1.19, 95% CI 1.02-1.39). Other factors associated with risk for depression included perceived stress score (OR = 1.34, 95% CI 1.24-1.45), loneliness score (OR = 1.37, 95% CI 1.05-1.80), and days with poor physical health (OR = 1.06, 95% CI 1.02-1.11). Findings suggest that psychosocial factors and social networks should be considered when addressing depression in clinical practice.

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

NASA Astrophysics Data System (ADS)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

Immigrant maternal depression and social networks. A multilevel Bayesian spatial logistic regression in South Western Sydney, Australia.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A; Phung, Hai N; Barnett, Bryanne E W

2013-09-01

The purpose is to explore the multilevel spatial distribution of depressive symptoms among migrant mothers in South Western Sydney and to identify any group level associations that could inform subsequent theory building and local public health interventions. Migrant mothers (n=7256) delivering in 2002 and 2003 were assessed at 2-3 weeks after delivery for risk factors for depressive symptoms. The binary outcome variables were Edinburgh Postnatal Depression Scale scores (EPDS) of >9 and >12. Individual level variables included were: financial income, self-reported maternal health, social support network, emotional support, practical support, baby trouble sleeping, baby demanding and baby not content. The group level variable reported here is aggregated social support networks. We used Bayesian hierarchical multilevel spatial modelling with conditional autoregression. Migrant mothers were at higher risk of having depressive symptoms if they lived in a community with predominantly Australian-born mothers and strong social capital as measured by aggregated social networks. These findings suggest that migrant mothers are socially isolated and current home visiting services should be strengthened for migrant mothers living in communities where they may have poor social networks. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

NASA Astrophysics Data System (ADS)

García-Rodríguez, M. J.; Malpica, J. A.

2010-06-01

This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs). The computational method used for the training process is a back-propagation learning algorithm. It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred on 13 January 2001 (Mw 7.7) and 13 February 2001 (Mw 6.6). The first one triggered more than 600 landslides (including the most tragic, Las Colinas landslide) and killed at least 844 people. The ANN is designed and programmed to develop landslide susceptibility analysis techniques at a regional scale. This approach uses an inventory of landslides and different parameters of slope instability: slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness. The information obtained from ANN is then used by a Geographic Information System (GIS) to map the landslide susceptibility. In a previous work, a Logistic Regression (LR) was analysed with the same parameters considered in the ANN as independent variables and the occurrence or non-occurrence of landslides as dependent variables. As a result, the logistic approach determined the importance of terrain roughness and soil type as key factors within the model. The results of the landslide susceptibility analysis with ANN are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone. Finally, a comparative analysis of the ANN and LR models are made. The advantages and disadvantages of both approaches are discussed using Receiver Operating Characteristic (ROC) curves.

Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

The US Strategic Logistics Plan In The CBI Theater And Its Contemporary Significance

DTIC Science & Technology

2016-05-26

SUBJECT TERMS CBI Theater, Logistics, Lend-Lease Aid, LOC Network, Ledo Road, Burma Road, The Hump, AMMISCA 16. SECURITY CLASSIFICATION OF: a...19 Stilwell versus Chennault………………………………………………….………………………….......26 Efficiency of the LOC Network... LOC Line of Communication NATO North Atlantic Treaty Organization SLOC Sea Line of Communication SME Subject Matter Expert SOS Services of Supply SPOD

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems

DTIC Science & Technology

2007-05-03

34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each

Modeling Air Traffic Management Technologies with a Queuing Network Model of the National Airspace System

NASA Technical Reports Server (NTRS)

Long, Dou; Lee, David; Johnson, Jesse; Gaier, Eric; Kostiuk, Peter

1999-01-01

This report describes an integrated model of air traffic management (ATM) tools under development in two National Aeronautics and Space Administration (NASA) programs -Terminal Area Productivity (TAP) and Advanced Air Transport Technologies (AATT). The model is made by adjusting parameters of LMINET, a queuing network model of the National Airspace System (NAS), which the Logistics Management Institute (LMI) developed for NASA. Operating LMINET with models of various combinations of TAP and AATT will give quantitative information about the effects of the tools on operations of the NAS. The costs of delays under different scenarios are calculated. An extension of Air Carrier Investment Model (ACIM) under ASAC developed by the Institute for NASA maps the technologies' impacts on NASA operations into cross-comparable benefits estimates for technologies and sets of technologies.

Customer Churn Prediction for Broadband Internet Services

NASA Astrophysics Data System (ADS)

Huang, B. Q.; Kechadi, M.-T.; Buckley, B.

Although churn prediction has been an area of research in the voice branch of telecommunications services, more focused studies on the huge growth area of Broadband Internet services are limited. Therefore, this paper presents a new set of features for broadband Internet customer churn prediction, based on Henley segments, the broadband usage, dial types, the spend of dial-up, line-information, bill and payment information, account information. Then the four prediction techniques (Logistic Regressions, Decision Trees, Multilayer Perceptron Neural Networks and Support Vector Machines) are applied in customer churn, based on the new features. Finally, the evaluation of new features and a comparative analysis of the predictors are made for broadband customer churn prediction. The experimental results show that the new features with these four modelling techniques are efficient for customer churn prediction in the broadband service field.

Use of Ubiquitous Technologies in Military Logistic System in Iran

NASA Astrophysics Data System (ADS)

Jafari, P.; Sadeghi-Niaraki, A.

2013-09-01

This study is about integration and evaluation of RFID and ubiquitous technologies in military logistic system management. Firstly, supply chain management and the necessity of a revolution in logistic systems especially in military area, are explained. Secondly RFID and ubiquitous technologies and the advantages of their use in supply chain management are introduced. Lastly a system based on these technologies for controlling and increasing the speed and accuracy in military logistic system in Iran with its unique properties, is presented. The system is based on full control of military logistics (supplies) from the time of deployment to replenishment using sensor network, ubiquitous and RFID technologies.

48 CFR 204.7202-1 - CAGE codes.

Code of Federal Regulations, 2014 CFR

2014-10-01

... issued by DLA Logistics Information Service. (Their address is: Customer Service, Federal Center, 74... Logistics Information Service assigns or records and maintains CAGE codes to identify commercial and... Volume 7 of DoD 4100.39-M, Federal Logistics Information System (FLIS) Procedures Manual, prescribe use...

48 CFR 204.7202-1 - CAGE codes.

Code of Federal Regulations, 2011 CFR

2011-10-01

... issued by DLA Logistics Information Service. (Their address is: Customer Service, Federal Center, 74... Logistics Information Service assigns or records and maintains CAGE codes to identify commercial and... Volume 7 of DoD 4100.39-M, Federal Logistics Information System (FLIS) Procedures Manual, prescribe use...

48 CFR 204.7202-1 - CAGE codes.

Code of Federal Regulations, 2013 CFR

2013-10-01

... issued by DLA Logistics Information Service. (Their address is: Customer Service, Federal Center, 74... Logistics Information Service assigns or records and maintains CAGE codes to identify commercial and... Volume 7 of DoD 4100.39-M, Federal Logistics Information System (FLIS) Procedures Manual, prescribe use...

48 CFR 204.7202-1 - CAGE codes.

Code of Federal Regulations, 2012 CFR

2012-10-01

... issued by DLA Logistics Information Service. (Their address is: Customer Service, Federal Center, 74... Logistics Information Service assigns or records and maintains CAGE codes to identify commercial and... Volume 7 of DoD 4100.39-M, Federal Logistics Information System (FLIS) Procedures Manual, prescribe use...

LOGISTIC MANAGEMENT INFORMATION SYSTEM - MANUAL DATA STORAGE AND RETRIEVAL SYSTEM.

DTIC Science & Technology

Logistics Management Information System . The procedures are applicable to manual storage and retrieval of all data used in the Logistics Management ... Information System (LMIS) and include the following: (1) Action Officer data source file. (2) Action Officer presentation format file. (3) LMI Coordination

A development of logistics management models for the Space Transportation System

NASA Technical Reports Server (NTRS)

Carrillo, M. J.; Jacobsen, S. E.; Abell, J. B.; Lippiatt, T. F.

1983-01-01

A new analytic queueing approach was described which relates stockage levels, repair level decisions, and the project network schedule of prelaunch operations directly to the probability distribution of the space transportation system launch delay. Finite source population and limited repair capability were additional factors included in this logistics management model developed specifically for STS maintenance requirements. Data presently available to support logistics decisions were based on a comparability study of heavy aircraft components. A two-phase program is recommended by which NASA would implement an integrated data collection system, assemble logistics data from previous STS flights, revise extant logistics planning and resource requirement parameters using Bayes-Lin techniques, and adjust for uncertainty surrounding logistics systems performance parameters. The implementation of these recommendations can be expected to deliver more cost-effective logistics support.

Innovative hyperchaotic encryption algorithm for compressed video

NASA Astrophysics Data System (ADS)

Yuan, Chun; Zhong, Yuzhuo; Yang, Shiqiang

2002-12-01

It is accepted that stream cryptosystem can achieve good real-time performance and flexibility which implements encryption by selecting few parts of the block data and header information of the compressed video stream. Chaotic random number generator, for example Logistics Map, is a comparatively promising substitute, but it is easily attacked by nonlinear dynamic forecasting and geometric information extracting. In this paper, we present a hyperchaotic cryptography scheme to encrypt the compressed video, which integrates Logistics Map with Z(232 - 1) field linear congruential algorithm to strengthen the security of the mono-chaotic cryptography, meanwhile, the real-time performance and flexibility of the chaotic sequence cryptography are maintained. It also integrates with the dissymmetrical public-key cryptography and implements encryption and identity authentification on control parameters at initialization phase. In accord with the importance of data in compressed video stream, encryption is performed in layered scheme. In the innovative hyperchaotic cryptography, the value and the updating frequency of control parameters can be changed online to satisfy the requirement of the network quality, processor capability and security requirement. The innovative hyperchaotic cryprography proves robust security by cryptoanalysis, shows good real-time performance and flexible implement capability through the arithmetic evaluating and test.

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

PubMed

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

Association between family history of mood disorders and clinical characteristics of bipolar disorder: results from the Brazilian bipolar research network.

PubMed

Berutti, Mariangeles; Nery, Fabiano G; Sato, Rodrigo; Scippa, Angela; Kapczinski, Flavio; Lafer, Beny

2014-06-01

To compare clinical characteristics of bipolar disorder (BD) in patients with and without a family history of mood disorders (FHMD) in a large sample from the Brazilian Research Network of Bipolar Disorders. Four-hundred eighty-eight DSM-IV BD patients participating in the Brazilian Research Network of Bipolar Disorders were included. Participants were divided between those with FHMD (n=230) and without FHMD (n=258). We compared these two groups on demographic and clinical variables and performed a logistic regression to identify which variables were most strongly associated with positive family history of mood disorders. BD patients with FHMD presented with significantly higher lifetime prevalence of any anxiety disorder, obsessive-compulsive disorder, social phobia, substance abuse, and were more likely to present history of suicide attempts, family history of suicide attempts and suicide, and more psychiatric hospitalizations than BD patients without FHMD. Logistic regression showed that the variables most strongly associated with a positive FHMD were any comorbid anxiety disorder, comorbid substance abuse, and family history of suicide. Cross-sectional study and verification of FHMD by indirect information. BD patients with FHMD differ from BD patients without FHMD in rates of comorbid anxiety disorder and substance abuse, number of hospitalizations and suicide attempts. As FHMD is routinely assessed in clinical practice, these findings may help to identify patients at risk for particular manifestations of BD and may point to a common, genetically determined neurobiological substrate that increases the risk of conditions such as comorbidities and suicidality in BD patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Reliability assessment of a multistate freight network for perishable merchandise with multiple suppliers and buyers

NASA Astrophysics Data System (ADS)

Lin, Yi-Kuei; Yeh, Cheng-Ta; Huang, Cheng-Fu

2017-01-01

This study develops a multistate freight network for single and perishable merchandise to assess the freight performance, where a node denotes a supplier, a distribution centre, or a buyer, while a logistics company providing a freight traffic service is denoted by an edge. For each logistics company, carrying capacity should be multistate since partial capacity may be reserved by some customers. The merchandise may perish or be perished during conveyance because of disadvantageous weather or collision in carrying such that the number of intact cargoes may be insufficient for the buyers. Hence, according to the perspective of supply chain management, the reliability, a probability of the network to successfully deliver the cargoes from the suppliers to the buyers subject to a budget, is proposed to be a performance index, where the suppliers and buyers are not the previous customers. An algorithm in terms of minimal paths to assess the reliability is developed. A fruit logistics case is adopted to explore the managerial implications of the reliability using sensitivity analysis.

Physical-enhanced secure strategy in an OFDM-PON.

PubMed

Zhang, Lijia; Xin, Xiangjun; Liu, Bo; Yu, Jianjun

2012-01-30

The physical layer of optical access network is vulnerable to various attacks. As the dramatic increase of users and network capacity, the issue of physical-layer security becomes more and more important. This paper proposes a physical-enhanced secure strategy for orthogonal frequency division multiplexing passive optical network (OFDM-PON) by employing frequency domain chaos scrambling. The Logistic map is adopted for the chaos mapping. The chaos scrambling strategy can dynamically allocate the scrambling matrices for different OFDM frames according to the initial condition, which enhance the confidentiality of the physical layer. A mathematical model of this secure system is derived firstly, which achieves a secure transmission at physical layer in OFDM-PON. The results from experimental implementation using Logistic mapped chaos scrambling are also given to further demonstrate the efficiency of this secure strategy. An 10.125 Gb/s 64QAM-OFDM data with Logistic mapped chaos scrambling are successfully transmitted over 25-km single mode fiber (SMF), and the experimental results show that proposed security scheme can protect the system from eavesdropper and attacker, while keep a good performance for the legal ONU.

76 FR 4708 - Agency Information Collection Activities: Submission for OMB Review; Comment Request, OMB No...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-26

... assess disaster logistics planning and response capabilities and identify areas of relative strength and...; Logistics Capability Assessment Tool (LCAT) AGENCY: Federal Emergency Management Agency, DHS. ACTION: Notice...: Collection of Information Title: Logistics Capability Assessment Tool (LCAT). Type of Information Collection...

Research on logistics scheduling based on PSO

NASA Astrophysics Data System (ADS)

Bao, Huifang; Zhou, Linli; Liu, Lei

2017-08-01

With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.

Depression, Smoking, and Ego-Centric Social Network Characteristics in Ohio Appalachian Women

PubMed Central

Lam, Jeffrey; Lu, Bo; Doogan, Nate; Thomson, Tiffany; Ferketich, Amy; Paskett, Electra D.; Wewers, Mary Ellen

2017-01-01

Depression is a serious, costly, and debilitating disorder that is understudied in rural women. Studies show that depression is associated with low social integration and support, but few studies investigate the relationship between depression and social network characteristics. This study examined the associations among women from three Ohio Appalachian counties enrolled in a health study, which aimed to collect information for a future social network smoking cessation intervention. An address-based sampling method was used to randomly select and recruit 404 women. A cross-sectional survey and interview were used to collect information about demographic, psychosocial, behavioral factors, and ego-centric social network characteristics, which are variables derived from an individual (ego) and her first degree contacts (alters). The CES-D scale assessed depressive symptoms. A multivariable logistic regression analysis described the association between these factors and participants with depression (defined as CES-D≥16). Higher network density, or greater number of relationships among alters divided by the total amount of alters, reduced the risk for depression (OR = 0.84, 95% confidence interval [CI] 0.73–0.95). Additionally, women with a high percentage of smoking alters were at greater risk for depression (OR = 1.19, 95% CI 1.02–1.39). Other factors associated with risk for depression included perceived stress score (OR = 1.34, 95% CI 1.24–1.45), loneliness score (OR = 1.37, 95% CI 1.05–1.80), and days with poor physical health (OR = 1.06, 95% CI 1.02–1.11). Findings suggest that psychosocial factors and social networks should be considered when addressing depression in clinical practice. PMID:29081878

Father Absence, Social Networks, and Maternal Ratings of Child Health: Evidence from the 2013 Social Networks and Health Information Survey in Mexico.

PubMed

Edelblute, Heather B; Altman, Claire E

2018-04-01

Objectives To bridge the literature on the effect of father absence, international migration, and social networks on child health, we assess the association between father absence and maternal ratings of child poor health (MCPH). Next we test whether social networks of immediate and extended kin mediate the relationship between fathers' absence and MCPH. Methods Nested logistic regression models predicting MCPH are estimated using the 2013 Social Networks and Health Information Survey, collected in a migrant-sending community in Guanajuato, Mexico. These unique data distinguish among father absence due to migration versus other reasons and between immediate and extended kin ties. Results Descriptive results indicate that 25% of children with migrant fathers are assessed as having poor health, more often than children with present (15.5%) or otherwise absent fathers (17.5%). In the multivariate models, fathers' absence is not predictive of MCPH. However, the presence of extended kin ties for the mother was associated with approximately a 50% reduction in the odds of MCPH. Additionally, mother's poor self-assessed health was associated with increased odds of MCPH while the presence of a co-resident adult lowered the odds of MCPH. In sensitivity analysis among children with migrant fathers, the receipt of paternal remittances lowered the odds of MCPH. Conclusions for Practice Social networks have a direct and positive association with MCPH rather than mediating the father absence-MCPH relationship. The presence of extended kin ties in the local community is salient for more favorable child health and should be considered in public health interventions aimed at improving child health.

Incorporation of RAM techniques into simulation modeling

NASA Astrophysics Data System (ADS)

Nelson, S. C., Jr.; Haire, M. J.; Schryver, J. C.

1995-01-01

This work concludes that reliability, availability, and maintainability (RAM) analytical techniques can be incorporated into computer network simulation modeling to yield an important new analytical tool. This paper describes the incorporation of failure and repair information into network simulation to build a stochastic computer model to represent the RAM Performance of two vehicles being developed for the US Army: The Advanced Field Artillery System (AFAS) and the Future Armored Resupply Vehicle (FARV). The AFAS is the US Army's next generation self-propelled cannon artillery system. The FARV is a resupply vehicle for the AFAS. Both vehicles utilize automation technologies to improve the operational performance of the vehicles and reduce manpower. The network simulation model used in this work is task based. The model programmed in this application requirements a typical battle mission and the failures and repairs that occur during that battle. Each task that the FARV performs--upload, travel to the AFAS, refuel, perform tactical/survivability moves, return to logistic resupply, etc.--is modeled. Such a model reproduces a model reproduces operational phenomena (e.g., failures and repairs) that are likely to occur in actual performance. Simulation tasks are modeled as discrete chronological steps; after the completion of each task decisions are programmed that determine the next path to be followed. The result is a complex logic diagram or network. The network simulation model is developed within a hierarchy of vehicle systems, subsystems, and equipment and includes failure management subnetworks. RAM information and other performance measures are collected which have impact on design requirements. Design changes are evaluated through 'what if' questions, sensitivity studies, and battle scenario changes.

48 CFR 204.7204 - Maintenance of the CAGE file.

Code of Federal Regulations, 2014 CFR

2014-10-01

... electronic equivalent, to— DLA Logistics Information Service, DLIS-SBB, Federal Center, 74 Washington Avenue... Maintenance of the CAGE file. (a) DLA Logistics Information Service will accept written requests for changes...) Additional guidance for maintaining CAGE codes is in Volume 7 of DoD 4100.39-M, Federal Logistics Information...

48 CFR 204.7204 - Maintenance of the CAGE file.

Code of Federal Regulations, 2011 CFR

2011-10-01

... electronic equivalent, to— DLA Logistics Information Service, DLIS-SBB, Federal Center, 74 Washington Avenue... Maintenance of the CAGE file. (a) DLA Logistics Information Service will accept written requests for changes...) Additional guidance for maintaining CAGE codes is in Volume 7 of DoD 4100.39-M, Federal Logistics Information...

48 CFR 204.7204 - Maintenance of the CAGE file.

Code of Federal Regulations, 2013 CFR

2013-10-01

... electronic equivalent, to— DLA Logistics Information Service, DLIS-SBB, Federal Center, 74 Washington Avenue... Maintenance of the CAGE file. (a) DLA Logistics Information Service will accept written requests for changes...) Additional guidance for maintaining CAGE codes is in Volume 7 of DoD 4100.39-M, Federal Logistics Information...

48 CFR 204.7204 - Maintenance of the CAGE file.

Code of Federal Regulations, 2012 CFR

2012-10-01

... electronic equivalent, to— DLA Logistics Information Service, DLIS-SBB, Federal Center, 74 Washington Avenue... Maintenance of the CAGE file. (a) DLA Logistics Information Service will accept written requests for changes...) Additional guidance for maintaining CAGE codes is in Volume 7 of DoD 4100.39-M, Federal Logistics Information...

Sexual Health Information Seeking Online Among Runaway and Homeless Youth.

PubMed

Barman-Adhikari, Anamika; Rice, Eric

2011-06-01

Research shows runaway and homeless youth are reluctant to seek help from traditional health providers. The Internet can be useful in engaging this population and meeting their needs for sexual health information, including information about HIV and other sexually transmitted infections (STIs). Using a sample of homeless youth living in Los Angeles, California in June 2009, this study assesses the frequency with which runaway and homeless youth seek sexual health information via the Internet, and assesses which youth are more likely to engage in seeking health information from online sources. Drawing from Andersen's (1968) health behavior model and Pescosolido's (1992) network episode model, we develop and refine a model for seeking online sexual health information among homeless youth. Rather than testing the predicative strength of a given model, our aim is to identify and explore conceptually driven correlates that may shed light on the characteristics associated with these help seeking behaviors among homeless youth. Analyses using multivariate logistic regression models reveal that among the sample of youth, females and gay males most frequently seek sexual health information online. We demonstrate the structure of social network ties (e.g., connection with parents) and the content of interactions (e.g., e-mail forwards of health information) across ties are critical correlates of online sexual health information seeking. Results show a continued connection with parents via the Internet is significantly associated with youth seeking HIV or STI information. Similarly for content of interactions, more youth who were sent health information online also reported seeking HIV information and HIV-testing information. We discuss implications for intervention and practice, focusing on how the Internet may be used for dissemination of sexual health information and as a resource for social workers to link transient, runaway, and homeless youth to care.

Sexual Health Information Seeking Online Among Runaway and Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Rice, Eric

2012-01-01

Research shows runaway and homeless youth are reluctant to seek help from traditional health providers. The Internet can be useful in engaging this population and meeting their needs for sexual health information, including information about HIV and other sexually transmitted infections (STIs). Using a sample of homeless youth living in Los Angeles, California in June 2009, this study assesses the frequency with which runaway and homeless youth seek sexual health information via the Internet, and assesses which youth are more likely to engage in seeking health information from online sources. Drawing from Andersen’s (1968) health behavior model and Pescosolido’s (1992) network episode model, we develop and refine a model for seeking online sexual health information among homeless youth. Rather than testing the predicative strength of a given model, our aim is to identify and explore conceptually driven correlates that may shed light on the characteristics associated with these help seeking behaviors among homeless youth. Analyses using multivariate logistic regression models reveal that among the sample of youth, females and gay males most frequently seek sexual health information online. We demonstrate the structure of social network ties (e.g., connection with parents) and the content of interactions (e.g., e-mail forwards of health information) across ties are critical correlates of online sexual health information seeking. Results show a continued connection with parents via the Internet is significantly associated with youth seeking HIV or STI information. Similarly for content of interactions, more youth who were sent health information online also reported seeking HIV information and HIV-testing information. We discuss implications for intervention and practice, focusing on how the Internet may be used for dissemination of sexual health information and as a resource for social workers to link transient, runaway, and homeless youth to care. PMID:22247795

Exploring the Lived Experiences of Program Managers Regarding an Automated Logistics Environment

ERIC Educational Resources Information Center

Allen, Ronald Timothy

2014-01-01

Automated Logistics Environment (ALE) is a new term used by Navy and aerospace industry executives to describe the aggregate of logistics-related information systems that support modern aircraft weapon systems. The development of logistics information systems is not always well coordinated among programs, often resulting in solutions that cannot…

Novel solutions for an old disease: diagnosis of acute appendicitis with random forest, support vector machines, and artificial neural networks.

PubMed

Hsieh, Chung-Ho; Lu, Ruey-Hwa; Lee, Nai-Hsin; Chiu, Wen-Ta; Hsu, Min-Huei; Li, Yu-Chuan Jack

2011-01-01

Diagnosing acute appendicitis clinically is still difficult. We developed random forests, support vector machines, and artificial neural network models to diagnose acute appendicitis. Between January 2006 and December 2008, patients who had a consultation session with surgeons for suspected acute appendicitis were enrolled. Seventy-five percent of the data set was used to construct models including random forest, support vector machines, artificial neural networks, and logistic regression. Twenty-five percent of the data set was withheld to evaluate model performance. The area under the receiver operating characteristic curve (AUC) was used to evaluate performance, which was compared with that of the Alvarado score. Data from a total of 180 patients were collected, 135 used for training and 45 for testing. The mean age of patients was 39.4 years (range, 16-85). Final diagnosis revealed 115 patients with and 65 without appendicitis. The AUC of random forest, support vector machines, artificial neural networks, logistic regression, and Alvarado was 0.98, 0.96, 0.91, 0.87, and 0.77, respectively. The sensitivity, specificity, positive, and negative predictive values of random forest were 94%, 100%, 100%, and 87%, respectively. Random forest performed better than artificial neural networks, logistic regression, and Alvarado. We demonstrated that random forest can predict acute appendicitis with good accuracy and, deployed appropriately, can be an effective tool in clinical decision making. Copyright © 2011 Mosby, Inc. All rights reserved.

Cold-Chain Logistics: A Study of the Department of the Defense OCONUS Pre-Pandemic Influenza Vaccine Distribution Network

DTIC Science & Technology

2007-12-01

AUTHOR( S ) LT Daniel “Travis” Jones LT Christopher “Craig” Tecmire 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME( S ...NAME( S ) AND ADDRESS(ES) N/A 10. SPONSORING/MONITORING AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES The views expressed in this thesis are...merchandise, and not necessarily in the warehousing and the internal logistics associated with the production. The typical logistics manager of the 70’ s and

Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaoguang; Lin, Lin; Gen, Mitsuo; Shiota, Mitsushige

Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently. In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.

Educational commitment and social networking: The power of informal networks

NASA Astrophysics Data System (ADS)

Zwolak, Justyna P.; Zwolak, Michael; Brewe, Eric

2018-06-01

The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic and social integration has been long thought to be important for students' persistence. Yet, it is rarely investigated. In particular, the relative impact of in-class and out-of-class interactions remains an open issue. Here, we demonstrate that, surprisingly, for students whose grades fall in the "middle of the pack," the out-of-class network is the most significant predictor of persistence. To do so, we use logistic regression combined with Akaike's information criterion to assess in- and out-of-class networks, grades, and other factors. For students with grades at the very top (and bottom), final grade, unsurprisingly, is the best predictor of persistence—these students are likely already committed (or simply restricted from continuing) so they persist (or drop out). For intermediate grades, though, only out-of-class closeness—a measure of one's immersion in the network—helps predict persistence. This does not negate the need for in-class ties. However, it suggests that, in this cohort, only students that get past the convenient in-class interactions and start forming strong bonds outside of class are or become committed to their studies. Since many students are lost through attrition, our results suggest practical routes for increasing students' persistence in STEM majors.

Sexual Behavior and Network Characteristics and Their Association with Bacterial Sexually Transmitted Infections among Black Men Who Have Sex with Men in the United States.

PubMed

Scott, Hyman M; Irvin, Risha; Wilton, Leo; Van Tieu, Hong; Watson, Chauncey; Magnus, Manya; Chen, Iris; Gaydos, Charlotte; Hussen, Sophia A; Mannheimer, Sharon; Mayer, Kenneth; Hessol, Nancy A; Buchbinder, Susan

2015-01-01

Black men who have sex with men (MSM) have a high prevalence of bacterial sexually transmitted infections (STIs), and individual risk behavior does not fully explain the higher prevalence when compared with other MSM. Using the social-ecological framework, we evaluated individual, social and sexual network, and structural factors and their association with prevalent STIs among Black MSM. The HIV Prevention Trials Network 061 was a multi-site cohort study designed to determine the feasibility and acceptability of a multi-component intervention for Black MSM in six US cities. Baseline assessments included demographics, risk behavior, and social and sexual network questions collected information about the size, nature and connectedness of their sexual network. Logistic regression was used to estimate the odds of having any prevalent sexually transmitted infection (gonorrhea, chlamydia, or syphilis). A total of 1,553 Black MSM were enrolled in this study. In multivariate analysis, older age (aOR = 0.57; 95% CI 0.49-0.66, p<0.001) was associated with a lower odds of having a prevalent STI. Compared with reporting one male sexual partner, having 2-3 partners (aOR = 1.74; 95% CI 1.08-2.81, p<0.024) or more than 4 partners (aOR = 2.29; 95% CI 1.43-3.66, p<0.001) was associated with prevalent STIs. Having both Black and non-Black sexual partners (aOR = 0.67; 95% CI 0.45-0.99, p = 0.042) was the only sexual network factor associated with prevalent STIs. Age and the number and racial composition of sexual partners were associated with prevalent STIs among Black MSM, while other sexual network factors were not. Further studies are needed to evaluate the effects of the individual, network, and structural factors on prevalent STIs among Black MSM to inform combination interventions to reduce STIs among these men.

Sexual Behavior and Network Characteristics and Their Association with Bacterial Sexually Transmitted Infections among Black Men Who Have Sex with Men in the United States

PubMed Central

Scott, Hyman M.; Irvin, Risha; Wilton, Leo; Van Tieu, Hong; Watson, Chauncey; Magnus, Manya; Chen, Iris; Gaydos, Charlotte; Hussen, Sophia A.; Mannheimer, Sharon; Mayer, Kenneth; Hessol, Nancy A.; Buchbinder, Susan

2015-01-01

Background Black men who have sex with men (MSM) have a high prevalence of bacterial sexually transmitted infections (STIs), and individual risk behavior does not fully explain the higher prevalence when compared with other MSM. Using the social-ecological framework, we evaluated individual, social and sexual network, and structural factors and their association with prevalent STIs among Black MSM. Methods The HIV Prevention Trials Network 061 was a multi-site cohort study designed to determine the feasibility and acceptability of a multi-component intervention for Black MSM in six US cities. Baseline assessments included demographics, risk behavior, and social and sexual network questions collected information about the size, nature and connectedness of their sexual network. Logistic regression was used to estimate the odds of having any prevalent sexually transmitted infection (gonorrhea, chlamydia, or syphilis). Results A total of 1,553 Black MSM were enrolled in this study. In multivariate analysis, older age (aOR = 0.57; 95% CI 0.49–0.66, p<0.001) was associated with a lower odds of having a prevalent STI. Compared with reporting one male sexual partner, having 2–3 partners (aOR = 1.74; 95% CI 1.08–2.81, p<0.024) or more than 4 partners (aOR = 2.29; 95% CI 1.43–3.66, p<0.001) was associated with prevalent STIs. Having both Black and non-Black sexual partners (aOR = 0.67; 95% CI 0.45–0.99, p = 0.042) was the only sexual network factor associated with prevalent STIs. Conclusions Age and the number and racial composition of sexual partners were associated with prevalent STIs among Black MSM, while other sexual network factors were not. Further studies are needed to evaluate the effects of the individual, network, and structural factors on prevalent STIs among Black MSM to inform combination interventions to reduce STIs among these men. PMID:26720332

The Southeast Asian Influenza Clinical Research Network: development and challenges for a new multilateral research endeavor.

PubMed

Higgs, Elizabeth S; Hayden, Frederick G; Chotpitayasunondh, Tawee; Whitworth, Jimmy; Farrar, Jeremy

2008-04-01

The Southeast Asia Influenza Clinical Research Network (SEA ICRN) (www.seaclinicalresearch.org) is a recently developed multilateral, collaborative partnership that aims to advance scientific knowledge and management of human influenza through integrated clinical investigation. The partnership of hospitals and institutions in Indonesia, Thailand, United Kingdom, United States, and Viet Nam was established in late 2005 after agreement on the general principles and mission of the initiative and after securing initial financial support. The establishment of the SEA ICRN was both a response to the re-emergence of the highly pathogenic avian influenza A(H5N1) virus in Southeast Asia in late 2003 and an acknowledgment that clinical trials on emerging infectious diseases require prepared and coordinated research capacity. The objectives of the Network also include building sustainable research capacity in the region, compliance with international standards, and prompt dissemination of information and sharing of samples. The scope of research includes diagnosis, pathogenesis, treatment and prevention of human influenza due to seasonal or novel viruses. The Network has overcome numerous logistical and scientific challenges but has now successfully initiated several clinical trials. The establishment of a clinical research network is a vital part of preparedness and an important element during an initial response phase to a pandemic.

Tobacco use and friendship networks: a cross-sectional study among Brazilian adolescents.

PubMed

Jorge, Kelly Oliva; Cota, Luís Otavio; e Ferreira, Efigênia Ferreira; do Vale, Miriam Pimenta; Kawachi, Ichiro; Zarzar, Patrícia Maria

2015-05-01

To determine the prevalence of tobacco use and its association with types of friendship networks, socioeconomic status and gender among Brazilian adolescents. A cross-sectional study was carried out with a representative sample of 905 students aged 15 to 19 years. Information on social networks and tobacco use was collected by the self-administered questionnaire 'Alcohol, Smoking and Substance Involvement Screening Test" and the question "What is your most important group of close friends?'. Socioeconomic status was assessed using an area-based social vulnerability index and type of school. Multinomial logistic regression analysis was employed to test associations between tobacco use and the independent variables. The overall prevalence of tobacco use was 18.9%. Female adolescents had 3.80-fold greater odds of reporting weekly to daily tobacco use compared to male adolescents. Participants who reported that their most important groups of close friends were from church had a lower risk of reporting weekly to daily tobacco use in comparison to those who reported that their best friends were from school. The prevalence of tobacco use was high and was associated with school-based (as compared to church-based) friendship networks, female gender and higher area-level socioeconomic status.

Community mapping and respondent-driven sampling of gay and bisexual men’s communities in Vancouver, Canada

PubMed Central

Forrest, Jamie I; Stevenson, Benjamin; Rich, Ashleigh; Michelow, Warren; Pai, Jayaram; Jollimore, Jody; Raymond, H. Fisher; Moore, David; Hogg, Robert S; Roth, Eric A

2014-01-01

Literature suggests formative research is vital for those using respondent-driven sampling (RDS) to study hidden populations of interest. However, few authors have described in detail how different qualitative methodologies can address the objectives of formative research for understanding the social network properties of the study population, selecting seeds, and adapting survey logistics to best fit the population. In this paper we describe the use of community mapping exercises as a tool within focus groups to collect data on social and sexual network characteristics of gay and bisexual men in the metropolitan area of Vancouver, Canada. Three key themes emerged from analyzing community maps along with other formative research data: (a) connections between physical spaces and social networks of gay and bisexual men, (b) diversity in communities, and (c) substance use connected with formation of sub-communities. We discuss how these themes informed the planning and operations of a longitudinal epidemiological cohort study recruited by RDS. We argue that using community mapping within formative research is a valuable qualitative tool for characterizing network structures of a diverse and differentiated population of gay and bisexual men in a highly developed urban setting. PMID:24512070

Look Who's Talking. Explaining Water-Related Information Sharing and Demand for Action Among Ugandan Villagers

NASA Astrophysics Data System (ADS)

Holvoet, Nathalie; Dewachter, Sara; Molenaers, Nadia

2016-11-01

Many national water policies propagate community-based participatory approaches to overcome weaknesses in supply-driven rural water provision, operation, and maintenance. Citizen involvement is thought to stimulate bottom-up accountability and broaden the information base, which may enrich design and implementation processes and foster improved water accessibility and sustainability. Practices on the ground, however, are embedded in socio-political realities which mediate possible beneficial effects of participatory approaches. This paper builds on full social network data collected in a Ugandan village to study the social and political reality of two distinct levels of participation, i.e. local information sharing among citizens and a more active appeal to fellow citizens to improve water services. We use Logistic Regression Quadratic Assignment Procedure to explore what type of actor and network traits influence information sharing and whether the same factors are in play in the demand for action to remedy water-related problems. Whereas social aspects (social support relations) and homophily (using the same water source, the same gender) play an important role in information sharing, it is the educational level, in particular, of the villager who is called upon that is important when villagers demand action. Our findings also demonstrate that those most in need of safe water do not mobilize their information sharing ties to demand for action. This indicates that building local water policies and practice exclusively on locally existing demand for action may fail to capture the needs of the most deprived citizens.

Research and design of logistical information system based on SOA

NASA Astrophysics Data System (ADS)

Zhang, Bo

2013-03-01

Through the study on the existing logistics information systems and SOA technology, based on the current situation of enterprise logistics management and business features, this paper puts forward a SOA-based logistics system design program. This program is made in the WCF framework, with the combination of SOA and the actual characteristics of logistics enterprises, is simple to realize, easy to operate, and has strong expansion characteristic, therefore has high practical value.

Information Processing Capacity of Dynamical Systems

NASA Astrophysics Data System (ADS)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

Information Processing Capacity of Dynamical Systems

PubMed Central

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

Interplanetary Supply Chain Risk Management

NASA Technical Reports Server (NTRS)

Galluzzi, Michael C.

2018-01-01

Emphasis on KSC ground processing operations, reduced spares up-mass lift requirements and campaign-level flexible path perspective for space systems support as Regolith-based ISM is achieved by; Network modeling for sequencing space logistics and in-space logistics nodal positioning to include feedstock. Economic modeling to assess ISM 3D printing adaption and supply chain risk.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

DISPLA: decision information system for procurement and logistics analysis

NASA Astrophysics Data System (ADS)

Calvo, Alberto B.; Danish, Alexander J.; Lamonakis, Gregory G.

2002-08-01

This paper describes an information-exchange system for Display systems acquisition and logistics support. DISPLA (Decision Information System for Procurement and Logistics Analysis) is an Internet-based system concept for bringing sellers (display system and component suppliers) and buyers (Government Program Offices and System Integrators) together in an electronic exchange to improve the acquisition and logistics analysis support of Flat Panel Displays for the military. A proof-of-concept demonstration is presented in this paper using sample data from vendor Web sites and Government data sources.

Use of neural networks to model complex immunogenetic associations of disease: human leukocyte antigen impact on the progression of human immunodeficiency virus infection.

PubMed

Ioannidis, J P; McQueen, P G; Goedert, J J; Kaslow, R A

1998-03-01

Complex immunogenetic associations of disease involving a large number of gene products are difficult to evaluate with traditional statistical methods and may require complex modeling. The authors evaluated the performance of feed-forward backpropagation neural networks in predicting rapid progression to acquired immunodeficiency syndrome (AIDS) for patients with human immunodeficiency virus (HIV) infection on the basis of major histocompatibility complex variables. Networks were trained on data from patients from the Multicenter AIDS Cohort Study (n = 139) and then validated on patients from the DC Gay cohort (n = 102). The outcome of interest was rapid disease progression, defined as progression to AIDS in <6 years from seroconversion. Human leukocyte antigen (HLA) variables were selected as network inputs with multivariate regression and a previously described algorithm selecting markers with extreme point estimates for progression risk. Network performance was compared with that of logistic regression. Networks with 15 HLA inputs and a single hidden layer of five nodes achieved a sensitivity of 87.5% and specificity of 95.6% in the training set, vs. 77.0% and 76.9%, respectively, achieved by logistic regression. When validated on the DC Gay cohort, networks averaged a sensitivity of 59.1% and specificity of 74.3%, vs. 53.1% and 61.4%, respectively, for logistic regression. Neural networks offer further support to the notion that HIV disease progression may be dependent on complex interactions between different class I and class II alleles and transporters associated with antigen processing variants. The effect in the current models is of moderate magnitude, and more data as well as other host and pathogen variables may need to be considered to improve the performance of the models. Artificial intelligence methods may complement linear statistical methods for evaluating immunogenetic associations of disease.

The ANTARES observation network

NASA Astrophysics Data System (ADS)

Dogliotti, Ana I.; Ulloa, Osvaldo; Muller-Karger, Frank; Hu, Chuanmin; Murch, Brock; Taylor, Charles; Yuras, Gabriel; Kampel, Milton; Lutz, Vivian; Gaeta, Salvador; Gagliardini, Domingo A.; Garcia, Carlos A. E.; Klein, Eduardo; Helbling, Walter; Varela, Ramon; Barbieri, Elena; Negri, Ruben; Frouin, Robert; Sathyendranath, Shubha; Platt, Trevor

2005-08-01

The ANTARES network seeks to understand the variability of the coastal environment on a continental scale and the local, regional, and global factors and processes that effect this change. The focus are coastal zones of South America and the Caribbean Sea. The initial approach includes developing time series of in situ and satellite-based environmental observations in coastal and oceanic regions. The network is constituted by experts that seek to exchange ideas, develop an infrastructure for mutual logistical and knowledge support, and link in situ time series of observations located around the Americas with real-time and historical satellite-derived time series of relevant products. A major objective is to generate information that will be distributed publicly and openly in the service of coastal ocean research, resource management, science-based policy making and education in the Americas. As a first stage, the network has linked oceanographic time series located in Argentina, Brazil, Chile and Venezuela. The group has also developed an online tool to examine satellite data collected with sensors such as NASA's MODIS. Specifically, continental-scale high-resolution (1 km) maps of chlorophyll and of sea surface temperature are generated and served daily over the web according to specifications of users within the ANTARES network. Other satellite-derived variables will be added as support for the network is solidified. ANTARES serves data and offers simple analysis tools that anyone can use with the ultimate goal of improving coastal assessments, management and policies.

Lessons from Initiating the First Veterans Health Administration (VA) Women's Health Practice-based Research Network (WH-PBRN) Study.

PubMed

Pomernacki, Alyssa; Carney, Diane V; Kimerling, Rachel; Nazarian, Deborah; Blakeney, Jill; Martin, Brittany D; Strehlow, Holly; Yosef, Julia; Goldstein, Karen M; Sadler, Anne G; Bean-Mayberry, Bevanne A; Bastian, Lori A; Bucossi, Meggan M; McLean, Caitlin; Sonnicksen, Shannan; Klap, Ruth; Yano, Elizabeth M; Frayne, Susan M

2015-01-01

The Veterans Health Administration (VA) Women's Health Practice-Based Research Network (WH-PBRN) was created to foster innovations for the health care of women veterans. The inaugural study by the WH-PBRN was designed to identify women veterans' own priorities and preferences for mental health services and to inform refinements to WH-PBRN operational procedures. Addressing the latter, this article reports lessons learned from the inaugural study. WH-PBRN site coordinators at the 4 participating sites convened weekly with the study coordinator and the WH-PBRN program manager to address logistical issues and identify lessons learned. Findings were categorized into a matrix of challenges and facilitators related to key study elements. Challenges to the conduct of PBRN-based research included tracking of regulatory documents; cross-site variability in some regulatory processes; and troubleshooting logistics of clinic-based recruitment. Facilitators included a central institutional review board, strong relationships between WH-PBRN research teams and women's health clinic teams, and the perception that women want to help other women veterans. Our experience with the inaugural WH-PBRN study demonstrated the feasibility of establishing productive relationships between local clinicians and researchers, and of recruiting a special population (women veterans) in diverse sites within an integrated health care system. This identified strengths of a PBRN approach. © Copyright 2015 by the American Board of Family Medicine.

Haughton-Mars Project Expedition 2005

NASA Technical Reports Server (NTRS)

deWeck, Olivier; Simchi-Levi, David

2006-01-01

The 2005 expedition to the Haughton-Mars Project (HMP) research station on Devon Island was part of a NASA-funded project on Space Logistics. A team of nine r&searchers from MIT went to the Canadian Arctic to participate in the annual I-IMP field campaign from July 8 to August 12, 2005. We investigated the applicability of the HMP research station as an analogue for planetary macro- and micro-logistics to the Moon and Mars, and began collecting data for modeling purposes. We also tested new technologies and procedures to enhance the ability of humans and robots to jointly explore remote environments. The expedition had four main objectives. We briefly summarize our key findings in each of these areas. 1. Classes of Supply: First, we wanted to understand what supply items existed at the HMP research station in support of planetary science and exploration research at and around the Haughton Crater. We also wanted to quantify the total amount of imported mass at HMP and compare this with predictions from existing parametric lunar base demand models. 2. Macro-Logistics Transportation Network: Our second objective was to understand the nodes, transportation routes, vehicles, capacities and crew and cargo mass flow rates required to support the HMP logistics network. 3. Agent and Asset Tracking: Since the current inventory management system on ISS relies heavily on barcodes and manual tracking, we wanted to test new automated technologies and procedures such as radio frequency identification RFID) to support exploration logistics. 4. Micro-Logistics (EVA): Finally, we wanted to understand the micro-logistical requirements of conducting both short (<1 day) and long traverses in the Mars-analog terrain on Devon Island. Micro-logistics involves the movement of surface vehicles, people and supplies from base to various exploration sites over short distances (<100 km).

Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases.

PubMed

Masías, Víctor Hugo; Valle, Mauricio; Morselli, Carlo; Crespo, Fernando; Vargas, Augusto; Laengle, Sigifredo

2016-01-01

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers-Logistic Regression, Naïve Bayes and Random Forest-with a range of social network measures and the necessary databases to model the verdicts in two real-world cases: the U.S. Watergate Conspiracy of the 1970's and the now-defunct Canada-based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures.

Design of Tactical Support Strategies in Military Logistics: Trade-offs Between Efficiency and Effectiveness. A Column and Cut Generation Modeling Methods

DTIC Science & Technology

2011-12-01

problems need to be addressed in the design of military logis- tics networks. The design problem includes strategic decisions, such as the location of...military strategic logistics [11–13]. In this study, we focus on the design of tactical logistics strategies, which achieve different optimal balances...is clear that our problem is N P−Hard 1 since it generalizes the CVPR and the BPP . Different solutions to handle the loading and routing of

Using an Adaptive Logistics Network in Africa: How Much and How Far

DTIC Science & Technology

2009-06-01

the United States. Arlington, Virginia, 9 May 2005. http://www.fas.org/irp/agency/dod/obc.pdf Coyle, John J ., Edward J . Bardi , and Robert A . Novack... J ” logistics integration (Lyden, 2008). Whereas the term “joint” in a military context signifies more than one branch of military service, Admiral...Conference and Exhibition, 13 March 2008. www.dtic.mil/ndia/2008logistics/Lyden.pdf McKinzie, Kaye LtCol. and J . Wesley Barnes. “ A Review of Strategic

Resilience to leaking--dynamic systems modeling of information security.

PubMed

Hamacher, Kay

2012-01-01

Leaking of confidential material is a major threat to information security within organizations and to society as a whole. This insight has gained traction in the political realm since the activities of Wikileaks, which hopes to attack 'unjust' systems or 'conspiracies'. Eventually, such threats to information security rely on a biologistic argument on the benefits and drawbacks that uncontrolled leaking might pose for 'just' and 'unjust' entities. Such biological metaphors are almost exclusively based on the economic advantage of participants. Here, I introduce a mathematical model of the complex dynamics implied by leaking. The complex interactions of adversaries are modeled by coupled logistic equations including network effects of econo-communication networks. The modeling shows, that there might arise situations where the leaking envisioned and encouraged by Wikileaks and the like can strengthen the defending entity (the 'conspiracy'). In particular, the only severe impact leaking can have on an organization seems to originate in the exploitation of leaks by another entity the organization competes with. Therefore, the model suggests that leaks can be used as a `tactical mean' in direct adversary relations, but do not necessarily increase public benefit and societal immunization to 'conspiracies'. Furthermore, within the model the exploitation of the (open) competition between entities seems to be a more promising approach to control malicious organizations : divide-et-impera policies triumph here.

A Network-Based Kernel Machine Test for the Identification of Risk Pathways in Genome-Wide Association Studies

PubMed Central

Freytag, Saskia; Manitz, Juliane; Schlather, Martin; Kneib, Thomas; Amos, Christopher I.; Risch, Angela; Chang-Claude, Jenny; Heinrich, Joachim; Bickeböller, Heike

2014-01-01

Biological pathways provide rich information and biological context on the genetic causes of complex diseases. The logistic kernel machine test integrates prior knowledge on pathways in order to analyze data from genome-wide association studies (GWAS). Here, the kernel converts genomic information of two individuals to a quantitative value reflecting their genetic similarity. With the selection of the kernel one implicitly chooses a genetic effect model. Like many other pathway methods, none of the available kernels accounts for topological structure of the pathway or gene-gene interaction types. However, evidence indicates that connectivity and neighborhood of genes are crucial in the context of GWAS, because genes associated with a disease often interact. Thus, we propose a novel kernel that incorporates the topology of pathways and information on interactions. Using simulation studies, we demonstrate that the proposed method maintains the type I error correctly and can be more effective in the identification of pathways associated with a disease than non-network-based methods. We apply our approach to genome-wide association case control data on lung cancer and rheumatoid arthritis. We identify some promising new pathways associated with these diseases, which may improve our current understanding of the genetic mechanisms. PMID:24434848

Post-installation activities in the Comprehensive Nuclear Test Ban Treaty (CTBT) International Monitoring System (IMS) infrasound network

NASA Astrophysics Data System (ADS)

Vivas Veloso, J. A.; Christie, D. R.; Hoffmann, T. L.; Campus, P.; Bell, M.; Langlois, A.; Martysevich, P.; Demirovik, E.; Carvalho, J.; Kramer, A.; Wu, Sean F.

2002-11-01

The provisional operation and maintenance of IMS infrasound stations after installation and subsequent certification has the objective to prepare the infrasound network for entry into force of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The goal is to maintain and fine tune the technical capabilities of the network, to repair faulty equipment, and to ensure that stations continue to meet the minimum specifications through evaluation of data quality and station recalibration. Due to the globally dispersed nature of the network, this program constitutes a significant undertaking that requires careful consideration of possible logistic approaches and their financial implications. Currently, 11 of the 60 IMS infrasound stations are transmitting data in the post-installation Testing & Evaluation mode. Another 5 stations are under provisional operation and are maintained in post-certification mode. It is expected that 20% of the infrasound network will be certified by the end of 2002. This presentation will focus on the different phases of post-installation activities of the IMS infrasound program and the logistical challenges to be tackled to ensure a cost-efficient management of the network. Specific topics will include Testing & Evaluation and Certification of Infrasound Stations, as well as Configuration Management and Network Sustainment.

Variations in Social Network Type Membership Among Older African Americans, Caribbean Blacks, and Non-Hispanic Whites.

PubMed

Nguyen, Ann W

2017-07-01

This study examined race differences in the probability of belonging to a specific social network typology of family, friends, and church members. Samples of African Americans, Caribbean blacks, and non-Hispanic whites aged 55+ were drawn from the National Survey of American Life. Typology indicators related to social integration and negative interactions with family, friendship, and church networks were used. Latent class analysis was used to identify typologies, and latent class multinomial logistic regression was used to assess the influence of race, and interactions between race and age, and race and education on typology membership. Four network typologies were identified: optimal (high social integration, low negative interaction), family-centered (high social integration within primarily the extended family network, low negative interaction), strained (low social integration, high negative interaction), and ambivalent (high social integration and high negative interaction). Findings for race and age and race and education interactions indicated that the effects of education and age on typology membership varied by race. Overall, the findings demonstrate how race interacts with age and education to influence the probability of belonging to particular network types. A better understanding of the influence of race, education, and age on social network typologies will inform future research and theoretical developments in this area. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep

PubMed Central

Manlove, Kezia R.; Cassirer, E. Frances; Plowright, Raina K.; Cross, Paul C.; Hudson, Peter J.

2018-01-01

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife.We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia.We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections.Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs.Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit.This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology. PMID:28317104

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep.

PubMed

Manlove, Kezia R; Cassirer, E Frances; Plowright, Raina K; Cross, Paul C; Hudson, Peter J

2017-07-01

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia. We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs. Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep

USGS Publications Warehouse

Manlove, Kezia R.; Cassirer, E. Frances; Plowright, Raina K.; Cross, Paul C.; Hudson, Peter J.

2017-01-01

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife.We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia.We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections.Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs.Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit.This analysis demonstrates a simple logistic regression approach for testing a priorihypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.

Re-Purposing Google Maps Visualisation for Teaching Logistics Systems

ERIC Educational Resources Information Center

Cheong, France; Cheong, Christopher; Jie, Ferry

2012-01-01

Routing is the process of selecting appropriate paths and ordering waypoints in a network. It plays an important part in logistics and supply chain management as choosing the optimal route can minimise distribution costs. Routing optimisation, however, is a difficult problem to solve and computer software is often used to determine the best route.…

How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

PubMed

Saqr, Mohammed; Fors, Uno; Tedre, Matti

2018-02-06

Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance. Interaction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students' performance was calculated, and automatic linear regression was used to predict students' performance. By using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user's position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student's position and role in information relay in online case discussions, combined with the strength of that student's network (social capital), can be used as predictors of performance in relevant settings. By using social network analysis, researchers can analyze the social structure of an online course and reveal important information about students' and teachers' interactions that can be valuable in guiding teachers, improve students' engagement, and contribute to learning analytics insights.

Android platform based smartphones for a logistical remote association repair framework.

PubMed

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-06-25

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use.

Economic assessment of biodiesel production from waste frying oils.

PubMed

Araujo, Victor Kraemer Wermelinger Sancho; Hamacher, Silvio; Scavarda, Luiz Felipe

2010-06-01

Waste frying oils (WFO) can be a good source for the production of biodiesel because this raw material is not part of the food chain, is low cost and can be used in a way that resolves environmental problems (i.e. WFO is no longer thrown into the sewage network). The goal of this article is to propose a method to evaluate the costs of biodiesel production from WFO to develop an economic assessment of this alternative. This method embraces a logistics perspective, as the cost of collection of oil from commercial producers and its delivery to biodiesel depots or plants can be relevant and is an issue that has been little explored in the academic literature. To determine the logistics cost, a mathematical programming model is proposed to solve the vehicle routing problem (VRP), which was applied in an important urban center in Brazil (Rio de Janeiro), a relevant and potential center for biodiesel production and consumption. Eighty-one biodiesel cost scenarios were compared with information on the commercialization of biodiesel in Brazil. The results obtained demonstrate the economic viability of biodiesel production from WFO in the urban center studied and the relevance of logistics in the total biodiesel production cost. (c) 2010 Elsevier Ltd. All rights reserved.

Architectural Guidelines for Multimedia and Hypermedia Data Interchange: Computer Aided Acquisition and Logistics Support/Concurrent Engineering (CALS/ CE) and Electronic Commerce/Electronic Data Interchange (EC/EDI)

DTIC Science & Technology

1991-09-01

other networks . 69 For example, E-mail can be sent to an SNA network through a Softswitch gateway, but at a very slow rate. As discussed in Chapter III...10 6. Communication Protocols ..................... 10 D. NEW INFRASTRUCTURES ....................... 11 1. CALS Test Network (CTN...11 2. Industrial Networks ......................... 12 3. FTS-2000 and ISDN ........................ 12 4. CALS Operational Resource

Mitigating TCP Degradation over Intermittent Link Failures using Intermediate Buffers

DTIC Science & Technology

2006-06-01

signal strength [10]. The Preemptive routing in ad hoc networks [10] attempts to predict that a route will fail by looking at the signal power of the...when the error rate is high there are non -optimal back offs in the Retransmission Timeout. And third, in the high error situation the slow start...network storage follows. In Beck et. al. [3], Logistical Networking is outlined as a means of storing data throughout the network. End to end

Methods for inferring health-related social networks among coworkers from online communication patterns.

PubMed

Matthews, Luke J; DeWan, Peter; Rula, Elizabeth Y

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network.

Methods for Inferring Health-Related Social Networks among Coworkers from Online Communication Patterns

PubMed Central

Matthews, Luke J.; DeWan, Peter; Rula, Elizabeth Y.

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network. PMID:23418436

78 FR 50134 - Altus Pharmaceuticals, Inc., Blackhawk Capital Group BDC, Inc., Cargo Connection Logistics...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

... lack of current and accurate information concerning the securities of Cargo Connection Logistics... Group BDC, Inc., Cargo Connection Logistics Holding, Inc., Diapulse Corporation of America, Globus... current and accurate information concerning the securities of Altus Pharmaceuticals, Inc. because it has...

How do quality information and cost affect patient choice of provider in a tiered network setting? Results from a survey.

PubMed

Sinaiko, Anna D

2011-04-01

To assess how quality information from multiple sources and financial incentives affect consumer choice of physicians in tiered physician networks. Survey of a stratified random sample of Massachusetts state employees. Respondents were assigned a hypothetical structure with differential copayments for "Tier 1" (preferred) and "Tier 2" (nonpreferred) physicians. Half of respondents were told they needed to select a cardiologist, and half were told they needed to select a dermatologist. Patients were asked whether they would choose a Tier 1 doctor, a Tier 2 doctor, or had no preference in a case where they had no further quality information, a case where a family member or friend recommended a Tier 2 doctor, and a case where their personal physician recommended a Tier 2 doctor. The effects of copayments, recommendations, physician specialty, and patient characteristics on the reported probability of selecting a Tier 1 doctor are analyzed using multinomial logit and logistic regression. Relative to a case where there is no copayment differential between tiers, copayment differences of U.S.$10-U.S.$35 increase the number of respondents indicating they would select a Tier 1 physician by 3.5-11.7 percent. Simulations suggest copayments must exceed U.S.$300 to counteract the recommendation for a lower tiered physician from friends, family, or a referring physician. Sensitivity to the copayments varied with physician specialty. Tiered provider networks with these copayment levels appear to have limited influence on physician choice when contradicted by other trusted sources. Consumers' response likely varies with physician specialty. © Health Research and Educational Trust.

Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases

PubMed Central

2016-01-01

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers–Logistic Regression, Naïve Bayes and Random Forest–with a range of social network measures and the necessary databases to model the verdicts in two real–world cases: the U.S. Watergate Conspiracy of the 1970’s and the now–defunct Canada–based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures. PMID:26824351

Artificial Neural Networks: A New Approach to Predicting Application Behavior.

ERIC Educational Resources Information Center

Gonzalez, Julie M. Byers; DesJardins, Stephen L.

2002-01-01

Applied the technique of artificial neural networks to predict which students were likely to apply to one research university. Compared the results to the traditional analysis tool, logistic regression modeling. Found that the addition of artificial intelligence models was a useful new tool for predicting student application behavior. (EV)

Network characteristics and patent value-Evidence from the Light-Emitting Diode industry.

PubMed

Huang, Way-Ren; Hsieh, Chia-Jen; Chang, Ke-Chiun; Kiang, Yen-Jo; Yuan, Chien-Chung; Chu, Woei-Chyn

2017-01-01

This study proposes a different angle to social network analysis that evaluates patent value and explores its influencing factors using the network centrality and network position. This study utilizes a logistic regression model to explore the relationships in the LED industry between patent value and network centrality as measured from out-degree centrality, in-degree centrality, in-closeness centrality, and network position, which is measured from effect size. The empirical result shows that out-degree centrality and in-degree centrality have significant positive effects on patent value and that effect size has a significant negative effect on patent value.

Requirement analysis for the one-stop logistics management of fresh agricultural products

NASA Astrophysics Data System (ADS)

Li, Jun; Gao, Hongmei; Liu, Yuchuan

2017-08-01

Issues and concerns for food safety, agro-processing, and the environmental and ecological impact of food production have been attracted many research interests. Traceability and logistics management of fresh agricultural products is faced with the technological challenges including food product label and identification, activity/process characterization, information systems for the supply chain, i.e., from farm to table. Application of one-stop logistics service focuses on the whole supply chain process integration for fresh agricultural products is studied. A collaborative research project for the supply and logistics of fresh agricultural products in Tianjin was performed. Requirement analysis for the one-stop logistics management information system is studied. The model-driven business transformation, an approach uses formal models to explicitly define the structure and behavior of a business, is applied for the review and analysis process. Specific requirements for the logistic management solutions are proposed. Development of this research is crucial for the solution of one-stop logistics management information system integration platform for fresh agricultural products.

A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

ERIC Educational Resources Information Center

Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

2010-01-01

The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

Rapid Network Design

DTIC Science & Technology

2013-09-01

control GCE ground combat element LCE logistics combat element MAGTF Marine Air Ground Task Force MWCS Marine Wing Communications Squadron NPS Naval...elements: command element (CE), ground combat el- ement ( GCE ), aviation combat element (ACE), and logistics combat element (LCE). Each ele- ment...This layer provides unimpeded high-speed connectivity between remote sites and the Internet. Limited security policies are applied at this level to

Optimizing biomass feedstock logistics for forest residue processing and transportation on a tree-shaped road network

Treesearch

Hee Han; Woodam Chung; Lucas Wells; Nathaniel Anderson

2018-01-01

An important task in forest residue recovery operations is to select the most cost-efficient feedstock logistics system for a given distribution of residue piles, road access, and available machinery. Notable considerations include inaccessibility of treatment units to large chip vans and frequent, long-distance mobilization of forestry equipment required to process...

Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

PubMed

Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

2017-06-01

To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (P<0.05). In addition, a comparison of the area under receiver operating characteristic curves of the two models showed a statistically significant difference (P<0.05). The RBF ANNs model is more likely to predict the occurrence of PVT induced by AP than logistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

Fleet logistics system : data administration plans and procedures manual

DOT National Transportation Integrated Search

1996-01-23

This manual provides data administration (DA) procedures for developers and maintainers of Coast Guard fleet logistics information systems. Fleet logistics includes a community of supply, logistics, maintenance, and shipboard functions. The informati...

Analysis of Friendship Network and its Role in Explaining Obesity

PubMed Central

Marathe, Achla; Pan, Zhengzheng; Apolloni, Andrea

2013-01-01

We employ Add Health data to show that friendship networks, constructed from mutual friendship nominations, are important in building weight perception, setting weight goals and measuring social marginalization among adolescents and young adults. We study the relationship between individuals’ perceived weight status, actual weight status, weight status relative to friends’ weight status and weight goals. This analysis helps us understand how individual weight perceptions might be formed, what these perceptions do to the weight goals, and how does friends’ relative weight affect weight perception and weight goals. Combining this information with individuals’ friendship network helps determine the influence of social relationships on weight related variables. Multinomial logistic regression results indicate that relative status is indeed a significant predictor of perceived status, and perceived status is a significant predictor of weight goals. We also address the issue of causality between actual weight status and social marginalization (as measured by the number of friends) and show that obesity precedes social marginalization in time rather than the other way around. This lends credence to the hypothesis that obesity leads to social marginalization not vice versa. Attributes of friendship network can provide new insights into effective interventions for combating obesity since adolescent friendships provide an important social context for weight related behaviors. PMID:25328818

An Interactive Logistics Centre Information Integration System Using Virtual Reality

NASA Astrophysics Data System (ADS)

Hong, S.; Mao, B.

2018-04-01

The logistics industry plays a very important role in the operation of modern cities. Meanwhile, the development of logistics industry has derived various problems that are urgent to be solved, such as the safety of logistics products. This paper combines the study of logistics industry traceability and logistics centre environment safety supervision with virtual reality technology, creates an interactive logistics centre information integration system. The proposed system utilizes the immerse characteristic of virtual reality, to simulate the real logistics centre scene distinctly, which can make operation staff conduct safety supervision training at any time without regional restrictions. On the one hand, a large number of sensor data can be used to simulate a variety of disaster emergency situations. On the other hand, collecting personnel operation data, to analyse the improper operation, which can improve the training efficiency greatly.

Competition of information channels in the spreading of innovations

NASA Astrophysics Data System (ADS)

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Towards smart mobility in urban spaces: Bus tracking and information application

NASA Astrophysics Data System (ADS)

Yue, Wong Seng; Chye, Koh Keng; Hoy, Cheong Wan

2017-10-01

Smart city can be defined as an urban space with complete and advanced infrastructure, intelligent networks and platforms, with millions of sensors among which people themselves and their mobile devices. Urban mobility is one of the global smart city project which offers traffic management in real-time, management of passenger transport means, tracking applications and logistics, car sharing services, car park management and more smart mobility services. Due to the frustrated waiting time for the arrival of buses and the difficulty of accessing shuttle bus-related information in a one-stop centre, bus tracking and information application (BTA) is one the proposed solutions to solve the traffic problems in urban spaces. This paper is aimed to design and develop a bus tracking and information application in a selected city in Selangor state, Malaysia. Next, this application also provides an alternative to design public transport tracking and information application for the urban places in Malaysia. Furthermore, the application also provides a smart solution for the management of public infrastructures and urban facilities in Malaysia in future.

Competition of information channels in the spreading of innovations.

PubMed

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

PubMed Central

Kondo, Katsunori; Yamamoto, Tatsuo; Saito, Masashige; Ito, Kanade; Suzuki, Kayo; Osaka, Ken; Kawachi, Ichiro

2016-01-01

Background We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors. Methods Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10–19, 1–9, and 0). Results Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2). The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation), marital status, health status (diabetes and mental health), and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04–1.11). Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste), significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02–1.08)). Conclusion Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss. PMID:27459102

Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

PubMed

Aida, Jun; Kondo, Katsunori; Yamamoto, Tatsuo; Saito, Masashige; Ito, Kanade; Suzuki, Kayo; Osaka, Ken; Kawachi, Ichiro

2016-01-01

We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors. Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10-19, 1-9, and 0). Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2). The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation), marital status, health status (diabetes and mental health), and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04-1.11). Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste), significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02-1.08)). Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss.

32 CFR Appendix A to Part 300 - Access to DLA Records

Code of Federal Regulations, 2014 CFR

2014-07-01

... OF INFORMATION ACT PROGRAM DEFENSE LOGISTICS AGENCY FREEDOM OF INFORMATION ACT PROGRAM Appendix A to Part 300—Access to DLA Records (a) General. (1) The Defense Logistics Agency, established pursuant to... control of the Assistant Secretary of Defense for Logistics and Materiel Readiness, and is subject to DoD...

Defense Logistics: Improved Performance Measures and Information Needed for Assessing Asset Visibility Initiatives

DTIC Science & Technology

2017-03-01

Accountability Office Highlights of GAO-17-183, a report to congressional committees March 2017 DEFENSE LOGISTICS Improved Performance Measures ...DEFENSE LOGISTICS Improved Performance Measures and Information Needed for Assessing Asset Visibility Initiatives...Report to Congressional Committees March 2017 GAO-17-183 United States Government Accountability Office United States Government

Validation of in situ networks via field sampling: case study in the South Fork Experimental Watershed

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Therefore, these stations are located along field boundaries or in non-representative sites with regards to so...

Landscape-scale spatial abundance distributions discriminate core from random components of boreal lake bacterioplankton.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-12-01

Aquatic bacterial communities harbour thousands of coexisting taxa. To meet the challenge of discriminating between a 'core' and a sporadically occurring 'random' component of these communities, we explored the spatial abundance distribution of individual bacterioplankton taxa across 198 boreal lakes and their associated fluvial networks (188 rivers). We found that all taxa could be grouped into four distinct categories based on model statistical distributions (normal like, bimodal, logistic and lognormal). The distribution patterns across lakes and their associated river networks showed that lake communities are composed of a core of taxa whose distribution appears to be linked to in-lake environmental sorting (normal-like and bimodal categories), and a large fraction of mostly rare bacteria (94% of all taxa) whose presence appears to be largely random and linked to downstream transport in aquatic networks (logistic and lognormal categories). These rare taxa are thus likely to reflect species sorting at upstream locations, providing a perspective of the conditions prevailing in entire aquatic networks rather than only in lakes. © 2016 John Wiley & Sons Ltd/CNRS.

It's Easy To Be Wise after the Event: Concepts for Redesigning an Educational System on Logistics Derived from Reflecting Its Development and Use.

ERIC Educational Resources Information Center

Neumann, Gaby; Ziems, Dietrich; Hopner, Christian

This paper introduces a multimedia-based educational system on logistics developed at the University of Magdeburg (Germany), reports on development and implementation of the prototype, and discusses ideas for redesign. The system was tested, used, and evaluated at the university and within a European network of 24 universities, colleges, and…

Phase transition in tumor growth: I avascular development

NASA Astrophysics Data System (ADS)

Izquierdo-Kulich, E.; Rebelo, I.; Tejera, E.; Nieto-Villar, J. M.

2013-12-01

We propose a mechanism for avascular tumor growth based on a simple chemical network. This model presents a logistic behavior and shows a “second order” phase transition. We prove the fractal origin of the empirical logistics and Gompertz constant and its relation to mitosis and apoptosis rate. Finally, the thermodynamics framework developed demonstrates the entropy production rate as a Lyapunov function during avascular tumor growth.

USMC Logistics Resource Allocation Optimization Tool

DTIC Science & Technology

2015-12-01

Virtual Warehouse Concept ..........................................12  3.  New Models in Logistics Network Design and Implications for Third Party...is the smallest DD activity in terms of manpower , but due to its proximity to USMC units, stocks a much greater quantity of USMC-demanded materiel...salient conclusion to reference with respect to this thesis. 12 2. Inventory Management of Repairables in the U.S. Marine Corps— A Virtual Warehouse

2005 21st National Logistics Conference and Exhibition

DTIC Science & Technology

2005-03-03

Logistics Transformation ... Achieving Knowledge-Enabled Logistics Panel: Sustained Materiel Readiness, by Mr. David V. Pauling , Assistant Deputy Under... John Erb, Deputy Director for Strategic Logistics, The Joint Staff Desired Operational Logistics Capabilities, by COL Dave Mintus, USA, NORAD-US...KBR Government Operations Session 8: Operational Logistics Information Technology Government Chair: Mr. John J. Erb, Deputy Director for Strategic

Profile of e-patients: analysis of their cancer information-seeking from a national survey.

PubMed

Kim, Kyunghye; Kwon, Nahyun

2010-10-01

Researchers have yet to fully understand how competent e-patients are in selecting and using health information sources, or, more importantly, who e-patients are. This study attempted to uncover how cancer e-patients differ from other cancer information seekers in terms of their sociodemographic background, social networks, information competence, and selection of cancer information sources. We analyzed data from the National Cancer Institute's 2005 Health Information National Trends Survey, and a series of chi-square tests showed that factors that distinguished cancer e-patients from other cancer information seekers were age, gender, education, employment status, health insurance, and membership in online support groups. They were not different in the other factors measured by the survey. Our logistic regression analysis revealed that the e-patients were older and talked about their health issues with friends or family more frequently compared with online health information seekers without cancer. While preferring information from their doctors over the Internet, e-patients used the Internet as their primary source. In contrast to previous literature, we found little evidence that e-patients were savvy health information consumers who could make informed decisions on their own health. The findings of this study addressed a need for a better design and delivery of health information literacy programs for cancer e-patients.

Confounding adjustment in comparative effectiveness research conducted within distributed research networks.

PubMed

Toh, Sengwee; Gagne, Joshua J; Rassen, Jeremy A; Fireman, Bruce H; Kulldorff, Martin; Brown, Jeffrey S

2013-08-01

A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interests. We describe the strengths and limitations of different confounding adjustment approaches that can be considered in observational CER studies conducted within DRNs, and the theoretical and practical issues to consider when selecting among them in various study settings. Several methods can be used to adjust for multiple confounders simultaneously, either as individual covariates or as confounder summary scores (eg, propensity scores and disease risk scores), including: (1) centralized analysis of patient-level data, (2) case-centered logistic regression of risk set data, (3) stratified or matched analysis of aggregated data, (4) distributed regression analysis, and (5) meta-analysis of site-specific effect estimates. These methods require different granularities of information be shared across sites and afford investigators different levels of analytic flexibility. DRNs are growing in use and sharing of highly detailed patient-level information is not always feasible in DRNs. Methods that incorporate confounder summary scores allow investigators to adjust for a large number of confounding factors without the need to transfer potentially identifiable information in DRNs. They have the potential to let investigators perform many analyses traditionally conducted through a centralized dataset with detailed patient-level information.

More than just a question of technology: factors related to hospitals' adoption and implementation of health information exchange.

PubMed

Vest, Joshua R

2010-12-01

The provisions of the American Recovery & Reinvestment Act increased the likelihood of more widespread health information exchange (HIE), the electronic transfer of patient-level information between organizations, by essentially mandating the use of electronic health record systems. While important, the sparse body of research on HIE efforts and anecdotal reports indicate the barriers to HIE adoption and implementation include factors beyond simply the presence or absence of a specific technology. This paper examines those technological, organizational, and environmental factors that are associated with both HIE adoption and implementation in a sample of 4830 U.S. hospitals. Factors associated with adoption and implementation were modeled using random-intercept logistic regression. Consistent with a perspective that adoption and implementation are different phenomena, many factors associated with an increased odds of adoption, were unassociated with implementation and vice versa. Non-profit status, public hospitals, more live and operation applications, more emergency room visits, network membership, and the presence of physician portals all increased hospitals' odds of HIE adoption. However, only network membership increased the odds of HIE implementation, whereas competition decreased those odds significantly. This study agreed with earlier case-studies and anecdotal reports that factors beyond technology were important to both adoption and implementation. While current U.S. policy on healthcare information technology adoption focuses on technological barriers, many other non-technological factors may ultimately hinder effective HIE. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Network characteristics and patent value—Evidence from the Light-Emitting Diode industry

PubMed Central

Huang, Way-Ren; Hsieh, Chia-Jen; Chang, Ke-Chiun; Kiang, Yen-Jo; Yuan, Chien-Chung; Chu, Woei-Chyn

2017-01-01

This study proposes a different angle to social network analysis that evaluates patent value and explores its influencing factors using the network centrality and network position. This study utilizes a logistic regression model to explore the relationships in the LED industry between patent value and network centrality as measured from out-degree centrality, in-degree centrality, in-closeness centrality, and network position, which is measured from effect size. The empirical result shows that out-degree centrality and in-degree centrality have significant positive effects on patent value and that effect size has a significant negative effect on patent value. PMID:28817587

Predicting β-Turns in Protein Using Kernel Logistic Regression

PubMed Central

Elbashir, Murtada Khalafallah; Sheng, Yu; Wang, Jianxin; Wu, FangXiang; Li, Min

2013-01-01

A β-turn is a secondary protein structure type that plays a significant role in protein configuration and function. On average 25% of amino acids in protein structures are located in β-turns. It is very important to develope an accurate and efficient method for β-turns prediction. Most of the current successful β-turns prediction methods use support vector machines (SVMs) or neural networks (NNs). The kernel logistic regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems. However, it is often not found in β-turns classification, mainly because it is computationally expensive. In this paper, we used KLR to obtain sparse β-turns prediction in short evolution time. Secondary structure information and position-specific scoring matrices (PSSMs) are utilized as input features. We achieved Q total of 80.7% and MCC of 50% on BT426 dataset. These results show that KLR method with the right algorithm can yield performance equivalent to or even better than NNs and SVMs in β-turns prediction. In addition, KLR yields probabilistic outcome and has a well-defined extension to multiclass case. PMID:23509793

Predicting β-turns in protein using kernel logistic regression.

PubMed

Elbashir, Murtada Khalafallah; Sheng, Yu; Wang, Jianxin; Wu, Fangxiang; Li, Min

2013-01-01

A β-turn is a secondary protein structure type that plays a significant role in protein configuration and function. On average 25% of amino acids in protein structures are located in β-turns. It is very important to develope an accurate and efficient method for β-turns prediction. Most of the current successful β-turns prediction methods use support vector machines (SVMs) or neural networks (NNs). The kernel logistic regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems. However, it is often not found in β-turns classification, mainly because it is computationally expensive. In this paper, we used KLR to obtain sparse β-turns prediction in short evolution time. Secondary structure information and position-specific scoring matrices (PSSMs) are utilized as input features. We achieved Q total of 80.7% and MCC of 50% on BT426 dataset. These results show that KLR method with the right algorithm can yield performance equivalent to or even better than NNs and SVMs in β-turns prediction. In addition, KLR yields probabilistic outcome and has a well-defined extension to multiclass case.

A Capacity Forecast Model for Volatile Data in Maintenance Logistics

NASA Astrophysics Data System (ADS)

Berkholz, Daniel

2009-05-01

Maintenance, repair and overhaul processes (MRO processes) are elaborate and complex. Rising demands on these after sales services require reliable production planning and control methods particularly for maintaining valuable capital goods. Downtimes lead to high costs and an inability to meet delivery due dates results in severe contract penalties. Predicting the required capacities for maintenance orders in advance is often difficult due to unknown part conditions unless the goods are actually inspected. This planning uncertainty results in extensive capital tie-up by rising stock levels within the whole MRO network. The article outlines an approach to planning capacities when maintenance data forecasting is volatile. It focuses on the development of prerequisites for a reliable capacity planning model. This enables a quick response to maintenance orders by employing appropriate measures. The information gained through the model is then systematically applied to forecast both personnel capacities and the demand for spare parts. The improved planning reliability can support MRO service providers in shortening delivery times and reducing stock levels in order to enhance the performance of their maintenance logistics.

Resilience to Leaking — Dynamic Systems Modeling of Information Security

PubMed Central

Hamacher, Kay

2012-01-01

Leaking of confidential material is a major threat to information security within organizations and to society as a whole. This insight has gained traction in the political realm since the activities of Wikileaks, which hopes to attack ‘unjust’ systems or ‘conspiracies’. Eventually, such threats to information security rely on a biologistic argument on the benefits and drawbacks that uncontrolled leaking might pose for ‘just’ and ‘unjust’ entities. Such biological metaphors are almost exclusively based on the economic advantage of participants. Here, I introduce a mathematical model of the complex dynamics implied by leaking. The complex interactions of adversaries are modeled by coupled logistic equations including network effects of econo-communication networks. The modeling shows, that there might arise situations where the leaking envisioned and encouraged by Wikileaks and the like can strengthen the defending entity (the ‘conspiracy’). In particular, the only severe impact leaking can have on an organization seems to originate in the exploitation of leaks by another entity the organization competes with. Therefore, the model suggests that leaks can be used as a `tactical mean’ in direct adversary relations, but do not necessarily increase public benefit and societal immunization to ‘conspiracies’. Furthermore, within the model the exploitation of the (open) competition between entities seems to be a more promising approach to control malicious organizations : divide-et-impera policies triumph here. PMID:23227151

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem.

PubMed

Schilde, M; Doerner, K F; Hartl, R F

2014-10-01

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches.

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS

PubMed Central

Almquist, Zack W.; Butts, Carter T.

2015-01-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach. PMID:26120218

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS.

PubMed

Almquist, Zack W; Butts, Carter T

2014-08-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach.

Support, Inclusion, and Special Education Teachers' Attitudes toward the Education of Students with Autism Spectrum Disorders

PubMed Central

Rodríguez, Isabel R.; Saldaña, David; Moreno, F. Javier

2012-01-01

This study is aimed at assessing special education teachers' attitudes toward teaching pupils with autism spectrum disorders (ASDs) and at determining the role of variables associated with a positive attitude towards the children and their education. Sixty-nine special education teachers were interviewed. The interview included two multiple-choice Likert-type questionnaires, one about teachers' attitude, and another about teachers' perceived needs in relation to the specific education of the pupil with ASD. The study shows a positive view of teachers' expectations regarding the education of pupils with ASD. A direct logistic regression analysis was performed testing for experience with the child, school relationship with an ASD network and type of school (mainstream or special) as potential predictors. Although all three variables are useful in predicting special education teachers' attitudes, the most relevant was the relationship with an ASD network. Need for information and social support are the relatively highest needs expressed by teachers. PMID:22934171

Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

On the basis of dynamical principles we i) advance a derivation of the Logistic Equation (LE), widely employed (among multiple applications) in the simulation of population growth, and ii) demonstrate that scale-invariance and a mean-value constraint are sufficient and necessary conditions for obtaining it. We also generalize the LE to multi-component systems and show that the above dynamical mechanisms underlie a large number of scale-free processes. Examples are presented regarding city-populations, diffusion in complex networks, and popularity of technological products, all of them obeying the multi-component logistic equation in an either stochastic or deterministic way.

Social Context and Problem Factors among Youth with Juvenile Justice Involvement Histories.

PubMed

Voisin, Dexter R; Sales, Jessica M; Hong, Jun Sung; Jackson, Jerrold M; Rose, Eve S; DiClemente, Ralph J

2017-01-01

Youth with juvenile justice histories often reside in poorly resourced communities and report high rates of depression, gang involved networks, and STI-sexual related risk behaviors, compared to their counterparts. The primary aim of this study was to examine the relationship between social context (ie, a combined index score comprised of living in public housing, being a recipient of free school lunch, and witnessing community violence) and risk factors that are disproportionately worse for juvenile justice youth such as depression, gang involved networks and STI sexual risk behaviors. Data were collected from a sample of detained youth ages 14 to 16 (N = 489). Questions assessed demographics, social context, depression, gang-involved networks, and STI risk behaviors. Multiple logistic regression models, controlling for age, gender, race, school enrollment, and family social support, indicated that participants who reported poorer social context had double the odds of reporting being depressed; three times higher odds of being in a gang; three times higher odds of personally knowing a gang member; and double the odds of having engaged in STI-risk behaviors. These results provide significant information that can help service providers target certain profiles of youth with juvenile justice histories for early intervention initiatives.

Artificial neural networks in gynaecological diseases: current and potential future applications.

PubMed

Siristatidis, Charalampos S; Chrelias, Charalampos; Pouliakis, Abraham; Katsimanis, Evangelos; Kassanos, Dimitrios

2010-10-01

Current (and probably future) practice of medicine is mostly associated with prediction and accurate diagnosis. Especially in clinical practice, there is an increasing interest in constructing and using valid models of diagnosis and prediction. Artificial neural networks (ANNs) are mathematical systems being used as a prospective tool for reliable, flexible and quick assessment. They demonstrate high power in evaluating multifactorial data, assimilating information from multiple sources and detecting subtle and complex patterns. Their capability and difference from other statistical techniques lies in performing nonlinear statistical modelling. They represent a new alternative to logistic regression, which is the most commonly used method for developing predictive models for outcomes resulting from partitioning in medicine. In combination with the other non-algorithmic artificial intelligence techniques, they provide useful software engineering tools for the development of systems in quantitative medicine. Our paper first presents a brief introduction to ANNs, then, using what we consider the best available evidence through paradigms, we evaluate the ability of these networks to serve as first-line detection and prediction techniques in some of the most crucial fields in gynaecology. Finally, through the analysis of their current application, we explore their dynamics for future use.

dLOGIS: Disaster Logistics Information System

NASA Astrophysics Data System (ADS)

Koesuma, Sorja; Riantana, Rio; Siswanto, Budi; Aji Purnomo, Fendi; Lelono, Sarjoko

2017-11-01

There are three timing of disaster mitigation which is pre-disaster, emergency response and post-disaster. All of those is important in disaster mitigation, but emergency response is important when we are talking about time. Emergency response has limited time when we should give help. Rapid assessment of kind of logistic, the number of survivors, number children and old people, their gender and also for difable person. It should be done in emergency response time. Therefore we make a mobile application for logistics management system. The name of application is dLOGIS, i.e. Disaster Logistics Information System. The application is based on Android system for mobile phone. Otherwise there is also website version. The website version is for maintenance, data input and registration. So the people or government can use it directly when there is a disaster. After login in dLOGIS, there is five main menus. The first main menu shows disaster information, refugees conditions, logistics needed, available logistics stock and already accepted logistics. In the second menu is used for entering survivors data. The field coordinator can enter survivors data based on the rapid assessment in disaster location. The third menu is used for entering kind of logistic. Number and kind of logistics are based on the BNPB needed standard for the survivor. The fourth menu displays the logistics stock available in field coordinator. And the last menu displays the logistics help that already accepted and sent by donation. By using this application when a disaster happened, field coordinator or local government can use maintenance distribution of logistics base on their needs. Also for donor people who will give help to survivor, they can give logistics with the corresponding of survivor needs.

Research on public logistics centers of Zhenzhou city based on GIS

NASA Astrophysics Data System (ADS)

Zeng, Yuhuai; Chen, Shuisen; Tian, Zhihui; Miao, Quansheng

2008-10-01

The regional public logistics center (PLC) is the intermedium that transports goods or commodity from producer to wholesaler, retailer and end consumer through whole supply chains. According to the Central Place Theory, the PLC should be multi-centric and of more kinds of graded degrees. From the road network planning discipline, an unique index---Importance Degree, is presented to measure the capacity of a PLC. The Importance Degree selects three township criteria: total population, gross industry product and budget income as weights to calculate the weighted vectors by principle component analysis method. Finally, through the clustering analysis, we can get the graded degrees of PLCs. It proves that that this research method is very effective for the road network planning of Zhengzhou City.

Guidelines for the Development and Implementation of a Logistic Resource Annex to the Five Year Defense Program. Volume 4. A Logistic Resource Annex for the Marine Corps Section of the DNFYP

DTIC Science & Technology

1978-10-01

Information ; Logistics Planning; Management Planning and Control; Management Information Systems; Management; Military Supplies; Acquisition; JO...Arlington, Virginia 22202 Contract DAHC 15-73C-0200 Task 78-II-1 CONTENTS GLOSSARY : v SUMMARY ix I. INTRODUCTION 1 II. MARINE CORPS SUPPORT OP...Materiel Command Navy Cost Information System/FYDP Subsystem Non-Industrial Fund Non-Telecommunications Offfice of the Assistant Secretary of Defense

Concurrency and HIV transmission network characteristics among MSM with recent HIV infection.

PubMed

Pines, Heather A; Wertheim, Joel O; Liu, Lin; Garfein, Richard S; Little, Susan J; Karris, Maile Y

2016-11-28

Sexual partner concurrency is common among MSM and may increase the probability of HIV transmission during recent (acute or early) infection. We examined the relationship between concurrency and HIV transmission network characteristics (proxies for HIV transmission) among MSM with recent HIV infection. Observational study integrating behavioral, clinical, and molecular epidemiology. We inferred a partial HIV transmission network using 986 HIV-1 pol sequences obtained from HIV-infected individuals in San Diego, California (1996-2015). We further analyzed data from 285 recently HIV-infected MSM in the network who provided information on up to three sexual partners in the past 3 months, including the timing of intercourse with each partner. Concurrency was defined as sexual partners overlapping in time. Logistic and negative binomial regressions were used to investigate the link between concurrency and HIV transmission network characteristics (i.e. clustering and degree or number of connections to others in the network) among these MSM. Of recently HIV-infected MSM (n = 285), 54% reported concurrent partnerships and 54% were connected by at least one putative transmission link to others (i.e. clustered) in the network (median degree = 1.0; interquartile range: 0.0-3.0). Concurrency was positively associated with HIV transmission network clustering (adjusted odds ratio = 1.83, 95% confidence interval: 1.08, 3.10) and degree (adjusted incidence rate ratio = 1.48, 95% confidence interval: 1.02, 2.15). Our findings provide empirical evidence consistent with the hypothesis that concurrency facilitates HIV transmission during recent infection. Interventions to mitigate the impact of concurrency on HIV transmission may help curb the HIV epidemic among MSM.

Android Platform Based Smartphones for a Logistical Remote Association Repair Framework

PubMed Central

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-01-01

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use. PMID:24967603

Automated system for characterization and classification of malaria-infected stages using light microscopic images of thin blood smears.

PubMed

Das, D K; Maiti, A K; Chakraborty, C

2015-03-01

In this paper, we propose a comprehensive image characterization cum classification framework for malaria-infected stage detection using microscopic images of thin blood smears. The methodology mainly includes microscopic imaging of Leishman stained blood slides, noise reduction and illumination correction, erythrocyte segmentation, feature selection followed by machine classification. Amongst three-image segmentation algorithms (namely, rule-based, Chan-Vese-based and marker-controlled watershed methods), marker-controlled watershed technique provides better boundary detection of erythrocytes specially in overlapping situations. Microscopic features at intensity, texture and morphology levels are extracted to discriminate infected and noninfected erythrocytes. In order to achieve subgroup of potential features, feature selection techniques, namely, F-statistic and information gain criteria are considered here for ranking. Finally, five different classifiers, namely, Naive Bayes, multilayer perceptron neural network, logistic regression, classification and regression tree (CART), RBF neural network have been trained and tested by 888 erythrocytes (infected and noninfected) for each features' subset. Performance evaluation of the proposed methodology shows that multilayer perceptron network provides higher accuracy for malaria-infected erythrocytes recognition and infected stage classification. Results show that top 90 features ranked by F-statistic (specificity: 98.64%, sensitivity: 100%, PPV: 99.73% and overall accuracy: 96.84%) and top 60 features ranked by information gain provides better results (specificity: 97.29%, sensitivity: 100%, PPV: 99.46% and overall accuracy: 96.73%) for malaria-infected stage classification. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

The NASA Real Time Mission Monitor - A Situational Awareness Tool for Conducting Tropical Cyclone Field Experiments

NASA Technical Reports Server (NTRS)

Goodman, Michael; Blakeslee, Richard; Hall, John; Parker, Philip; He, Yubin

2008-01-01

The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, aircraft state information, airborne and surface instruments, and weather state data in to a single visualization package for real time field experiment management. RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses (investigated African easterly waves and Tropical Storm Debby and Helene) during August-September 2006 in Cape Verde, the Tropical Composition, Cloud and Climate Coupling experiment during July-August 2007 in Costa Rica, and the Hurricane Aerosonde mission into Hurricane Noel in 2-3 November 2007. The integration and delivery of this information is made possible through data acquisition systems, network communication links, and network server resources built and managed by collaborators at NASA Marshall Space Flight Center (MSFC) and Dryden Flight Research Center (DFRC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols. Each field experiment presents unique challenges and opportunities for advancing the functionality of RTMM. A description of RTMM, the missions it has supported, and its new features that are under development will be presented.

Planning the bioterrorism response supply chain: learn and live.

PubMed

Brandeau, Margaret L; Hutton, David W; Owens, Douglas K; Bravata, Dena M

2007-01-01

Responses to bioterrorism require rapid procurement and distribution of medical and pharmaceutical supplies, trained personnel, and information. Thus, they present significant logistical challenges. On the basis of a review of the manufacturing and service supply chain literature, the authors identified five supply chain strategies that can potentially increase the speed of response to a bioterrorism attack, reduce inventories, and save money: effective supply chain network design; effective inventory management; postponement of product customization and modularization of component parts; coordination of supply chain stakeholders and appropriate use of incentives; and effective information management. The authors describe how concepts learned from published evaluations of manufacturing and service supply chains, as well as lessons learned from responses to natural disasters, naturally occurring outbreaks, and the 2001 US anthrax attacks, can be applied to design, evaluate, and improve the bioterrorism response supply chain. Such lessons could also be applied to the response supply chains for disease outbreaks and natural and manmade disasters.

Going Mobile: An Empirical Model for Explaining Successful Information Logistics in Ward Rounds.

PubMed

Esdar, Moritz; Liebe, Jan-David; Babitsch, Birgit; Hübner, Ursula

2018-01-01

Medical ward rounds are critical focal points of inpatient care that call for uniquely flexible solutions to provide clinical information at the bedside. While this fact is undoubted, adoption rates of mobile IT solutions remain rather low. Our goal was to investigate if and how mobile IT solutions influence successful information provision at the bedside, i.e. clinical information logistics, as well as to shed light at socio-organizational factors that facilitate adoption rates from a user-centered perspective. Survey data were collected from 373 medical and nursing directors of German, Austrian and Swiss hospitals and analyzed using variance-based Structural Equation Modelling (SEM). The adoption of mobile IT solutions explains large portions of clinical information logistics and is in itself associated with an organizational culture of innovation and end user participation. Results should encourage decision makers to understand mobility as a core constituent of information logistics and thus to promote close end-user participation as well as to work towards building a culture of innovation.

A Data Scheduling and Management Infrastructure for the TEAM Network

NASA Astrophysics Data System (ADS)

Andelman, S.; Baru, C.; Chandra, S.; Fegraus, E.; Lin, K.; Unwin, R.

2009-04-01

The objective of the Tropical Ecology Assessment and Monitoring Network (www.teamnetwork.org) is "To generate real time data for monitoring long-term trends in tropical biodiversity through a global network of TEAM sites (i.e. field stations in tropical forests), providing an early warning system on the status of biodiversity to effectively guide conservation action". To achieve this, the TEAM Network operates by collecting data via standardized protocols at TEAM Sites. The standardized TEAM protocols include the Climate, Vegetation and Terrestrial Vertebrate Protocols. Some sites also implement additional protocols. There are currently 7 TEAM Sites with plans to grow the network to 15 by June 30, 2009 and 50 TEAM Sites by the end of 2010. Climate Protocol The Climate Protocol entails the collection of climate data via meteorological stations located at the TEAM Sites. This includes information such as precipitation, temperature, wind direction and strength and various solar radiation measurements. Vegetation Protocol The Vegetation Protocol collects standardized information on tropical forest trees and lianas. A TEAM Site will have between 6-9 1ha plots where trees and lianas larger than a pre-specified size are mapped, identified and measured. This results in each TEAM Site repeatedly measuring between 3000-5000 trees annually. Terrestrial Vertebrate Protocol The Terrestrial Vertebrate Protocol collects standardized information on mid-sized tropical forest fauna (i.e. birds and mammals). This information is collected via camera traps (i.e. digital cameras with motion sensors housed in weather proof casings). The images taken by the camera trap are reviewed to identify what species are captured in the image by the camera trap. The image and the interpretation of what is in the image are the data for the Terrestrial Vertebrate Protocol. The amount of data collected through the TEAM protocols provides a significant yet exciting IT challenge. The TEAM Network is currently partnering with the San Diego Super Computer Center to build the data management infrastructure. Data collected from the three core protocols as well as others are currently made available through the TEAM Network portal, which provides the content management framework, the data scheduling and management framework, an administrative framework to implement and manage TEAM sites, collaborative tools and a number of tools and applications utilizing Google Map and Google Earth products. A critical element of the TEAM Network data management infrastructure is to make the data publicly available in as close to real-time as possible (the TEAM Network Data Use Policy: http://www.teamnetwork.org/en/data/policy). This requires two essential tasks to be accomplished, 1) A data collection schedule has to be planned, proposed and approved for a given TEAM site. This is a challenging process since TEAM sites are geographically distributed across the tropics and hence have different seasons where they schedule field sampling for the different TEAM protocols. Capturing this information and ensuring that TEAM sites follow the outlined legal contract is key to the data collection process and 2) A stream-lined and efficient information management system to ensure data collected from the field meet the minimum data standards (i.e. are of the highest scientific quality) and are securely transferred, archived, processed and be rapidly made publicaly available, as a finished consumable product via the TEAM Network portal. The TEAM Network is achieving these goals by implementing an end-to-end framework consisting of the Sampling Scheduler application and the Data Management Framework. Sampling Scheduler The Sampling Scheduler is a project management, calendar based portal application that will allow scientists at a TEAM site to schedule field sampling for each of the TEAM protocols implemented at that site. The sampling scheduler addresses the specific requirements established in the TEAM protocols with the logistical scheduling needs of each TEAM Site. For example, each TEAM protocol defines when data must be collected (e.g. time of day, number of times per year, during which seasons, etc) as well as where data must be collected (from which sampling units, which trees, etc). Each TEAM Site has a limited number of resources and must create plans that will both satisfy the requirements of the protocols as well as be logistically feasible for their TEAM Site. With 15 TEAM Sites (and many more coming soon) the schedules of each TEAM Site must be communicated to the Network Office to ensure data are being collected as scheduled and to address the many problems when working in difficult environments like Tropical Forests. The Sampling Schedule provides built-in proposal and approval functionality to ensure that the TEAM Sites are and the Network office are in sync as well as provides the capability to modify schedules when needed. The Data Management Framework The Data Management framework is a three-tier data ingestion, edit and review application for protocols defined in the TEAM network. The data ingestion framework provides online web forms for field personnel to submit and edit data collected at TEAM Sites. These web forms will be accessible from the TEAM content management site. Once the data is securely uploaded, cured, processed and approved, it will be made publicly available for consumption by the scientific community. The Data Management framework, when combined with the Sampling Scheduler provides a closed loop Data Scheduling and Management infrastructure. All information starting from data collection plan, tools to input, modify and curate data, review and run QA/QC tests, as well as verify data are collected as planed are included. Finally, TEAM Network data are available for download via the Data Query and Download Application. This application utilizes a Google Maps custom interface to search, visualize, and download TEAM Network data. References • TEAM Network, http://www.teamnetwork.org • Center for Applied Biodiversity Science, Conservation International. http://science.conservation.org/portal/server.pt • TEAM Data Query and Download Application, http://www.teamnetwork.org/en/data/query

Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

NASA Astrophysics Data System (ADS)

Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

Sex differences in how social networks and relationship quality influence experimental pain sensitivity.

PubMed

Vigil, Jacob M; Rowell, Lauren N; Chouteau, Simone; Chavez, Alexandre; Jaramillo, Elisa; Neal, Michael; Waid, David

2013-01-01

This is the first study to examine how both structural and functional components of individuals' social networks may moderate the association between biological sex and experimental pain sensitivity. One hundred and fifty-two healthy adults (mean age = 22yrs., 53% males) were measured for cold pressor task (CPT) pain sensitivity (i.e., intensity ratings) and core aspects of social networks (e.g., proportion of friends vs. family, affection, affirmation, and aid). Results showed consistent sex differences in how social network structures and intimate relationship functioning modulated pain sensitivity. Females showed higher pain sensitivity when their social networks consisted of a higher proportion of intimate types of relationship partners (e.g., kin vs. non kin), when they had known their network partners for a longer period of time, and when they reported higher levels of logistical support from their significant other (e.g., romantic partner). Conversely, males showed distinct patterns in the opposite direction, including an association between higher levels of logistical support from one's significant other and lower CPT pain intensity. These findings show for the first time that the direction of sex differences in exogenous pain sensitivity is likely dependent on fundamental components of the individual's social environment. The utility of a social-signaling perspective of pain behaviors for examining, comparing, and interpreting individual and group differences in experimental and clinical pain reports is discussed.

Sex Differences in How Social Networks and Relationship Quality Influence Experimental Pain Sensitivity

PubMed Central

Vigil, Jacob M.; Rowell, Lauren N.; Chouteau, Simone; Chavez, Alexandre; Jaramillo, Elisa; Neal, Michael; Waid, David

2013-01-01

This is the first study to examine how both structural and functional components of individuals’ social networks may moderate the association between biological sex and experimental pain sensitivity. One hundred and fifty-two healthy adults (mean age = 22yrs., 53% males) were measured for cold pressor task (CPT) pain sensitivity (i.e., intensity ratings) and core aspects of social networks (e.g., proportion of friends vs. family, affection, affirmation, and aid). Results showed consistent sex differences in how social network structures and intimate relationship functioning modulated pain sensitivity. Females showed higher pain sensitivity when their social networks consisted of a higher proportion of intimate types of relationship partners (e.g., kin vs. non kin), when they had known their network partners for a longer period of time, and when they reported higher levels of logistical support from their significant other (e.g., romantic partner). Conversely, males showed distinct patterns in the opposite direction, including an association between higher levels of logistical support from one’s significant other and lower CPT pain intensity. These findings show for the first time that the direction of sex differences in exogenous pain sensitivity is likely dependent on fundamental components of the individual’s social environment. The utility of a social-signaling perspective of pain behaviors for examining, comparing, and interpreting individual and group differences in experimental and clinical pain reports is discussed. PMID:24223836

Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics

NASA Astrophysics Data System (ADS)

Chen, Lei; Kou, Yingxin; Li, Zhanwu; Xu, An; Wu, Cheng

2018-01-01

We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core-periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes.

Software Development With Application Generators: The Naval Aviation Logistics Command Management Information System Case

DTIC Science & Technology

1992-09-01

Aviation Logistics Command Management Information System (NALCOMIS) prototyping development effort, the critical success factors required to implement prototyping with application generators in other areas of DoD.

Prototyping with Application Generators: Lessons Learned from the Naval Aviation Logistics Command Management Information System Case

DTIC Science & Technology

1992-10-01

Prototyping with Application Generators: Lessons Learned from the Naval Aviation Logistics Command Management Information System Case. This study... management information system to automate manual Naval aviation maintenance tasks-NALCOMIS. With the use of a fourth-generation programming language

Transmission Risks of Schistosomiasis Japonica: Extraction from Back-propagation Artificial Neural Network and Logistic Regression Model

PubMed Central

Xu, Jun-Fang; Xu, Jing; Li, Shi-Zhu; Jia, Tia-Wu; Huang, Xi-Bao; Zhang, Hua-Ming; Chen, Mei; Yang, Guo-Jing; Gao, Shu-Jing; Wang, Qing-Yun; Zhou, Xiao-Nong

2013-01-01

Background The transmission of schistosomiasis japonica in a local setting is still poorly understood in the lake regions of the People's Republic of China (P. R. China), and its transmission patterns are closely related to human, social and economic factors. Methodology/Principal Findings We aimed to apply the integrated approach of artificial neural network (ANN) and logistic regression model in assessment of transmission risks of Schistosoma japonicum with epidemiological data collected from 2339 villagers from 1247 households in six villages of Jiangling County, P.R. China. By using the back-propagation (BP) of the ANN model, 16 factors out of 27 factors were screened, and the top five factors ranked by the absolute value of mean impact value (MIV) were mainly related to human behavior, i.e. integration of water contact history and infection history, family with past infection, history of water contact, infection history, and infection times. The top five factors screened by the logistic regression model were mainly related to the social economics, i.e. village level, economic conditions of family, age group, education level, and infection times. The risk of human infection with S. japonicum is higher in the population who are at age 15 or younger, or with lower education, or with the higher infection rate of the village, or with poor family, and in the population with more than one time to be infected. Conclusion/Significance Both BP artificial neural network and logistic regression model established in a small scale suggested that individual behavior and socioeconomic status are the most important risk factors in the transmission of schistosomiasis japonica. It was reviewed that the young population (≤15) in higher-risk areas was the main target to be intervened for the disease transmission control. PMID:23556015

Predicting The Type Of Pregnancy Using Flexible Discriminate Analysis And Artificial Neural Networks: A Comparison Study

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

Hooman, A.; Mohammadzadeh, M

Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. With regard to the type of pregnancy there are four possible states: wanted, unwanted by wife, unwanted by husband and unwanted by couple. In this paper, we have predicted the type of pregnancy, as well as the factors influencing it using three different models and comparing them. Regarding the type of pregnancy with several levels, we developed a multinomial logistic regression, a neural network and a flexible discrimination based on the data and compared their results using tow statistical indices: Surface under curvemore » (ROC) and kappa coefficient. Based on these tow indices, flexible discrimination proved to be a better fit for prediction on data in comparison to other methods. When the relations among variables are complex, one can use flexible discrimination instead of multinomial logistic regression and neural network to predict the nominal response variables with several levels in order to gain more accurate predictions.« less

Propensity score estimation: machine learning and classification methods as alternatives to logistic regression

PubMed Central

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-01-01

Summary Objective Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this Review was to assess machine learning alternatives to logistic regression which may accomplish the same goals but with fewer assumptions or greater accuracy. Study Design and Setting We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. Results We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (CART), and meta-classifiers (in particular, boosting). Conclusion While the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and to a lesser extent decision trees (particularly CART) appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. PMID:20630332

A Note on the Item Information Function of the Four-Parameter Logistic Model

ERIC Educational Resources Information Center

Magis, David

2013-01-01

This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

PubMed

Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

78 FR 73872 - Agency Information Collection Activities: Proposed Collection; Comment Request; Logistics...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-09

..., and tribal entities to evaluate their current disaster logistics readiness, identify areas for...; Logistics Capability Assistance Tool (LCAT) AGENCY: Federal Emergency Management Agency, DHS. ACTION: Notice... Reduction Act of 1995, this notice seeks comments concerning the Logistics Capability Assistance Tool (LCAT...

Focused Logistics: Putting Agility in Agile Logistics

DTIC Science & Technology

2011-05-19

list, ahead of companies like American Express, DuPont and Coca Cola ; Supports nearly 1,900 weapon systems; DLA manages eight supply chains and...35 7) Force Health Protection...Distribution, Information Fusion, Joint Theater Logistics Command and Control, Multinational Logistics, Joint Health Services Support, and Agile

Telestroke network fundamentals.

PubMed

Meyer, Brett C; Demaerschalk, Bart M

2012-10-01

The objectives of this manuscript are to identify key components to maintaining the logistic and/or operational sustainability of a telestroke network, to identify best practices to be considered for assessment and management of acute stroke when planning for and developing a telestroke network, to show practical steps to enable progress toward implementing a telestroke solution for optimizing acute stroke care, to incorporate evidence-based practice guidelines and care pathways into a telestroke network, to emphasize technology variables and options, and to propose metrics to use when determining the performance, outcomes, and quality of a telestroke network. Copyright © 2012 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Hybrid information privacy system: integration of chaotic neural network and RSA coding

NASA Astrophysics Data System (ADS)

Hsu, Ming-Kai; Willey, Jeff; Lee, Ting N.; Szu, Harold H.

2005-03-01

Electronic mails are adopted worldwide; most are easily hacked by hackers. In this paper, we purposed a free, fast and convenient hybrid privacy system to protect email communication. The privacy system is implemented by combining private security RSA algorithm with specific chaos neural network encryption process. The receiver can decrypt received email as long as it can reproduce the specified chaos neural network series, so called spatial-temporal keys. The chaotic typing and initial seed value of chaos neural network series, encrypted by the RSA algorithm, can reproduce spatial-temporal keys. The encrypted chaotic typing and initial seed value are hidden in watermark mixed nonlinearly with message media, wrapped with convolution error correction codes for wireless 3rd generation cellular phones. The message media can be an arbitrary image. The pattern noise has to be considered during transmission and it could affect/change the spatial-temporal keys. Since any change/modification on chaotic typing or initial seed value of chaos neural network series is not acceptable, the RSA codec system must be robust and fault-tolerant via wireless channel. The robust and fault-tolerant properties of chaos neural networks (CNN) were proved by a field theory of Associative Memory by Szu in 1997. The 1-D chaos generating nodes from the logistic map having arbitrarily negative slope a = p/q generating the N-shaped sigmoid was given first by Szu in 1992. In this paper, we simulated the robust and fault-tolerance properties of CNN under additive noise and pattern noise. We also implement a private version of RSA coding and chaos encryption process on messages.

Function of local networks in palliative care: a Dutch view.

PubMed

Nikbakht-Van de Sande, C V M Vahedi; van der Rijt, C C D; Visser, A Ph; ten Voorde, M A; Pruyn, J F A

2005-08-01

Although network formation is considered an effective method of stimulating the integrated delivery of palliative care, scientific evidence on the usefulness of network formation is scarce. In 1998 the Ministry of Health of The Netherlands started a 5-year stimulation program on palliative care by founding and funding six regional Centres for the Development of Palliative Care. These centers were structured around pivotal organizations such as university hospitals and comprehensive cancer centers. As part of the stimulation program a locoregional network model was introduced within each center for the Development of Palliative Care to integrate palliative care services in the Dutch health care system. We performed a study on network formation in the southwestern area of The Netherlands with 2.4 million inhabitants. The study aimed to answer the following questions: (1) how do networks in palliative care develop, which care providers participate and how do they function? (2) which are the achievements of the palliative care networks as perceived by their participants? (3) which are the success factors of the palliative care networks according to their participants and which factors predict the achievements? Between September 2000 and January 2004 eight local palliative care networks in the region of the Center for Development of Palliative Care-Rotterdam (southwestern area of The Netherlands) were closely followed to gain information on their characteristics and developmental course. At the start of the study semistructured interviews were held with the coordinators of the eight networks. The information from these interviews and from the network documents were used to constitute a questionnaire to assess the opinions and experiences of the network participants. According to the vast majority of responders, the most important reason to install the networks was the lack of integration between the existing local health care services. The networks were initiated to stimulate mutual collaboration, improve accessibility to health care services and increase the quality of these services. The most important achievements obtained by the palliative care networks were: increase in personal contacts between colleagues in a region, improved engagement and collaboration between participating organizations, enhanced insight in the health care provisions, joined initiatives for the development of new care products, and organization of patient-tailored care. Important success factors for the networks were deemed: fruitful mutual contacts, regular funding and the collective development of care products. By logistic regression analyses, the collective development of new care products and the organization of case discussions between caregivers from different health care services turned out to be the most important predictors for success of the palliative care networks. Projects that stimulate the communication between professionals appear to improve the mutual collaboration between individual participants and between the participating organizations, which consequently enhances the quality of palliative care.

New machine-learning algorithms for prediction of Parkinson's disease

NASA Astrophysics Data System (ADS)

Mandal, Indrajit; Sairam, N.

2014-03-01

This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease (PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference system. New machine-learning methods are proposed and performance comparisons are based on specificity, sensitivity, accuracy and other measurable parameters. The robust methods of treating Parkinson's disease (PD) includes sparse multinomial logistic regression, rotation forest ensemble with support vector machines and principal components analysis, artificial neural networks, boosting methods. A new ensemble method comprising of the Bayesian network optimised by Tabu search algorithm as classifier and Haar wavelets as projection filter is used for relevant feature selection and ranking. The highest accuracy obtained by linear logistic regression and sparse multinomial logistic regression is 100% and sensitivity, specificity of 0.983 and 0.996, respectively. All the experiments are conducted over 95% and 99% confidence levels and establish the results with corrected t-tests. This work shows a high degree of advancement in software reliability and quality of the computer-aided diagnosis system and experimentally shows best results with supportive statistical inference.

Mobile Support For Logistics

DTIC Science & Technology

2016-03-01

Infrastructure to Support Mobile Devices (Takai, 2012, p. 2). The objectives needed in order to meet this goal are to: evolve spectrum management, expand... infrastructure to support wireless capabilities, and establish a mobile device security architecture (Takai, 2012, p. 2). By expanding infrastructure to...often used on Mobile Ad-Hoc Networks (MANETs). MANETS are infrastructure -less networks that include, but are not limited to, mobile devices. These

A Comparison of Alternative Methods of Obtaining Defense Logistics Agency (DLA) Cognizance Spare Parts for Contractor Furnished Equipment (CFE) during Initial Outfitting of New Construction U.S. Navy Ships

DTIC Science & Technology

1991-12-01

database, the Real Time Operation Management Information System (ROMIS), and Fitting Out Management Information System (FOMIS). These three configuration...Codes ROMIS Real Time Operation Management Information System SCLSIS Ship’s Configuration and Logistics Information System SCN Shipbuilding and

A Simulation Based Approach for Contingency Planning for Aircraft Turnaround Operation System Activities in Airline Hubs

NASA Technical Reports Server (NTRS)

Adeleye, Sanya; Chung, Christopher

2006-01-01

Commercial aircraft undergo a significant number of maintenance and logistical activities during the turnaround operation at the departure gate. By analyzing the sequencing of these activities, more effective turnaround contingency plans may be developed for logistical and maintenance disruptions. Turnaround contingency plans are particularly important as any kind of delay in a hub based system may cascade into further delays with subsequent connections. The contingency sequencing of the maintenance and logistical turnaround activities were analyzed using a combined network and computer simulation modeling approach. Experimental analysis of both current and alternative policies provides a framework to aid in more effective tactical decision making.

Survey on paediatric tumour boards in Europe: current situation and results from the ExPo-r-Net project.

PubMed

Juan Ribelles, A; Berlanga, P; Schreier, G; Nitzlnader, M; Brunmair, B; Castel, V; Essiaf, S; Cañete, A; Ladenstein, R

2018-01-08

Under the ExPO-r-NeT project (European Expert Paediatric Oncology Reference Network for Diagnostics and Treatment), we aimed to identify paediatric oncology tumour boards in Europe to investigate the kind of technologies and logistics that are in place in different countries and to explore current differences between regions. A 20-question survey regarding several features of tumor boards was designed. Data collected included infrastructure, organization, and clinical decision-making information from the centres. The survey was distributed to the National Paediatric Haematology and Oncology Societies that forwarded the survey to the sites. For comparative analysis, respondents were grouped into four geographical regions. The questionnaire was distributed amongst 30 countries. Response was obtained from 23 (77%) that altogether have 212 paediatric oncology treating centres. A total of 121 institutions answered (57%). Ninety-one percent of the centres hold multidisciplinary boards; however, international second consultations are performed in 36% and only 15% participate on virtual tumor boards. Videoconferencing facilities and standard operational procedures (SOPs) are available in 49 and 43% of the centres, respectively. There were statistically significant differences between European regions concerning meeting infrastructure and organization/logistics: specific room, projecting equipment, access to medical records, videoconferencing facilities, and existence of SOPs. Paediatric tumor boards are a common feature in Europe. To reduce inequalities and have equal access to healthcare, a virtual network is needed. Important differences on the functioning and access to technology between regions in Europe have been observed and need to be addressed.

Patient engagement in patient-centered outcomes research: challenges, facilitators and actions to strengthen the field.

PubMed

Ellis, Lauren E; Kass, Nancy E

2017-06-01

To describe challenges to and facilitators of patient engagement to inform future strategies and suggested actions to strengthen engagement. Interviews with 19 principal investigators of projects funded by the Patient-Centered Outcomes Research Institute and with 33 patients from 18 of the 19 projects. Facilitators included using existing resources, having clear goals, educating patients and treating patients respectfully. Logistical challenges included extra time and work, institutional barriers and difficulty having meetings. Substantive challenges to selecting, educating and engaging patients, and incorporating feedback were also reported. To bolster the infrastructure for engagement, we suggest funders, institutions and researchers focus on resources and training for researchers and patients, networks and programs to connect stakeholders and model policies.

STS-96 Crew Interview: Dan Barry

NASA Technical Reports Server (NTRS)

1999-01-01

Live footage of a preflight interview with Mission Specialist Daniel T. Barry is seen. The interview addresses many different questions including why Barry became an astronaut, and the events that led to his interest. Other interesting information that this one-on-one interview discusses is the logistics and supply mission, why it is important to send equipment to the International Space Station (ISS), and the Integrated Cargo Carrier (ICC). Barry mentions Discovery's anticipated docking with the ISS, his scheduled space walk with Tamara E. Jernigan, plans for the supply and equipment transfers, and his responsibility during this transfer. A fly-around maneuver to take pictures of the ISS, and the deployment of the Student Tracked Atmospheric Research Satellite for Heuristic International Networking Equipment (STARSHINE) are also discussed.

NASA Experimental Program to Stimulate Competitive Research: South Carolina

NASA Technical Reports Server (NTRS)

Sutton, Michael A.

2004-01-01

The use of an appropriate relationship model is critical for reliable prediction of future urban growth. Identification of proper variables and mathematic functions and determination of the weights or coefficients are the key tasks for building such a model. Although the conventional logistic regression model is appropriate for handing land use problems, it appears insufficient to address the issue of interdependency of the predictor variables. This study used an alternative approach to simulation and modeling urban growth using artificial neural networks. It developed an operational neural network model trained using a robust backpropagation method. The model was applied in the Myrtle Beach region of South Carolina, and tested with both global datasets and areal datasets to examine the strength of both regional models and areal models. The results indicate that the neural network model not only has many theoretic advantages over other conventional mathematic models in representing the complex urban systems, but also is practically superior to the logistic model in its capability to predict urban growth with better - accuracy and less variation. The neural network model is particularly effective in terms of successfully identifying urban patterns in the rural areas where the logistic model often falls short. It was also found from the area-based tests that there are significant intra-regional differentiations in urban growth with different rules and rates. This suggests that the global modeling approach, or one model for the entire region, may not be adequate for simulation of a urban growth at the regional scale. Future research should develop methods for identification and subdivision of these areas and use a set of area-based models to address the issues of multi-centered, intra- regionally differentiated urban growth.

Natural Hazards and Supply Chain Disruptions

NASA Astrophysics Data System (ADS)

Haraguchi, M.

2016-12-01

Natural hazards distress the global economy through disruptions in supply chain networks. Moreover, despite increasing investment to infrastructure for disaster risk management, economic damages and losses caused by natural hazards are increasing. Manufacturing companies today have reduced inventories and streamlined logistics in order to maximize economic competitiveness. As a result, today's supply chains are profoundly susceptible to systemic risks, which are the risk of collapse of an entire network caused by a few node of the network. For instance, the prolonged floods in Thailand in 2011 caused supply chain disruptions in their primary industries, i.e. electronic and automotive industries, harming not only the Thai economy but also the global economy. Similar problems occurred after the Great East Japan Earthquake and Tsunami in 2011, the Mississippi River floods and droughts during 2011 - 2013, and the Earthquake in Kumamoto Japan in 2016. This study attempts to discover what kind of effective measures are available for private companies to manage supply chain disruptions caused by floods. It also proposes a method to estimate potential risks using a Bayesian network. The study uses a Bayesian network to create synthetic networks that include variables associated with the magnitude and duration of floods, major components of supply chains such as logistics, multiple layers of suppliers, warehouses, and consumer markets. Considering situations across different times, our study shows desirable data requirements for the analysis and effective measures to improve Value at Risk (VaR) for private enterprises and supply chains.

USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 1.

DTIC Science & Technology

1998-12-31

solely to have a record that could be matched with the CMOS receipt data. (This problem is caused by DLA systems that currently do not populate CMOS with...unable to obtain passwords to the Depot D035 systems. Figure 16 shows daily savings as of 30 September 1998 (current time frame ) and projects savings...Engineering, modeling, and systems/software development company LAN Local Area Network LFA Large Frame Aircraft LMA Logistics Management Agency LMR

Technogeopologistics: Supply Networks and Military Power in the Industrial Age

DTIC Science & Technology

2012-06-01

communication ( LOCs ) to the battlefield in ever more complex ways. Thus, logistics exhibit sensitivity to technological change. Logistics also have...War will serve as a lens for sea versus land LOCs . With the addition of the air LOC under the inter-war airpower thinkers Giulio Douhet and Billy...Mitchell, the Second World War will be a testing ground for all three domains. The interaction among sea, land, and air LOCs with both the industrial

Product unit neural network models for predicting the growth limits of Listeria monocytogenes.

PubMed

Valero, A; Hervás, C; García-Gimeno, R M; Zurera, G

2007-08-01

A new approach to predict the growth/no growth interface of Listeria monocytogenes as a function of storage temperature, pH, citric acid (CA) and ascorbic acid (AA) is presented. A linear logistic regression procedure was performed and a non-linear model was obtained by adding new variables by means of a Neural Network model based on Product Units (PUNN). The classification efficiency of the training data set and the generalization data of the new Logistic Regression PUNN model (LRPU) were compared with Linear Logistic Regression (LLR) and Polynomial Logistic Regression (PLR) models. 92% of the total cases from the LRPU model were correctly classified, an improvement on the percentage obtained using the PLR model (90%) and significantly higher than the results obtained with the LLR model, 80%. On the other hand predictions of LRPU were closer to data observed which permits to design proper formulations in minimally processed foods. This novel methodology can be applied to predictive microbiology for describing growth/no growth interface of food-borne microorganisms such as L. monocytogenes. The optimal balance is trying to find models with an acceptable interpretation capacity and with good ability to fit the data on the boundaries of variable range. The results obtained conclude that these kinds of models might well be very a valuable tool for mathematical modeling.

Selecting a provider: what factors influence patients' decision making?

PubMed

Abraham, Jean; Sick, Brian; Anderson, Joseph; Berg, Andrea; Dehmer, Chad; Tufano, Amanda

2011-01-01

Each year consumers make a variety of decisions relating to their healthcare. Some experts argue that stronger consumer engagement in decisions about where to obtain medical care is an important mechanism for improving efficiency in healthcare delivery and financing. Consumers' ability and motivation to become more active decision makers are affected by several factors, including financial incentives and access to information. This study investigates the set of factors that consumers consider when selecting a provider, including attributes of the provider and the care experience and the reputation of the provider. Additionally, the study evaluates consumers awareness and use of formal sources of provider selection information. Our results from analyzing data from a survey of 467 patients at four clinics in Minnesota suggest that the factors considered of greatest importance include reputation of the physician and reputation of the healthcare organization. Contractual and logistical factors also play a role, with respondents highlighting the importance of seeing a provider affiliated with their health plan and appointment availability. Few respondents indicated that advertisements or formal sources of quality information affected their decision making. The key implication for provider organizations is to carefully manage referral sources to ensure that they consistently meet the needs of referrers. Excellent service to existing patients and to the network of referring physicians yields patient and referrer satisfaction that is critical to attracting new patients. Finally, organizations more generally may want to explore the capabilities of new media and social networking sites for building reputation.

Harnessing Social Networks along with Consumer-Driven Electronic Communication Technologies to Identify and Engage Members of 'Hard-to-Reach' Populations: A Methodological Case Report

PubMed Central

2010-01-01

Background Sampling in the absence of accurate or comprehensive information routinely poses logistical, ethical, and resource allocation challenges in social science, clinical, epidemiological, health service and population health research. These challenges are compounded if few members of a target population know each other or regularly interact. This paper reports on the sampling methods adopted in ethnographic case study research with a 'hard-to-reach' population. Methods To identify and engage a small yet diverse sample of people who met an unusual set of criteria (i.e., pet owners who had been treating cats or dogs for diabetes), four sampling strategies were used. First, copies of a recruitment letter were posted in pet-friendly places. Second, information about the study was diffused throughout the study period via word of mouth. Third, the lead investigator personally sent the recruitment letter via email to a pet owner, who then circulated the information to others, and so on. Fourth, veterinarians were enlisted to refer people who had diabetic pets. The second, third and fourth strategies rely on social networks and represent forms of chain referral sampling. Results Chain referral sampling via email proved to be the most efficient and effective, yielding a small yet diverse group of respondents within one month, and at negligible cost. Conclusions The widespread popularity of electronic communication technologies offers new methodological opportunities for researchers seeking to recruit from hard-to-reach populations. PMID:20089187

Harnessing social networks along with consumer-driven electronic communication technologies to identify and engage members of 'hard-to-reach' populations: a methodological case report.

PubMed

Rock, Melanie J

2010-01-20

Sampling in the absence of accurate or comprehensive information routinely poses logistical, ethical, and resource allocation challenges in social science, clinical, epidemiological, health service and population health research. These challenges are compounded if few members of a target population know each other or regularly interact. This paper reports on the sampling methods adopted in ethnographic case study research with a 'hard-to-reach' population. To identify and engage a small yet diverse sample of people who met an unusual set of criteria (i.e., pet owners who had been treating cats or dogs for diabetes), four sampling strategies were used. First, copies of a recruitment letter were posted in pet-friendly places. Second, information about the study was diffused throughout the study period via word of mouth. Third, the lead investigator personally sent the recruitment letter via email to a pet owner, who then circulated the information to others, and so on. Fourth, veterinarians were enlisted to refer people who had diabetic pets. The second, third and fourth strategies rely on social networks and represent forms of chain referral sampling. Chain referral sampling via email proved to be the most efficient and effective, yielding a small yet diverse group of respondents within one month, and at negligible cost. The widespread popularity of electronic communication technologies offers new methodological opportunities for researchers seeking to recruit from hard-to-reach populations.

Predicting Engineering Student Attrition Risk Using a Probabilistic Neural Network and Comparing Results with a Backpropagation Neural Network and Logistic Regression

ERIC Educational Resources Information Center

Mason, Cindi; Twomey, Janet; Wright, David; Whitman, Lawrence

2018-01-01

As the need for engineers continues to increase, a growing focus has been placed on recruiting students into the field of engineering and retaining the students who select engineering as their field of study. As a result of this concentration on student retention, numerous studies have been conducted to identify, understand, and confirm…

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part II: an illustrative example.

PubMed

Cevenini, Gabriele; Barbini, Emanuela; Scolletta, Sabino; Biagioli, Bonizella; Giomarelli, Pierpaolo; Barbini, Paolo

2007-11-22

Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example. Eight models were developed: Bayes linear and quadratic models, k-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively. Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and k-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, k-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results. Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.

Designing Hydrologic Observatories as a Community Resource

NASA Astrophysics Data System (ADS)

Hooper, R. P.; Duncan, J. M.

2004-12-01

CUAHSI convened a workshop in August 2004 to explore what makes a successful hydrologic observatory. Because of their high cost, only a small number of observatories will be operated, at least initially. (CUAHSI has recommended a pilot network of 5 observatories to develop operational experience and an eventual network of approximately 15 sites.) Because hydrologic scientists can work "in their backyard" (unlike oceanographers or astronomers), hydrologic observatories must offer significant advantages over current methods of field work to successfully attract researchers. Twenty-four teams of scientists submitted "prospectuses" of potential locations for hydrologic observatories for consideration by network attendees. These documents (available at http://www.cuahsi.org) were marketing documents to the workshop participants, who voted for a hypothetical network of 5 observatories from the 24 proposed sites. This network formed the basis for a day of discussions on necessary attributes of core data and how to form a network of observatories from a collection of sites that are designed and implemented individually. Key findings included: 1) Core data must be balanced among disciplines. Although the hydrologic cycle is an organizing principle for the design of HOs, physical data cannot dominate the core data; chemical and biological data, although more expensive to collect, must be given equal footing. 2) New data collection must strategically leverage existing data. Resources are always limited, so that a successful HO must carefully target gaps in existing data, as determined by an explicitly stated conceptual model, and fill them rather than designing an independent study. 3) Site logistics must support remote researchers. Significant resources will be necessary for on-site staff to handle housing, transportation, permitting and other needs. 4) Network-level hypotheses are required early in the implementation of HOs. A network will only emerge around hypotheses. Network-level hypotheses are currently being solicited by CUAHSI to help inform proposing team of important community questions.

Using Video Conferencing to Deliver a Brief Motivational Intervention for Alcohol and Sex Risk to Emergency Department Patients: A Proof-of-Concept Pilot Study

PubMed Central

Celio, Mark A.; Mastroleo, Nadine R.; DiGuiseppi, Graham; Barnett, Nancy P.; Colby, Suzanne M.; Kahler, Christopher W.; Operario, Don; Suffoletto, Brian; Monti, Peter M.

2016-01-01

Brief motivational intervention (MI) is an efficacious approach to reduce heavy drinking and associated sexual risk behavior among Emergency Department (ED) patients, but the intensity of demands placed on ED staff makes the implementation of in-person MIs logistically challenging. This proof-of-concept pilot study examined the acceptability and logistic feasibility of using video-conferencing technology to deliver an MI targeting heavy drinking and risky sexual behavior to patients in an ED setting. Rigorous screening procedures were employed to ensure that the pilot sample represents the target portion of ED patients who would benefit from this multi-target MI. Mixed qualitative and quantitative data from a sample of seven ED patients (57% Female; Mage = 35 years) who received MI by video conference consistently demonstrated high levels of satisfaction, engagement, and acceptability. The observed completion rate supports logistic feasibility, and patient feedback identified methods to improve the experience by using high-definition hardware, ensuring stronger network connectivity, and effectively communicating information regarding protection of privacy. Post-intervention patient ratings and independent ratings of the audio-recorded sessions (using the Motivational Interviewing Skills Coding system) were very high, suggesting that intervention fidelity and MI adherence was not compromised by delivery modality. Collectively, these data suggest video conferencing is a viable technology that can be employed to implement brief evidence-based MIs in ED settings. PMID:28649188

Using Video Conferencing to Deliver a Brief Motivational Intervention for Alcohol and Sex Risk to Emergency Department Patients: A Proof-of-Concept Pilot Study.

PubMed

Celio, Mark A; Mastroleo, Nadine R; DiGuiseppi, Graham; Barnett, Nancy P; Colby, Suzanne M; Kahler, Christopher W; Operario, Don; Suffoletto, Brian; Monti, Peter M

2017-01-01

Brief motivational intervention (MI) is an efficacious approach to reduce heavy drinking and associated sexual risk behavior among Emergency Department (ED) patients, but the intensity of demands placed on ED staff makes the implementation of in-person MIs logistically challenging. This proof-of-concept pilot study examined the acceptability and logistic feasibility of using video-conferencing technology to deliver an MI targeting heavy drinking and risky sexual behavior to patients in an ED setting. Rigorous screening procedures were employed to ensure that the pilot sample represents the target portion of ED patients who would benefit from this multi-target MI. Mixed qualitative and quantitative data from a sample of seven ED patients (57% Female; M age = 35 years) who received MI by video conference consistently demonstrated high levels of satisfaction, engagement, and acceptability. The observed completion rate supports logistic feasibility, and patient feedback identified methods to improve the experience by using high-definition hardware, ensuring stronger network connectivity, and effectively communicating information regarding protection of privacy. Post-intervention patient ratings and independent ratings of the audio-recorded sessions (using the Motivational Interviewing Skills Coding system) were very high, suggesting that intervention fidelity and MI adherence was not compromised by delivery modality. Collectively, these data suggest video conferencing is a viable technology that can be employed to implement brief evidence-based MIs in ED settings.

Supply Chain Management in Humanitarian Relief Logistics

DTIC Science & Technology

2004-03-01

information (1) Pre- and post - disaster assessment (4,14,19,30) Cluster sampling (20) Community vulnerability maps (5,21) Implement a logistics information...evaluated? Are post - disaster assessment responsibilities identified and formally assigned? Have agreements with the host government been made to make use

78 FR 20900 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-08

...; Comment Request AGENCY: United States Air Force Logistics Transformation Office (HQ USAF/A4IT), DoD... United States Air Force Logistics Transformation Office announces a proposed public information... identify necessary course corrections to ensure all personnel have received the information and education...

Comparison of Centralized-Manual, Centralized-Computerized, and Decentralized-Computerized Order and Management Information Models for the Turkish Air Force Logistics System.

DTIC Science & Technology

1986-09-01

differentiation between the systems. This study will investigate an appropriate Order Processing and Management Information System (OP&MIS) to link base-level...methodology: 1. Reviewed the current order processing and information model of the TUAF Logistics System. (centralized-manual model) 2. Described the...RDS program’s order processing and information system. (centralized-computerized model) 3. Described the order irocessing and information system of

Exploration of Logistics Information Technology (IT) Solutions for the Royal Saudi Naval Force Within the Saudi Naval Expansion Program II (SNEP II)

DTIC Science & Technology

2017-12-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT EXPLORATION OF LOGISTICS INFORMATION TECHNOLOGY (IT) SOLUTIONS FOR THE...OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for... information . Send comments regarding this burden estimate or any other aspect of this collection of information , including suggestions for reducing this

Fishing in the Amazonian forest: a gendered social network puzzle

PubMed Central

Díaz-Reviriego, I.; Fernández-Llamazares, Á.; Howard, P.L; Molina, JL; Reyes-García, V

2016-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers’ emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane’ Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers’ expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers’ expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use. PMID:28479670

Fishing in the Amazonian forest: a gendered social network puzzle.

PubMed

Díaz-Reviriego, I; Fernández-Llamazares, Á; Howard, P L; Molina, J L; Reyes-García, V

2017-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers' emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane' Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers' expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers' expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use.

32 CFR 300.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... INFORMATION ACT PROGRAM DEFENSE LOGISTICS AGENCY FREEDOM OF INFORMATION ACT PROGRAM General Provisions § 300.3...-6091. Appeals are to be addressed to the Appellate Authority, Defense Logistics Agency, Suite 1644... (iii) Searching through hardcopy files to include records stored at a Federal Records Center. The term...

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem

PubMed Central

Schilde, M.; Doerner, K.F.; Hartl, R.F.

2014-01-01

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches. PMID:25844013

Service-Oriented Architecture Approach to MAGTF Logistics Support Systems

DTIC Science & Technology

2013-09-01

Support System-Marine Corps IT Information Technology KPI Key Performance Indicators LCE Logistics Command Element ITV In-transit Visibility LCM...building blocks, options, KPI (key performance indicators), design decisions and the corresponding; the physical attributes which is the second attribute... KPI ) that they impact. h. Layer 8 (Information Architecture) The business intelligence layer and information architecture safeguards the inclusion

NDIA 34th Annual National Logistics Forum: Logistics Innovation to Ensure Global Readiness. Held in Tampa, Florida on 15-16 May 2018

DTIC Science & Technology

2018-05-16

KEYNOTE ADDRESS BAYSHORE 1-3 Ward Heinke Vice President, Strategic Alliances, Government Markets , Forcepoint 9:45 – 10:15 am NETWORKING BREAK GALLERIA B 6...or conditions of sale (including allowances, credit terms, and warranties); allocation of markets or customers or division of territories; or refusals...Army War College. 11 WARD HEINKE Vice President, Strategic Alliances, Government Markets Forcepoint Ward is VP for Strategic Alliances, Government

A Collection of Technical Studies Completed for the Computer-Aided Acquisition and Logistic Support (CALS) Program Fiscal Year 1988. Volume 1. Text, Security and Data Management

DTIC Science & Technology

1991-03-01

management methodologies claim to be "expert systems" with security intelligence built into them to I derive a body of both facts and speculative data ... Data Administration considerations . III -21 IV. ARTIFICIAL INTELLIGENCE . .. .. .. . .. IV - 1 A. Description of Technologies . . . . . .. IV - 1 1...as intelligent gateways, wide area networks, and distributed databases for the distribution of logistics products. The integrity of CALS data and the

The role of social support and social networks in smoking behavior among middle and older aged people in rural areas of South Korea: A cross-sectional study

PubMed Central

2010-01-01

Background Although the number of studies on anti-smoking interventions has increased, studies focused on identifying social contextual factors in rural areas are scarce. The purpose of this study was to explore the role of social support and social networks in smoking behavior among middle and older aged people living in rural areas of South Korea. Methods The study employed a cross-sectional design. Participants included 1,057 adults, with a mean age of 60.7 years, residing in rural areas. Information on participants' tobacco use, stress, social support, and social networks was collected using structured questionnaires. The chi-square test, the t-test, ANOVA, and logistic regression were used for data analysis. Results The overall smoking prevalence in the study was 17.4% (men, 38.8%; women, 5.1%). Overall, stress was high among women, and social support was high among men. Smokers had high levels of social support (t = -2.90, p = .0038) and social networks (t = -2.22, p = .0271), as compared to non- and former smokers. Those in the high social support group were likely to be smokers (AOR = 2.21, 95% CI 1.15-4.26). Women with moderate social ties were less likely to smoke (AOR = 0.18, 95% CI 0.05-0.61). Conclusion There was a protective role of a moderate social network level among women, and a high level of social support was associated with smoking behaviors in rural areas. Findings suggest the need for a comprehensive understanding of the functions and characteristics of social contextual factors including social support and social networks in order to conduct more effective anti-smoking interventions in rural areas. PMID:20167103

SIMS: addressing the problem of heterogeneity in databases

NASA Astrophysics Data System (ADS)

Arens, Yigal

1997-02-01

The heterogeneity of remotely accessible databases -- with respect to contents, query language, semantics, organization, etc. -- presents serious obstacles to convenient querying. The SIMS (single interface to multiple sources) system addresses this global integration problem. It does so by defining a single language for describing the domain about which information is stored in the databases and using this language as the query language. Each database to which SIMS is to provide access is modeled using this language. The model describes a database's contents, organization, and other relevant features. SIMS uses these models, together with a planning system drawing on techniques from artificial intelligence, to decompose a given user's high-level query into a series of queries against the databases and other data manipulation steps. The retrieval plan is constructed so as to minimize data movement over the network and maximize parallelism to increase execution speed. SIMS can recover from network failures during plan execution by obtaining data from alternate sources, when possible. SIMS has been demonstrated in the domains of medical informatics and logistics, using real databases.

An Integrative, Multilevel, and Transdisciplinary Research Approach to Challenges of Work, Family, and Health

PubMed Central

Bray, Jeremy W.; Kelly, Erin L.; Hammer, Leslie B.; Almeida, David M.; Dearing, James W.; King, Rosalind B.; Buxton, Orfeu M.

2013-01-01

Recognizing a need for rigorous, experimental research to support the efforts of workplaces and policymakers in improving the health and wellbeing of employees and their families, the National Institutes of Health and the Centers for Disease Control and Prevention formed the Work, Family & Health Network (WFHN). The WFHN is implementing an innovative multisite study with a rigorous experimental design (adaptive randomization, control groups), comprehensive multilevel measures, a novel and theoretically based intervention targeting the psychosocial work environment, and translational activities. This paper describes challenges and benefits of designing a multilevel and transdisciplinary research network that includes an effectiveness study to assess intervention effects on employees, families, and managers; a daily diary study to examine effects on family functioning and daily stress; a process study to understand intervention implementation; and translational research to understand and inform diffusion of innovation. Challenges were both conceptual and logistical, spanning all aspects of study design and implementation. In dealing with these challenges, however, the WFHN developed innovative, transdisciplinary, multi-method approaches to conducting workplace research that will benefit both the research and business communities. PMID:24618878

The relationship between income and food insecurity among Oregon residents: does social support matter?

PubMed

De Marco, Molly; Thorburn, Sheryl

2009-11-01

Millions of US households experienced food insecurity in 2005. Research indicates that low wages and little social support contribute to food insecurity. The present study aimed to examine whether social support moderates the relationship between income and food insecurity. Using a mail survey, we collected data on social support sources (social network, intimate partner and community) and social support functions from a social network (instrumental, informational and emotional). We used hierarchical logistic regression to examine the potential moderation of various measures of social support on the relationship between income and food insecurity, adjusting for potential confounding variables. Oregon, USA. A stratified random sample of Oregonians aged 18-64 years (n 343). We found no evidence of an association between social support and food insecurity, nor any evidence that social support acts as a moderator between income and food insecurity, regardless of the measure of social support used. Although previous research suggested that social support could offset the negative impact of low income on food security, our study did not find support for such an effect.

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

PubMed

Enshaei, A; Robson, C N; Edmondson, R J

2015-11-01

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.

Buddhist social networks and health in old age: A study in central Thailand.

PubMed

Sasiwongsaroj, Kwanchit; Wada, Taizo; Okumiya, Kiyohito; Imai, Hissei; Ishimoto, Yasuko; Sakamoto, Ryota; Fujisawa, Michiko; Kimura, Yumi; Chen, Wen-ling; Fukutomi, Eriko; Matsubayashi, Kozo

2015-11-01

Religious social networks are well known for their capacity to improve individual health, yet the effects of friendship networks within the Buddhist context remain largely unknown. The present study aimed to compare health status and social support in community-dwelling older adults according to their level of Buddhist social network (BSN) involvement, and to examine the association between BSN involvement and functional health among older adults. A cross-sectional survey was carried out among 427 Buddhist community-dwelling older adults aged ≥60 years in Nakhon Pathom, Thailand. Data were collected from home-based personal interviews using a structured questionnaire. Health status was defined according to the measures of basic and advanced activities of daily living (ADL), the 15-item Geriatric Depression Scale and subjective quality of life. Perceived social support was assessed across the four dimensions of tangible, belonging, emotional and information support. Multiple logistic regression was used for analysis. Older adults with BSN involvement reported better functional, mental and social health status, and perceived greater social support than those without BSN involvement. In addition, BSN involvement was positively associated with independence in basic and advanced ADL. After adjusting for age, sex, education, income, morbidity and depressive symptoms, BSN showed a strong association with advanced ADL and a weak association with basic ADL. The results show that involvement in BSN could contribute positively to functional health, particularly with regard to advanced ADL. Addressing the need for involvement in these networks by older adults might help delay functional decline and save on healthcare costs. © 2014 Japan Geriatrics Society.

Utilization of social media and web forums by HIV patients - A cross-sectional study on adherence and reported anxiety level.

PubMed

Longinetti, Elisa; Manoharan, Vinoth; Ayoub, Hala; Surkan, Pamela J; El-Khatib, Ziad

2017-06-01

Due to the high stigma surrounding the Human Immunodeficiency Virus (HIV), people living with HIV (PLWH) often reach out peers over the Internet for emotional and social support. The purpose of this study was to assess the characteristics of PLWH who use HIV internet forums. A cross-sectional study was conducted using an online survey investigating demographic characteristics of PLWH, level of satisfaction of the HIV Internet forums, time living with HIV, forum users' anxiety levels, self-reported adherence to antiretroviral treatment (ART), and reasons for missing pills (n = 222). Logistic regression models were constructed to compare the use of general HIV forums with social networking sites, general HIV forums with group emails, and social networking sites with group emails. Two hundred and twenty-two patients responded to the survey. Social networking sites were used by recently diagnosed PLWH who were on antiretroviral treatment (ART) > 1 year. Young patients (≤ 40 years) and those diagnosed < 1 year before, tended to use social networking sites, while older patients (> 40 years), those diagnosed > 5 years, and from low- and middle-income countries, were more likely to use emailing lists. There was no significant difference between PLWH's adherence to treatment and anxiety levels and the usage of different Internet forums. PLWH's Internet resource choice varied depending on the availability of Internet and illness duration. Different segments of the population could be reached via social networking sites versus group emails to provide HIV information.

Going the Extra Mile: Enabling Joint Logistics for the Tactical War Fighter

DTIC Science & Technology

2010-05-04

few of the links when relocating hubs. Chains v. Networks Supply Chain Too brittle , long CPL, low clustering, simple pattern, simple control...Mass Service Perspective Efficiency Highly Optimized Brittle , Rigid Supply Chains vs Networked Cross-Service Mutual Support Cross-Enterprise...Storage and Distribution Centei\\" Army Logistician 39, no. 6 (November-December 2007): 40. 68 Glen R Dowling, "Army and Marine Joint Ammunition

The social network index and its relation to later-life depression among the elderly aged ≥80 years in Northern Thailand.

PubMed

Aung, Myo Nyein; Moolphate, Saiyud; Aung, Thin Nyein Nyein; Katonyoo, Chitima; Khamchai, Songyos; Wannakrairot, Pongsak

2016-01-01

Having a diverse social network is considered to be beneficial to a person's well-being. The significance, however, of social network diversity in the geriatric assessment of people aged ≥80 years has not been adequately investigated within the Southeast Asian context. This study explored the social networks belonging to the elderly aged ≥80 years and assessed the relation of social network and geriatric depression. This study was a community-based cross-sectional survey conducted in Chiang Mai Province, Northern Thailand. A representative sample of 435 community residents, aged ≥80 years, were included in a multistage sample. The participants' social network diversity was assessed by applying Cohen's social network index (SNI). The geriatric depression scale and activities of daily living measures were carried out during home visits. Descriptive analyses revealed the distribution of SNI, while the relationship between the SNI and the geriatric depression scale was examined by ordinal logistic regression models controlling possible covariants such as age, sex, and educational attainment. The median age of the sample was 83 years, with females comprising of 54.94% of the sample. The participants' children, their neighbors, and members of Buddhist temples were reported as the most frequent contacts of the study participants. Among the 435 participants, 25% were at risk of social isolation due to having a "limited" social network group (SNI 0-3), whereas 37% had a "medium" social network (SNI 4-5), and 38% had a "diverse" social network (SNI ≥6). The SNI was not different among the two sexes. Activities of daily living scores in the diverse social network group were significantly higher than those in the limited social network group. Multivariate ordinal logistic regression analysis models revealed a significant negative association between social network diversity and geriatric depression. Regular and frequent contact with various social contacts may safeguard common geriatric depression among persons aged ≥80 years. As a result, screening those at risk of social isolation is recommended to be integrated into routine primary health care-based geriatric assessment and intervention programs.

Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings.

PubMed

Eken, Cenker; Bilge, Ugur; Kartal, Mutlu; Eray, Oktay

2009-06-03

Logistic regression is the most common statistical model for processing multivariate data in the medical literature. Artificial intelligence models like an artificial neural network (ANN) and genetic algorithm (GA) may also be useful to interpret medical data. The purpose of this study was to perform artificial intelligence models on a medical data sheet and compare to logistic regression. ANN, GA, and logistic regression analysis were carried out on a data sheet of a previously published article regarding patients presenting to an emergency department with flank pain suspicious for renal colic. The study population was composed of 227 patients: 176 patients had a diagnosis of urinary stone, while 51 ultimately had no calculus. The GA found two decision rules in predicting urinary stones. Rule 1 consisted of being male, pain not spreading to back, and no fever. In rule 2, pelvicaliceal dilatation on bedside ultrasonography replaced no fever. ANN, GA rule 1, GA rule 2, and logistic regression had a sensitivity of 94.9, 67.6, 56.8, and 95.5%, a specificity of 78.4, 76.47, 86.3, and 47.1%, a positive likelihood ratio of 4.4, 2.9, 4.1, and 1.8, and a negative likelihood ratio of 0.06, 0.42, 0.5, and 0.09, respectively. The area under the curve was found to be 0.867, 0.720, 0.715, and 0.713 for all applications, respectively. Data mining techniques such as ANN and GA can be used for predicting renal colic in emergency settings and to constitute clinical decision rules. They may be an alternative to conventional multivariate analysis applications used in biostatistics.

48 CFR 204.7202-1 - CAGE codes.

Code of Federal Regulations, 2010 CFR

2010-10-01

....39-M, Federal Logistics Information System (FLIS) Procedures Manual, prescribe use of CAGE codes. (b..., Federal Center, 74 Washington Avenue, North, Battle Creek, MI 49017-3084. Their telephone number is: toll-free 1-888-352-9333); (B) The on-line access to the CAGE file through the Defense Logistics Information...

78 FR 65300 - Notice of Availability (NOA) for General Purpose Warehouse and Information Technology Center...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... (NOA) for General Purpose Warehouse and Information Technology Center Construction (GPW/IT)--Tracy Site-- Environmental Assessment AGENCY: Defense Logistics Agency, DoD. ACTION: Notice of Availability (NOA) for GPW/IT--Tracy Site-- Environmental Assessment. SUMMARY: The Defense Logistics Agency (DLA) announces the...

48 CFR 204.7204 - Maintenance of the CAGE file.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) Submit requests for changes to CAGE files on DD Form 2051, or electronic equivalent, to—Defense Logistics Information Service, DLIS-SBB, Federal Center, 74 Washington Avenue, North, Battle Creek, MI 49017-3084... codes is in Volume 7 of DoD 4100.39-M, Federal Logistics Information System (FLIS) Procedures Manual...

Logistic Approximation to the Normal: The KL Rationale

ERIC Educational Resources Information Center

Savalei, Victoria

2006-01-01

A rationale is proposed for approximating the normal distribution with a logistic distribution using a scaling constant based on minimizing the Kullback-Leibler (KL) information, that is, the expected amount of information available in a sample to distinguish between two competing distributions using a likelihood ratio (LR) test, assuming one of…

Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

PubMed

Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

2010-03-01

Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians Postgraduate Press, Inc.

Differences in Professional and Informal Help Seeking among Older African Americans, Black Caribbeans and Non-Hispanic Whites

PubMed Central

Woodward, Amanda T.; Chatters, Linda M.; Taylor, Robert Joseph; Neighbors, Harold W.; Jackson, James S.

2011-01-01

This study uses a national probability sample of older adults to examine racial and ethnic differences in the use of professional services and informal support for a stressful personal problem. Using data from the National Survey of American Life, this study focuses on African Americans, Black Caribbean immigrants, and Whites aged 55 years and older who experienced a personal problem that caused them significant distress (n=862). Multinomial logistic regression is used to estimate the association of race with the use of professional services only, informal support only, both professional services and informal support, or no help at all, while controlling for demographic and socioeconomic variables, characteristics of the informal support network, the type of problem experienced, and experiences of racial discrimination. Examining the use of professional services and informal support provides a more complete picture of racial and ethnic differences of help-seeking behaviors among older adults, and the factors associated with the sources from which these adults request help. Most respondents use informal support alone or in combination with professional services. Black Caribbeans are more likely than African Americans to rely on informal support only, whereas African Americans are more likely than Whites to not receive help. However, these findings are accounted for by differences in social support and experiences of discrimination. PMID:21666782

Unraveling the contact patterns and network structure of pig shipments in the United States and its association with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks.

PubMed

Lee, Kyuyoung; Polson, Dale; Lowe, Erin; Main, Rodger; Holtkamp, Derald; Martínez-López, Beatriz

2017-03-01

The analysis of the pork value chain is becoming key to understanding the risk of infectious disease dissemination in the swine industry. In this study, we used social network analysis to characterize the swine shipment network structure and properties in a typical multisite swine production system in the US. We also aimed to evaluate the association between network properties and porcine respiratory and reproductive syndrome virus (PRRSV) transmission between production sites. We analyzed the 109,868 swine shipments transporting over 93 million swine between more than 500 production sites from 2012 to 2014. A total of 248 PRRSV positive occurrences were reported from 79 production sites during those 3 years. The temporal dynamics of swine shipments was evaluated by computing network properties in one-month and three-month networks. The association of PRRS occurrence in sow farms with centrality properties from one-month and three-month networks was assessed by using the multilevel logistic regression. All monthly networks showed a scale-free network topology with positive degree assortativity. The regression model revealed that out-degree centrality had a negative association with PRRS occurrence in sow farms in both one-month and three-month networks [OR=0.79 (95% CI, 0.63-0.99) in one-month network and 0.56 (95% CI, 0.36, 0.88) in three-month network] and in-closeness centrality model was positively associated with PRRS occurrence in sow farms in the three-month network [OR=2.45 (95% CI, 1.14-5.26)]. We also describe how the occurrence of porcine epidemic diarrheac (PED) outbreaks severely affected the network structure as well as the PRRS occurrence reports and its association with centrality measures in sow farms. The structure of the swine shipment network and the connectivity between production sites influenced on the PRRSV transmission. The use of network topology and characteristics combining with spatial analysis based on fine scale geographical location of production sites will be useful to inform the design of more cost-efficient, risk-based surveillance and control measures for PRRSV as well as other diseases in the US swine industry. Copyright © 2017 Elsevier B.V. All rights reserved.

Critical issues in medical education and the implications for telemedicine technology.

PubMed

Mahapatra, Ashok Kumar; Mishra, Saroj Kanta; Kapoor, Lily; Singh, Indra Pratap

2009-01-01

Ensuring quality medical education in all the medical colleges across India based on uniform curriculum prescribed by a regulatory body and maintaining a uniform standard are dependent on availability of an excellent infrastructure. Such infrastructure includes qualified teachers, knowledge resources, learning materials, and advanced education technology, which is a challenge in developing countries due to financial and logistic constraints. Advancement in telecommunication, information science, and technology provides an opportunity to exchange knowledge and skill across geographically dispersed organizations by networking academic medical centers of excellence with medical colleges and institutes to practice distance learning using information and communication technology (ICT)-based tools. These may be as basic as commonly used Web-based tools or may be as advanced as virtual reality, simulation, and telepresence-based collaborative learning environment. The scenario in India is no different from any developing country, but there is considerable progress due to technical advancement in these sectors. Telemedicine and tele-education in health science, is gradually getting adopted into the Indian Health System after decade-long pilot studies across the country. A recent recommendation of the National Knowledge Commission, once implemented, would ensure a gigabyte network across all the educational institutions of the country including medical colleges. Availability of indigenous satellite communication technology and the government policy of free bandwidth provision for societal development sector have added strength to set up infrastructure to pilot several telemedicine educational projects across the country.

Evaluation of correlation between CT image features and ERCC1 protein expression in assessing lung cancer prognosis

NASA Astrophysics Data System (ADS)

Tan, Maxine; Emaminejad, Nastaran; Qian, Wei; Sun, Shenshen; Kang, Yan; Guan, Yubao; Lure, Fleming; Zheng, Bin

2014-03-01

Stage I non-small-cell lung cancers (NSCLC) usually have favorable prognosis. However, high percentage of NSCLC patients have cancer relapse after surgery. Accurately predicting cancer prognosis is important to optimally treat and manage the patients to minimize the risk of cancer relapse. Studies have shown that an excision repair crosscomplementing 1 (ERCC1) gene was a potentially useful genetic biomarker to predict prognosis of NSCLC patients. Meanwhile, studies also found that chronic obstructive pulmonary disease (COPD) was highly associated with lung cancer prognosis. In this study, we investigated and evaluated the correlations between COPD image features and ERCC1 gene expression. A database involving 106 NSCLC patients was used. Each patient had a thoracic CT examination and ERCC1 genetic test. We applied a computer-aided detection scheme to segment and quantify COPD image features. A logistic regression method and a multilayer perceptron network were applied to analyze the correlation between the computed COPD image features and ERCC1 protein expression. A multilayer perceptron network (MPN) was also developed to test performance of using COPD-related image features to predict ERCC1 protein expression. A nine feature based logistic regression analysis showed the average COPD feature values in the low and high ERCC1 protein expression groups are significantly different (p < 0.01). Using a five-fold cross validation method, the MPN yielded an area under ROC curve (AUC = 0.669±0.053) in classifying between the low and high ERCC1 expression cases. The study indicates that CT phenotype features are associated with the genetic tests, which may provide supplementary information to help improve accuracy in assessing prognosis of NSCLC patients.

Development of a web service for analysis in a distributed network.

PubMed

Jiang, Xiaoqian; Wu, Yuan; Marsolo, Keith; Ohno-Machado, Lucila

2014-01-01

We describe functional specifications and practicalities in the software development process for a web service that allows the construction of the multivariate logistic regression model, Grid Logistic Regression (GLORE), by aggregating partial estimates from distributed sites, with no exchange of patient-level data. We recently developed and published a web service for model construction and data analysis in a distributed environment. This recent paper provided an overview of the system that is useful for users, but included very few details that are relevant for biomedical informatics developers or network security personnel who may be interested in implementing this or similar systems. We focus here on how the system was conceived and implemented. We followed a two-stage development approach by first implementing the backbone system and incrementally improving the user experience through interactions with potential users during the development. Our system went through various stages such as concept proof, algorithm validation, user interface development, and system testing. We used the Zoho Project management system to track tasks and milestones. We leveraged Google Code and Apache Subversion to share code among team members, and developed an applet-servlet architecture to support the cross platform deployment. During the development process, we encountered challenges such as Information Technology (IT) infrastructure gaps and limited team experience in user-interface design. We figured out solutions as well as enabling factors to support the translation of an innovative privacy-preserving, distributed modeling technology into a working prototype. Using GLORE (a distributed model that we developed earlier) as a pilot example, we demonstrated the feasibility of building and integrating distributed modeling technology into a usable framework that can support privacy-preserving, distributed data analysis among researchers at geographically dispersed institutes.

Development of a Web Service for Analysis in a Distributed Network

PubMed Central

Jiang, Xiaoqian; Wu, Yuan; Marsolo, Keith; Ohno-Machado, Lucila

2014-01-01

Objective: We describe functional specifications and practicalities in the software development process for a web service that allows the construction of the multivariate logistic regression model, Grid Logistic Regression (GLORE), by aggregating partial estimates from distributed sites, with no exchange of patient-level data. Background: We recently developed and published a web service for model construction and data analysis in a distributed environment. This recent paper provided an overview of the system that is useful for users, but included very few details that are relevant for biomedical informatics developers or network security personnel who may be interested in implementing this or similar systems. We focus here on how the system was conceived and implemented. Methods: We followed a two-stage development approach by first implementing the backbone system and incrementally improving the user experience through interactions with potential users during the development. Our system went through various stages such as concept proof, algorithm validation, user interface development, and system testing. We used the Zoho Project management system to track tasks and milestones. We leveraged Google Code and Apache Subversion to share code among team members, and developed an applet-servlet architecture to support the cross platform deployment. Discussion: During the development process, we encountered challenges such as Information Technology (IT) infrastructure gaps and limited team experience in user-interface design. We figured out solutions as well as enabling factors to support the translation of an innovative privacy-preserving, distributed modeling technology into a working prototype. Conclusion: Using GLORE (a distributed model that we developed earlier) as a pilot example, we demonstrated the feasibility of building and integrating distributed modeling technology into a usable framework that can support privacy-preserving, distributed data analysis among researchers at geographically dispersed institutes. PMID:25848586

Prediction of successful weight reduction after bariatric surgery by data mining technologies.

PubMed

Lee, Yi-Chih; Lee, Wei-Jei; Lee, Tian-Shyug; Lin, Yang-Chu; Wang, Weu; Liew, Phui-Ly; Huang, Ming-Te; Chien, Ching-Wen

2007-09-01

Surgery is the only long-lasting effective treatment for morbid obesity. Prediction on successful weight loss after surgery by data mining technologies is lacking. We analyze the available information during the initial evaluation of patients referred to bariatric surgery by data mining methods for predictors of successful weight loss. 249 patients undergoing laparoscopic mini-gastric bypass (LMGB) or adjustable gastric banding (LAGB) were enrolled. Logistic Regression and Artificial Neural Network (ANN) technologies were used to predict weight loss. Overall classification capability of the designed diagnostic models was evaluated by the misclassification costs. We studied 249 patients consisting of 72 men and 177 women over 2 years. Mean age was 33 +/- 9 years. 208 (83.5%) patients had successful weight reduction while 41 (16.5%) did not. Logistic Regression revealed that the type of operation had a significant prediction effect (P = 0.000). Patients receiving LMGB had a better weight loss than those receiving LAGB (78.54% +/- 26.87 vs 43.65% +/- 26.08). ANN provided the same predicted factor on the type of operation but it further proposed that HbAlc and triglyceride were associated with success. HbAlc is lower in the successful than failed group (5.81 +/- 1.06 vs 6.05 +/- 1.49; P = NS), and triglyceride in the successful group is higher than in the failed group (171.29 +/- 112.62 vs 144.07 +/- 89.90; P = NS). Artificial neural network is a better modeling technique and the overall predictive accuracy is higher on the basis of multiple variables related to laboratory tests. LMGB, high preoperative triglyceride level, and low HbAlc level can predict successful weight reduction at 2 years.

3 CFR 8675 - Proclamation 8675 of May 13, 2011. National Defense Transportation Day and National...

Code of Federal Regulations, 2012 CFR

2012-01-01

... ourselves for the next revolutionary breakthroughs in transportation technology. We must provide increased... world-class logistics network, create new jobs, and win the future for our children. In recognition of...

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

PubMed

Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

2018-03-01

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

Optimising reverse logistics network to support policy-making in the case of Electrical and Electronic Equipment.

PubMed

Achillas, Ch; Vlachokostas, Ch; Aidonis, D; Moussiopoulos, N; Iakovou, E; Banias, G

2010-12-01

Due to the rapid growth of Waste Electrical and Electronic Equipment (WEEE) volumes, as well as the hazardousness of obsolete electr(on)ic goods, this type of waste is now recognised as a priority stream in the developed countries. Policy-making related to the development of the necessary infrastructure and the coordination of all relevant stakeholders is crucial for the efficient management and viability of individually collected waste. This paper presents a decision support tool for policy-makers and regulators to optimise electr(on)ic products' reverse logistics network. To that effect, a Mixed Integer Linear Programming mathematical model is formulated taking into account existing infrastructure of collection points and recycling facilities. The applicability of the developed model is demonstrated employing a real-world case study for the Region of Central Macedonia, Greece. The paper concludes with presenting relevant obtained managerial insights. Copyright © 2010 Elsevier Ltd. All rights reserved.

A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

Low emotion-oriented coping and informal help-seeking behaviour as major predictive factors for improvement in major depression at 5-year follow-up in the adult community.

PubMed

Rodgers, S; Vandeleur, C L; Strippoli, M-P F; Castelao, E; Tesic, A; Glaus, J; Lasserre, A M; Müller, M; Rössler, W; Ajdacic-Gross, V; Preisig, M

2017-09-01

Given the broad range of biopsychosocial difficulties resulting from major depressive disorder (MDD), reliable evidence for predictors of improved mental health is essential, particularly from unbiased prospective community samples. Consequently, a broad spectrum of potential clinical and non-clinical predictors of improved mental health, defined as an absence of current major depressive episode (MDE) at follow-up, were examined over a 5-year period in an adult community sample. The longitudinal population-based PsyCoLaus study from the city of Lausanne, Switzerland, was used. Subjects having a lifetime MDD with a current MDE at baseline assessment were selected, resulting in a subsample of 210 subjects. Logistic regressions were applied to the data. Coping styles were the most important predictive factors in the present study. More specifically, low emotion-oriented coping and informal help-seeking behaviour at baseline were associated with the absence of an MDD diagnosis at follow-up. Surprisingly, neither formal help-seeking behaviour, nor psychopharmacological treatment, nor childhood adversities, nor depression subtypes turned out to be relevant predictors in the current study. The paramount role of coping styles as predictors of improvement in depression found in the present study might be a valuable target for resource-oriented therapeutic models. On the one hand, the positive impact of low emotion-oriented coping highlights the utility of clinical interventions interrupting excessive mental ruminations during MDE. On the other hand, the importance of informal social networks raises questions regarding how to enlarge the personal network of affected subjects and on how to best support informal caregivers.

An improved advertising CTR prediction approach based on the fuzzy deep neural network

PubMed Central

Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise. PMID:29727443

An improved advertising CTR prediction approach based on the fuzzy deep neural network.

PubMed

Jiang, Zilong; Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise.

Depression and Chronic Health Conditions Among Latinos: The Role of Social Networks.

PubMed

Soto, Sandra; Arredondo, Elva M; Villodas, Miguel T; Elder, John P; Quintanar, Elena; Madanat, Hala

2016-12-01

The purpose of this study was to examine the "buffering hypothesis" of social network characteristics in the association between chronic conditions and depression among Latinos. Cross-sectional self-report data from the San Diego Prevention Research Center's community survey of Latinos were used (n = 393). Separate multiple logistic regression models tested the role of chronic conditions and social network characteristics in the likelihood of moderate-to-severe depressive symptoms. Having a greater proportion of the network comprised of friends increased the likelihood of depression among those with high cholesterol. Having a greater proportion of women in the social network was directly related to the increased likelihood of depression, regardless of the presence of chronic health conditions. Findings suggest that network characteristics may play a role in the link between chronic conditions and depression among Latinos. Future research should explore strategies targeting the social networks of Latinos to improve health outcomes.

Scaling of global input-output networks

NASA Astrophysics Data System (ADS)

Liang, Sai; Qi, Zhengling; Qu, Shen; Zhu, Ji; Chiu, Anthony S. F.; Jia, Xiaoping; Xu, Ming

2016-06-01

Examining scaling patterns of networks can help understand how structural features relate to the behavior of the networks. Input-output networks consist of industries as nodes and inter-industrial exchanges of products as links. Previous studies consider limited measures for node strengths and link weights, and also ignore the impact of dataset choice. We consider a comprehensive set of indicators in this study that are important in economic analysis, and also examine the impact of dataset choice, by studying input-output networks in individual countries and the entire world. Results show that Burr, Log-Logistic, Log-normal, and Weibull distributions can better describe scaling patterns of global input-output networks. We also find that dataset choice has limited impacts on the observed scaling patterns. Our findings can help examine the quality of economic statistics, estimate missing data in economic statistics, and identify key nodes and links in input-output networks to support economic policymaking.

Impact of RFID Information-Sharing Coordination over a Supply Chain with Reverse Logistics

ERIC Educational Resources Information Center

Nativi Nicolau, Juan Jose

2016-01-01

Companies have adopted environmental practices such as reverse logistics over the past few decades. However, studies show that aligning partners inside the green supply chain can be a substantial problem. This lack of coordination can increase overall supply chain cost. Information technology such as Radio Frequency Identification (RFID) has the…

Management of Customer Service in Terms of Logistics Information Systems

NASA Astrophysics Data System (ADS)

Kampf, Rudolf; Ližbetinová, Lenka; Tišlerová, Kamila

2017-03-01

This paper is focused on perceiving the logistic services as the competition advantage in frame of the ecommerce. Customers consider their purchases in its complexity and all the logistic services should be designed to meet with customers' preferences as much as possible. Our aim was to identify and evaluate of customers perceiving in frame of sales proposals offered by e-shops. Collected data of research were processed with the usage of cluster analysis. The aim of this paper is to present the results and conclusions from this research with focus on the elements of logistics services within e-commerce. These outputs can be used for knowledge base of information systems through which enterprises evaluate their decisions and selection of variants. For the enterprise, it is important to appropriate decisions about resource allocation and design of the structure of logistics services were set based on real customer preferences.

75 FR 17910 - Privacy Act of 1974; Systems of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-08

...; Systems of Records AGENCY: Defense Logistics Agency, DoD. ACTION: Notice to delete a system of records. SUMMARY: The Defense Logistics Agency proposes to delete a system of records notice in its existing...-5045. SUPPLEMENTARY INFORMATION: The Defense Logistics Agency systems of records notices subject to the...

75 FR 15694 - Privacy Act of 1974; Systems of Records

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2010-03-30

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ADP SYSTEMS ANALYSIS - COMMITTED VS. AVAILABLE MILITARY TRANSPORTATION (LMI T1).

DTIC Science & Technology

LOGISTICS , * MANAGEMENT ENGINEERING), (*DATA PROCESSING, LOGISTICS), INFORMATION RETRIEVAL, SYSTEMS ENGINEERING, MILITARY TRANSPORTATION, CARGO VEHICLES, SCHEDULING, COMPUTER PROGRAMMING, MANAGEMENT PLANNING AND CONTROL

Social inequalities in health information seeking among young adults in Montreal.

PubMed

Gagné, Thierry; Ghenadenik, Adrian E; Abel, Thomas; Frohlich, Katherine L

2018-06-01

Over their lifecourse, young adults develop different skills and preferences in relationship to the information sources they seek when having questions about health. Health information seeking behaviour (HISB) includes multiple, unequally accessed sources; yet most studies have focused on single sources and did not examine HISB's association with social inequalities. This study explores 'multiple-source' profiles and their association with socioeconomic characteristics. We analyzed cross-sectional data from the Interdisciplinary Study of Inequalities in Smoking involving 2093 young adults recruited in Montreal, Canada, in 2011-2012. We used latent class analysis to create profiles based on responses to questions regarding whether participants sought health professionals, family, friends or the Internet when having questions about health. Using multinomial logistic regression, we examined the associations between profiles and economic, social and cultural capital indicators: financial difficulties and transportation means, friend satisfaction and network size, and individual, mother's, and father's education. Five profiles were found: 'all sources' (42%), 'health professional centred' (29%), 'family only' (14%), 'Internet centred' (14%) and 'no sources' (2%). Participants with a larger social network and higher friend satisfaction were more likely to be in the 'all sources' group. Participants who experienced financial difficulties and completed college/university were less likely to be in the 'family only' group; those whose mother had completed college/university were more likely to be in this group. Our findings point to the importance of considering multiple sources to study HISB, especially when the capacity to seek multiple sources is unequally distributed. Scholars should acknowledge HISB's implications for health inequalities.

Decision-making tools for distribution networks in disaster relief.

DOT National Transportation Integrated Search

2011-08-05

The devastation caused by the 2010 earthquake in Haiti was compounded by the significant logistical : challenges of distributing relief to those in need. Unfortunately this is the case with many disasters. : Rapid and efficient distribution of water,...

[Factors regarding awareness of preventive care exercises: Distance to exercise facilities and their social networks].

PubMed

Soma, Yuki; Tsunoda, Kenji; Kitano, Naruki; Jindo, Takashi; Okura, Tomohiro

2015-01-01

The present study examines factors affecting individuals' awareness of certain types of preventive care exercises, particularly the distance from their home to an exercise facility and their social networks. Participants were 3206 men (age, 73.0±6.2 years) and 3395 women (age, 73.2±6.4 years) aged ≥65 years who had not been certified as persons with care needs and who had responded to an inventory survey conducted in Kasama City, Japan, in 2013. We performed multiple logistic regression analysis to assess the characteristics associated with participants' awareness of two types of exercises for preventive care: "silver rehabili taisou" (SRT) and "square-stepping exercise" (SSE). Independent variables were distance from home to the exercise facility, social networks, transportation availability, physical function, cognitive function, and neighborhood population density. Older adults who were aware of the exercises lived significantly closer to an exercise facility (SRT, aware: 1,148.5±961.3 m vs. unaware: 1,284.2±1,027.4 m; SSE, aware: 1,415.9±1104.1 m vs. unaware: 1,615.7±1,172.2 m). Multiple logistic regression analysis showed that participation in community activities (men, SRT-odds ratio [OR]=2.54 and SSE-OR=2.19; women, SRT-OR=4.14 and SSE-OR=3.34] and visiting friends (men, SRT-OR=1.45 and SSE-OR=1.49; women SRT-OR=1.44 and SSE-OR=1.73) were promoting factors for awareness of both types of exercises. In men and women, low physical function (SRT-OR=0.73 and SSE-OR=0.56) and dependence on another person to drive them to the destination (SRT-OR=0.79 and SSE-OR=0.78) were inhibiting factors, respectively. A distance of >500 m between their home and the facility tended to be an inhibiting factor. A shorter distance from home to an exercise facility and better social networks increased awareness of preventive care exercises in both sexes and for both types of exercise. Establishing exercise centers and devising effective methods of imparting information to individuals (e.g., via community magazines and home visits) may promote participation in preventive care exercises.

Sensors-network and its application in the intelligent storage security

NASA Astrophysics Data System (ADS)

Zhang, Qingying; Nicolescu, Mihai; Jiang, Xia; Zhang, Ying; Yue, Weihong; Xiao, Weihong

2004-11-01

Intelligent storage systems run on different advanced technologies, such as linear layout, business intelligence and data mining. Security, the basic desire of the storage system, has been focused on with the indraught of multimedia communication technology and sensors" network. Along with the developing of science and the social demands, multifarious alarming system has been designed and improved to be intelligentized, modularized and have network connections. It is of great moment to make the storage, and further more, the logistics system more and more efficient and perfect with modern science and technology. Diversified information on the spot should be caught by different kinds of sensors. Those signals are treated and communicated to the control center to give the further actions. For fire-proofing, broad-spectrum gas sensors, fume sensors, flame sensors and temperature sensors are used to catch the information in their own ways. Once the fire is taken somewhere, the sensors work by the fume, temperature, and flame as well as gas immediately. Meanwhile the intelligent control system starts. It passes the tidings to the center unit. At the same time, it sets those movable walls on to work quickly to obstruct the fire"s spreading. While for guarding the warehouse against theft, cut-off sensors, body sensors, photoelectric sensors, microwave sensors and closed-circuit television as well as electronic clocks are available to monitor the warehouse reasonably. All of those sensors work in a net way. The intelligent control system is made with a digital circuit instead of traditional switch one. This system can work in a better way in many cases. Its reliability is high and the cost is low.

Peculiarities of solving the problems of modern logistics in high-rise construction and industrial production

NASA Astrophysics Data System (ADS)

Rubtsov, Anatoliy E.; Ushakova, Elena V.; Chirkova, Tamara V.

2018-03-01

Basing on the analysis of the enterprise (construction organization) structure and infrastructure of the entire logistics system in which this enterprise (construction organization) operates, this article proposes an approach to solve the problems of structural optimization and a set of calculation tasks, based on customer orders as well as on the required levels of insurance stocks, transit stocks and other types of stocks in the distribution network, modes of operation of the in-company transport and storage complex and a number of other factors.

Essential elements of online information networks on invasive alien species

USGS Publications Warehouse

Simpson, A.; Sellers, E.; Grosse, A.; Xie, Y.

2006-01-01

In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia-North American IAS Information Network (EA-NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up. ?? 2006 Springer.

Harmony search optimization algorithm for a novel transportation problem in a consolidation network

NASA Astrophysics Data System (ADS)

Davod Hosseini, Seyed; Akbarpour Shirazi, Mohsen; Taghi Fatemi Ghomi, Seyed Mohammad

2014-11-01

This article presents a new harmony search optimization algorithm to solve a novel integer programming model developed for a consolidation network. In this network, a set of vehicles is used to transport goods from suppliers to their corresponding customers via two transportation systems: direct shipment and milk run logistics. The objective of this problem is to minimize the total shipping cost in the network, so it tries to reduce the number of required vehicles using an efficient vehicle routing strategy in the solution approach. Solving several numerical examples confirms that the proposed solution approach based on the harmony search algorithm performs much better than CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for realistic size problem instances.

Application of two neural network paradigms to the study of voluntary employee turnover.

PubMed

Somers, M J

1999-04-01

Two neural network paradigms--multilayer perceptron and learning vector quantization--were used to study voluntary employee turnover with a sample of 577 hospital employees. The objectives of the study were twofold. The 1st was to assess whether neural computing techniques offered greater predictive accuracy than did conventional turnover methodologies. The 2nd was to explore whether computer models of turnover based on neural network technologies offered new insights into turnover processes. When compared with logistic regression analysis, both neural network paradigms provided considerably more accurate predictions of turnover behavior, particularly with respect to the correct classification of leavers. In addition, these neural network paradigms captured nonlinear relationships that are relevant for theory development. Results are discussed in terms of their implications for future research.

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Post-diagnosis social networks, and lifestyle and treatment factors in the After Breast Cancer Pooling Project.

PubMed

Kroenke, Candyce H; Michael, Yvonne L; Shu, Xiao-Ou; Poole, Elizabeth M; Kwan, Marilyn L; Nechuta, Sarah; Caan, Bette J; Pierce, John P; Chen, Wendy Y

2017-04-01

Larger social networks have been associated with better breast cancer survival. To investigate potential mediators, we evaluated associations of social network size and diversity with lifestyle and treatment factors associated with prognosis. We included 9331 women from the After Breast Cancer Pooling Project who provided data on social networks within approximately two years following diagnosis. A social network index was derived from information about the presence of a spouse or intimate partner, religious ties, community participation, friendship ties, and numbers of living relatives. Diversity was assessed as variety of ties, independent of size. We used logistic regression to evaluate associations with outcomes and evaluated whether effect estimates differed using meta-analytic techniques. Associations were similar across cohorts though analyses of smoking and alcohol included US cohorts only because of low prevalence of these behaviors in the Shanghai cohort. Socially isolated women were more likely to be obese (OR = 1.21, 95% CI:1.03-1.42), have low physical activity (<10 MET-hours/week, OR = 1.55, 95% CI:1.36-1.78), be current smokers (OR = 2.77, 95% CI:2.09-3.68), and have high alcohol intake (≥15 g/d, OR = 1.23, 95% CI:1.00-1.51), compared with socially integrated women. Among node positive cases from three cohorts, socially isolated women were more likely not to receive chemotherapy (OR = 2.10, 95% CI:1.30-3.39); associations differed in a fourth cohort. Other associations (nonsignificant) were consistent with less intensive treatment in socially isolated women. Low social network diversity was independently associated with more adverse lifestyle, but not clinical, factors. Small, less diverse social networks measured post-diagnosis were associated with more adverse lifestyle factors and less intensive cancer treatment. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Social networks, social support mechanisms, and quality of life after breast cancer diagnosis.

PubMed

Kroenke, Candyce H; Kwan, Marilyn L; Neugut, Alfred I; Ergas, Isaac J; Wright, Jaime D; Caan, Bette J; Hershman, Dawn; Kushi, Lawrence H

2013-06-01

We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006 to 2011 and provided data on social networks (the presence of a spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible support, emotional/informational support, affection, positive social interaction), and QOL, measured by the FACT-B, approximately 2 months post diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower versus higher than median QOL scores. We further stratified by stage at diagnosis and treatment. In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR = 2.18, 95 % CI: 1.72-2.77), physical well-being (WB) (OR = 1.61, 95 % CI: 1.27-2.03), functional WB (OR = 2.08, 95 % CI: 1.65-2.63), social WB (OR = 3.46, 95 % CI: 2.73-4.39), and emotional WB (OR = 1.67, 95 % CI: 1.33-2.11) scores and higher breast cancer symptoms (OR = 1.48, 95 % CI: 1.18-1.87) compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was "positive social interaction." However, each type of support was important depending on outcome, stage, and treatment status. Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

Stretched exponential dynamics of coupled logistic maps on a small-world network

NASA Astrophysics Data System (ADS)

Mahajan, Ashwini V.; Gade, Prashant M.

2018-02-01

We investigate the dynamic phase transition from partially or fully arrested state to spatiotemporal chaos in coupled logistic maps on a small-world network. Persistence of local variables in a coarse grained sense acts as an excellent order parameter to study this transition. We investigate the phase diagram by varying coupling strength and small-world rewiring probability p of nonlocal connections. The persistent region is a compact region bounded by two critical lines where band-merging crisis occurs. On one critical line, the persistent sites shows a nonexponential (stretched exponential) decay for all p while for another one, it shows crossover from nonexponential to exponential behavior as p → 1 . With an effectively antiferromagnetic coupling, coupling to two neighbors on either side leads to exchange frustration. Apart from exchange frustration, non-bipartite topology and nonlocal couplings in a small-world network could be a reason for anomalous relaxation. The distribution of trap times in asymptotic regime has a long tail as well. The dependence of temporal evolution of persistence on initial conditions is studied and a scaling form for persistence after waiting time is proposed. We present a simple possible model for this behavior.

Panel 2.18: logistics, information technology (IT), and telecommunications in crisis management.

PubMed

De Silva, Terrence; Chikersal, Jyotsna; Snoad, Nigel; Woodworth, Brent; Ghaly, Cherif; Catterall, Martin

2005-01-01

This is a summary of the presentations and discussion of Panel 2.18, Logistics, Information Technology, and Telecommunications in Crisis Management of the Conference, Health Aspects of the Tsunami Disaster in Asia, convened by the World Health Organization (WHO) in Phuket, Thailand, 04-06 May 2005. The topics discussed included issues related to logistics, information technology (IT), and crisis communication pertaining to the responses to the damage created by the Tsunami. It is presented in the following major sections: (1) issues; (2) lessons learned; (3) what was done well; (4) what could have been done better; and (5) conclusions and recommendations. Each major section is presented in four sub-sections: (1) needs assessments; (2) coordination; (3) filling the gaps; and (4) capacity building.

The Role of Social-Emotional and Social Network Factors in the Relationship Between Academic Achievement and Risky Behaviors.

PubMed

Wong, Mitchell D; Strom, Danielle; Guerrero, Lourdes R; Chung, Paul J; Lopez, Desiree; Arellano, Katherine; Dudovitz, Rebecca N

2017-08-01

We examined whether standardized test scores and grades are related to risky behaviors among low-income minority adolescents and whether social networks and social-emotional factors explained those relationships. We analyzed data from 929 high school students exposed by natural experiment to high- or low-performing academic environments in Los Angeles. We collected information on grade point average (GPA), substance use, sexual behaviors, participation in fights, and carrying a weapon from face-to-face interviews and obtained California math and English standardized test results. Logistic regression and mediation analyses were used to examine the relationship between achievement and risky behaviors. Better GPA and California standardized test scores were strongly associated with lower rates of substance use, high-risk sexual behaviors, and fighting. The unadjusted relative odds of monthly binge drinking was 0.72 (95% confidence interval, 0.56-0.93) for 1 SD increase in standardized test scores and 0.46 (95% confidence interval, 0.29-0.74) for GPA of B- or higher compared with C+ or lower. Most associations disappeared after controlling for social-emotional and social network factors. Averaged across the risky behaviors, mediation analysis revealed social-emotional factors accounted for 33% of the relationship between test scores and risky behaviors and 43% of the relationship between GPA with risky behaviors. Social network characteristics accounted for 31% and 38% of the relationship between behaviors with test scores and GPA, respectively. Demographic factors, parenting, and school characteristics were less important explanatory factors. Social-emotional factors and social network characteristics were the strongest explanatory factors of the achievement-risky behavior relationship and might be important to understanding the relationship between academic achievement and risky behaviors. Published by Elsevier Inc.

Making Supply Chains Resilient to Floods Using a Bayesian Network

NASA Astrophysics Data System (ADS)

Haraguchi, M.

2015-12-01

Natural hazards distress the global economy by disrupting the interconnected supply chain networks. Manufacturing companies have created cost-efficient supply chains by reducing inventories, streamlining logistics and limiting the number of suppliers. As a result, today's supply chains are profoundly susceptible to systemic risks. In Thailand, for example, the GDP growth rate declined by 76 % in 2011 due to prolonged flooding. Thailand incurred economic damage including the loss of USD 46.5 billion, approximately 70% of which was caused by major supply chain disruptions in the manufacturing sector. Similar problems occurred after the Great East Japan Earthquake and Tsunami in 2011, the Mississippi River floods and droughts during 2011 - 2013, and Hurricane Sandy in 2012. This study proposes a methodology for modeling supply chain disruptions using a Bayesian network analysis (BNA) to estimate expected values of countermeasures of floods, such as inventory management, supplier management and hard infrastructure management. We first performed a spatio-temporal correlation analysis between floods and extreme precipitation data for the last 100 years at a global scale. Then we used a BNA to create synthetic networks that include variables associated with the magnitude and duration of floods, major components of supply chains and market demands. We also included decision variables of countermeasures that would mitigate potential losses caused by supply chain disruptions. Finally, we conducted a cost-benefit analysis by estimating the expected values of these potential countermeasures while conducting a sensitivity analysis. The methodology was applied to supply chain disruptions caused by the 2011 Thailand floods. Our study demonstrates desirable typical data requirements for the analysis, such as anonymized supplier network data (i.e. critical dependencies, vulnerability information of suppliers) and sourcing data(i.e. locations of suppliers, and production rates and volume), and data from previous experiences (i.e. companies' risk mitigation strategy decisions).

Posting behaviour patterns in an online smoking cessation social network: implications for intervention design and development.

PubMed

Healey, Benjamin; Hoek, Janet; Edwards, Richard

2014-01-01

Online Cessation Support Networks (OCSNs) are associated with increased quit success rates, but few studies have examined their use over time. We identified usage patterns in New Zealand's largest OCSN over two years and explored implications for OCSN intervention design and evaluation. We analysed metadata relating to 133,096 OCSN interactions during 2011 and 2012. Metrics covered aggregate network activity, user posting activity and longevity, and between-user commenting. Binary logistic regression models were estimated to investigate the feasibility of predicting low user engagement using early interaction data. Repeating periodic peaks and troughs in aggregate activity related not only to seasonality (e.g., New Year), but also to day of the week. Out of 2,062 unique users, 69 Highly Engaged Users (180+ interactions each) contributed 69% of all OCSN interactions in 2012 compared to 1.3% contributed by 864 Minimally Engaged Users (< = 2 items each). The proportion of Highly Engaged Users increased with network growth between 2011 and 2012 (with marginal significance), but the proportion of Minimally Engaged Users did not decline substantively. First week interaction data enabled identification of Minimally Engaged Users with high specificity and sensitivity (AUROC= 0.94). Results suggest future research should develop and test interventions that promote activity, and hence cessation support, amongst specific user groups or at key time points. For example, early usage information could help identify Minimally Engaged Users for tests of targeted messaging designed to improve their integration into, or re-engagement with, the OCSN. Furthermore, although we observed strong growth over time on varied metrics including posts and comments, this change did not coincide with large gains in first-time user persistence. Researchers assessing intervention effects should therefore examine multiple measures when evaluating changes in network dynamics over time.

What Makes a Tweet Fly? Analysis of Twitter Messaging at Four Infection Control Conferences.

PubMed

Mitchell, Brett G; Russo, Philip L; Otter, Jonathan A; Kiernan, Martin A; Aveling, Landon

2017-11-01

OBJECTIVE To examine tweeting activity, networks, and common topics mentioned on Twitter at 4 international infection control and infectious disease conferences. DESIGN A cross-sectional study. METHODS An independent company was commissioned to undertake a Twitter 'trawl' each month between July 1, 2016, and November 31, 2016. The trawl identified any tweets that contained the official hashtags of the conferences for (1) the UK Infection Prevention Society, (2) IDWeek 2016, (3) the Federation of Infectious Society/Hospital Infection Society, and (4) the Australasian College for Infection Prevention and Control. Topics from each tweet were identified, and an examination of the frequency and timing of tweets was performed. A social network analysis was performed to illustrate connections between users. A multivariate binary logistic regression model was developed to explore the predictors of 'retweets.' RESULTS In total, 23,718 tweets were identified as using 1 of the 2 hashtags of interest. The results demonstrated that the most tweets were posted during the conferences. Network analysis demonstrated a diversity of twitter networks. A link to a web address was a significant predictor of whether a tweet would be retweeted (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.9-2.1). Other significant factors predicting a retweet included tweeting on topics such as Clostridium difficile (OR, 2.0; 95% CI, 1.7-2.4) and the media (OR, 1.8; 95% CI, 1.6-2.0). Tweets that contained a picture were significantly less likely to be retweeted (OR, 0.06; 95% CI, 0.05-0.08). CONCLUSION Twitter is a useful tool for information sharing and networking at infection control conferences. Infect Control Hosp Epidemiol 2017;38:1271-1276.

Metamodeling and the Critic-based approach to multi-level optimization.

PubMed

Werbos, Ludmilla; Kozma, Robert; Silva-Lugo, Rodrigo; Pazienza, Giovanni E; Werbos, Paul J

2012-08-01

Large-scale networks with hundreds of thousands of variables and constraints are becoming more and more common in logistics, communications, and distribution domains. Traditionally, the utility functions defined on such networks are optimized using some variation of Linear Programming, such as Mixed Integer Programming (MIP). Despite enormous progress both in hardware (multiprocessor systems and specialized processors) and software (Gurobi) we are reaching the limits of what these tools can handle in real time. Modern logistic problems, for example, call for expanding the problem both vertically (from one day up to several days) and horizontally (combining separate solution stages into an integrated model). The complexity of such integrated models calls for alternative methods of solution, such as Approximate Dynamic Programming (ADP), which provide a further increase in the performance necessary for the daily operation. In this paper, we present the theoretical basis and related experiments for solving the multistage decision problems based on the results obtained for shorter periods, as building blocks for the models and the solution, via Critic-Model-Action cycles, where various types of neural networks are combined with traditional MIP models in a unified optimization system. In this system architecture, fast and simple feed-forward networks are trained to reasonably initialize more complicated recurrent networks, which serve as approximators of the value function (Critic). The combination of interrelated neural networks and optimization modules allows for multiple queries for the same system, providing flexibility and optimizing performance for large-scale real-life problems. A MATLAB implementation of our solution procedure for a realistic set of data and constraints shows promising results, compared to the iterative MIP approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

Logistics in the Computer Lab.

ERIC Educational Resources Information Center

Cowles, Jim

1989-01-01

Discusses ways to provide good computer laboratory facilities for elementary and secondary schools. Topics discussed include establishing the computer lab and selecting hardware; types of software; physical layout of the room; printers; networking possibilities; considerations relating to the physical environment; and scheduling methods. (LRW)

Crowdsourcing for large-scale mosquito (Diptera: Culicidae) sampling

USDA-ARS?s Scientific Manuscript database

Sampling a cosmopolitan mosquito (Diptera: Culicidae) species throughout its range is logistically challenging and extremely resource intensive. Mosquito control programmes and regional networks operate at the local level and often conduct sampling activities across much of North America. A method f...

A general framework for the use of logistic regression models in meta-analysis.

PubMed

Simmonds, Mark C; Higgins, Julian Pt

2016-12-01

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

Differential Impact of Types of Social Support in the Mental Health of Formerly Incarcerated Latino Men

PubMed Central

Muñoz-Laboy, Miguel; Severson, Nicolette; Perry, Ashley; Guilamo-Ramos, Vincent

2015-01-01

The role of social support in the mental health of formerly incarcerated Latino men (FILM) is an issue overlooked in public health prevention efforts. The objectives of this analysis were to (a) describe the levels of social support perceived and received by FILM; (b) identify the associations, if any, between levels of social support and mental health indicators such as depression and anxiety; and (c) explore the impact of familism and hypermasculinity on the receptivity of social support and the potential role of these factors in mediating associations between social support and mental health indicators. To accomplish the objectives, we conducted a cross-sectional survey with FILM (n = 259), ages 18 to 59, in New York City, and one nominated member of their social network (n = 130 dyads). In this analysis, we examined four dimensions of social support (instrumental, informational, appraisal, and emotional) from two perspectives: provided (as reported by members of the social networks) and perceived (as reported by FILM). The major outcome variables for this analysis were the presence/absence of major anxiety and depressive symptoms. Our logistic regression analyses suggest that perceived emotional support was inversely associated with both anxiety and depression. Our findings suggest that familism mediated the association between perceived emotional support and anxiety/depression. Therefore, we must consider designing network enhancement interventions that focus on both FILM and their social support systems. PMID:24323767

32 CFR 300.1 - Purpose.

Code of Federal Regulations, 2014 CFR

2014-07-01

... PROGRAM DEFENSE LOGISTICS AGENCY FREEDOM OF INFORMATION ACT PROGRAM General Provisions § 300.1 Purpose. This part provides policies and procedures for the Defense Logistics Agency (DLA) implementation of the...

32 CFR 323.5 - Access to systems of records information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... (CONTINUED) PRIVACY PROGRAM DEFENSE LOGISTICS AGENCY PRIVACY PROGRAM § 323.5 Access to systems of records... Logistics Agency, ATTN: DGA, 8725 John J. Kingman Road, Suite 1644, Fort Belvoir, VA 22060-6221. Any written... General Counsel, Defense Logistics Agency, ATTN: DGA, Suite 1644, 8725 John J. Kingman Road, Fort Belvoir...

32 CFR 323.5 - Access to systems of records information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... (CONTINUED) PRIVACY PROGRAM DEFENSE LOGISTICS AGENCY PRIVACY PROGRAM § 323.5 Access to systems of records... Logistics Agency, ATTN: DGA, 8725 John J. Kingman Road, Suite 1644, Fort Belvoir, VA 22060-6221. Any written... General Counsel, Defense Logistics Agency, ATTN: DGA, Suite 1644, 8725 John J. Kingman Road, Fort Belvoir...

Power Extension Package (PEP) system definition extension, orbital service module systems analysis study. Volume 7: PEP logistics and training plan requirements

NASA Technical Reports Server (NTRS)

1979-01-01

Recommendations for logistics activities and logistics planning are presented based on the assumption that a system prime contractor will perform logistics functions to support all program hardware and will implement a logistics system to include the planning and provision of products and services to assure cost effective coverage of the following: maintainability; maintenance; spares and supply support; fuels; pressurants and fluids; operations and maintenance documentation training; preservation, packaging and packing; transportation and handling; storage; and logistics management information reporting. The training courses, manpower, materials, and training aids required will be identified and implemented in a training program.

Space Shuttle Orbiter logistics - Managing in a dynamic environment

NASA Technical Reports Server (NTRS)

Renfroe, Michael B.; Bradshaw, Kimberly

1990-01-01

The importance and methods of monitoring logistics vital signs, logistics data sources and acquisition, and converting data into useful management information are presented. With the launch and landing site for the Shuttle Orbiter project at the Kennedy Space Center now totally responsible for its own supportability posture, it is imperative that logistics resource requirements and management be continually monitored and reassessed. Detailed graphs and data concerning various aspects of logistics activities including objectives, inventory operating levels, customer environment, and data sources are provided. Finally, some lessons learned from the Shuttle Orbiter project and logistics options which should be considered by other space programs are discussed.

A Collection of Technical Papers

NASA Technical Reports Server (NTRS)

1995-01-01

Papers presented at the 6th Space Logistics Symposium covered such areas as: The International Space Station; The Hubble Space Telescope; Launch site computer simulation; Integrated logistics support; The Baikonur Cosmodrome; Probabalistic tools for high confidence repair; A simple space station rescue vehicle; Integrated Traffic Model for the International Space Station; Packaging the maintenance shop; Leading edge software support; Storage information management system; Consolidated maintenance inventory logistics planning; Operation concepts for a single stage to orbit vehicle; Mission architecture for human lunar exploration; Logistics of a lunar based solar power satellite scenario; Just in time in space; NASA acquisitions/logistics; Effective transition management; Shuttle logistics; and Revitalized space operations through total quality control management.

High-risk sexual activity in the House and Ball community: influence of social networks.

PubMed

Schrager, Sheree M; Latkin, Carl A; Weiss, George; Kubicek, Katrina; Kipke, Michele D

2014-02-01

We investigated the roles of House membership and the influence of social and sexual network members on the sexual risk behavior of men in the Los Angeles House and Ball community. From February 2009 to January 2010, male participants (n = 233) completed interviewer-assisted surveys during a House meeting or Ball event. We used logistic regression to model the effects of sexual network size, influence of sexual network members, House membership status, and their interactions on high-risk sex. Significant predictors of high-risk sex included number of sexual partners in the nominated social network, multiethnicity, and previous diagnosis of sexually transmitted infection. House membership was protective against high-risk sex. Additionally, a 3-way interaction emerged between number of sexual partners in the network, influence, and network members' House membership. Future research should assess network members' attitudes and behavior in detail to provide a greater understanding of the dynamics of social influence and to identify additional avenues for intervention.

Availability and quality of coronary heart disease family history in primary care medical records: implications for cardiovascular risk assessment.

PubMed

Dhiman, Paula; Kai, Joe; Horsfall, Laura; Walters, Kate; Qureshi, Nadeem

2014-01-01

The potential to use data on family history of premature disease to assess disease risk is increasingly recognised, particularly in scoring risk for coronary heart disease (CHD). However the quality of family health information in primary care records is unclear. To assess the availability and quality of family history of CHD documented in electronic primary care records. Cross-sectional study. 537 UK family practices contributing to The Health Improvement Network database. Data were obtained from patients aged 20 years or more, registered with their current practice between 1(st) January 1998 and 31(st) December 2008, for at least one year. The availability and quality of recorded CHD family history was assessed using multilevel logistic and ordinal logistic regression respectively. In a cross-section of 1,504,535 patients, 19% had a positive or negative family history of CHD recorded. Multilevel logistic regression showed patients aged 50-59 had higher odds of having their family history recorded compared to those aged 20-29 (OR:1.23 (1.21 to 1.25)), however most deprived patients had lower odds compared to those least deprived (OR: 0.86 (0.85 to 0.88)). Of the 140,058 patients with a positive family history recorded (9% of total cohort), age of onset was available in 45%; with data specifying both age of onset and relative affected available in only 11% of records. Multilevel ordinal logistic regression confirmed no statistical association between the quality of family history recording and age, gender, deprivation and year of registration. Family history of CHD is documented in a small proportion of primary care records; and where positive family history is documented the details are insufficient to assess familial risk or populate cardiovascular risk assessment tools. Data capture needs to be improved particularly for more disadvantaged patients who may be most likely to benefit from CHD risk assessment.

Logistics or patient care: which features do independent Finnish pharmacy owners prioritize in a strategic plan for future information technology systems?

PubMed

Westerling, Anna M; Haikala, Veikko E; Bell, J Simon; Airaksinen, Marja S

2010-01-01

To determine Finnish community pharmacy owners' requirements for the next generation of software systems. Descriptive, nonexperimental, cross-sectional study. Finland during December 2006. 308 independent pharmacy owners. Survey listing 126 features that could potentially be included in the new information technology (IT) system. The list was grouped into five categories: (1) drug information and patient counseling, (2) medication safety, (3) interprofessional collaboration, (4) pharmacy services, and (5) pharmacy internal processes. Perceived value of potential features for a new IT system. The survey was mailed to all independent pharmacy owners in Finland (n = 580; response rate 53% [n = 308]). Respondents gave priority to logistical functions and functions related to drug information and patient care. The highest rated individual features were tracking product expiry (rated as very or quite important by 100% of respondents), computerized drug-drug interaction screening (99%), an electronic version of the national pharmaceutical reference book (97%), and a checklist-type drug information database to assist patient counseling (95%). In addition to the high ranking for logistical features, Finnish pharmacy owners put a priority on support for cognitive pharmaceutical services in the next IT system. Although the importance of logistical functions is understandable, the owners demonstrated a commitment to strategic health policy goals when planning their business IT system.

An integrated conceptual framework for selecting reverse logistics providers in the presence of vagueness

NASA Astrophysics Data System (ADS)

Fırdolaş, Tugba; Önüt, Semih; Kongar, Elif

2005-11-01

In recent years, relating organization's attitude towards sustainable development, environmental management is gaining an increasing interest among researchers in supply chain management. With regard to a long term requirement of a shift from a linear economy towards a cycle economy, businesses should be motivated to embrace change brought about by consumers, government, competition, and ethical responsibility. To achieve business goals and objectives, a company must reply to increasing consumer demand for "green" products and implement environmentally responsible plans. Reverse logistics is an activity within organizations delegated to the customer service function, where customers with warranted or defective products would return them to their supplier. Emergence of reverse logistics enables to provide a competitive advantage and significant return on investment with an indirect effect on profitability. Many organizations are hiring third-party providers to implement reverse logistics programs designed to retain value by getting products back. Reverse logistics vendors play an important role in helping organizations in closing the loop for products offered by the organizations. In this regard, the selection of third-party providers issue is increasingly becoming an area of reverse logistics concept and practice. This study aims to assist managers in determining which third-party logistics provider to collaborate in the reverse logistics process with an alternative approach based on an integrated model using neural networks and fuzzy logic. An illustrative case study is discussed and the best provider is identified through the solution of this model.

The Effects of Peer Group Network Properties on Drug Use Among Homeless Youth

PubMed Central

Rice, Eric; Milburn, Norweeta G.; Rotheram-Borus, Mary Jane; Mallett, Shelley; Rosenthal, Doreen

2010-01-01

The authors examine how the properties of peer networks affect amphetamine, cocaine, and injection drug use over 3 months among newly homeless adolescents, aged 12 to 20 in Los Angeles (n = 217; 83% retention at 3 months) and Melbourne (n = 119; 72% retention at 3 months). Several hypotheses regarding the effects of social network properties on the peer influence process are developed. Multivariate logistic regression analyses show that higher concentrations of homeless peers in networks at recruitment were associated with increased likelihood of amphetamine and cocaine use at 3-month follow-up. Higher concentrations of injecting peers were associated with increased risk of injection drug use 3 months later. Change in network structure over time toward increased concentrations of homeless peers was associated with increased risk of cocaine use and injecting. Higher density networks at baseline were positively associated with increased likelihood of cocaine and amphetamine use at 3 months. PMID:20539820

Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

NASA Astrophysics Data System (ADS)

Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.

We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

Reliability of a Bayesian network to predict an elevated aldosterone-to-renin ratio.

PubMed

Ducher, Michel; Mounier-Véhier, Claire; Lantelme, Pierre; Vaisse, Bernard; Baguet, Jean-Philippe; Fauvel, Jean-Pierre

2015-05-01

Resistant hypertension is common, mainly idiopathic, but sometimes related to primary aldosteronism. Thus, most hypertension specialists recommend screening for primary aldosteronism. To optimize the selection of patients whose aldosterone-to-renin ratio (ARR) is elevated from simple clinical and biological characteristics. Data from consecutive patients referred between 1 June 2008 and 30 May 2009 were collected retrospectively from five French 'European excellence hypertension centres' institutional registers. Patients were included if they had at least one of: onset of hypertension before age 40 years, resistant hypertension, history of hypokalaemia, efficient treatment by spironolactone, and potassium supplementation. An ARR>32 ng/L and aldosterone>160 ng/L in patients treated without agents altering the renin-angiotensin system was considered as elevated. Bayesian network and stepwise logistic regression were used to predict an elevated ARR. Of 334 patients, 89 were excluded (31 for incomplete data, 32 for taking agents that alter the renin-angiotensin system and 26 for other reasons). Among 245 included patients, 110 had an elevated ARR. Sensitivity reached 100% or 63.3% using Bayesian network or logistic regression, respectively, and specificity reached 89.6% or 67.2%, respectively. The area under the receiver-operating-characteristic curve obtained with the Bayesian network was significantly higher than that obtained by stepwise regression (0.93±0.02 vs. 0.70±0.03; P<0.001). In hypertension centres, Bayesian network efficiently detected patients with an elevated ARR. An external validation study is required before use in primary clinical settings. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Integrated disaster relief logistics: a stepping stone towards viable civil-military networks?

PubMed

Tatham, Peter; Rietjens, Sebastiaan Bas

2016-01-01

The twenty-first century has seen a significant rise in all forms of disasters and this has resulted in military and humanitarian organisations becoming more frequently engaged in the provision of support to those affected. Achieving an efficient and effective logistic preparation and response is one of the key elements in mitigating the impact of such events, but the establishment of mechanisms to deliver an appropriately integrated civil-military approach remains elusive. Not least because of the high percentage of assistance budgets spent on logistics, this area is considered to represent fertile ground for developing improved processes and understanding. In practice, the demands placed on civilian and military logisticians are broadly similar, as is the solution space. Speaking a common language and using common concepts, it is argued, therefore, that the logistic profession should be in the vanguard of the development of an improved civil-military interface. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.

An inexact reverse logistics model for municipal solid waste management systems.

PubMed

Zhang, Yi Mei; Huang, Guo He; He, Li

2011-03-01

This paper proposed an inexact reverse logistics model for municipal solid waste management systems (IRWM). Waste managers, suppliers, industries and distributors were involved in strategic planning and operational execution through reverse logistics management. All the parameters were assumed to be intervals to quantify the uncertainties in the optimization process and solutions in IRWM. To solve this model, a piecewise interval programming was developed to deal with Min-Min functions in both objectives and constraints. The application of the model was illustrated through a classical municipal solid waste management case. With different cost parameters for landfill and the WTE, two scenarios were analyzed. The IRWM could reflect the dynamic and uncertain characteristics of MSW management systems, and could facilitate the generation of desired management plans. The model could be further advanced through incorporating methods of stochastic or fuzzy parameters into its framework. Design of multi-waste, multi-echelon, multi-uncertainty reverse logistics model for waste management network would also be preferred. Copyright © 2010 Elsevier Ltd. All rights reserved.

A comparative study on entrepreneurial attitudes modeled with logistic regression and Bayes nets.

PubMed

López Puga, Jorge; García García, Juan

2012-11-01

Entrepreneurship research is receiving increasing attention in our context, as entrepreneurs are key social agents involved in economic development. We compare the success of the dichotomic logistic regression model and the Bayes simple classifier to predict entrepreneurship, after manipulating the percentage of missing data and the level of categorization in predictors. A sample of undergraduate university students (N = 1230) completed five scales (motivation, attitude towards business creation, obstacles, deficiencies, and training needs) and we found that each of them predicted different aspects of the tendency to business creation. Additionally, our results show that the receiver operating characteristic (ROC) curve is affected by the rate of missing data in both techniques, but logistic regression seems to be more vulnerable when faced with missing data, whereas Bayes nets underperform slightly when categorization has been manipulated. Our study sheds light on the potential entrepreneur profile and we propose to use Bayesian networks as an additional alternative to overcome the weaknesses of logistic regression when missing data are present in applied research.

The humanitarian common logistic operating picture: a solution to the inter-agency coordination challenge.

PubMed

Tatham, Peter; Spens, Karen; Kovács, Gyöngyi

2017-01-01

Although significant progress has been made in developing the practice of humanitarian logistics, further improvements in efficiency and effectiveness have the potential to save lives and reduce suffering. This paper explores how the military/emergency services' concept of a common operating picture (COP) can be adapted to the humanitarian logistics context, and analyses a practical and proven approach to addressing the key challenge of inter-agency coordination and decision-making. Successful adaptation could provide the mechanism through which predicted and actual demands, together with the location and status of material in transit, are captured, evaluated, and presented in real time as the basis for enhanced decision-making between actors in the humanitarian supply network. Through the introduction of a humanitarian logistics COP and its linkages to national disaster management systems, local communities and countries affected by disasters and emergencies will be better placed to oversee and manage their response activities. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

Two Superintendents, One Home.

ERIC Educational Resources Information Center

Pardini, Priscilla

2000-01-01

Spouses working as superintendents confront agonizing logistics while establishing ground rules for dinner talk. Couples sharing the same career risk eclipsing their personal lives with professional issues. Having one's personal support network under the same roof can be mutually beneficial and synergistic. A married superintendents roster is…

Data Management Standards in Computer-aided Acquisition and Logistic Support (CALS)

NASA Technical Reports Server (NTRS)

Jefferson, David K.

1990-01-01

Viewgraphs and discussion on data management standards in computer-aided acquisition and logistic support (CALS) are presented. CALS is intended to reduce cost, increase quality, and improve timeliness of weapon system acquisition and support by greatly improving the flow of technical information. The phase 2 standards, industrial environment, are discussed. The information resource dictionary system (IRDS) is described.

Careful with Those Priors: A Note on Bayesian Estimation in Two-Parameter Logistic Item Response Theory Models

ERIC Educational Resources Information Center

Marcoulides, Katerina M.

2018-01-01

This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…

Information Exchange Between Resilient and High-Threat Networks: Techniques for Threat Mitigation

DTIC Science & Technology

2004-11-01

Information Exchange between Resilient and High-Threat Networks : Techniques for Threat Mitigation Tim Dean and Graham Wyatt QinetiQ...SUMMARY High resilience military networks frequently have requirements for exchange of information with networks of low assurance, including networks of...assured, two-way, information flow between high resilience networks and other networks of unknown threat. The techniques include conventional and

The Cyber Threat to Military Just-in-Time Logistics: Risk Mitigation and the Return to Forward Basing

DTIC Science & Technology

2017-05-26

Generation Warfare (RNGW) ......................................................4 What is Traditional Forward-Based or “Just-in- Case ” Logistics...Industrial Control Systems-Cyber Emergency Response Team IT Information Technology JFC Joint Force Commander JIC Just-in- Case JIT Just-in-Time JP Joint...aspects of demand-driven or “Just-in-Time” (JIT) logistics, and bringing back the concept of traditional large inventory or “Just-in- Case ” (JIC) logistics

Associations Between Internet-Based Professional Social Networking and Emotional Distress.

PubMed

Jones, Jacquelynn R; Colditz, Jason B; Shensa, Ariel; Sidani, Jaime E; Lin, Liu Yi; Terry, Martha Ann; Primack, Brian A

2016-10-01

Professional social networking websites are commonly used among young professionals. In light of emerging concerns regarding social networking use and emotional distress, the purpose of this study was to investigate the association between frequency of use of LinkedIn, the most commonly used professional social networking website, and depression and anxiety among young adults. In October 2014, we assessed a nationally representative sample of 1,780 U.S. young adults between the ages of 19-32 regarding frequency of LinkedIn use, depression and anxiety, and sociodemographic covariates. We measured depression and anxiety using validated Patient-Reported Outcomes Measurement Information System measures. We used bivariable and multivariable logistic regression to assess the association between LinkedIn use and depression and anxiety, while controlling for age, sex, race, relationship status, living situation, household income, education level, and overall social media use. In weighted analyses, 72% of participants did not report use of LinkedIn, 16% reported at least some use, but less than once each week, and 12% reported use at least once per week. In multivariable analyses controlling for all covariates, compared with those who did not use LinkedIn, participants using LinkedIn at least once per week had significantly greater odds of increased depression (adjusted odds ratio [AOR] = 2.10, 95% confidence interval [CI] = 1.31-3.38) and increased anxiety (AOR = 2.79, 95% CI = 1.72-4.53). LinkedIn use was significantly related to both outcomes in a dose-response manner. Future research should investigate directionality of this association and possible reasons for it.

The unrest of the San Miguel volcano (El Salvador, Central America): installation of the monitoring network and observed volcano-tectonic ground deformation

NASA Astrophysics Data System (ADS)

Bonforte, Alessandro; Hernandez, Douglas Antonio; Gutiérrez, Eduardo; Handal, Louis; Polío, Cecilia; Rapisarda, Salvatore; Scarlato, Piergiorgio

2016-08-01

On 29 December 2013, the Chaparrastique volcano in El Salvador, close to the town of San Miguel, erupted suddenly with explosive force, forming a column more than 9 km high and projecting ballistic projectiles as far as 3 km away. Pyroclastic density currents flowed to the north-northwest side of the volcano, while tephras were dispersed northwest and north-northeast. This sudden eruption prompted the local Ministry of Environment to request cooperation with Italian scientists in order to improve the monitoring of the volcano during this unrest. A joint force, made up of an Italian team from the Istituto Nazionale di Geofisica e Vulcanologia and a local team from the Ministerio de Medio Ambiente y Recursos Naturales, was organized to enhance the volcanological, geophysical and geochemical monitoring system to study the evolution of the phenomenon during the crisis. The joint team quickly installed a multiparametric mobile network comprising seismic, geodetic and geochemical sensors (designed to cover all the volcano flanks from the lowest to the highest possible altitudes) and a thermal camera. To simplify the logistics for a rapid installation and for security reasons, some sensors were colocated into multiparametric stations. Here, we describe the prompt design and installation of the geodetic monitoring network, the processing and results. The installation of a new ground deformation network can be considered an important result by itself, while the detection of some crucial deforming areas is very significant information, useful for dealing with future threats and for further studies on this poorly monitored volcano.

The unrest of S. Miguel volcano (El Salvador, CA): installation of the monitoring network and observed volcano-tectonic ground deformation

NASA Astrophysics Data System (ADS)

Bonforte, A.; Hernandez, D.; Gutiérrez, E.; Handal, L.; Polío, C.; Rapisarda, S.; Scarlato, P.

2015-10-01

On 29 December 2013, the Chaparrastique volcano in El Salvador, close to the town of S. Miguel, erupted suddenly with explosive force, forming a more than 9 km high column and projecting ballistic projectiles as far as 3 km away. Pyroclastic Density Currents flowed to the north-northwest side of the volcano, while tephras were dispersed northwest and north-northeast. This sudden eruption prompted the local Ministry of Environment to request cooperation with Italian scientists in order to improve the monitoring of the volcano during this unrest. A joint force made up of an Italian team from the Istituto Nazionale di Geofisica e Vulcanologia and a local team from the Ministerio de Medio Ambiente y Recursos Naturales was organized to enhance the volcanological, geophysical and geochemical monitoring system to study the evolution of the phenomenon during the crisis. The joint team quickly installed a multi-parametric mobile network comprising seismic, geodetic and geochemical sensors, designed to cover all the volcano flanks from the lowest to the highest possible altitudes, and a thermal camera. To simplify the logistics for a rapid installation and for security reasons, some sensors were co-located into multi-parametric stations. Here, we describe the prompt design and installation of the geodetic monitoring network, the processing and results. The installation of a new ground deformation network can be considered an important result by itself, while the detection of some crucial deforming areas is very significant information, useful for dealing with future threats and for further studies on this poorly monitored volcano.

A Selfish Constraint Satisfaction Genetic Algorithms for Planning a Long-Distance Transportation Network

NASA Astrophysics Data System (ADS)

Onoyama, Takashi; Maekawa, Takuya; Kubota, Sen; Tsuruta, Setuso; Komoda, Norihisa

To build a cooperative logistics network covering multiple enterprises, a planning method that can build a long-distance transportation network is required. Many strict constraints are imposed on this type of problem. To solve these strict-constraint problems, a selfish constraint satisfaction genetic algorithm (GA) is proposed. In this GA, each gene of an individual satisfies only its constraint selfishly, disregarding the constraints of other genes in the same individuals. Moreover, a constraint pre-checking method is also applied to improve the GA convergence speed. The experimental result shows the proposed method can obtain an accurate solution in a practical response time.

2017 SmartWay Logistics Tool Demonstration

EPA Pesticide Factsheets

This EPA presentation provides information on the SmartWay Logistics Carrier Tool: its background and development, participation in the program, application process, emission metrics, tool demonstration, data collection, and schedule for 2017.

A Channel Network Evolution Model with Subsurface Saturation Mechanism and Analysis of the Chaotic Behavior of the Model

DTIC Science & Technology

1990-09-01

between basin shapes and hydrologic responses is fundamental for the purpose of hydrologic predictions , especially in ungaged basins. Another goal is...47] studied this model and showed analitically how very small differences in the c field generated completely different leaf vein network structures... predictability impossible. Complexity is by no means a requirement in order for a system to exhibit SIC. A system as simple as the logistic equation x,,,,=ax,,(l

GIS-based spatial decision support system for grain logistics management

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

Grain logistics is the important component of the social logistics, which can be attributed to frequent circulation and the great quantity. At present time, there is no modern grain logistics distribution management system, and the logistics cost is the high. Geographic Information Systems (GIS) have been widely used for spatial data manipulation and model operations and provide effective decision support through its spatial database management capabilities and cartographic visualization. In the present paper, a spatial decision support system (SDSS) is proposed to support policy makers and to reduce the cost of grain logistics. The system is composed of two major components: grain logistics goods tracking model and vehicle routing problem optimization model and also allows incorporation of data coming from external sources. The proposed system is an effective tool to manage grain logistics in order to increase the speed of grain logistics and reduce the grain circulation cost.

Social Network Concordance in Food Choice Among Spouses, Friends, and Siblings

PubMed Central

Jacques, Paul F.; Christakis, Nicholas A.

2011-01-01

Objectives. We investigated whether eating behaviors were concordant among diverse sets of social ties. Methods. We analyzed the socioeconomic and demographic distribution of eating among 3418 members of the Framingham Heart Study observed from 1991 to 2001. We used a data-classification procedure to simplify choices into 7 nonoverlapping patterns that we matched with information on social network ties. We used correlation analysis to examine eating associations among 4 types of peers (spouses, friends, brothers, and sisters). Longitudinal multiple logistic regression was used to evaluate evidence for peer influences on eating. Results. Of all peer types, spouses showed the strongest concordances in eating patterns over time after adjustment for social contextual factors. Across all peers, the eating pattern most likely to be shared by socially connected individuals was “alcohol and snacks.” Models estimating one's current eating pattern on the basis of a peer's prior eating provided supportive evidence of a social influence process. Conclusions. Certain eating patterns appeared to be socially transmissible across different kinds of relationships. These findings represent an important step in specifying the relevant social environment in the study of health behaviors to include eating. PMID:21940920

Using Zigbee to integrate medical devices.

PubMed

Frehill, Paul; Chambers, Desmond; Rotariu, Cosmin

2007-01-01

Wirelessly enabling Medical Devices such as Vital Signs Monitors, Ventilators and Infusion Pumps allows central data collection. This paper discusses how data from these types of devices can be integrated into hospital systems using wireless sensor networking technology. By integrating devices you are protecting investment and opening up the possibility of networking with similar devices. In this context we present how Zigbee meets our requirements for bandwidth, power, security and mobility. We have examined the data throughputs for various medical devices, the requirement of data frequency, security of patient data and the logistics of moving patients while connected to devices. The paper describes a new tested architecture that allows this data to be seamlessly integrated into a User Interface or Healthcare Information System (HIS). The design supports the dynamic addition of new medical devices to the system that were previously unsupported by the system. To achieve this, the hardware design is kept generic and the software interface for different types of medical devices is well defined. These devices can also share the wireless resources with other types of sensors being developed in conjunction on this project such as wireless ECG (Electrocardiogram) and Pulse-Oximetry sensors.

Structural diversity effect on hashtag adoption in Twitter

NASA Astrophysics Data System (ADS)

Zhang, Aihua; Zheng, Mingxing; Pang, Bowen

2018-03-01

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

London Measure of Unplanned Pregnancy: guidance for its use as an outcome measure

PubMed Central

Hall, Jennifer A; Barrett, Geraldine; Copas, Andrew; Stephenson, Judith

2017-01-01

Background The London Measure of Unplanned Pregnancy (LMUP) is a psychometrically validated measure of the degree of intention of a current or recent pregnancy. The LMUP is increasingly being used worldwide, and can be used to evaluate family planning or preconception care programs. However, beyond recommending the use of the full LMUP scale, there is no published guidance on how to use the LMUP as an outcome measure. Ordinal logistic regression has been recommended informally, but studies published to date have all used binary logistic regression and dichotomized the scale at different cut points. There is thus a need for evidence-based guidance to provide a standardized methodology for multivariate analysis and to enable comparison of results. This paper makes recommendations for the regression method for analysis of the LMUP as an outcome measure. Materials and methods Data collected from 4,244 pregnant women in Malawi were used to compare five regression methods: linear, logistic with two cut points, and ordinal logistic with either the full or grouped LMUP score. The recommendations were then tested on the original UK LMUP data. Results There were small but no important differences in the findings across the regression models. Logistic regression resulted in the largest loss of information, and assumptions were violated for the linear and ordinal logistic regression. Consequently, robust standard errors were used for linear regression and a partial proportional odds ordinal logistic regression model attempted. The latter could only be fitted for grouped LMUP score. Conclusion We recommend the linear regression model with robust standard errors to make full use of the LMUP score when analyzed as an outcome measure. Ordinal logistic regression could be considered, but a partial proportional odds model with grouped LMUP score may be required. Logistic regression is the least-favored option, due to the loss of information. For logistic regression, the cut point for un/planned pregnancy should be between nine and ten. These recommendations will standardize the analysis of LMUP data and enhance comparability of results across studies. PMID:28435343

Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

NASA Astrophysics Data System (ADS)

Wang, Lin; Liu, Gaozhi

2018-02-01

This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Internet and mobile technology use among urban African American parents: survey study of a clinical population.

PubMed

Mitchell, Stephanie J; Godoy, Leandra; Shabazz, Kanya; Horn, Ivor B

2014-01-13

There is considerable potential for mobile technologies to empower pediatric patients and families by improving their communication with health professionals. National surveys suggest minority parents frequently communicate via mobile technology, but it is uncertain how amenable they are to receiving health care information in this format. Although the low cost and far reach characteristics of mobile health (mHealth) technology makes it advantageous for communication with minority parents, data on acceptance are needed. The objective of the study was to determine utilization of mobile and Internet technology by African American parents in an urban, underserved population, and to assess their interest in receiving health information via text messaging or other technologies (eg, social media and the Internet). A survey was administered to parents of children aged 1-12 years covered by public insurance receiving care at 3 pediatric primary care centers in Washington, DC. The African American sample (N=302) was composed of primarily single (75.8%, 229/302) mothers. Almost half had more than a high school education (47.7%, 144/302) and incomes above US $25,000 per year (43.0%, 130/302). Most (97.0%, 293/302) reported owning a cell phone, of which 91.1% (275/302) used it to text and 78.5% (237/302) used it to access the Internet. Most had service plans with unlimited text and data, but 26.5% (80/302) experienced service interruptions in the previous year. Home Internet access was more prevalent among those with higher income (86.2%, 112/130), but it was still relatively pervasive among lower income families (66.9%, 83/124). In adjusted logistic regression models, African American mothers with income greater than US $25,000 annually were 4 times as likely to own a tablet computer than their lower income counterparts. Of the participants, 80.8% (244/302) used social networking, primarily Facebook, and 74.2% (224/302) were interested in joining a social networking group about a health topic concerning their child. Although relatively few African American mothers (17.9%, 54/302) shared health information via texting, there was strong interest in receiving health information via mobile phones (87.4%, 264/302). There was no significant difference in Internet/mobile device use or interest in using these outlets to send/receive information about their children's health between parents of healthy children and parents of children with chronic health conditions. Urban African American parents are active users of the Internet and mobile technology for social interactions, but they are less likely to use it for accessing or communicating health information. However, most parents expressed an interest in receiving health information or utilizing social networking to learn more about health topics. Mobile technology and social networks may be an underutilized method of providing health information to underserved minority populations.

Internet and Mobile Technology Use Among Urban African American Parents: Survey Study of a Clinical Population

PubMed Central

Godoy, Leandra; Shabazz, Kanya

2014-01-01

Background There is considerable potential for mobile technologies to empower pediatric patients and families by improving their communication with health professionals. National surveys suggest minority parents frequently communicate via mobile technology, but it is uncertain how amenable they are to receiving health care information in this format. Although the low cost and far reach characteristics of mobile health (mHealth) technology makes it advantageous for communication with minority parents, data on acceptance are needed. Objective The objective of the study was to determine utilization of mobile and Internet technology by African American parents in an urban, underserved population, and to assess their interest in receiving health information via text messaging or other technologies (eg, social media and the Internet). Methods A survey was administered to parents of children aged 1-12 years covered by public insurance receiving care at 3 pediatric primary care centers in Washington, DC. Results The African American sample (N=302) was composed of primarily single (75.8%, 229/302) mothers. Almost half had more than a high school education (47.7%, 144/302) and incomes above US $25,000 per year (43.0%, 130/302). Most (97.0%, 293/302) reported owning a cell phone, of which 91.1% (275/302) used it to text and 78.5% (237/302) used it to access the Internet. Most had service plans with unlimited text and data, but 26.5% (80/302) experienced service interruptions in the previous year. Home Internet access was more prevalent among those with higher income (86.2%, 112/130), but it was still relatively pervasive among lower income families (66.9%, 83/124). In adjusted logistic regression models, African American mothers with income greater than US $25,000 annually were 4 times as likely to own a tablet computer than their lower income counterparts. Of the participants, 80.8% (244/302) used social networking, primarily Facebook, and 74.2% (224/302) were interested in joining a social networking group about a health topic concerning their child. Although relatively few African American mothers (17.9%, 54/302) shared health information via texting, there was strong interest in receiving health information via mobile phones (87.4%, 264/302). There was no significant difference in Internet/mobile device use or interest in using these outlets to send/receive information about their children’s health between parents of healthy children and parents of children with chronic health conditions. Conclusions Urban African American parents are active users of the Internet and mobile technology for social interactions, but they are less likely to use it for accessing or communicating health information. However, most parents expressed an interest in receiving health information or utilizing social networking to learn more about health topics. Mobile technology and social networks may be an underutilized method of providing health information to underserved minority populations. PMID:24418967

Security Shift in Future Network Architectures

DTIC Science & Technology

2010-11-01

RTO-MP-IST-091 2 - 1 Security Shift in Future Network Architectures Tim Hartog, M.Sc Information Security Dept. TNO Information and...current practice military communication infrastructures are deployed as stand-alone networked information systems. Network -Enabled Capabilities (NEC) and...information architects and security specialists about the separation of network and information security, the consequences of this shift and our view

Understanding latent structures of clinical information logistics: A bottom-up approach for model building and validating the workflow composite score.

PubMed

Esdar, Moritz; Hübner, Ursula; Liebe, Jan-David; Hüsers, Jens; Thye, Johannes

2017-01-01

Clinical information logistics is a construct that aims to describe and explain various phenomena of information provision to drive clinical processes. It can be measured by the workflow composite score, an aggregated indicator of the degree of IT support in clinical processes. This study primarily aimed to investigate the yet unknown empirical patterns constituting this construct. The second goal was to derive a data-driven weighting scheme for the constituents of the workflow composite score and to contrast this scheme with a literature based, top-down procedure. This approach should finally test the validity and robustness of the workflow composite score. Based on secondary data from 183 German hospitals, a tiered factor analytic approach (confirmatory and subsequent exploratory factor analysis) was pursued. A weighting scheme, which was based on factor loadings obtained in the analyses, was put into practice. We were able to identify five statistically significant factors of clinical information logistics that accounted for 63% of the overall variance. These factors were "flow of data and information", "mobility", "clinical decision support and patient safety", "electronic patient record" and "integration and distribution". The system of weights derived from the factor loadings resulted in values for the workflow composite score that differed only slightly from the score values that had been previously published based on a top-down approach. Our findings give insight into the internal composition of clinical information logistics both in terms of factors and weights. They also allowed us to propose a coherent model of clinical information logistics from a technical perspective that joins empirical findings with theoretical knowledge. Despite the new scheme of weights applied to the calculation of the workflow composite score, the score behaved robustly, which is yet another hint of its validity and therefore its usefulness. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Artificial intelligence applications in logistics information systems : final report

DOT National Transportation Integrated Search

1990-04-01

This report is the principal deliverable from the LIMSS-AI project. It summarizes the results of a survey of existing applications and discusses the feasibility and benefits of specific candidate logistics applications.

Logistics modelling: improving resource management and public information strategies in Florida.

PubMed

Walsh, Daniel M; Van Groningen, Chuck; Craig, Brian

2011-10-01

One of the most time-sensitive and logistically-challenging emergency response operations today is to provide mass prophylaxis to every man, woman and child in a community within 48 hours of a bioterrorism attack. To meet this challenge, federal, state and local public health departments in the USA have joined forces to develop, test and execute large-scale bioterrorism response plans. This preparedness and response effort is funded through the US Centers for Disease Control and Prevention's Cities Readiness Initiative, a programme dedicated to providing oral antibiotics to an entire population within 48 hours of a weaponised inhalation anthrax attack. This paper will demonstrate how the State of Florida used a logistics modelling tool to improve its CRI mass prophylaxis plans. Special focus will be on how logistics modelling strengthened Florida's resource management policies and validated its public information strategies.

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

NASA Technical Reports Server (NTRS)

Griffin, Sandy (Editor)

1987-01-01

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered.

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

NASA Astrophysics Data System (ADS)

Shishebori, Davood; Babadi, Abolghasem Yousefi

2018-03-01

This study investigates the reliable multi-configuration capacitated logistics network design problem (RMCLNDP) under system disturbances, which relates to locating facilities, establishing transportation links, and also allocating their limited capacities to the customers conducive to provide their demand on the minimum expected total cost (including locating costs, link constructing costs, and also expected costs in normal and disturbance conditions). In addition, two types of risks are considered; (I) uncertain environment, (II) system disturbances. A two-level mathematical model is proposed for formulating of the mentioned problem. Also, because of the uncertain parameters of the model, an efficacious possibilistic robust optimization approach is utilized. To evaluate the model, a drug supply chain design (SCN) is studied. Finally, an extensive sensitivity analysis was done on the critical parameters. The obtained results show that the efficiency of the proposed approach is suitable and is worthwhile for analyzing the real practical problems.

The moderating role of social networks in the relationship between alcohol consumption and treatment utilization for alcohol-related problems

PubMed Central

Mowbray, Orion

2014-01-01

Many individuals wait until alcohol use becomes severe before treatment is sought. However, social networks, or the number of social groups an individual belongs to, may play a moderating role in this relationship. Logistic regression examined the interaction of alcohol consumption and social networks as a predictor of treatment utilization while adjusting for sociodemographic and clinical variables among 1,433 lifetime alcohol-dependent respondents from wave 2 of the National Epidemiologic Survey on Alcohol Related Conditions (NESARC). Results showed that social networks moderate the relationship between alcohol consumption and treatment utilization such that for individuals with few network ties, the relationship between alcohol consumption and treatment utilization was diminished, compared to the relationship between alcohol consumption and treatment utilization for individuals with many network ties. Findings offer insight into how social networks, at times, can influence individuals to pursue treatment, while at other times, influence individuals to stay out of treatment, or seek treatment substitutes. PMID:24462223

Social support network characteristics and sexual risk taking among a racially/ethnically diverse sample of young, urban men who have sex with men.

PubMed

Kapadia, F; Siconolfi, D E; Barton, S; Olivieri, B; Lombardo, L; Halkitis, P N

2013-06-01

Associations between social support network characteristics and sexual risk among racially/ethnically diverse young men who have sex with men (YMSM) were examined using egocentric network data from a prospective cohort study of YMSM (n = 501) recruited in New York City. Bivariate and multivariable logistic regression analyses examined associations between social support network characteristics and sexual risk taking behaviors in Black, Hispanic/Latino, and White YMSM. Bivariate analyses indicated key differences in network size, composition, communication frequency and average relationship duration by race/ethnicity. In multivariable analyses, controlling for individual level sociodemographic, psychosocial and relationship factors, having a sexual partner in one's social support network was associated with unprotected sexual behavior for both Hispanic/Latino (AOR = 3.90) and White YMSM (AOR = 4.93). Further examination of key network characteristics across racial/ethnic groups are warranted in order to better understand the extant mechanisms for provision of HIV prevention programming to racially/ethnically diverse YMSM at risk for HIV.

How Did the Information Flow in the #AlphaGo Hashtag Network? A Social Network Analysis of the Large-Scale Information Network on Twitter.

PubMed

Kim, Jinyoung

2017-12-01

As it becomes common for Internet users to use hashtags when posting and searching information on social media, it is important to understand who builds a hashtag network and how information is circulated within the network. This article focused on unlocking the potential of the #AlphaGo hashtag network by addressing the following questions. First, the current study examined whether traditional opinion leadership (i.e., the influentials hypothesis) or grassroot participation by the public (i.e., the interpersonal hypothesis) drove dissemination of information in the hashtag network. Second, several unique patterns of information distribution by key users were identified. Finally, the association between attributes of key users who exerted great influence on information distribution (i.e., the number of followers and follows) and their central status in the network was tested. To answer the proffered research questions, a social network analysis was conducted using a large-scale hashtag network data set from Twitter (n = 21,870). The results showed that the leading actors in the network were actively receiving information from their followers rather than serving as intermediaries between the original information sources and the public. Moreover, the leading actors played several roles (i.e., conversation starters, influencers, and active engagers) in the network. Furthermore, the number of their follows and followers were significantly associated with their central status in the hashtag network. Based on the results, the current research explained how the information was exchanged in the hashtag network by proposing the reciprocal model of information flow.

Federal Logistics Information System (FLIS) Procedures Manual. Volume 5: Data Bank Interrogations/Search.

DTIC Science & Technology

1995-04-01

NO. 5 DoD 4100.39-M D oD 4100.39-MN Volume 5 DLSC- VPH 1 January 1997 "N FEDERAL LOGISTICS INFORMATION SYSTEM (FLIS) PROCEDURES MANUAL I. Volume 5. DoD...LOGISTICS SERVICES CENTER 74 WASHINGTON AVE N BATTLE CREEK MI 49017-3084 CH 4 CHANGE NO. 4 DoD 4100.39-M DoD 4100.39-M Volume 5 DLSC- VPH 1 July 1996 "FEDERAL...CENTER Volume 5 74 WASHINGTON AVE N BATTLE CREEK, MI 49017-3084 DLSC- VPH 1 April 1995 FOREWORD This is one of the volumes (see backside of cover for

Defense Logistics: DOD Needs to Take Additional Actions to Address Challenges in Supply Chain Management

DTIC Science & Technology

2011-07-01

Jack E. Edwa appendix III. t rds Director, Defense Capabilities and Managemen Page 36 GAO-11-569 Defense Logistics List of Committees...Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302... operations . DOD faces asset visibility challenges due, in part, to a lack of interoperability among information technology

Network structure of subway passenger flows

NASA Astrophysics Data System (ADS)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

Distributed Data Networks That Support Public Health Information Needs.

PubMed

Tabano, David C; Cole, Elizabeth; Holve, Erin; Davidson, Arthur J

Data networks, consisting of pooled electronic health data assets from health care providers serving different patient populations, promote data sharing, population and disease monitoring, and methods to assess interventions. Better understanding of data networks, and their capacity to support public health objectives, will help foster partnerships, expand resources, and grow learning health systems. We conducted semistructured interviews with 16 key informants across the United States, identified as network stakeholders based on their respective experience in advancing health information technology and network functionality. Key informants were asked about their experience with and infrastructure used to develop data networks, including each network's utility to identify and characterize populations, usage, and sustainability. Among 11 identified data networks representing hundreds of thousands of patients, key informants described aggregated health care clinical data contributing to population health measures. Key informant interview responses were thematically grouped to illustrate how networks support public health, including (1) infrastructure and information sharing; (2) population health measures; and (3) network sustainability. Collaboration between clinical data networks and public health entities presents an opportunity to leverage infrastructure investments to support public health. Data networks can provide resources to enhance population health information and infrastructure.

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

Logistics Force Planner Assistant (Log Planner)

DTIC Science & Technology

1989-09-01

elements. The system is implemented on a MS-DOS based microcomputer, using the "Knowledge Pro’ software tool., 20 DISTRIBUTION/AVAILABILITY OF... service support structure. 3. A microcomputer-based knowledge system was developed and successfully demonstrated. Four modules of information are...combat service support (CSS) units planning process to Army Staff logistics planners. Personnel newly assigned to logistics planning need an

Physical inactivity mediates the association between the perceived exercising behavior of social network members and obesity: a cross-sectional study.

PubMed

Leroux, Janette S; Moore, Spencer; Richard, Lucie; Gauvin, Lise

2012-01-01

Social networks influence the spread of depression, health behaviors, and obesity. The social networks of older urban-dwelling adults were examined to assess whether physical inactivity mediated the association between social networks and obesity. Data come from the Montreal Neighborhood Networks and Healthy Aging study (n=2707). Self-reported height and weight were used to calculate body mass index (BMI) with obesity defined as a BMI ≥ 30. A name generator/interpreter instrument was used to elicit participants' core ties (i.e., alters), and assess whether alters exercised regularly and resided in participants' neighborhoods. The International Physical Activity Questionnaire was used to measure physical inactivity. Separate multilevel logistic regression analyses were conducted for younger (18-54 years) and older (55 years plus) age groups to examine the association between the exercising behavior of alters and obesity. Ancillary analyses examined whether the residential location of alters was associated with obesity. Mediation analyses assessed whether physical inactivity mediated the association between alter exercising behavior and obesity. Models adjusted for participant socio-demographic and -economic characteristics. Among the older age stratum (55 years plus), physically inactive individuals were more likely obese (OR 2.14; 95% CIs: 1.48-3.10); participants who had more exercising alters were less likely obese (OR: 0.85; 95% CIs: 0.72-0.99). Physical inactivity mediated the association between exercising alters and obesity. Ancillary analyses showed that having exercising alters in the neighborhood compared to other locations tended to reduce the odds of obesity. This work demonstrates the importance of social networks among older adults in facilitating a physically active lifestyle and reducing the odds of obesity. Such findings can inform the design of public health interventions that seek to improve the environmental conditions supporting the physical activity of older adults.

Integrated palliative care is about professional networking rather than standardisation of care: A qualitative study with healthcare professionals in 19 integrated palliative care initiatives in five European countries

PubMed Central

den Herder-van der Eerden, Marlieke; van Wijngaarden, Jeroen; Preston, Nancy; Linge-Dahl, Lisa; Radbruch, Lukas; Van Beek, Karen; Menten, Johan; Busa, Csilla; Csikos, Agnes; Vissers, Kris; van Gurp, Jelle; Hasselaar, Jeroen

2018-01-01

Background: Integrated palliative care aims at improving coordination of palliative care services around patients’ anticipated needs. However, international comparisons of how integrated palliative care is implemented across four key domains of integrated care (content of care, patient flow, information logistics and availability of (human) resources and material) are lacking. Aim: To examine how integrated palliative care takes shape in practice across abovementioned key domains within several integrated palliative care initiatives in Europe. Design: Qualitative group interview design. Setting/participants: A total of 19 group interviews were conducted (2 in Belgium, 4 in the Netherlands, 4 in the United Kingdom, 4 in Germany and 5 in Hungary) with 142 healthcare professionals from several integrated palliative care initiatives in five European countries. The majority were nurses (n = 66; 46%) and physicians (n = 50; 35%). Results: The dominant strategy for fostering integrated palliative care is building core teams of palliative care specialists and extended professional networks based on personal relationships, shared norms, values and mutual trust, rather than developing standardised information exchange and referral pathways. Providing integrated palliative care with healthcare professionals in the wider professional community appears difficult, as a shared proactive multidisciplinary palliative care approach is lacking, and healthcare professionals often do not know palliative care professionals or services. Conclusion: Achieving better palliative care integration into regular healthcare and convincing the wider professional community is a difficult task that will take time and effort. Enhancing standardisation of palliative care into education, referral pathways and guidelines and standardised information exchange may be necessary. External authority (policy makers, insurance companies and professional bodies) may be needed to support integrated palliative care practices across settings. PMID:29436279

Integrated palliative care is about professional networking rather than standardisation of care: A qualitative study with healthcare professionals in 19 integrated palliative care initiatives in five European countries.

PubMed

den Herder-van der Eerden, Marlieke; van Wijngaarden, Jeroen; Payne, Sheila; Preston, Nancy; Linge-Dahl, Lisa; Radbruch, Lukas; Van Beek, Karen; Menten, Johan; Busa, Csilla; Csikos, Agnes; Vissers, Kris; van Gurp, Jelle; Hasselaar, Jeroen

2018-06-01

Integrated palliative care aims at improving coordination of palliative care services around patients' anticipated needs. However, international comparisons of how integrated palliative care is implemented across four key domains of integrated care (content of care, patient flow, information logistics and availability of (human) resources and material) are lacking. To examine how integrated palliative care takes shape in practice across abovementioned key domains within several integrated palliative care initiatives in Europe. Qualitative group interview design. A total of 19 group interviews were conducted (2 in Belgium, 4 in the Netherlands, 4 in the United Kingdom, 4 in Germany and 5 in Hungary) with 142 healthcare professionals from several integrated palliative care initiatives in five European countries. The majority were nurses ( n = 66; 46%) and physicians ( n = 50; 35%). The dominant strategy for fostering integrated palliative care is building core teams of palliative care specialists and extended professional networks based on personal relationships, shared norms, values and mutual trust, rather than developing standardised information exchange and referral pathways. Providing integrated palliative care with healthcare professionals in the wider professional community appears difficult, as a shared proactive multidisciplinary palliative care approach is lacking, and healthcare professionals often do not know palliative care professionals or services. Achieving better palliative care integration into regular healthcare and convincing the wider professional community is a difficult task that will take time and effort. Enhancing standardisation of palliative care into education, referral pathways and guidelines and standardised information exchange may be necessary. External authority (policy makers, insurance companies and professional bodies) may be needed to support integrated palliative care practices across settings.

Usage and acceptability of HIV self-testing in men who have sex with men in Hong Kong.

PubMed

Wong, Horas Tze Hoo; Tam, Hoi Yan; Chan, Denise Pui Chung; Lee, Shui Shan

2015-03-01

Whilst studies on over-the-counter HIV tests continue to accumulate after FDA's approval of OraQuick Advance in 2012, few have focused on men who have sex with men (MSM) in Asian cities. An internet survey was conducted on 1,122 MSM in Hong Kong, revealing a low usage (6.1 %) and acceptability rate (43.8 %) on self-testing despite its availability in the market. Hierarchical logistic regression models showed that having received relevant information and users' attitudes on self-testing were the determinants of usage and acceptability. These factors had greater effects than sexual behaviors and social-networking on MSM's decision on self-testing. Majority of ever self-testers only repeated the self-test after a non-negative result, and overall only 26.6 % went for a formal test subsequent to the self-test. Concerns regarding the tests' accuracy were expressed by respondents. In conclusion, appropriate and accessible information and evidence-based guidance are needed to incorporate self-testing into HIV prevention strategies targeting MSM.

Development and evaluation of an ambulatory stress monitor based on wearable sensors.

PubMed

Choi, Jongyoon; Ahmed, Beena; Gutierrez-Osuna, Ricardo

2012-03-01

Chronic stress is endemic to modern society. However, as it is unfeasible for physicians to continuously monitor stress levels, its diagnosis is nontrivial. Wireless body sensor networks offer opportunities to ubiquitously detect and monitor mental stress levels, enabling improved diagnosis, and early treatment. This article describes the development of a wearable sensor platform to monitor a number of physiological correlates of mental stress. We discuss tradeoffs in both system design and sensor selection to balance information content and wearability. Using experimental signals collected from the wearable sensor, we describe a selected number of physiological features that show good correlation with mental stress. In particular, we propose a new spectral feature that estimates the balance of the autonomic nervous system by combining information from the power spectral density of respiration and heart rate variability. We validate the effectiveness of our approach on a binary discrimination problem when subjects are placed under two psychophysiological conditions: mental stress and relaxation. When used in a logistic regression model, our feature set is able to discriminate between these two mental states with a success rate of 81% across subjects. © 2012 IEEE

An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry.

PubMed

Tung, Feng-Cheng; Chang, Su-Chao; Chou, Chi-Min

2008-05-01

Ever since National Health Insurance was introduced in 1995, the number of insurants increased to over 96% from 50 to 60%, with a continuous satisfaction rating of about 70%. However, the premium accounted for 5.77% of GDP in 2001 and the Bureau of National Health Insurance had pressing financial difficulties, so it reformed its expenditure systems, such as fee for service, capitation, case payment and the global budget system in order to control the rising medical costs. Since the change in health insurance policy, most hospitals attempted to reduce their operating expenses and improve efficiency. Introducing the electronic logistics information system is one way of reducing the cost of the department of central warehouse and the nursing stations. Hence, the study proposes a technology acceptance research model and examines how nurses' acceptance of the e-logistics information system has been affected in the medical industry. This research combines innovation diffusion theory, technology acceptance model and added two research parameters, trust and perceived financial cost to propose a new hybrid technology acceptance model. Taking Taiwan's medical industry as an experimental example, this paper studies nurses' acceptance of the electronic logistics information system. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to examine the reliability and validity of the measurement model. The results of the survey strongly support the new hybrid technology acceptance model in predicting nurses' intention to use the electronic logistics information system. The study shows that 'compatibility', 'perceived usefulness', 'perceived ease of use', and 'trust' all have great positive influence on 'behavioral intention to use'. On the other hand 'perceived financial cost' has great negative influence on behavioral intention to use.

High density ozone monitoring using gas sensitive semi-conductor sensors in the Lower Fraser Valley, British Columbia.

PubMed

Bart, Mark; Williams, David E; Ainslie, Bruce; McKendry, Ian; Salmond, Jennifer; Grange, Stuart K; Alavi-Shoshtari, Maryam; Steyn, Douw; Henshaw, Geoff S

2014-04-01

A cost-efficient technology for accurate surface ozone monitoring using gas-sensitive semiconducting oxide (GSS) technology, solar power, and automated cell-phone communications was deployed and validated in a 50 sensor test-bed in the Lower Fraser Valley of British Columbia, over 3 months from May-September 2012. Before field deployment, the entire set of instruments was colocated with reference instruments for at least 48 h, comparing hourly averaged data. The standard error of estimate over a typical range 0-50 ppb for the set was 3 ± 2 ppb. Long-term accuracy was assessed over several months by colocation of a subset of ten instruments each at a different reference site. The differences (GSS-reference) of hourly average ozone concentration were normally distributed with mean -1 ppb and standard deviation 6 ppb (6000 measurement pairs). Instrument failures in the field were detected using network correlations and consistency checks on the raw sensor resistance data. Comparisons with modeled spatial O3 fields demonstrate the enhanced monitoring capability of a network that was a hybrid of low-cost and reference instruments, in which GSS sensors are used both to increase station density within a network as well as to extend monitoring into remote areas. This ambitious deployment exposed a number of challenges and lessons, including the logistical effort required to deploy and maintain sites over a summer period, and deficiencies in cell phone communications and battery life. Instrument failures at remote sites suggested that redundancy should be built into the network (especially at critical sites) as well as the possible addition of a "sleep-mode" for GSS monitors. At the network design phase, a more objective approach to optimize interstation distances, and the "information" content of the network is recommended. This study has demonstrated the utility and affordability of the GSS technology for a variety of applications, and the effectiveness of this technology as a means substantially and economically to extend the coverage of an air quality monitoring network. Low-cost, neighborhood-scale networks that produce reliable data can be envisaged.

The transfer and transformation of collective network information in gene-matched networks.

PubMed

Kitsukawa, Takashi; Yagi, Takeshi

2015-10-09

Networks, such as the human society network, social and professional networks, and biological system networks, contain vast amounts of information. Information signals in networks are distributed over nodes and transmitted through intricately wired links, making the transfer and transformation of such information difficult to follow. Here we introduce a novel method for describing network information and its transfer using a model network, the Gene-matched network (GMN), in which nodes (neurons) possess attributes (genes). In the GMN, nodes are connected according to their expression of common genes. Because neurons have multiple genes, the GMN is cluster-rich. We show that, in the GMN, information transfer and transformation were controlled systematically, according to the activity level of the network. Furthermore, information transfer and transformation could be traced numerically with a vector using genes expressed in the activated neurons, the active-gene array, which was used to assess the relative activity among overlapping neuronal groups. Interestingly, this coding style closely resembles the cell-assembly neural coding theory. The method introduced here could be applied to many real-world networks, since many systems, including human society and various biological systems, can be represented as a network of this type.

Information network architectures

NASA Technical Reports Server (NTRS)

Murray, N. D.

1985-01-01

Graphs, charts, diagrams and outlines of information relative to information network architectures for advanced aerospace missions, such as the Space Station, are presented. Local area information networks are considered a likely technology solution. The principle needs for the network are listed.

Analysis of Logistics in Support of a Human Lunar Outpost

NASA Technical Reports Server (NTRS)

Cirillo, William; Earle, Kevin; Goodliff, Kandyce; Reeves, j. D.; Andrashko, Mark; Merrill, R. Gabe; Stromgren, Chel

2008-01-01

Strategic level analysis of the integrated behavior of lunar transportation system and lunar surface system architecture options is performed to inform NASA Constellation Program senior management on the benefit, viability, affordability, and robustness of system design choices. This paper presents an overview of the approach used to perform the campaign (strategic) analysis, with an emphasis on the logistics modeling and the impacts of logistics resupply on campaign behavior. An overview of deterministic and probabilistic analysis approaches is provided, with a discussion of the importance of each approach to understanding the integrated system behavior. The logistics required to support lunar surface habitation are analyzed from both 'macro-logistics' and 'micro-logistics' perspectives, where macro-logistics focuses on the delivery of goods to a destination and micro-logistics focuses on local handling of re-supply goods at a destination. An example campaign is provided to tie the theories of campaign analysis to results generation capabilities.

Sample size determination for logistic regression on a logit-normal distribution.

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

Some Initiatives in a Business Forecasting Course

ERIC Educational Resources Information Center

Chu, Singfat

2007-01-01

The paper reports some initiatives to freshen up the typical undergraduate business forecasting course. These include (1) students doing research and presentations on contemporary tools and industry practices such as neural networks and collaborative forecasting (2) insertion of Logistic Regression in the curriculum (3) productive use of applets…

Riparian Sediment Delivery Ratio: Stiff Diagrams and Artifical Neural Networks

EPA Science Inventory

Various methods are used to estimate sediment transport through riparian buffers and grass jilters with the sediment delivery ratio having been the most widely applied. The U.S. Forest Service developed a sediment delivery ratio using the stiff diagram and a logistic curve to int...

Data Mining in Child Welfare.

ERIC Educational Resources Information Center

Schoech, Dick; Quinn, Andrew; Rycraft, Joan R.

2000-01-01

Examines the historical and larger context of data mining and describes data mining processes, techniques, and tools. Illustrates these using a child welfare dataset concerning the employee turnover that is mined, using logistic regression and a Bayesian neural network. Discusses the data mining process, the resulting models, their predictive…

Logistics in hospitals: a case study of some Singapore hospitals.

PubMed

Pan, Zhi Xiong; Pokharel, Shaligram

2007-01-01

The purpose of this paper is to investigate logistics activities in Singapore hospitals. It defines various types of activities handled by a logistics division. Inventory management policy and the use of information and communication technologies (ICT) for logistics purposes are also discussed. The study identifies the nature of strategic alliances in Singapore's health care industry. This study was conducted by utilizing a framework for data collection, pre-testing the questionnaire and conducting interviews. Various relevant literature was reviewed to design the questionnaire. This study finds that logistics division carry out many related activities and some of them also provide engineering services. The hospitals make use of ICT. The hospitals are clustered under various groups to minimize the cost of operation, including the logistics related costs. However, hospitals do not see alliances with suppliers as a strategic option; rather they focus on outsourcing of logistics services. The findings also show that Singapore hospitals have a good stocking policy for both medical and non-medical items so that changes in patient mix can be easily handled. Singapore is continuously improving its health care industry and therefore, the findings will help hospitals in other regions to adopt some of the practices, like concentrating on local vendors, outsourcing, clustering, and maximum use of information technology as competitive factors that can improve the service and reduce the cost of operation. The paper suggests motivators and barriers to the use of ICT in logistics in the health care industry.

Hazards of New Media: Youth’s Exposure to Tobacco Ads/Promotions

PubMed Central

2014-01-01

Background: A gap in knowledge exists about the youth’s exposure to protobacco campaigns via new electronic media outlets. In response, we use national data to delineate the associations between tobacco ads/promotions delivered through new media outlets (i.e., social network sites and text messages) and youth attitudes/beliefs about tobacco and intent to use (among youth who had not yet used tobacco). Methods: Data were derived from the 2011 National Youth Tobacco Survey, a nationally representative sample of U.S. youth enrolled in both public and private schools (N = 15,673). Logistic regression models were used to examine associations between demographic characteristics and reported exposure to tobacco ads/promotions via social networking sites and text messages. Logistic regression models were also used to investigate associations between exposure tobacco ads/promotions and attitudes toward tobacco. Results: We found that highly susceptible youth (i.e., minorities, very young youth, and youth who have not yet used tobacco) have observed tobacco ads/promotions on social networking sites and text messages. These youth are more likely to have favorable attitudes toward tobacco, including the intention to use tobacco among those who had not yet used tobacco. Conclusions: Our findings underscore the need for policy strategies to more effectively monitor and regulate tobacco advertising via new media outlets. PMID:24163285

Hazards of new media: youth's exposure to tobacco Ads/promotions.

PubMed

Cavazos-Rehg, Patricia A; Krauss, Melissa J; Spitznagel, Edward L; Grucza, Richard A; Bierut, Laura Jean

2014-04-01

A gap in knowledge exists about the youth's exposure to protobacco campaigns via new electronic media outlets. In response, we use national data to delineate the associations between tobacco ads/promotions delivered through new media outlets (i.e., social network sites and text messages) and youth attitudes/beliefs about tobacco and intent to use (among youth who had not yet used tobacco). Data were derived from the 2011 National Youth Tobacco Survey, a nationally representative sample of U.S. youth enrolled in both public and private schools (N = 15,673). Logistic regression models were used to examine associations between demographic characteristics and reported exposure to tobacco ads/promotions via social networking sites and text messages. Logistic regression models were also used to investigate associations between exposure tobacco ads/promotions and attitudes toward tobacco. We found that highly susceptible youth (i.e., minorities, very young youth, and youth who have not yet used tobacco) have observed tobacco ads/promotions on social networking sites and text messages. These youth are more likely to have favorable attitudes toward tobacco, including the intention to use tobacco among those who had not yet used tobacco. Our findings underscore the need for policy strategies to more effectively monitor and regulate tobacco advertising via new media outlets.

78 FR 17418 - Rural Health Information Technology Network Development Grant

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-21

... Information Technology Network Development Grant AGENCY: Health Resources and Services Administration (HRSA...-competitive replacement award under the Rural Health Information Technology Network Development Grant (RHITND... relinquishing its fiduciary responsibilities for the Rural Health Information Technology Network Development...

The effects of social networks on tobacco use among high-school adolescents in Mexico.

PubMed

Ramírez-Ortiz, Guadalupe; Caballero-Hoyos, Ramiro; Ramírez-López, Guadalupe; Valente, Thomas W

2012-01-01

To identify the effect of centrality in social network positions on tobacco-use among high-school adolescents in Tonala, Jalisco, Mexico. Longitudinal sociometric social network data were collected among 486 high-school adolescents in 2003 and 399 in 2004. The survey included: social network components, smoking and sociodemographic characteristics. Social network measures of centrality were calculated and multivariate logistic regression was used. Ever used tobacco (OR= 44.98), marginalized-low stratum (OR= 2.16) and in-degree (OR=1.10) predicted tobacco use. Out-degree (OR= 0 .89) and out-in-degree (OR= 0.90) protected against tobacco use. Nominating more friends rather than receiving such nominations was protective for tobacco use. Popular students, those receiving many nominations, were at higher risk for tobacco use. Involvement of leaders with capacity to influence might be an efficient strategy for dissemination of preventive messages.

Analysis of Transportation and Logistics Challenges Affecting the Deployment of Larger Wind Turbines: Summary of Results

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

Cotrell, J.; Stehly, T.; Johnson, J.

There is relatively little literature that characterizes transportation and logistics challenges and the associated effects on U.S. wind markets. The objectives of this study were to identify the transportation and logistics challenges, assess the associated impacts, and provide recommendations for strategies and specific actions to address the challenges. The authors primarily relied on interviews with wind industry project developers, original equipment manufacturers, and transportation and logistics companies to obtain the information and industry perspectives needed for this study. They also reviewed published literature on trends and developments in increasing wind turbine size, logistics, and transportation issues.

48 CFR 247.301-70 - Definition.

Code of Federal Regulations, 2012 CFR

2012-10-01

... logistics services. Some examples of logistics services are the management of transportation, demand forecasting, information management, inventory maintenance, warehousing, and distribution. [65 FR 50145, Aug..., DEPARTMENT OF DEFENSE CONTRACT MANAGEMENT TRANSPORTATION Transportation in Supply Contracts 247.301-70...

48 CFR 247.301-70 - Definition.

Code of Federal Regulations, 2014 CFR

2014-10-01

... logistics services. Some examples of logistics services are the management of transportation, demand forecasting, information management, inventory maintenance, warehousing, and distribution. [65 FR 50145, Aug..., DEPARTMENT OF DEFENSE CONTRACT MANAGEMENT TRANSPORTATION Transportation in Supply Contracts 247.301-70...

48 CFR 247.301-70 - Definition.

Code of Federal Regulations, 2013 CFR

2013-10-01

... logistics services. Some examples of logistics services are the management of transportation, demand forecasting, information management, inventory maintenance, warehousing, and distribution. [65 FR 50145, Aug..., DEPARTMENT OF DEFENSE CONTRACT MANAGEMENT TRANSPORTATION Transportation in Supply Contracts 247.301-70...

48 CFR 247.301-70 - Definition.

Code of Federal Regulations, 2010 CFR

2010-10-01

... logistics services. Some examples of logistics services are the management of transportation, demand forecasting, information management, inventory maintenance, warehousing, and distribution. [65 FR 50145, Aug..., DEPARTMENT OF DEFENSE CONTRACT MANAGEMENT TRANSPORTATION Transportation in Supply Contracts 247.301-70...

48 CFR 247.301-70 - Definition.

Code of Federal Regulations, 2011 CFR

2011-10-01

... logistics services. Some examples of logistics services are the management of transportation, demand forecasting, information management, inventory maintenance, warehousing, and distribution. [65 FR 50145, Aug..., DEPARTMENT OF DEFENSE CONTRACT MANAGEMENT TRANSPORTATION Transportation in Supply Contracts 247.301-70...

A prospective examination of online social network dynamics and smoking cessation

PubMed Central

Zhao, Kang; Papandonatos, George D.; Erar, Bahar; Wang, Xi; Amato, Michael S.; Cha, Sarah; Cohn, Amy M.; Pearson, Jennifer L.

2017-01-01

Introduction Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence. Method Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics. Results Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05). Conclusions This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors. PMID:28832621

Implementation of Motivational Interviewing in Substance Use Disorder Treatment: Research Network Participation and Organizational Compatibility.

PubMed

Rieckmann, Traci R; Abraham, Amanda J; Bride, Brian E

Despite considerable empirical evidence that psychosocial interventions improve addiction treatment outcomes across populations, implementation remains problematic. A small body of research points to the importance of research network participation as a facilitator of implementation; however, studies examined limited numbers of evidence-based practices. To address this gap, the present study examined factors impacting implementation of motivational interviewing (MI). This study used data from a national sample of privately funded treatment programs (n = 345) and programs participating in the National Drug Abuse Treatment Clinical Trials Network (CTN) (n = 156). Data were collected via face-to-face interviews with program administrators and clinical directors (2007-2009). Analysis included bivariate t tests and chi-square tests to compare private and CTN programs, and multivariable logistic regression of MI implementation. A majority (68.0%) of treatment programs reported use of MI. Treatment programs participating in the CTN (88.9%) were significantly more likely to report use of MI compared with non-CTN programs (58.5%; P < 0.01). CTN programs (82.1%) also were more likely to use trainers from the Motivational Interviewing Network of Trainers as compared with private programs (56.1%; P < 0.05). Multivariable logistic regression models reveal that CTN-affiliated programs and programs with a psychiatrist on staff were more likely to use MI. Programs that used the Stages of Change Readiness and Treatment Eagerness Scale assessment tool were more likely to use MI, whereas programs placing greater emphasis on confrontational group therapy were less likely to use MI. Findings suggest the critical role of research network participation, access to psychiatrists, and organizational compatibility in adoption and sustained use of MI.

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.

PubMed

Lenselink, Eelke B; Ten Dijke, Niels; Bongers, Brandon; Papadatos, George; van Vlijmen, Herman W T; Kowalczyk, Wojtek; IJzerman, Adriaan P; van Westen, Gerard J P

2017-08-14

The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method ('DNN_PCM') performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized 'DNN_PCM'). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols. Graphical Abstract .

Expeditionary Logistics: How the Marine Corps Supports Its Expeditionary Operations

DTIC Science & Technology

2015-06-01

little additional information of value with regard to the U.S. Marine Corps and expeditionary logistics methodology. Since the expeditionary methodology...size and scope, necessitating differing levels of material support. Additionally , the same variables define the level of Combat Service Support that is...lie outside of doctrine and few manuals have been written discussing how the Marine Corps performs expeditionary logistics. Additionally , few sources

LOGMIS Programmed Texts, Tests and Answers.

DTIC Science & Technology

1979-04-01

This publication contains the programmed text and related test and answer booklets produced to teach field users correct procedures for utilization of the Army’s Logistics Management Information System (LOGMIS). It was prepared by ARINC Research Corporation under Contract DAEA18-77-C-0184 for the Logistics Evaluation Branch, Plans and Programs Division of the Assistant Chief of Staff for Logistics, U.S. Army Communications Command. (Author)

Assessing the Robustness of Graph Statistics for Network Analysis Under Incomplete Information

DTIC Science & Technology

strategy for dismantling these networks based on their network structure. However, these strategies typically assume complete information about the...combat them with missing information . This thesis analyzes the performance of a variety of network statistics in the context of incomplete information by...leveraging simulation to remove nodes and edges from networks and evaluating the effect this missing information has on our ability to accurately

Intergenerational Social Networks and Health Behaviors Among Children Living in Public Housing.

PubMed

Kennedy-Hendricks, Alene; Schwartz, Heather; Thornton, Rachel Johnson; Griffin, Beth Ann; Green, Harold D; Kennedy, David P; Burkhauser, Susan; Pollack, Craig Evan

2015-11-01

In a survey of families living in public housing, we investigated whether caretakers' social networks are linked with children's health status. In 2011, 209 children and their caretakers living in public housing in suburban Montgomery County, Maryland, were surveyed regarding their health and social networks. We used logistic regression models to examine the associations between the perceived health composition of caretaker social networks and corresponding child health characteristics (e.g., exercise, diet). With each 10% increase in the proportion of the caretaker's social network that exercised regularly, the child's odds of exercising increased by 34% (adjusted odds ratio = 1.34; 95% confidence interval = 1.07, 1.69) after the caretaker's own exercise behavior and the composition of the child's peer network had been taken into account. Although children's overweight or obese status was associated with caretakers' social networks, the results were no longer significant after adjustment for caretakers' own weight status. We found that caretaker social networks are independently associated with certain aspects of child health, suggesting the importance of the broader social environment for low-income children's health.

The effect of high leverage points on the logistic ridge regression estimator having multicollinearity

NASA Astrophysics Data System (ADS)

Ariffin, Syaiba Balqish; Midi, Habshah

2014-06-01

This article is concerned with the performance of logistic ridge regression estimation technique in the presence of multicollinearity and high leverage points. In logistic regression, multicollinearity exists among predictors and in the information matrix. The maximum likelihood estimator suffers a huge setback in the presence of multicollinearity which cause regression estimates to have unduly large standard errors. To remedy this problem, a logistic ridge regression estimator is put forward. It is evident that the logistic ridge regression estimator outperforms the maximum likelihood approach for handling multicollinearity. The effect of high leverage points are then investigated on the performance of the logistic ridge regression estimator through real data set and simulation study. The findings signify that logistic ridge regression estimator fails to provide better parameter estimates in the presence of both high leverage points and multicollinearity.

“ADHD Knowledge, Perceptions and Information Sources: Perspectives from a Community Sample of Adolescents and their Parents”

PubMed Central

Bussing, Regina; Zima, Bonnie T.; Mason, Dana M.; Meyer, Johanna.M.; White, Kimberly; Garvan, Cynthia W.

2012-01-01

PURPOSE The chronic illness model advocates for psychoeducation within a collaborative care model to enhance outcomes. To inform psychoeducational approaches for attention-deficit/hyperactivity disorder (ADHD), this study describes parent and adolescent knowledge, perceptions and information sources and explores how these vary by sociodemographic characteristics, ADHD risk, and past child mental health service use. METHODS Parents and adolescents were assessed 7.7 years after initial school district screening for ADHD risk. The study sample included 374 adolescents (56% high and 44% low ADHD risk), on average 15.4 (SD 1.8) years old, and 36% were African American. Survey questions assessed ADHD knowledge, perceptions, and cues to action, and elicited utilized and preferred information sources. Multiple logistic regression was used to determine potential independent predictors of ADHD knowledge. McNemar's tests compared information source utilization against preference. RESULTS Despite relatively high self-rated ADHD familiarity, misperceptions among parents and adolescents were common, including a sugar etiology (25% and 27%, respectively) and medication overuse (85% and 67%). African American respondents expressed lower ADHD awareness and greater belief in sugar etiology than Caucasians. Parents used a wide range of ADHD information sources while adolescents relied on social network members and teachers/school. However, parents and adolescents expressed similar strong preferences for the Internet (49% and 51%) and doctor (40% and 27%) as ADHD information sources. CONCLUSION Culturally appropriate psychoeducational strategies are needed that combine doctor-provided ADHD information with reputable Internet sources. Despite time limitations during patient visits, both parents and teens place high priority on receiving information from their doctor. PMID:23174470

Automation of the longwall mining system

NASA Technical Reports Server (NTRS)

Zimmerman, W.; Aster, R. W.; Harris, J.; High, J.

1982-01-01

Cost effective, safe, and technologically sound applications of automation technology to underground coal mining were identified. The longwall analysis commenced with a general search for government and industry experience of mining automation technology. A brief industry survey was conducted to identify longwall operational, safety, and design problems. The prime automation candidates resulting from the industry experience and survey were: (1) the shearer operation, (2) shield and conveyor pan line advance, (3) a management information system to allow improved mine logistics support, and (4) component fault isolation and diagnostics to reduce untimely maintenance delays. A system network analysis indicated that a 40% improvement in productivity was feasible if system delays associated with all of the above four areas were removed. A technology assessment and conceptual system design of each of the four automation candidate areas showed that state of the art digital computer, servomechanism, and actuator technologies could be applied to automate the longwall system.

Green Collar Workers: An Emerging Workforce in the Environmental Sector

PubMed Central

McClure, Laura A.; LeBlanc, William G.; Fernandez, Cristina A.; Fleming, Lora E.; Lee, David J.; Moore, Kevin J.; Caban-Martinez, Alberto J.

2017-01-01

Objective We describe the socio-demographic, occupational, and health characteristics of “green collar” workers, a vital and emerging workforce in energy-efficiency and sustainability. Methods We linked data from the 2004–2012 National Health Interview Surveys (NHIS) and US Occupational Information Network (O*NET). Descriptive and logistic regression analyses were conducted using green collar worker status as the outcome (n=143,346). Results Green collar workers are more likely than non-green workers to be male, age 25–64y, obese, and with ≤ high school education. They are less likely to be racial/ethnic minorities and employed in small companies or government jobs. Conclusions Green collar workers have a distinct socio-demographic and occupational profile, and this workforce deserves active surveillance to protect its workers’ safety. The NHIS-O*NET linkage represents a valuable resource to further identify the unique exposures and characteristics of this occupational sector. PMID:28403016

Green Collar Workers: An Emerging Workforce in the Environmental Sector.

PubMed

McClure, Laura A; LeBlanc, William G; Fernandez, Cristina A; Fleming, Lora E; Lee, David J; Moore, Kevin J; Caban-Martinez, Alberto J

2017-05-01

We describe the socio-demographic, occupational, and health characteristics of "green collar" workers, a vital and emerging workforce in energy-efficiency and sustainability. We linked data from the 2004 to 2012 National Health Interview Surveys (NHIS) and US Occupational Information Network (O*NET). Descriptive and logistic regression analyses were conducted using green collar worker status as the outcome (n = 143,346). Green collar workers are more likely than non-green workers to be men, age 25 to 64 years, obese, and with less than or equal to high school (HS) education. They are less likely to be racial/ethnic minorities and employed in small companies or government jobs. Green collar workers have a distinct socio-demographic and occupational profile, and this workforce deserves active surveillance to protect its workers' safety. The NHIS-O*NET linkage represents a valuable resource to further identify the unique exposures and characteristics of this occupational sector.

Distributed Cognition and Process Management Enabling Individualized Translational Research: The NIH Undiagnosed Diseases Program Experience

PubMed Central

Links, Amanda E.; Draper, David; Lee, Elizabeth; Guzman, Jessica; Valivullah, Zaheer; Maduro, Valerie; Lebedev, Vlad; Didenko, Maxim; Tomlin, Garrick; Brudno, Michael; Girdea, Marta; Dumitriu, Sergiu; Haendel, Melissa A.; Mungall, Christopher J.; Smedley, Damian; Hochheiser, Harry; Arnold, Andrew M.; Coessens, Bert; Verhoeven, Steven; Bone, William; Adams, David; Boerkoel, Cornelius F.; Gahl, William A.; Sincan, Murat

2016-01-01

The National Institutes of Health Undiagnosed Diseases Program (NIH UDP) applies translational research systematically to diagnose patients with undiagnosed diseases. The challenge is to implement an information system enabling scalable translational research. The authors hypothesized that similar complex problems are resolvable through process management and the distributed cognition of communities. The team, therefore, built the NIH UDP integrated collaboration system (UDPICS) to form virtual collaborative multidisciplinary research networks or communities. UDPICS supports these communities through integrated process management, ontology-based phenotyping, biospecimen management, cloud-based genomic analysis, and an electronic laboratory notebook. UDPICS provided a mechanism for efficient, transparent, and scalable translational research and thereby addressed many of the complex and diverse research and logistical problems of the NIH UDP. Full definition of the strengths and deficiencies of UDPICS will require formal qualitative and quantitative usability and process improvement measurement. PMID:27785453

Web usage mining at an academic health sciences library: an exploratory study.

PubMed

Bracke, Paul J

2004-10-01

This paper explores the potential of multinomial logistic regression analysis to perform Web usage mining for an academic health sciences library Website. Usage of database-driven resource gateway pages was logged for a six-month period, including information about users' network addresses, referring uniform resource locators (URLs), and types of resource accessed. It was found that referring URL did vary significantly by two factors: whether a user was on-campus and what type of resource was accessed. Although the data available for analysis are limited by the nature of the Web and concerns for privacy, this method demonstrates the potential for gaining insight into Web usage that supplements Web log analysis. It can be used to improve the design of static and dynamic Websites today and could be used in the design of more advanced Web systems in the future.

Newborn screening progress in developing countries--overcoming internal barriers.

PubMed

Padilla, Carmencita D; Krotoski, Danuta; Therrell, Bradford L

2010-04-01

Newborn screening is an important public health measure aimed at early identification and management of affected newborns thereby lowering infant morbidity and mortality. It is a comprehensive system of education, screening, follow-up, diagnosis, treatment/management, and evaluation that must be institutionalized and sustained within public health systems often challenged by economic, political, and cultural considerations. As a result, developing countries face unique challenges in implementing and expanding newborn screening that can be grouped into the following categories: (1) planning, (2) leadership, (3) medical support, (4) technical support, (5) logistical support, (6) education, (7) protocol and policy development, (8) administration, (9) evaluation, and (10) sustainability. We review some of the experiences in overcoming implementation challenges in developing newborn screening programs, and discuss recent efforts to encourage increased newborn screening through support networking and information exchange activities in 2 regions-the Asia Pacific and the Middle East/North Africa. Copyright 2010 Elsevier Inc. All rights reserved.

76 FR 67750 - Homeland Security Information Network Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-02

... DEPARTMENT OF HOMELAND SECURITY [Docket No. DHS-2011-0107] Homeland Security Information Network... Information Network Advisory Committee. SUMMARY: The Secretary of Homeland Security has determined that the renewal of the Homeland Security Information Network Advisory Committee (HSINAC) is necessary and in the...

78 FR 7797 - Homeland Security Information Network Advisory Committee (HSINAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-04

... DEPARTMENT OF HOMELAND SECURITY [Docket No. DHS-2013-0005] Homeland Security Information Network... Committee Meeting. SUMMARY: The Homeland Security Information Network Advisory Committee (HSIN AC) will meet... received by the (Homeland Security Information Network Advisory Committee), go to http://www.regulations...

78 FR 71631 - Committee Name: Homeland Security Information Network Advisory Committee (HSINAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-29

... Network Advisory Committee (HSINAC) AGENCY: Operation Coordination and Planning/Office of Chief.... SUMMARY: The Homeland Security Information Network Advisory Council (HSINAC) will meet December 17, 2013... , Phone: 202-343-4212. SUPPLEMENTARY INFORMATION: The Homeland Security Information Network Advisory...

78 FR 34665 - Homeland Security Information Network Advisory Committee (HSINAC); Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-10

... DEPARTMENT OF HOMELAND SECURITY [DHS-2013-0037] Homeland Security Information Network Advisory... Committee Meeting. SUMMARY: The Homeland Security Information Network Advisory Committee (HSINAC) will meet... posted beforehand at this link: http://www.dhs.gov/homeland-security-information-network-advisory...

75 FR 57521 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-21

... NATIONAL SCIENCE FOUNDATION Networking and Information Technology Research and Development (NITRD...) for Networking and Information Technology Research and Development (NITRD). ACTION: Notice, request.... SUMMARY: With this notice, the National Coordination Office for Networking and Information Technology...

Baby Bell Libraries?--An Update.

ERIC Educational Resources Information Center

Kessler, Jack

1993-01-01

Discusses the emerging three-tiered structure (i.e., the "Baby Bells," network nodes, and information marketers) that will assume responsibility for implementing a new national information network and getting networked information to the public. The role of libraries related to networked information is also considered. (EA)

Measuring Networking as an Outcome Variable in Undergraduate Research Experiences

PubMed Central

Hanauer, David I.; Hatfull, Graham

2015-01-01

The aim of this paper is to propose, present, and validate a simple survey instrument to measure student conversational networking. The tool consists of five items that cover personal and professional social networks, and its basic principle is the self-reporting of degrees of conversation, with a range of specific discussion partners. The networking instrument was validated in three studies. The basic psychometric characteristics of the scales were established by conducting a factor analysis and evaluating internal consistency using Cronbach’s alpha. The second study used a known-groups comparison and involved comparing outcomes for networking scales between two different undergraduate laboratory courses (one involving a specific effort to enhance networking). The final study looked at potential relationships between specific networking items and the established psychosocial variable of project ownership through a series of binary logistic regressions. Overall, the data from the three studies indicate that the networking scales have high internal consistency (α = 0.88), consist of a unitary dimension, can significantly differentiate between research experiences with low and high networking designs, and are related to project ownership scales. The ramifications of the networking instrument for student retention, the enhancement of public scientific literacy, and the differentiation of laboratory courses are discussed. PMID:26538387

Culture, economic development, social-network type, and mortality: Evidence from Chinese older adults.

PubMed

Li, Ting; Yang, Yang Claire; Zhang, Yanlong

2018-05-01

This study examined the patterns of social-network types and their relative survival benefits among Chinese older adults. We examined how macro-level social factors such as cultural norms and unbalanced regional economic development shaped older people's network behaviors, and whether these factors could moderate the association between network types and mortality. Using data from the Chinese Longitudinal Healthy Longevity Survey (2008-2014), we identified four network types-diverse, friend-focused, family-focused, and restricted-based on individuals' social network measures. Multinomial logistic analyses revealed that older people situated in an area with a deeply rooted family culture or a more advanced economy tend to be less likely to enroll in a diverse network than a family-focused one. This prevents them from achieving the best adaptive survival, as Cox regression analyses showed that the family-focused network type was less beneficial than the diverse one for the survival of older adults. Furthermore, while the survival advantage of the diverse-network type over the family-focused type did not change with cultural contexts, economic development attenuated the deleterious effects of the friend-focused network type. Copyright © 2018 Elsevier Ltd. All rights reserved.

Pattern of exposure to information and its impact on seasonal influenza vaccination uptake in nurses.

PubMed

Cheung, E K H; Lee, S; Lee, S S

2017-12-01

Uptake of annual influenza vaccination of healthcare workers (HCWs) varies, and remains at a suboptimal level in many countries. As HCWs are often exposed to a variety of information about vaccination, the pattern of exposure may impact their decision; this deserves further investigation. Practising nurses in Hong Kong were invited to participate in an anonymous online survey in February 2016, after the winter seasonal peak. The questionnaire covered demographics, work nature and experiences, vaccination uptake history and reasons for vaccination decisions. Two behavioural categories for access to information were defined - passive exposure to information and active information-seeking - differentiated by the source, type and nature of information accessed. Chi-squared test, Mann-Whitney U-test and logistic regression were performed to compare vaccinated and unvaccinated nurses. In total, 1177 valid returns were received from nurses. The median age of respondents was 32 years and 86% were female. The overall vaccination rate was 33%. Passive exposure to information from the workplace, professional body and social network was not predictive of vaccination decision, but passive exposure to information from mass media was predictive [odds ratio (OR) 1.78]. Active information-seeking, such as consulting a senior (OR 2.46), organizing promotional activities (OR 2.85) and undertaking an information search (OR 2.43), was significantly associated with increased vaccination uptake. A cumulative effect could be demonstrated for active information-seeking (OR 1.86), but not for passive exposure to information. The current strategy of promotions and campaigns for seasonal influenza vaccination in HCWs may not be effective in increasing vaccination coverage. Measures targeting information-seeking behaviours may serve as an alternative approach. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

The Radius of Trust: Religion, Social Embeddedness and Trust in Strangers

ERIC Educational Resources Information Center

Welch, Michael R.; Sikkink, David; Loveland, Matthew T.

2007-01-01

Data from the 2002 Religion and Public Activism Survey were used to examine relationships among measures of religious orientation, embeddedness in social networks and the level of trust individuals direct toward others. Results from ordered logistic regression analysis demonstrate that Catholics and members of other denominations show…

Using a novel flood prediction model and GIS automation to measure the valley and channel morphology of large river networks

EPA Science Inventory

Traditional methods for measuring river valley and channel morphology require intensive ground-based surveys which are often expensive, time consuming, and logistically difficult to implement. The number of surveys required to assess the hydrogeomorphic structure of large river n...

75 FR 28181 - National Defense Transportation Day and National Transportation Week, 2010

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-20

... ensure America has a world-class logistics and transportation system to support our military readiness... the President of the United States of America A Proclamation The transportation networks of early America connected our rapidly growing Nation with natural waterways and dirt roads, making travel...

It Takes a Village: Network Effects on Rural Education in Afghanistan. PRGS Dissertation

ERIC Educational Resources Information Center

Hoover, Matthew Amos

2014-01-01

Often, development organizations confront a tradeoff between program priorities and operational constraints. These constraints may be financial, capacity, or logistical; regardless, the tradeoff often requires sacrificing portions of a program. This work is concerned with figuring out how, when constrained, an organization or program manager can…

Stellar Parameter Determination With J-Plus Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Whitten, Devin D.

2017-10-01

The J-PLUS narrow-band filter system provides a unique opportunity for the determination of stellar parameters and chemical abundances from photometry alone. Mapping stellar magnitudes to estimates of surface temperature, [Fe/H], and [C/Fe] is an excellent application of machine learning and in particular, artificial neural networks (ANN). The logistics and performance of this ANN methodology is explored with the J-PLUS Early Data Release, as well as the potential impact of stellar parameters from J-PLUS on the field of Galactic chemical evolution.

New scaling relation for information transfer in biological networks

PubMed Central

Kim, Hyunju; Davies, Paul; Walker, Sara Imari

2015-01-01

We quantify characteristics of the informational architecture of two representative biological networks: the Boolean network model for the cell-cycle regulatory network of the fission yeast Schizosaccharomyces pombe (Davidich et al. 2008 PLoS ONE 3, e1672 (doi:10.1371/journal.pone.0001672)) and that of the budding yeast Saccharomyces cerevisiae (Li et al. 2004 Proc. Natl Acad. Sci. USA 101, 4781–4786 (doi:10.1073/pnas.0305937101)). We compare our results for these biological networks with the same analysis performed on ensembles of two different types of random networks: Erdös–Rényi and scale-free. We show that both biological networks share features in common that are not shared by either random network ensemble. In particular, the biological networks in our study process more information than the random networks on average. Both biological networks also exhibit a scaling relation in information transferred between nodes that distinguishes them from random, where the biological networks stand out as distinct even when compared with random networks that share important topological properties, such as degree distribution, with the biological network. We show that the most biologically distinct regime of this scaling relation is associated with a subset of control nodes that regulate the dynamics and function of each respective biological network. Information processing in biological networks is therefore interpreted as an emergent property of topology (causal structure) and dynamics (function). Our results demonstrate quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not share the same informational properties. PMID:26701883

Link prediction measures considering different neighbors’ effects and application in social networks

NASA Astrophysics Data System (ADS)

Luo, Peng; Wu, Chong; Li, Yongli

Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.

32 CFR 1285.4 - Responsibilities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Defense Other Regulations Relating to National Defense DEFENSE LOGISTICS AGENCY MISCELLANEOUS DEFENSE LOGISTICS AGENCY FREEDOM OF INFORMATION ACT PROGRAM § 1285.4 Responsibilities. (a) The Staff Director... program, providing guidance and instructions to PLFA's and PSE's. (2) Designates a FOIA manager to...

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow.

PubMed

Zubek, Julian; Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

2017-01-01

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems.

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow

PubMed Central

Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

2017-01-01

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems. PMID:28809957

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security... 47 Telecommunication 3 2013-10-01 2013-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.5111 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Proprietary Network Information. § 64.5111 Notification of customer proprietary network information security... 47 Telecommunication 3 2013-10-01 2013-10-01 false Notification of customer proprietary network information security breaches. 64.5111 Section 64.5111 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.5111 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Proprietary Network Information. § 64.5111 Notification of customer proprietary network information security... 47 Telecommunication 3 2014-10-01 2014-10-01 false Notification of customer proprietary network information security breaches. 64.5111 Section 64.5111 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security... 47 Telecommunication 3 2014-10-01 2014-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security... 47 Telecommunication 3 2012-10-01 2012-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

Logistics Lessons Learned in NASA Space Flight

NASA Technical Reports Server (NTRS)

Evans, William A.; DeWeck, Olivier; Laufer, Deanna; Shull, Sarah

2006-01-01

The Vision for Space Exploration sets out a number of goals, involving both strategic and tactical objectives. These include returning the Space Shuttle to flight, completing the International Space Station, and conducting human expeditions to the Moon by 2020. Each of these goals has profound logistics implications. In the consideration of these objectives,a need for a study on NASA logistics lessons learned was recognized. The study endeavors to identify both needs for space exploration and challenges in the development of past logistics architectures, as well as in the design of space systems. This study may also be appropriately applied as guidance in the development of an integrated logistics architecture for future human missions to the Moon and Mars. This report first summarizes current logistics practices for the Space Shuttle Program (SSP) and the International Space Station (ISS) and examines the practices of manifesting, stowage, inventory tracking, waste disposal, and return logistics. The key findings of this examination are that while the current practices do have many positive aspects, there are also several shortcomings. These shortcomings include a high-level of excess complexity, redundancy of information/lack of a common database, and a large human-in-the-loop component. Later sections of this report describe the methodology and results of our work to systematically gather logistics lessons learned from past and current human spaceflight programs as well as validating these lessons through a survey of the opinions of current space logisticians. To consider the perspectives on logistics lessons, we searched several sources within NASA, including organizations with direct and indirect connections with the system flow in mission planning. We utilized crew debriefs, the John Commonsense lessons repository for the JSC Mission Operations Directorate, and the Skylab Lessons Learned. Additionally, we searched the public version of the Lessons Learned Information System (LLIS) and verified that we received the same result using the internal version of LLIS for our logistics lesson searches. In conducting the research, information from multiple databases was consolidated into a single spreadsheet of 300 lessons learned. Keywords were applied for the purpose of sorting and evaluation. Once the lessons had been compiled, an analysis of the resulting data was performed, first sorting it by keyword, then finding duplication and root cause, and finally sorting by root cause. The data was then distilled into the top 7 lessons learned across programs, centers, and activities.

How multiple social networks affect user awareness: The information diffusion process in multiplex networks

NASA Astrophysics Data System (ADS)

Li, Weihua; Tang, Shaoting; Fang, Wenyi; Guo, Quantong; Zhang, Xiao; Zheng, Zhiming

2015-10-01

The information diffusion process in single complex networks has been extensively studied, especially for modeling the spreading activities in online social networks. However, individuals usually use multiple social networks at the same time, and can share the information they have learned from one social network to another. This phenomenon gives rise to a new diffusion process on multiplex networks with more than one network layer. In this paper we account for this multiplex network spreading by proposing a model of information diffusion in two-layer multiplex networks. We develop a theoretical framework using bond percolation and cascading failure to describe the intralayer and interlayer diffusion. This allows us to obtain analytical solutions for the fraction of informed individuals as a function of transmissibility T and the interlayer transmission rate θ . Simulation results show that interaction between layers can greatly enhance the information diffusion process. And explosive diffusion can occur even if the transmissibility of the focal layer is under the critical threshold, due to interlayer transmission.

Information Diffusion in Facebook-Like Social Networks Under Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Dynamic information routing in complex networks

PubMed Central

Kirst, Christoph; Timme, Marc; Battaglia, Demian

2016-01-01

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

Navy Technical Information Presentation System (NTIPS) Test and Implementation Strategy

DTIC Science & Technology

1981-12-01

IC AROEROCK I NAOI S ~ i P RF R M N C AVI AT OIO N A N DDEPARTMENT STIPRUCTRMNES COMPUATIONAN DEPARTMENT -MATHEMATICS AND 17 LOGISTICS DEPARTMENT leI...and Subtitle) S . TYPE OF REPORT & PERIOD COVERED NAVY TECHNICAL INFORMATION PRESENTATION Final SYSTEM (NTIPS) TEST AND IMPLEMENTATION 6. PERFORMING...CLASSIFICATION OP THIS PAGE (1nor. Data Enteed) ock 20 continued) system operation, training, maintenance, and logistics support. This system was

47 CFR 64.2005 - Use of customer proprietary network information without customer approval.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Use of customer proprietary network information without customer approval. 64.2005 Section 64.2005 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2005 Use of customer proprietary network information without customer...

77 FR 33229 - Notice of Proposed Information Collection: Comment Request; National Resource Network

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-05

... Information Collection: Comment Request; National Resource Network AGENCY: Office of the Assistant Secretary... information: Title of Proposal: National Resource Network. OMB Control Number, if applicable: None... and reporting information related to the proposed National Resource Network. The U.S. Department of...

47 CFR 64.2005 - Use of customer proprietary network information without customer approval.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Use of customer proprietary network information without customer approval. 64.2005 Section 64.2005 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2005 Use of customer proprietary network information without customer...

Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks

NASA Astrophysics Data System (ADS)

Kan, Jia-Qian; Zhang, Hai-Feng

2017-03-01

In this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results on single-layer network: local information based behavioral response can alter the epidemic threshold. Furthermore, our results indicate that the nodes with more neighbors (hub nodes) in information networks are easier to be informed, as a result, their risk of infection in contact networks can be effectively reduced.

The association of relationship quality and social networks with depression, anxiety, and suicidal ideation among older married adults: Findings from a cross-sectional analysis of the Irish Longitudinal Study on Ageing (TILDA).

PubMed

Santini, Ziggi Ivan; Koyanagi, Ai; Tyrovolas, Stefanos; Haro, Josep M

2015-07-01

Important associations have been found between social relationships and various mental health outcomes. However, limited data exists for these associations among older adults especially in terms of relationship quality in partnerships. This study aimed to examine the associations of positive and negative partner interactions and social networks with depression, anxiety and suicidal ideation. Nationally-representative, cross-sectional data of the Irish Longitudinal Study on Ageing (TILDA) was analyzed. The analytical sample consisted of 4988 community dwelling adults aged >50 years in spouse/partner relationships. Information on sociodemographics and social relationships were assessed using standard questions. Validated scales for depression and anxiety, and a single-item question for suicidal ideation were used to assess mental health outcomes. Multivariable logistic regression was used to assess the association between social relationships and depression, anxiety, and suicidal ideation. After adjusting for confounders, negative partner interactions were significantly associated with increased likelihood of depression, anxiety, and suicidal ideation, while positive partner interactions were significantly and inversely related to anxiety and suicidal ideation. Higher levels of social integration were significantly associated with lower odds for depression. Given the cross-sectional nature of the research, no firm conclusions can be made in terms of directions of causality. By assessing the available social network of older adults, as well as the areas in their social relationships that need to be addressed, it may be possible for practitioners and policy makers to maximize the benefits of network integration and minimize the potentially harmful aspects of social relationships, thereby improving overall mental health and emotional well-being. Copyright © 2015 Elsevier B.V. All rights reserved.

Associations Between Internet-Based Professional Social Networking and Emotional Distress

PubMed Central

Jones, Jacquelynn R.; Colditz, Jason B.; Shensa, Ariel; Sidani, Jaime E.; Lin, Liu Yi; Terry, Martha Ann

2016-01-01

Abstract Professional social networking websites are commonly used among young professionals. In light of emerging concerns regarding social networking use and emotional distress, the purpose of this study was to investigate the association between frequency of use of LinkedIn, the most commonly used professional social networking website, and depression and anxiety among young adults. In October 2014, we assessed a nationally representative sample of 1,780 U.S. young adults between the ages of 19–32 regarding frequency of LinkedIn use, depression and anxiety, and sociodemographic covariates. We measured depression and anxiety using validated Patient-Reported Outcomes Measurement Information System measures. We used bivariable and multivariable logistic regression to assess the association between LinkedIn use and depression and anxiety, while controlling for age, sex, race, relationship status, living situation, household income, education level, and overall social media use. In weighted analyses, 72% of participants did not report use of LinkedIn, 16% reported at least some use, but less than once each week, and 12% reported use at least once per week. In multivariable analyses controlling for all covariates, compared with those who did not use LinkedIn, participants using LinkedIn at least once per week had significantly greater odds of increased depression (adjusted odds ratio [AOR] = 2.10, 95% confidence interval [CI] = 1.31–3.38) and increased anxiety (AOR = 2.79, 95% CI = 1.72–4.53). LinkedIn use was significantly related to both outcomes in a dose–response manner. Future research should investigate directionality of this association and possible reasons for it. PMID:27732077

Mother ship and physical agents collaboration

NASA Astrophysics Data System (ADS)

Young, Stuart H.; Budulas, Peter P.; Emmerman, Philip J.

1999-07-01

This paper discusses ongoing research at the U.S. Army Research Laboratory that investigates the feasibility of developing a collaboration architecture between small physical agents and a mother ship. This incudes the distribution of planning, perception, mobility, processing and communications requirements between the mother ship and the agents. Small physical agents of the future will be virtually everywhere on the battlefield of the 21st century. A mother ship that is coupled to a team of small collaborating physical agents (conducting tasks such as Reconnaissance, Surveillance, and Target Acquisition (RSTA); logistics; sentry; and communications relay) will be used to build a completely effective and mission capable intelligent system. The mother ship must have long-range mobility to deploy the small, highly maneuverable agents that will operate in urban environments and more localized areas, and act as a logistics base for the smaller agents. The mother ship also establishes a robust communications network between the agents and is the primary information disseminating and receiving point to the external world. Because of its global knowledge and processing power, the mother ship does the high-level control and planning for the collaborative physical agents. This high level control and interaction between the mother ship and its agents (including inter agent collaboration) will be software agent architecture based. The mother ship incorporates multi-resolution battlefield visualization and analysis technology, which aids in mission planning and sensor fusion.