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.

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.

Experiences with engineering, making and deploying sensor networks

NASA Astrophysics Data System (ADS)

Martinez, K.; Hart, J. K.

2008-12-01

Engineers and computer scientists will usually persuade themselves that producing a sensor network is matter of design, test and deploy. After several deployments in and on Glaciers within the Glacsweb project we are in a better position to understand the reality of producing sensor networks for real-world deployments. Not only does the electronics design, programming, management and logistics have to be perfected but a full understanding of the geoscience user's priorities and needs have to be an integral part of the system. This talk will outline the achievements of the 2008 Iceland subglacial probe deployment concentrating on the unexpected things which can affect the success of such a system. This includes the design of a new sensor node which is designed for low power, easy programming and high flexibility.

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.

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.

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.

Application of wireless sensor network technology in logistics information system

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2017-04-01

This paper introduces the basic concepts of active RFID (WSN-ARFID) based on wireless sensor networks and analyzes the shortcomings of the existing RFID-based logistics monitoring system. Integrated wireless sensor network technology and the scrambling point of RFID technology. A new real-time logistics detection system based on WSN and RFID, a model of logistics system based on WSN-ARFID is proposed, and the feasibility of this technology applied to logistics field is analyzed.

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.

Strategies on the Implementation of China's Logistics Information Network

NASA Astrophysics Data System (ADS)

Dong, Yahui; Li, Wei; Guo, Xuwen

The economic globalization and trend of e-commerce network have determined that the logistics industry will be rapidly developed in the 21st century. In order to achieve the optimal allocation of resources, a worldwide rapid and sound customer service system should be established. The establishment of a corresponding modern logistics system is the inevitable choice of this requirement. It is also the inevitable choice for the development of modern logistics industry in China. The perfect combination of modern logistics and information network can better promote the development of the logistics industry. Through the analysis of Status of Logistics Industry in China, this paper summed up the domestic logistics enterprise logistics information system in the building of some common problems. According to logistics information systems planning methods and principles set out logistics information system to optimize the management model.

Designing optimal greenhouse gas monitoring networks for Australia

NASA Astrophysics Data System (ADS)

Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

2016-01-01

Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

The design of the automated control system for warehouse equipment under radio-electronic manufacturing

NASA Astrophysics Data System (ADS)

Kapulin, D. V.; Chemidov, I. V.; Kazantsev, M. A.

2017-01-01

In the paper, the aspects of design, development and implementation of the automated control system for warehousing under the manufacturing process of the radio-electronic enterprise JSC «Radiosvyaz» are discussed. The architecture of the automated control system for warehousing proposed in the paper consists of a server which is connected to the physically separated information networks: the network with a database server, which stores information about the orders for picking, and the network with the automated storage and retrieval system. This principle allows implementing the requirements for differentiation of access, ensuring the information safety and security requirements. Also, the efficiency of the developed automated solutions in terms of optimizing the warehouse’s logistic characteristics is researched.

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,...

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.

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

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

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

NASA Astrophysics Data System (ADS)

Vahdani, Behnam; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz; Baboli, Arman

2013-06-01

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

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.

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

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.

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.

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.

Developing a cross-docking network design model under uncertain environment

NASA Astrophysics Data System (ADS)

Seyedhoseini, S. M.; Rashid, Reza; Teimoury, E.

2015-06-01

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transportation and operating costs. The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock. To prepare a perfect illustration for performance of the model, a real case also has been examined that indicated effectiveness of the proposed model.

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.

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.

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.

PubMed

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant.

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

DTIC Science & Technology

1983-06-01

constrained at each step. Use of dis- crete simulation can be a powerful tool in this process if its role is carefully planned. The gross behavior of the...by projecting: - the arrival of units of work at SPLICE processing facilities (workload analysis) . - the amount of processing resources comsumed in

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.

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.

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

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.

Organizational Analysis of Energy Manpower Requirements in the United States Navy

DTIC Science & Technology

2013-06-01

ix LIST OF FIGURES Figure 1.  A 1.5 Megawatt wind turbine set up at the Marine Corps Logistics Base in Barstow, CA. (From Flores, 2010...Figure 1. A 1.5 Megawatt wind turbine set up at the Marine Corps Logistics Base in Barstow, CA. (From Flores, 2010) 9 In an effort to capture...electronic and information warfare systems ) (h ) Network Engineering (including wireless networks, sensor networks, high speed data networking, and

Global Supply Chain Management at Digital Equipment Corporation

DTIC Science & Technology

1995-01-01

Global Supply Chain Management at Digital Equipment Corporation BRUCE C. ARNTZEN Gr t~ALD G...answers change; and -Are tax havens worth the extra freight and duty. In designing a global logistics network, they must decide 71 ARNTZEN ET AL...but is solved with heunshcs. Cohen and Lee (1988, p . 216] continue 73 ARNTZEN ET AL. with a set of approximate stochastic sub- models and

In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

PubMed Central

Lu, Peng; Chen, Jianxin; Zhao, Huihui; Gao, Yibo; Luo, Liangtao; Zuo, Xiaohan; Shi, Qi; Yang, Yiping; Yi, Jianqiang; Wang, Wei

2012-01-01

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM. PMID:22567030

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.

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.

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.

Campaign-level dynamic network modelling for spaceflight logistics for the flexible path concept

NASA Astrophysics Data System (ADS)

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

2016-06-01

This paper develops a network optimization formulation for dynamic campaign-level space mission planning. Although many past space missions have been designed mainly from a mission-level perspective, a campaign-level perspective will be important for future space exploration. In order to find the optimal campaign-level space transportation architecture, a mixed-integer linear programming (MILP) formulation with a generalized multi-commodity flow and a time-expanded network is developed. Particularly, a new heuristics-based method, a partially static time-expanded network, is developed to provide a solution quickly. The developed method is applied to a case study containing human exploration of a near-Earth object (NEO) and Mars, related to the concept of the Flexible Path. The numerical results show that using the specific combinations of propulsion technologies, in-situ resource utilization (ISRU), and other space infrastructure elements can reduce the initial mass in low-Earth orbit (IMLEO) significantly. In addition, the case study results also show that we can achieve large IMLEO reduction by designing NEO and Mars missions together as a campaign compared with designing them separately owing to their common space infrastructure pre-deployment. This research will be an important step toward efficient and flexible campaign-level space mission planning.

Application of neural networks and sensitivity analysis to improved prediction of trauma survival.

PubMed

Hunter, A; Kennedy, L; Henry, J; Ferguson, I

2000-05-01

The performance of trauma departments is widely audited by applying predictive models that assess probability of survival, and examining the rate of unexpected survivals and deaths. Although the TRISS methodology, a logistic regression modelling technique, is still the de facto standard, it is known that neural network models perform better. A key issue when applying neural network models is the selection of input variables. This paper proposes a novel form of sensitivity analysis, which is simpler to apply than existing techniques, and can be used for both numeric and nominal input variables. The technique is applied to the audit survival problem, and used to analyse the TRISS variables. The conclusions discuss the implications for the design of further improved scoring schemes and predictive models.

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.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

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.

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.

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.

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

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.

The Logistics Knowledge Portal: Gateway to More Individualized Learning in Logistics.

ERIC Educational Resources Information Center

Neumann, Gaby; Krzyzaniak, Stanislaw; Lassen, Carl Christian

This paper describes a research and development project initiated by a network of European logistics educators to promote all types, forms, and levels of logistics education by benefiting from the educational potential of multimedia/hypermedia as well as information technology and telecommunications. The main outcome of this project will be a…

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.

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.

Logistics system design for biomass-to-bioenergy industry with multiple types of feedstocks.

PubMed

Zhu, Xiaoyan; Yao, Qingzhu

2011-12-01

It is technologically possible for a biorefinery to use a variety of biomass as feedstock including native perennial grasses (e.g., switchgrass) and agricultural residues (e.g., corn stalk and wheat straw). Incorporating the distinct characteristics of various types of biomass feedstocks and taking into account their interaction in supplying the bioenergy production, this paper proposed a multi-commodity network flow model to design the logistics system for a multiple-feedstock biomass-to-bioenergy industry. The model was formulated as a mixed integer linear programming, determining the locations of warehouses, the size of harvesting team, the types and amounts of biomass harvested/purchased, stored, and processed in each month, the transportation of biomass in the system, and so on. This paper demonstrated the advantages of using multiple types of biomass feedstocks by comparing with the case of using a single feedstock (switchgrass) and analyzed the relationship of the supply capacity of biomass feedstocks to the output and cost of biofuel. Copyright © 2011 Elsevier Ltd. All rights reserved.

An ultra low power feature extraction and classification system for wearable seizure detection.

PubMed

Page, Adam; Pramod Tim Oates, Siddharth; Mohsenin, Tinoosh

2015-01-01

In this paper we explore the use of a variety of machine learning algorithms for designing a reliable and low-power, multi-channel EEG feature extractor and classifier for predicting seizures from electroencephalographic data (scalp EEG). Different machine learning classifiers including k-nearest neighbor, support vector machines, naïve Bayes, logistic regression, and neural networks are explored with the goal of maximizing detection accuracy while minimizing power, area, and latency. The input to each machine learning classifier is a 198 feature vector containing 9 features for each of the 22 EEG channels obtained over 1-second windows. All classifiers were able to obtain F1 scores over 80% and onset sensitivity of 100% when tested on 10 patients. Among five different classifiers that were explored, logistic regression (LR) proved to have minimum hardware complexity while providing average F-1 score of 91%. Both ASIC and FPGA implementations of logistic regression are presented and show the smallest area, power consumption, and the lowest latency when compared to the previous work.

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...

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.

A Logical Design of a Session Services Control Layer of a Distributed Network Architecture for SPLICE (Stock Point Logistics Integrated Communication Environment).

DTIC Science & Technology

1984-06-01

Eacn stock point is autonomous witn respect to how it implements data processing support, as long as it accommodates the Navy Supply Systems Command...has its own data elements, files, programs , transactions, users, reports, and some have additional hardware. To augment them all and not force redesign... programs are written to request session establishments among them using only logical addressing names (mailboxes) whicn are independent from physical

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.

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.

Social influence and motivation to change health behaviors among Mexican origin adults: Implications for diet and physical activity

PubMed Central

Ashida, Sato; Wilkinson, Anna V.; Koehly, Laura M.

2011-01-01

Purpose To evaluate whether influence from social network members is associated with motivation to change dietary and physical activity behaviors. Design Baseline assessment followed by mailing of family health history-based personalized messages (2 weeks) and follow-up assessment (3 months). Setting Families from an ongoing population-based cohort in Houston, TX. Subjects 475 adults from 161 Mexican origin families. Out of 347 households contacted, 162 (47%) participated. Measures Family health history, social networks, and motivation to change behaviors. Analysis Two-level logistic regression modeling. Results Having at least one network member who encourages one to eat more fruits and vegetables (p=.010) and to engage in regular physical activity (p=.046) was associated with motivation to change the relevant behavior. About 40% of the participants did not have encouragers for these behaviors. Conclusions Identification of new encouragers within networks and targeting natural encouragers (e.g., children, spouses) may increase the efficacy of interventions to motivate behavioral changes among Mexican origin adults. PMID:22208416

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

Robust PRNG based on homogeneously distributed chaotic dynamics

NASA Astrophysics Data System (ADS)

Garasym, Oleg; Lozi, René; Taralova, Ina

2016-02-01

This paper is devoted to the design of new chaotic Pseudo Random Number Generator (CPRNG). Exploring several topologies of network of 1-D coupled chaotic mapping, we focus first on two dimensional networks. Two topologically coupled maps are studied: TTL rc non-alternate, and TTL SC alternate. The primary idea of the novel maps has been based on an original coupling of the tent and logistic maps to achieve excellent random properties and homogeneous /uniform/ density in the phase plane, thus guaranteeing maximum security when used for chaos base cryptography. In this aim two new nonlinear CPRNG: MTTL 2 sc and NTTL 2 are proposed. The maps successfully passed numerous statistical, graphical and numerical tests, due to proposed ring coupling and injection mechanisms.

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.

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

Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic

NASA Astrophysics Data System (ADS)

Levchenko, N. G.; Glushkov, S. V.; Sobolevskaya, E. Yu; Orlov, A. P.

2018-05-01

The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.

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.

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.

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.

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.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali mohammad

2014-01-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14% reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali Mohammad

2014-05-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

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.

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.

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

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.

Social Network Type and Subjective Well-being in a National Sample of Older Americans

PubMed Central

Litwin, Howard; Shiovitz-Ezra, Sharon

2011-01-01

Purpose: The study considers the social networks of older Americans, a population for whom there have been few studies of social network type. It also examines associations between network types and well-being indicators: loneliness, anxiety, and happiness. Design and Methods: A subsample of persons aged 65 years and older from the first wave of the National Social Life, Health, and Aging Project was employed (N = 1,462). We applied K-means cluster analysis to derive social network types using 7 criterion variables. In the multivariate stage, the well-being outcomes were regressed on the network type construct and on background and health characteristics by means of logistic regression. Results: Five social network types were derived: “diverse,” “friend,” “congregant,” “family,” and “restricted.” Social network type was found to be associated with each of the well-being indicators after adjusting for demographic and health confounders. Respondents embedded in network types characterized by greater social capital tended to exhibit better well-being in terms of less loneliness, less anxiety, and greater happiness. Implications: Knowledge about differing network types should make gerontological practitioners more aware of the varying interpersonal milieus in which older people function. Adopting network type assessment as an integral part of intake procedures and tracing network shifts over time can serve as a basis for risk assessment as well as a means for determining the efficacy of interventions. PMID:21097553

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.

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.

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.

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.

Connecting Land-Based Networks to Ships

DTIC Science & Technology

2013-06-01

multipoint wireless broadband systems, and WiMAX networks were initially deployed for fixed and nomadic (portable) applications. These standards...CAPABILITIES OF SHIP-TO-SHORE COMMUNICATIONS A. US Navy Automated Digital Network System (ADNS) The U.S. Navy’s Automated Digital Network System (ADNS...submit digitally any necessary documents to the terminal operators, contact their logistics providers, access tidal information and receive

Analysis of three-dimensionally proliferated sensor architectures for flexible SSA

NASA Astrophysics Data System (ADS)

Cunio, Phillip M.; Flewelling, Brien

2018-05-01

The evolution of space into a congested, contested, and competitive regime drives a commensurate need for awareness of events there. As the number of systems on orbit grows, so will the need for sensing and tracking these systems. One avenue for advanced sensing capability is a widespread network of small but capable Space Situational Awareness (SSA) sensors, proliferated widely in the three-dimensional volume extending from the Earth's surface to the Geosynchronous Earth Orbit (GEO) belt, incorporating multiple different varieties and types of sensors. Due to the freedom of movement afforded by solid surfaces and atmosphere, some of these sensors may have substantial mobility. Accordingly, designing a network for maximum SSA coverage at reasonable cost may entail heterogeneous architectures with common logistics (including modular sensor packages or mobility platforms, which may be flexibly re-assigned). Smaller mobile sensors leveraging Commercial-Off-The-Shelf (COTS) components and software are appealing for their ability to simplify logistics versus large, monolithic, uniquely-exquisite sensor systems. This paper examines concepts for such sensor systems, and analyzes the costs associated with their use, while assessing the benefits (including reduced gap time, weather resilience, and multiple-sensor coverage) that such an architecture enables. Recommendations for preferred modes and mixes of fielding sensors in a heterogeneous architecture are made, and directions for future related research are suggested.

Design logistics performance measurement model of automotive component industry for srengthening competitiveness of dealing AEC 2015

NASA Astrophysics Data System (ADS)

Amran, T. G.; Janitra Yose, Mindy

2018-03-01

As the free trade Asean Economic Community (AEC) causes the tougher competition, it is important that Indonesia’s automotive industry have high competitiveness as well. A model of logistics performance measurement was designed as an evaluation tool for automotive component companies to improve their logistics performance in order to compete in AEC. The design of logistics performance measurement model was based on the Logistics Scorecard perspectives, divided into two stages: identifying the logistics business strategy to get the KPI and arranging the model. 23 KPI was obtained. The measurement result can be taken into consideration of determining policies to improve the performance logistics competitiveness.

Logistics engineering education from the point of view environment

NASA Astrophysics Data System (ADS)

Bányai, Ágota

2010-05-01

A new field of MSc programme offered by the Faculty of Mechanical Engineering and Informatics of the University of Miskolc is represented by the programme in logistics engineering. The Faculty has always laid great emphasis on assigning processes connected with environment protection and globalisation issues the appropriate weight in its programmes. This is based on the fact that the Faculty has initiated and been involved in a great number of research and development projects with a substantial emphasis on the fundamental principles of sustainable development. The objective of the programme of logistics engineering is to train engineers who, in possession of the science, engineering, economic, informatics and industrial, transportation technological knowledge related to the professional field of logistics, are able to analyse, design, organise, and control logistics processes and systems (freight transportation, materials handling, storage, commissioning, loading, purchasing, distribution and waste management) as well as to design and develop machinery and equipment as the elements of logistic systems and also to be involved in their manufacture and quality control and are able to control their operation. The programme prepares its students for performing the logistics management tasks in a company, for creative participation in solving research and development problems in logistics and for pursuing logistics studies in doctoral programmes. There are several laboratories available for practice-oriented training. The 'Integrated Logistics Laboratory' consists of various fixed and mobile, real industrial, i.e. not model-level equipment, the integration of which in one system facilitates not only the presentation, examination and development of the individual self-standing facilities, but the study of their interaction as well in terms of mechatronics, engineering, control engineering, informatics, identification technology and logistics. The state-of-the-art, reliable, automated mechatronics-material flow system with its single control engineering system provides the academic staff with up-to-date research facilities, and enables the students to study sophisticated equipment and systems that could also operate under industrial conditions, thus offering knowledge that can be efficiently utilised in the industry after graduation. The laboratory measurements of the programme in logistics engineering are performed in this laboratory, and they are supplemented by the theoretical and practical measurements in the ‘Robotic Technology Assembly Laboratory', the ‘Power Electronics Laboratory', the ‘Mechatronics Laboratory', the ‘CAD/CAM Laboratory' and the ‘Acoustics and Product Laboratory'. The bodies of knowledge connected with environment protection and sustainable development can be grouped around three large topic areas. In environmental economics the objective is to present the corporate-organisational aspects of environmental management. Putting environmental management in the focal point, the objective of the programme is to impart knowledge that can be utilised in practice which can be used to shift the relation between the organisation and its environment in the direction of sustainability. The tools include environmental controlling, environmental marketing and various solutions of environmental performance evaluation. The second large topic area is globalization and its logistic aspects. In the field of global logistics the following knowledge carries special weight: logistic challenges in a globalised world; the concept of global logistics, its conditions and effects; delayed manufacture, assembly, packaging; the economic investigation of delayed assembly; globalised purchase and distribution in logistics; the logistic features of the globalised production supply/distribution chain; meta-logistics systems; logistics-related EU harmonisation issues; the effect of e-commerce on the global logistic system; logistic centres, connecting virtual logistic companies in a network; the environmental harmonisation of international transportation. The third large area is recycling logistics. Here the bodies of knowledge are as follows: the concept of developing a ‘closed-loop economy'; stages in the progress of products after discarding, connections between the uses of waste collection, processing, selection, deposition or reuse processes; features of European recommendations (e.g. EMAS), harmonisation of national practices and global solutions; presenting the logistics part-processes of recycling; presenting process organisation procedures for the foundation of designing one-route, multi-route, replacement container waste collecting and distributing part systems; recycling strategies with consideration of logistically serving the separation and storage of waste to be deposited, the technological processing systems of recyclable materials; presenting dismantling and product and material identification technologies, presenting logistics part-tasks, analysis of technical solutions; IT solutions for identifying products and their elements to be distributed and withdrawn from distribution after use (e.g. RFID systems) and monitoring their material flow; methodology of using efficiency analyses and incentive systems in the decision making processes of recycling processes, risk analysis for evaluating typical part processes; the methodology of recycling-oriented product design for specific product groups. Graduates of the Master programmes are able to use and utilise the knowledge obtained in practice, use problem-solving techniques; process the information, new problems and new phenomena arising in the border areas of the professional experience gained the discipline; formulate substantial criticism and opinions as far as possible, make decisions and draw conclusions; comprehending and solving the problems arising, suggesting original ideas; plan and perform tasks independently at a high professional standard; improve themselves, develop their knowledge to higher levels; view the management of technical/engineering - economic - human resources in a complex way; design complex systems in a global way based on a system-oriented and process-oriented way of thinking; use integrated knowledge from the professional fields of transport, mobile machinery, process theory, industrial production processes, electronics and informatics; combine the part processes of logistics systems and the part units performing their physical realisation (materials handling equipment, sensors, actuators, control systems, and database systems, etc.); perform state evaluations depending on their specialisation, use them to elaborate evaluations and recommendations, develop complex logistic systems, design, organise and control them at the highest level. This work was implemented with support by the European Union and co-funding of the European Social Fund.

Design, Development and Pre-Flight Testing of the Communications, Navigation, and Networking Reconfigurable Testbed (Connect) to Investigate Software Defined Radio Architecture on the International Space Station

NASA Technical Reports Server (NTRS)

Over, Ann P.; Barrett, Michael J.; Reinhart, Richard C.; Free, James M.; Cikanek, Harry A., III

2011-01-01

The Communication Navigation and Networking Reconfigurable Testbed (CoNNeCT) is a NASA-sponsored mission, which will investigate the usage of Software Defined Radios (SDRs) as a multi-function communication system for space missions. A softwaredefined radio system is a communication system in which typical components of the system (e.g., modulators) are incorporated into software. The software-defined capability allows flexibility and experimentation in different modulation, coding and other parameters to understand their effects on performance. This flexibility builds inherent redundancy and flexibility into the system for improved operational efficiency, real-time changes to space missions and enhanced reliability/redundancy. The CoNNeCT Project is a collaboration between industrial radio providers and NASA. The industrial radio providers are providing the SDRs and NASA is designing, building and testing the entire flight system. The flight system will be integrated on the Express Logistics Carrier (ELC) on the International Space Station (ISS) after launch on the H-IIB Transfer Vehicle in 2012. This paper provides an overview of the technology research objectives, payload description, design challenges and pre-flight testing results.

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...

Sustainable energy at the 100 W level for scientific sites on the Antarctic Plateau: Lessons learned from the Polar Experiment Network for Geospace Upper atmosphere Investigations-Automatic Geophysical Observatory project

NASA Astrophysics Data System (ADS)

Melville, R.; Stillinger, A.; Gerrard, A.; Weatherwax, A.

2014-04-01

The need to provide power to unmanned instrumentation over the course of an entire year on the Antarctic plateau presents a large number of engineering and logistical challenges. Designs formulated in ideal laboratory environments often fail in the Antarctic due to the harsh operating conditions, and field experience is necessary to achieve year-round operation in the 100 W power range. In this paper we present our current power design for the Automatic Geophysical Observatories; a design based on over two decades of experience on the ice and allows for relatively continuous operation at the aforementioned power level. We also discuss our various implementation methods, both failures and successes, in an effort assist other unmanned deployments on the ice.

Sustainable energy at the 100 W level for scientific sites on the Antarctic Plateau: lessons learned from the Polar Experiment Network for Geospace Upper atmosphere Investigations-Automatic Geophysical Observatory project.

PubMed

Melville, R; Stillinger, A; Gerrard, A; Weatherwax, A

2014-04-01

The need to provide power to unmanned instrumentation over the course of an entire year on the Antarctic plateau presents a large number of engineering and logistical challenges. Designs formulated in ideal laboratory environments often fail in the Antarctic due to the harsh operating conditions, and field experience is necessary to achieve year-round operation in the 100 W power range. In this paper we present our current power design for the Automatic Geophysical Observatories; a design based on over two decades of experience on the ice and allows for relatively continuous operation at the aforementioned power level. We also discuss our various implementation methods, both failures and successes, in an effort assist other unmanned deployments on the ice.

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

[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.

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.

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.

The watershed-scale optimized and rearranged landscape design (WORLD) model and local biomass processing depots for sustainable biofuel production: Integrated life cycle assessments

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

Eranki, Pragnya L.; Manowitz, David H.; Bals, Bryan D.

An array of feedstock is being evaluated as potential raw material for cellulosic biofuel production. Thorough assessments are required in regional landscape settings before these feedstocks can be cultivated and sustainable management practices can be implemented. On the processing side, a potential solution to the logistical challenges of large biorefi neries is provided by a network of distributed processing facilities called local biomass processing depots. A large-scale cellulosic ethanol industry is likely to emerge soon in the United States. We have the opportunity to influence the sustainability of this emerging industry. The watershed-scale optimized and rearranged landscape design (WORLD) modelmore » estimates land allocations for different cellulosic feedstocks at biorefinery scale without displacing current animal nutrition requirements. This model also incorporates a network of the aforementioned depots. An integrated life cycle assessment is then conducted over the unified system of optimized feedstock production, processing, and associated transport operations to evaluate net energy yields (NEYs) and environmental impacts.« less

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.

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.

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.

Social networks and alcohol use among older adults: a comparison with middle-aged adults.

PubMed

Kim, Seungyoun; Spilman, Samantha L; Liao, Diana H; Sacco, Paul; Moore, Alison A

2018-04-01

This study compared the association between social networks and alcohol consumption among middle-aged (MA) and older adults (OA) to better understand the nature of the relationship between those two factors among OA and MA. We examined Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Current drinkers aged over 50 were subdivided into two age groups: MA (50-64, n = 5214) and OA (65 and older, n = 3070). Each age group was stratified into drinking levels (low-risk vs. at-risk) based on alcohol consumption. The size and diversity of social networks were measured. Logistic regression models were used to examine age differences in the association between the social networks (size and diversity) and the probability of at-risk drinking among two age groups. A significant association between the social networks diversity and lower odds of at-risk drinking was found among MA and OA. However, the relationship between the diversity of social networks and the likelihood of at-risk drinking was weaker for OA than for MA. The association between social networks size and at-risk drinking was not significant among MA and OA. The current study suggests that the association between social networks diversity and alcohol use among OA differs from the association among MA, and few social networks were associated with alcohol use among OA. In the future, research should consider an in-depth exploration of the nature of social networks and alcohol consumption by using longitudinal designs and advanced methods of exploring drinking networks.

Social networks and alcohol use among older adults: a comparison with middle-aged adults

PubMed Central

Kim, Seungyoun; Spilman, Samantha L.; Liao, Diana H.; Sacco, Paul; Moore, Alison A.

2017-01-01

Objectives This study compared the association between social networks and alcohol consumption among middle-aged (MA) and older adults (OA) to better understand the nature of the relationship between those two factors among OA and MA. Method We examined Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Current drinkers aged over 50 were subdivided into two age groups: MA (50–64, n = 5214) and OA (65 and older, n = 3070). Each age group was stratified into drinking levels (low-risk vs. at-risk) based on alcohol consumption. The size and diversity of social networks were measured. Logistic regression models were used to examine age differences in the association between the social networks (size and diversity) and the probability of at-risk drinking among two age groups. Results A significant association between the social networks diversity and lower odds of at-risk drinking was found among MA and OA. However, the relationship between the diversity of social networks and the likelihood of at-risk drinking was weaker for OA than for MA. The association between social networks size and at-risk drinking was not significant among MA and OA. Conclusion The current study suggests that the association between social networks diversity and alcohol use among OA differs from the association among MA, and few social networks were associated with alcohol use among OA. In the future, research should consider an in-depth exploration of the nature of social networks and alcohol consumption by using longitudinal designs and advanced methods of exploring drinking networks. PMID:28006983

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.

[Research of regional medical consumables reagent logistics system in the modern hospital].

PubMed

Wu, Jingjiong; Zhang, Yanwen; Luo, Xiaochen; Zhang, Qing; Zhu, Jianxin

2013-09-01

To explore the modern hospital and regional medical consumable reagents logistics system management. The characteristics of regional logistics, through cooperation between medical institutions within the region, and organize a wide range of special logistics activities, to make reasonable of the regional medical consumable reagents logistics. To set the regional management system, dynamic management systems, supply chain information management system, after-sales service system and assessment system. By the research of existing medical market and medical resources, to establish the regional medical supplies reagents directory and the initial data. The emphasis is centralized dispatch of medical supplies reagents, to introduce qualified logistics company for dispatching, to improve the modern hospital management efficiency, to costs down. Regional medical center and regional community health service centers constitute a regional logistics network, the introduction of medical consumable reagents logistics services, fully embodies integrity level, relevance, purpose, environmental adaptability of characteristics by the medical consumable reagents regional logistics distribution. Modern logistics distribution systems can increase the area of medical consumables reagent management efficiency and reduce costs.

Space Station - An integrated approach to operational logistics support

NASA Technical Reports Server (NTRS)

Hosmer, G. J.

1986-01-01

Development of an efficient and cost effective operational logistics system for the Space Station will require logistics planning early in the program's design and development phase. This paper will focus on Integrated Logistics Support (ILS) Program techniques and their application to the Space Station program design, production and deployment phases to assure the development of an effective and cost efficient operational logistics system. The paper will provide the methodology and time-phased programmatic steps required to establish a Space Station ILS Program that will provide an operational logistics system based on planned Space Station program logistics support.

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.

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.

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields.

PubMed

Jahandideh, Samad; Abdolmaleki, Parviz; Movahedi, Mohammad Mehdi

2010-02-01

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes. (c) 2009 Wiley-Liss, Inc.

Tritium power source for long-lived sensors

NASA Astrophysics Data System (ADS)

Litz, M. S.; Katsis, D. C.; Russo, J. A.; Carroll, J. J.

2014-06-01

A tritium-based indirect converting photovoltaic (PV) power source has been designed and prototyped as a long-lived (~15 years) power source for sensor networks. Tritium is a biologically benign beta emitter and low-cost isotope acquired from commercial vendors for this purpose. The power source combines tritium encapsulated with a radioluminescent phosphor coupled to a commercial PV cell. The tritium, phosphor, and PV components are packaged inside a BA5590-style military-model enclosure. The package has been approved by the nuclear regulatory commission (NRC) for use by DOD. The power source is designed to produce 100μW electrical power for an unattended radiation sensor (scintillator and avalanche photodiode) that can detect a 20 μCi source of 137Cs at three meters. This beta emitting indirect photon conversion design is presented as step towards the development of practical, logistically acceptable, lowcost long-lived compact power sources for unattended sensor applications in battlefield awareness and environmental detection.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

Measuring Networking as an Outcome Variable in Undergraduate Research Experiences.

PubMed

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. © 2015 D. I. Hanauer and G. Hatfull. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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.

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.

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.

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.

Simulating Sustainment for an Unmanned Logistics System Concept of Operation in Support of Distributed Operations

DTIC Science & Technology

2017-06-01

designed experiment to model and explore a ship-to-shore logistics process supporting dispersed units via three types of ULSs, which vary primarily in...systems, simulation, discrete event simulation, design of experiments, data analysis, simplekit, nearly orthogonal and balanced designs 15. NUMBER OF... designed experiment to model and explore a ship-to-shore logistics process supporting dispersed units via three types of ULSs, which vary primarily

Posting Behaviour Patterns in an Online Smoking Cessation Social Network: Implications for Intervention Design and Development

PubMed Central

Healey, Benjamin; Hoek, Janet; Edwards, Richard

2014-01-01

Objectives 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. Methods 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. Results 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). Implications 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. PMID:25192174

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.

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

Descriptive and Injunctive Network Norms Associated with Non Medical Use of Prescription Drugs among Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Al Tayyib, Alia; Begun, Stephanie; Bowen, Elizabeth; Rice, Eric

2016-01-01

Background Nonmedical use of prescription drugs (NMUPD) among youth and young adults is being increasingly recognized as a significant public health problem. Homeless youth in particular are more likely to engage in NMUPD compared to housed youth. Studies suggest that network norms are strongly associated with a range of substance use behaviors. However, evidence regarding the association between network norms and NMUPD is scarce. We sought to understand whether social network norms of NMUPD are associated with engagement in NMUPD among homeless youth. Methods 1,046 homeless youth were recruited from three drop-in centers in Los Angeles, CA and were interviewed regarding their individual and social network characteristics. Multivariate logistic regression was employed to evaluate the significance of associations between social norms (descriptive and injunctive) and self-reported NMUPD. Results Approximately 25% of youth reported past 30-day NMUPD. However, more youth (32.28%) of youth believed that their network members engage in NMUPD, perhaps suggesting some pluralistic ignorance bias. Both descriptive and injunctive norms were associated with self-reported NMUPD among homeless youth. However, these varied by network type, with presence of NMUPD engaged street-based and home-based peers (descriptive norm) increasing the likelihood of NMUPD, while objections from family-members (injunctive norm) decreasing that likelihood. Conclusions Our findings suggest that, like other substance use behaviors, NMUPD is also influenced by youths’ perceptions of the behaviors of their social network members. Therefore, prevention and interventions programs designed to influence NMUPD might benefit from taking a social network norms approach. PMID:27563741

Descriptive and injunctive network norms associated with nonmedical use of prescription drugs among homeless youth.

PubMed

Barman-Adhikari, Anamika; Al Tayyib, Alia; Begun, Stephanie; Bowen, Elizabeth; Rice, Eric

2017-01-01

Nonmedical use of prescription drugs (NMUPD) among youth and young adults is being increasingly recognized as a significant public health problem. Homeless youth in particular are more likely to engage in NMUPD compared to housed youth. Studies suggest that network norms are strongly associated with a range of substance use behaviors. However, evidence regarding the association between network norms and NMUPD is scarce. We sought to understand whether social network norms of NMUPD are associated with engagement in NMUPD among homeless youth. 1046 homeless youth were recruited from three drop-in centers in Los Angeles, CA and were interviewed regarding their individual and social network characteristics. Multivariate logistic regression was employed to evaluate the significance of associations between social norms (descriptive and injunctive) and self-reported NMUPD. Approximately 25% of youth reported past 30-day NMUPD. However, more youth (32.28%) of youth believed that their network members engage in NMUPD, perhaps suggesting some pluralistic ignorance bias. Both descriptive and injunctive norms were associated with self-reported NMUPD among homeless youth. However, these varied by network type, with presence of NMUPD engaged street-based and home-based peers (descriptive norm) increasing the likelihood of NMUPD, while objections from family-members (injunctive norm) decreasing that likelihood. Our findings suggest that, like other substance use behaviors, NMUPD is also influenced by youths' perceptions of the behaviors of their social network members. Therefore, prevention and interventions programs designed to influence NMUPD might benefit from taking a social network norms approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Social network correlates of risky sexual behavior among adolescents in Bahir Dar and Mecha Districts, North West Ethiopia: an institution-based study.

PubMed

Asrese, Kerebih; Mekonnen, Alemtsehay

2018-04-11

Behaviors established during adolescence such as risky sexual behaviors have negative effects on future health and well-being. Extant literature indicated that individual attributes such as peer pressure and substance use have impacts on healthy development of young peoples' sexual behavior. The patterns of relationships (social network structure) and the social network content (members' norm regarding sexual practice) established by adolescents' network on adolescents' risky sexual behaviors are not well investigated. This cross-sectional study assessed the roles of social networks on sexual behavior of high school adolescents in Bahir Dar and Mecha district, North West Ethiopia. Data were collected from 806 high school adolescents using a pretested anonymously self administered questionnaire. Hierarchical logistic regression model was used for analysis. The results indicated that more than 13% had risky sexual behavior. Taking social networks into account improved the explanation of risky sexual behavior over individual attributes. Adolescents embedded within increasing sexual practice approving norm (AOR 1.61; 95%CI: 1.04 - 2.50), increasing network tie strength (AOR 1.12; 95% CI: 1.06 - 1.19), and homogeneous networks (AOR 1.58; 95% CI: .98 - 2.55) were more likely to had risky sexual behavior. Engaging within increasing number of sexuality discussion networks was found protective of risky sexual behavior (AOR .84; 95% CI: .72 - .97). Social networks better predict adolescent's risky sexual behavior than individual attributes. The findings indicated the circumstances or contexts that social networks exert risks or protective effects on adolescents' sexual behavior. Programs designed to reduce school adolescents' sexual risk behavior should consider their patterns of social relationships.

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.

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.…

Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries.

PubMed

Vassilev, Ivaylo; Rogers, Anne; Kennedy, Anne; Wensing, Michel; Koetsenruijter, Jan; Orlando, Rosanna; Portillo, Maria Carmen; Culliford, David

2016-01-01

Network types and characteristics have been linked to the capacity of inter-personal environments to mobilise and share resources. The aim of this paper is to examine personal network types in relation to long-term condition management in order to identify the properties of network types most likely to provide support for those with a long-term condition. A cross-sectional observational survey of people with type 2 diabetes using interviews and questionnaires was conducted between April and October 2013 in six European countries: Greece, Spain, Bulgaria, Norway, United Kingdom, and Netherlands. 1862 people with predominantly lower socio-economic status were recruited from each country. We used k-means clustering analysis to derive the network types, and one-way analysis of variance and multivariate logistic regression analysis to explore the relationship between network type socio-economic characteristics, self-management monitoring and skills, well-being, and network member work. Five network types of people with long-term conditions were identified: restricted, minimal family, family, weak ties, and diverse. Restricted network types represented those with the poorest self-management skills and were associated with limited support from social network members. Restricted networks were associated with poor indicators across self-management capacity, network support, and well-being. Diverse networks were associated with more enhanced self-management skills amongst those with a long-term condition and high level of emotional support. It was the three network types which had a large number of network members (diverse, weak ties, and family) where healthcare utilisation was most likely to correspond to existing health needs. Our findings suggest that type of increased social involvement is linked to greater self-management capacity and potentially lower formal health care costs indicating that diverse networks constitute the optimal network type as a policy in terms of the design of LTCM interventions and building support for people with LTCs.

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

Greenhouse gas network design using backward Lagrangian particle dispersion modelling - Part 1: Methodology and Australian test case

NASA Astrophysics Data System (ADS)

Ziehn, T.; Nickless, A.; Rayner, P. J.; Law, R. M.; Roff, G.; Fraser, P.

2014-03-01

This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly time scale. Prior uncertainties are derived on a weekly time scale for biosphere fluxes and fossil fuel emissions from high resolution BIOS2 model runs and from the Fossil Fuel Data Assimilation System (FFDAS), respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimization scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50% we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

Greenhouse gas network design using backward Lagrangian particle dispersion modelling - Part 1: Methodology and Australian test case

NASA Astrophysics Data System (ADS)

Ziehn, T.; Nickless, A.; Rayner, P. J.; Law, R. M.; Roff, G.; Fraser, P.

2014-09-01

This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

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.

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.

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.

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

78 FR 65975 - Notice of Availability (NOA) for Strategic Network Optimization (SNO) Environmental Assessment...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-04

... Impact (FONSI) AGENCY: Defense Logistics Agency, DoD. ACTION: Notice of Availability (NOA) for Strategic Network Optimization (SNO) Environmental Assessment (EA) Finding of No Significant Impact (FONSI). SUMMARY... impacts on the human environment are associated with this decision. FOR FURTHER INFORMATION CONTACT: Ann...

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)

Low carbon logistics through supply chain design and coordination.

DOT National Transportation Integrated Search

2010-02-01

"In this project, we propose to address carbon emissions in logistics through supply chain design, planning and : coordination. We argue that (1) supply chain design, planning, and coordination can help reduce carbon emissions : significantly, (2) su...

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.

Completing and sustaining IMS network for the CTBT Verification Regime

NASA Astrophysics Data System (ADS)

Meral Ozel, N.

2015-12-01

The CTBT International Monitoring System is to be comprised of 337 facilities located all over the world for the purpose of detecting and locating nuclear test explosions. Major challenges remain, namely the completion of the network where most of the remaining stations have either environmental, logistical and/or political issues to surmont (89% of the stations have already been built) and the sustainment of a reliable and state-of the-art network covering 4 technologies - seismic, infrasound , hydroacoustic and radionuclide. To have a credible and trustworthy verification system ready for entry into force of the Treaty, the CTBTO is protecting and enhancing its investment of its global network of stations and is providing effective data to the International Data Centre (IDC) and Member States. Regarding the protection of the CTBTO's investment and enhanced sustainment of IMS station operations, the IMS Division is enhancing the capabilities of the monitoring system by applying advances in instrumentation and introducing new software applications that are fit for purpose. Some examples are the development of noble gas laboratory systems to process and analyse subsoil samples, development of a mobile noble gas system for onsite inspection purposes, optimization of Beta Gamma detectors for Xenon detection, assessing and improving the efficiency of wind noise reduction systems for infrasound stations, development and testing of infrasound stations with a self-calibrating capability, and research into the use of modular designs for the hydroacoustic network.

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.

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

PubMed

Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

2017-06-01

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

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.

The emotional cost of distance: Geographic social network dispersion and post-traumatic stress among survivors of Hurricane Katrina.

PubMed

Morris, Katherine Ann; Deterding, Nicole M

2016-09-01

Social networks offer important emotional and instrumental support following natural disasters. However, displacement may geographically disperse network members, making it difficult to provide and receive support necessary for psychological recovery after trauma. We examine the association between distance to network members and post-traumatic stress using survey data, and identify potential mechanisms underlying this association using in-depth qualitative interviews. We use longitudinal, mixed-methods data from the Resilience in Survivors of Katrina (RISK) Project to capture the long-term effects of Hurricane Katrina on low-income mothers from New Orleans. Baseline surveys occurred approximately one year before the storm and follow-up surveys and in-depth interviews were conducted five years later. We use a sequential explanatory analytic design. With logistic regression, we estimate the association of geographic network dispersion with the likelihood of post-traumatic stress. With linear regressions, we estimate the association of network dispersion with the three post-traumatic stress sub-scales. Using maximal variation sampling, we use qualitative interview data to elaborate identified statistical associations. We find network dispersion is positively associated with the likelihood of post-traumatic stress, controlling for individual-level socio-demographic characteristics, exposure to hurricane-related trauma, perceived social support, and New Orleans residency. We identify two social-psychological mechanisms present in qualitative data: respondents with distant network members report a lack of deep belonging and a lack of mattering as they are unable to fulfill obligations to important distant ties. Results indicate the importance of physical proximity to emotionally-intimate network ties for long-term psychological recovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

NASA Supportability Engineering Implementation Utilizing DoD Practices and Processes

NASA Technical Reports Server (NTRS)

Smith, David A.; Smith, John V.

2010-01-01

The Ares I design and development program made the determination early in the System Design Review Phase to utilize DoD ILS and LSA approach for supportability engineering as an integral part of the system engineering process. This paper is to provide a review of the overall approach to design Ares-I with an emphasis on a more affordable, supportable, and sustainable launch vehicle. Discussions will include the requirements development, design influence, support concept alternatives, ILS and LSA planning, Logistics support analyses/trades performed, LSA tailoring for NASA Ares Program, support system infrastructure identification, ILS Design Review documentation, Working Group coordination, and overall ILS implementation. At the outset, the Ares I Project initiated the development of the Integrated Logistics Support Plan (ILSP) and a Logistics Support Analysis process to provide a path forward for the management of the Ares-I ILS program and supportability analysis activities. The ILSP provide the initial planning and coordination between the Ares-I Project Elements and Ground Operation Project. The LSA process provided a system engineering approach in the development of the Ares-I supportability requirements; influence the design for supportability and development of alternative support concepts that satisfies the program operability requirements. The LSA planning and analysis results are documented in the Logistics Support Analysis Report. This document was required during the Ares-I System Design Review (SDR) and Preliminary Design Review (PDR) review cycles. To help coordinate the LSA process across the Ares-I project and between programs, the LSA Report is updated and released quarterly. A System Requirement Analysis was performed to determine the supportability requirements and technical performance measurements (TPMs). Two working groups were established to provide support in the management and implement the Ares-I ILS program, the Integrated Logistics Support Working Group (ILSWG) and the Logistics Support Analysis Record Working Group (LSARWG). The Ares I ILSWG is established to assess the requirements and conduct, evaluate analyses and trade studies associated with acquisition logistic and supportability processes and to resolve Ares I integrated logistics and supportability issues. It established a strategic collaborative alliance for coordination of Logistics Support Analysis activates in support of the integrated Ares I vehicle design and development of logistics support infrastructure. A Joint Ares I - Orion LSAR Working Group was established to: 1) Guide the development of Ares-I and Orion LSAR data and serve as a model for future Constellation programs, 2) Develop rules and assumptions that will apply across the Constellation program with regards to the program's LSAR development, and 3) Maintain the Constellation LSAR Style Guide.

An agronomic field-scale sensor network for monitoring soil water and temperature variation

NASA Astrophysics Data System (ADS)

Brown, D. J.; Gasch, C.; Brooks, E. S.; Huggins, D. R.; Campbell, C. S.; Cobos, D. R.

2014-12-01

Environmental sensor networks have been deployed in a variety of contexts to monitor plant, air, water and soil properties. To date, there have been relatively few such networks deployed to monitor dynamic soil properties in cropped fields. Here we report on experience with a distributed soil sensor network that has been deployed for seven years in a research farm with ongoing agronomic field operations. The Washington State University R. J. Cook Agronomy Farm (CAF), Pullman, WA, USA has recently been designated a United States Department of Agriculture (USDA) Long-Term Agro-Ecosystem Research (LTAR) site. In 2007, 12 geo-referenced locations at CAF were instrumented, then in 2009 this network was expended to 42 locations distributed across the 37-ha farm. At each of this locations, Decagon 5TE probes (Decagon Devices Inc., Pullman, WA, USA) were installed at five depths (30, 60, 90, 120, and 150 cm), with temperature and volumetric soil moisture content recorded hourly. Initially, data loggers were wirelessly connected to a data station that could be accessed through a cell connection, but due to the logistics of agronomic field operations, we later buried the dataloggers at each site and now periodically download data via local radio transmission. In this presentation, we share our experience with the installation, maintenance, calibration and data processing associated with an agronomic soil monitoring network. We also present highlights of data derived from this network, including seasonal fluctuations of soil temperature and volumetric water content at each depth, and how these measurements are influenced by crop type, soil properties, landscape position, and precipitation events.

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.

Totally Integrated Munitions Enterprise ''Affordable Munitions Production for the 21st Century''

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

Burleson, R.R.; Poggio, M.E.; Rosenberg, S.J.

2000-09-13

The U.S. Army faces several munitions manufacturing issues: downsizing of the organic production base, timely fielding of affordable smart munitions, and munitions replenishment during national emergencies. Totally Integrated Munitions Enterprise (TIME) is addressing these complex issues via the development and demonstration of an integrated enterprise. The enterprise will include the tools, network, and open modular architecture controllers to enable accelerated acquisition, shortened concept to volume production, lower life cycle costs, capture of critical manufacturing processes, and communication of process parameters between remote sites to rapidly spin-off production for replenishment by commercial sources. TIME addresses the enterprise as a system, integratingmore » design, engineering, manufacturing, administration, and logistics.« less

Totally Integrated Munitions Enterprise ''Affordable Munitions Production for the 21st Century''

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

Burleson, R.R.; Poggio, M.E.; Rosenberg, S.J.

2000-07-14

The U.S. Army faces several munitions manufacturing issues: downsizing of the organic production base, timely fielding of affordable smart munitions, and munitions replenishment during national emergencies. TIME is addressing these complex issues via the development and demonstration of an integrated enterprise. The enterprise will include the tools, network, and open modular architecture controller to enable accelerated acquisition, shortened concept to volume production, lower life cycle costs, capture of critical manufacturing processes, and communication of process parameters between remote sites to rapidly spin-off production for replenishment by commercial sources. TIME addresses the enterprise as a system, integrating design, engineering, manufacturing, administration,more » and logistics.« less

Totally Integrated Munitions Enterprise ''Affordable Munitions Production for the 21st Century''

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

Burleson, R.R.; Poggio, M.E.; Rosenberg, S.J.

2000-08-18

The U.S. Army faces several munitions manufacturing issues: downsizing of the organic production base, timely fielding of affordable smart munitions, and munitions replenishment during national emergencies. Totally Integrated Munitions Enterprise (TIME) is addressing these complex issues via the development and demonstration of an integrated enterprise. The enterprise will include the tools, network, and open modular architecture controllers to enable accelerated acquisition, shortened concept to volume production, lower life cycle costs, capture of critical manufacturing processes, and communication of process parameters between remote sites to rapidly spin-off production for replenishment by commercial sources. TIME addresses the enterprise as a system, integratingmore » design, engineering, manufacturing, administration, and logistics.« less

Design and logistics of integrated spacecraft/lander lunar habitat concepts

NASA Technical Reports Server (NTRS)

Hypes, Warren D.; Wright, Robert L.; Gould, Marston J.; Lovelace, U. M.

1991-01-01

Integrated spacecraft/lander combinations have been designed to provide a support structure for thermal and galactic radiation shielding for three initial lunar habitat concepts. Integrating the support structure with the habitat reduces the logistics requirements for the implantation of the initial base. The designs are simple, make use of existing technologies, and minimize the amount of lunar surface preparation and crew activity. The design facilitates continued use of all elements in the development of a permanent lunar base and precludes the need for an entirely different structure of larger volume and increased complexity of implantation. This design philosophy, coupled with the reduced logistics, increases overall cost effectiveness.

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

Thakur, Gautam

A data-driven realistic design and evalua- tion of vehicular mobility has been particularly chal- lenging due to a lack of large-scale real-world mea- surements in the research community. Current research methodologies rely on articial scenarios, random con- nectivity, and use small and biased samples. In this pa- per, we perform a combined study to learn the struc- ture and connectivity of urban streets and modeling and characterization of vehicular trac densities on them. Our dataset is a collection of more than 222 thousand routes and 25 million vehicular mobility images from 1091 online web cameras located in six dierent re-more » gions of the world. Our results centered around four major observations: i. study shows that driving routes and visiting locations of regions demonstrate power-law distribution, indicating a planned or recently designed road infrastructure; ii. we represent regions by network graphs in which nodes are camera locations and edges are urban streets that connect the nodes. Such represen- tation exhibits small world properties with short path lengths and large clustering coecient; iii. trac densi- ties show 80% temporal correlation during several hours of a day; iv. modeling trac densities against known theoretical distributions show less than 5% deviation for heavy-trailed models such as log-logistic and log- gamma distributions. We believe this work will provide a much-needed contribution to the research community for design and evaluation of future vehicular networks and smart cities.« less

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.

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

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.

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.

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.

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.

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.

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.

Sense and Respond Logistics: Integrating Prediction, Responsiveness, and Control Capabilities

DTIC Science & Technology

2006-01-01

logistics SAR sense and respond SCM Supply Chain Management SCN Supply Chain Network SIDA sense, interpret, decide, act SOS source of supply TCN...commodity supply chain management ( SCM ), will have WS- SCMs that focus on integrating information for a particular MDS. 8 In the remainder of this...developed applications of ABMs for SCM .21 Applications of Agents and Agent-Based Modeling Agents have been used in telecommunications, e-commerce

What Is Different About Worker’s Compensation Patients?

PubMed Central

Atlas, Steven J.; Tosteson, Tor D.; Hanscom, Brett; Blood, Emily A.; Pransky, Glenn S.; Abdu, William A.; Andersson, Gunnar B.; Weinstein, James N.

2010-01-01

Study Design Combined analysis of 2 prospective clinical studies. Objective To identify socioeconomic characteristics associated with workers’ compensation in patients with an intervertebral disc herniation (IDH) or spinal stenosis (SpS). Summary of Background Data Few studies have compared socioeconomic differences between those receiving or not receiving workers’ compensation with the same underlying clinical conditions. Methods Patients were identified from the Spine Patient Outcomes Research Trial (SPORT) and the National Spine Network (NSN) practice-based outcomes study. Patients with IDH and SpS within NSN were identified satisfying SPORT eligibility criteria. Information on disability and work status at baseline evaluation was used to categorize patients into 3 groups: workers’ compensation, other disability compensation, or work-eligible controls. Enrollment rates of patients with disability in a clinical efficacy trial (SPORT) and practice-based network (NSN) were compared. Independent socioeconomic predictors of baseline workers’ compensation status were identified in multivariate logistic regression models controlling for clinical condition, study cohort, and initial treatment designation. Results Among 3759 eligible patients (1480 in SPORT and 2279 in NSN), 564 (15%) were receiving workers’ compensation, 317 (8%) were receiving other disability compensation, and 2878 (77%) were controls. Patients receiving workers’ compensation were less common in SPORT than NSN (9.2% vs. 18.8%, P < 0.001), but patients receiving other disability compensation were similarly represented (8.9% vs. 7.7%, P = 0.19). In univariate analyses, many socioeconomic characteristics significantly differed according to baseline workers’ compensation status. In multiple logistic regression analyses, gender, educational level, work characteristics, legal action, and expectations about ability to work without surgery were independently associated with receiving workers’ compensation. Conclusion Clinical trials involving conditions commonly seen in patients with workers’ compensation may need special efforts to ensure adequate representation. Socioeconomic characteristics markedly differed between patients receiving and not receiving workers’ compensation. Identifying the independent effects of workers’ compensation on outcomes will require controlling for these baseline characteristics and other clinical features associated with disability status. PMID:17700451

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.

Space Station fluid management logistics

NASA Technical Reports Server (NTRS)

Dominick, Sam M.

1990-01-01

Viewgraphs and discussion on space station fluid management logistics are presented. Topics covered include: fluid management logistics - issues for Space Station Freedom evolution; current fluid logistics approach; evolution of Space Station Freedom fluid resupply; launch vehicle evolution; ELV logistics system approach; logistics carrier configuration; expendable fluid/propellant carrier description; fluid carrier design concept; logistics carrier orbital operations; carrier operations at space station; summary/status of orbital fluid transfer techniques; Soviet progress tanker system; and Soviet propellant resupply system observations.

Disassortative mixing patterns of drug-using and sex networks on HIV risk behaviour among young drug users in Yunnan, China.

PubMed

Li, J; Luo, J; Li, J; Liu, H

2015-09-01

The dominant mode of HIV transmission in China has changed from injection drug use to sexual contact. The objectives of this study were to describe the disassortative and assortative mixing patterns of drug-using and sex networks among young drug users in China. Cross-sectional study. Respondent-driven sampling (RDS) was used to recruit young drug users in an egocentric network study in Yunnan, China. Egos were categorized as having disassortative mixing network patterns if they reported both sex and drug-using networks. Egos who only had a sex network (no drug-using network), or only a drug-using network (no sex network) were categorized as having assortative mixing network patterns. Multiple logistic regression was performed to analyze the relationships between disassortative patterns with risky sexual behaviour and drug-using practices. A total of 426 participants were recruited into the study. Two hundred forty-two egos reported disassortative mixing patterns and 139 egos had assortative patterns. The RDS-adjusted proportion of having a disassortative pattern was 53.2%. Participants with disassortative patterns were more likely to engage in HIV risk behaviour compared to those with assortative patterns. Specifically, drug users with disassortative patterns reported more multiple sex partners (31.4% vs 19.6%), concurrent partnerships (52.1% vs 39.0%), non-regular sex partners (12.0% vs 4.3%), and sex partners who were IDUs (24.9% vs 12.5%). Consistent condom use with regular or non-regular partners was low (between 18.9% and 47.2%) regardless of the mixing pattern. However, parenteral risk for HIV transmission was relatively low in both groups. The transition of the HIV epidemic in China from injection drug use to sexual contact may be attributed to disassortative mixing in drug-use and sexual networks. HIV programs should consider disassortative mixing patterns when designing new behavioural interventions. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

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

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.

[Predictors of institutionalization of elderly persons in dependency situation in Andalusia].

PubMed

Pinzón-Pulido, Sandra; Garrido Peña, Francisco; Reyes Alcázar, Víctor; Lima-Rodríguez, Joaquín Salvador; Raposo Triano, María Fernanda; Martínez Domene, Manuel; Alonso Trujillo, Federico

2016-01-01

Identifying preferences regarding type of care and risk factors for institutionalization of elderly persons in dependency situations in Andalusia. The data on 200,039 persons registered in the System for Autonomy and Dependency Care over the period 2007-2012 were analysed. The study population was described in terms of: age, dependency situation, preferences, support network and clinical factors at the time of inclusion in the study. Separate analysis was made for men and women. A logistic regression model was designed to determine the risk factors for institutionalization for each sex. 87,4% of women and 85,9% of men expressed their wish to receive care in their own home. The risk of institutionalization is three times higher among men than among women. Among women, the risks of institutionalization are: level of dependency, wishing to move into a residential care home, medium consistency and fragility of support network and being diagnosed with dementia. Among men, the risks are: wishing to move into a residential care home and low or medium consistency of support network. Care in the home is the preferred alternative for elderly persons in dependency situations. The risk of institutionalization is conditioned more by the preferences of the person and their family and the characteristics of the support network than by individual's clinical condition. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Depression in the barrio: An analysis of the risk and protective nature of cultural values among Mexican American substance users.

PubMed

Villarreal, Yolanda R; Torres, Luis R; Stotts, Angela L; Ren, Yi; Sampson, Mcclain; Klawans, Michelle R; Bordnick, Patrick S

2017-06-07

Understanding the effect of cultural values on depression and how social networks influence these relationships may be important in the treatment of substance-using, Mexican American populations. Latino cultural values, familismo, personalismo, fatalismo, and machismo, may be associated with depression among Latinos. The current study identified the association of traditional Latino values on depressive symptomatology among a sample of Mexican American heroin injectors. A cross-sectional research design and field-intensive outreach methodology were utilized to recruit 227 Mexican American men. Participants were categorized into depressed and nondepressed groups. Relations among cultural values and depression were examined using logistic regression. Findings indicate that drug-using men with higher familismo and fatalismo scores are protected against depressive symptomatology. Relations between familismo and depression seem to be moderated by having a drug use network. In addition, findings reveal that age is inversely related to depressive symptomatology. Young Mexican American heroin users who do not ascribe to traditional Latino values may be highly associated with depression and therefore more vulnerable to riskier drug use behaviors. Moreover, drug-using social networks may affect the protective nature of certain cultural values. Further research is needed to identify whether culturally tailored treatments can cultivate these values while simultaneously undermining the effect of substance-using social networks in order to reduce depression symptoms among this group of high-risk substance users.

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

Impact of trucking network flow on preferred biorefinery locations in the southern United States

Treesearch

Timothy M. Young; Lee D. Han; James H. Perdue; Stephanie R. Hargrove; Frank M. Guess; Xia Huang; Chung-Hao Chen

2017-01-01

The impact of the trucking transportation network flow was modeled for the southern United States. The study addresses a gap in existing research by applying a Bayesian logistic regression and Geographic Information System (GIS) geospatial analysis to predict biorefinery site locations. A one-way trucking cost assuming a 128.8 km (80-mile) haul distance was estimated...

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.

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.

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.

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.

Biomass Feedstock and Conversion Supply System Design and Analysis

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

Jacobson, Jacob J.; Roni, Mohammad S.; Lamers, Patrick

Idaho National Laboratory (INL) supports the U.S. Department of Energy’s bioenergy research program. As part of the research program INL investigates the feedstock logistics economics and sustainability of these fuels. A series of reports were published between 2000 and 2013 to demonstrate the feedstock logistics cost. Those reports were tailored to specific feedstock and conversion process. Although those reports are different in terms of conversion, some of the process in the feedstock logistic are same for each conversion process. As a result, each report has similar information. A single report can be designed that could bring all commonality occurred inmore » the feedstock logistics process while discussing the feedstock logistics cost for different conversion process. Therefore, this report is designed in such a way that it can capture different feedstock logistics cost while eliminating the need of writing a conversion specific design report. Previous work established the current costs based on conventional equipment and processes. The 2012 programmatic target was to demonstrate a delivered biomass logistics cost of $55/dry ton for woody biomass delivered to fast pyrolysis conversion facility. The goal was achieved by applying field and process demonstration unit-scale data from harvest, collection, storage, preprocessing, handling, and transportation operations into INL’s biomass logistics model. The goal of the 2017 Design Case is to enable expansion of biofuels production beyond highly productive resource areas by breaking the reliance of cost-competitive biofuel production on a single, low-cost feedstock. The 2017 programmatic target is to supply feedstock to the conversion facility that meets the in-feed conversion process quality specifications at a total logistics cost of $80/dry T. The $80/dry T. target encompasses total delivered feedstock cost, including both grower payment and logistics costs, while meeting all conversion in-feed quality targets. The 2012 $55/dry T. programmatic target included only logistics costs with a limited focus on biomass quantity, quality and did not include a grower payment. The 2017 Design Case explores two approaches to addressing the logistics challenge: one is an agronomic solution based on blending and integrated landscape management and the second is a logistics solution based on distributed biomass preprocessing depots. The concept behind blended feedstocks and integrated landscape management is to gain access to more regional feedstock at lower access fees (i.e., grower payment) and to reduce preprocessing costs by blending high quality feedstocks with marginal quality feedstocks. Blending has been used in the grain industry for a long time; however, the concept of blended feedstocks in the biofuel industry is a relatively new concept. The blended feedstock strategy relies on the availability of multiple feedstock sources that are blended using a least-cost formulation within an economical supply radius, which, in turn, decreases the grower payment by reducing the amount of any single biomass. This report will introduce the concepts of blending and integrated landscape management and justify their importance in meeting the 2017 programmatic goals.« less

An applied methodology for assessment of the sustainability of biomass district heating systems

NASA Astrophysics Data System (ADS)

Vallios, Ioannis; Tsoutsos, Theocharis; Papadakis, George

2016-03-01

In order to maximise the share of biomass in the energy supplying system, the designers should adopt the appropriate changes to the traditional systems and become more familiar with the design details of the biomass heating systems. The aim of this study is to present the development of methodology and its associated implementation in software that is useful for the design of biomass thermal conversion systems linked with district heating (DH) systems, taking into consideration the types of building structures and urban settlement layout around the plant. The methodology is based on a completely parametric logic, providing an impact assessment of variations in one or more technical and/or economic parameters and thus, facilitating a quick conclusion on the viability of this particular energy system. The essential energy parameters are presented and discussed for the design of biomass power and heat production system which are in connection with DH network, as well as for its environmental and economic evaluation (i.e. selectivity and viability of the relevant investment). Emphasis has been placed upon the technical parameters of biomass logistics, energy system's design, the economic details of the selected technology (integrated cogeneration combined cycle or direct combustion boiler), the DH network and peripheral equipment (thermal substations) and the greenhouse gas emissions. The purpose of this implementation is the assessment of the pertinent investment financial viability taking into account the available biomass feedstock, the economical and market conditions, and the capital/operating costs. As long as biomass resources (forest wood and cultivation products) are available and close to the settlement, disposal and transportation costs of biomass, remain low assuring the sustainability of such energy systems.

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.

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

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.

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.

Multiplex congruity: friendship networks and perceived popularity as correlates of adolescent alcohol use.

PubMed

Fujimoto, Kayo; Valente, Thomas W

2015-01-01

Adolescents interact with their peers in multiple social settings and form various types of peer relationships that affect drinking behavior. Friendship and popularity perceptions constitute critical relationships during adolescence. These two relations are commonly measured by asking students to name their friends, and this network is used to construct drinking exposure and peer status variables. This study takes a multiplex network approach by examining the congruity between friendships and popularity as correlates of adolescent drinking. Using data on friendship and popularity nominations among high school adolescents in Los Angeles, California (N = 1707; five schools), we examined the associations between an adolescent's drinking and drinking by (a) their friends only; (b) multiplexed friendships, friends also perceived as popular; and (c) congruent, multiplexed-friends, close friends perceived as popular. Logistic regression results indicated that friend-only drinking, but not multiplexed-friend drinking, was significantly associated with self-drinking (AOR = 3.51, p < 0.05). However, congruent, multiplexed-friend drinking also was associated with self-drinking (AOR = 3.10, p < 0.05). This study provides insight into how adolescent health behavior is predicated on the multiplexed nature of peer relationships. The results have implications for the design of health promotion interventions for adolescent drinking. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multiplex congruity: Friendship networks and perceived popularity as correlates of adolescent alcohol use

PubMed Central

Fujimoto, Kayo; Valente, Thomas W.

2014-01-01

Adolescents interact with their peers in multiple social settings and form various types of peer relationships that affect drinking behavior. Friendship and popularity perceptions constitute critical relationships during adolescence. These two relations are commonly measured by asking students to name their friends, and this network is used to construct drinking exposure and peer status variables. This study takes a multiplex network approach by examining the congruity between friendships and popularity as correlates of adolescent drinking. Using data on friendship and popularity nominations among high school adolescents in Los Angeles, California (N = 1707; five schools), we examined the associations between an adolescent's drinking and drinking by (a) their friends only; (b) multiplexed friendships, friends also perceived as popular; and (c) congruent, multiplexed-friends, close friends perceived as popular. Logistic regression results indicated that friend-only drinking, but not multiplexed-friend drinking, was significantly associated with self-drinking (AOR = 3.51, p < 0.05). However, congruent, multiplexed-friend drinking also was associated with self-drinking (AOR = 3.10, p < 0.05). This study provides insight into how adolescent health behavior is predicated on the multiplexed nature of peer relationships. The results have implications for the design of health promotion interventions for adolescent drinking. PMID:24913275

Telescience capability for the Sondre Stromfjord, Greenland, incoherent-scatter radar facility

NASA Astrophysics Data System (ADS)

Zambre, Yadunath B.

1993-01-01

SRI International (SRI) operates an upper-atmospheric research facility in Sondre Stromfjord (Sondrestrom), Greenland. In the past, the facility's remote location and limited logistical support imposed constraints on the research that could be carried out at the site. Campaigns involving multiple instruments were often constrained due to limited space, and experiments requiring coordination with other geographically separated facilities, though possible, were difficult. To provide greater access to the facility, an electronic connection between Sondrestrom and the mainland U.S.A. was established, providing access to the National Science Internet. SRI developed telescience software that sends data from the incoherent scatter radar at the Sondrestrom facility to SRI's offices in Menlo Park, California. This software uses the transmission control protocol (TCP/IP) to transmit the data in near real time between the two locations and the X window system to generate displays of the data in Menlo Park. This is in contrast to using the X window system to display data remotely across a wide-area network. Using CP to transport data over the long distance network has resulted in significantly improved network throughput and latency. While currently used to transport radar data, the telescience software is designed and intended for simultaneous use with other instruments at Sondrestrom and other facilities. Work incorporating additional instruments is currently in progress.

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.

Technical status of the International Monitoring System for the Comprehensive Nuclear-Test-Ban Treaty

NASA Astrophysics Data System (ADS)

Grenard, P.

2009-04-01

The International Monitoring System (IMS) for the Comprehensive Nuclear Test-ban-Treaty Organization is a global Network of stations for detecting and providing evidence of possible nuclear explosions. Upon completion, the IMS will consist of 321 monitoring facilities and 16 radionuclide laboratories distributed worldwide in locations designated by the Treaty. Many of these sites are located in areas that are remote and difficult to access, posing major engineering and logistical challenges. The IMS uses seismic, hydroacoustic and infrasound monitoring waveform technologies to detect signals released from an explosion or a naturally occurring event (e.g. earthquakes) in the underground, underwater and atmospheric environments. The radionuclide technology as an integral part of the IMS uses air samples to collect particular matter from the atmosphere. Samples are then analyzed for evidence of physical products created by a nuclear explosion and carried through the atmosphere. The certification process of the IMS stations assures their compliance with the IMS technical requirements. In 2008 significant progress was made towards the completion of the IMS Network. So far 75% of the IMS stations have been built and certified.

Power and sample size for multivariate logistic modeling of unmatched case-control studies.

PubMed

Gail, Mitchell H; Haneuse, Sebastien

2017-01-01

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

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

Are Parental Relationships Always Protective? A Social Network Analysis of Black, Latino, and White Homeless Youth and Sexual Risk-Taking Behaviors.

PubMed

Craddock, Jaih B; Rice, Eric; Rhoades, Harmony; Winetrobe, Hailey

2016-11-01

Black and Latino homeless youth are at high risk of HIV, and yet no HIV prevention interventions have been specifically designed for these groups. Given the success of parent-child intervention programs for housed Black and Latino youth, this study examined parental relationships that could be leveraged for future HIV prevention efforts targeting minority homeless youth, specifically the associations among presence of parents in social networks, parental influence, and parental support. A convenience sample of Black, Latino, and White homeless youth (N = 754) was recruited from three drop-in centers in Los Angeles. Participants completed a computerized, self-administered questionnaire and an interviewer-led personal social network interview. Multivariate logistic regression models assessed the association between parental relationships and sexual risk behaviors. Forty-five percent (n = 338) of youth identified a parent in their network. Having at least one parent in their network was significantly associated with decreased odds of using a condom for Black and White youth. Black youth were almost four times more likely to report being tested for HIV if they spoke to their parents about sex, whereas Latino youth were 91 % less likely to report being tested for HIV if they talked with their parents about sex. Black youth who identified a parent as a positive influence (i.e., promoting condom use or discouraging multiple partners) were almost four times more likely to have used a condom during their last sexual encounter. Parent-child HIV prevention interventions targeting homeless youth would benefit from culturally tailored adaptations.

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.

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

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

76 FR 42119 - 36(b)(1) Arms Sales Notification

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-18

.... Government and contractor engineering and logistics support services, and other related elements of logistics... documentation, U.S. Government and contractor engineering and logistics support services, and other related... range of adverse battlefield conditions. The hardware itself is Unclassified. The engineering design and...

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

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

Acoustic Multipurpose Cargo Transfer Bag

NASA Technical Reports Server (NTRS)

Baccus, Shelley

2015-01-01

The Logistics Reduction (LR) project within the Advanced Exploration Systems (AES) program is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) are designed to be the same external volume as a regular cargo transfer bag, the common logistics carrier for the International Space Station. After use as a cargo bag, the MCTB can be unzipped and unfolded to be reused. This Acoustic MCTBs transform into acoustic blankets after the initial logistics carrying objective is complete.

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.

Broadening the Quality and Capabilities of the EarthScope Alaska Transportable Array

NASA Astrophysics Data System (ADS)

Busby, R. W.

2016-12-01

In 2016, the EarthScope Transportable Array (TA) program will have 195 broadband seismic stations operating in Alaska and western Canada. This ambitious project will culminate in a network of 268 new or upgraded real-time seismic stations operating through 2019. The challenging environmental conditions and the remoteness of Alaska have motivated a new method for constructing a high-quality, temporary seismic network. The Alaska TA station design builds on experience of the Lower 48 TA deployment and adds design requirements because most stations are accessible only by helicopter. The stations utilize new high-performance posthole sensors, a specially built hammer/auger drill, and lightweight lithium ion batteries to minimize sling loads. A uniform station design enables a modest crew to build the network on a short timeline and operate them through the difficult conditions of rural Alaska. The Alaska TA deployment has increased the quality of seismic data, with some well-sited 2-3 m posthole stations approaching the performance of permanent Global Seismic Network stations emplaced in 100 m boreholes. The real-time data access, power budget, protective enclosure and remote logistics of these TA stations has attracted collaborations with NASA, NOAA, USGS, AVO and other organizations to add auxiliary sensors to the suite of instruments at many TA stations. Strong motion sensors have been added to (18) stations near the subduction trench to complement SM stations operated by AEC, ANSS and GSN. All TA and most upgraded stations have pressure and infrasound sensors, and 150 TA stations are receiving a Vaisala weather sensor, supplied by the National Weather Service Alaska Region and NASA, capable of measuring temperature, pressure, relative humidity, wind speed/direction, and precipitation intensity. We are also installing about (40) autonomous soil temperature profile kits adjacent to northern stations. While the priority continues to be collecting seismic data, these additional strong motion, atmospheric, and soil temperature sensors may motivate the desire extend the operation of certain stations in cooperation with these organizations. The TA has always been amenable to partnerships in the research and education communities that extend the capabilities and reach of the EarthScope Transportable Array.

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

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

A method of network topology optimization design considering application process characteristic

NASA Astrophysics Data System (ADS)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

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.

Challenges and models in supporting logistics system design for dedicated-biomass-based bioenergy industry.

PubMed

Zhu, Xiaoyan; Li, Xueping; Yao, Qingzhu; Chen, Yuerong

2011-01-01

This paper analyzed the uniqueness and challenges in designing the logistics system for dedicated biomass-to-bioenergy industry, which differs from the other industries, due to the unique features of dedicated biomass (e.g., switchgrass) including its low bulk density, restrictions on harvesting season and frequency, content variation with time and circumambient conditions, weather effects, scattered distribution over a wide geographical area, and so on. To design it, this paper proposed a mixed integer linear programming model. It covered from planting and harvesting switchgrass to delivering to a biorefinery and included the residue handling, concentrating on integrating strategic decisions on the supply chain design and tactical decisions on the annual operation schedules. The present numerical examples verified the model and demonstrated its use in practice. This paper showed that the operations of the logistics system were significantly different for harvesting and non-harvesting seasons, and that under the well-designed biomass logistics system, the mass production with a steady and sufficient supply of biomass can increase the unit profit of bioenergy. The analytical model and practical methodology proposed in this paper will help realize the commercial production in biomass-to-bioenergy industry. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

Logistical Support for the Installation of the Plate Boundary Observatory GPS and Borehole Strainmeter Networks

NASA Astrophysics Data System (ADS)

Kurnik, C.; Austin, K.; Coyle, B.; Dittmann, T.; Feaux, K.; Friesen, B.; Johnson, W.; Mencin, D.; Pauk, B.; Walls, C.

2007-12-01

The Plate Boundary Observatory (PBO), part of the NSF-funded EarthScope project, is designed to study the three- dimensional strain field resulting from deformation across the active boundary zone between the Pacific and North American plates in the western United States. To meet these goals, UNAVCO will install 880 continuous GPS stations, 103 borehole strainmeter stations, 28 tiltmeters, and five laser strainmeters by October 2008. Such a broad network presents significant logisitical challenges, including moving supplies, equipment, and personnel around 6 million square kilometers, and this requires accurate tracking and careful planning. The PBO logistics chain includes the PBO headquarters at UNAVCO in Boulder, Colorado and five regional offices in the continental United States and Alaska, served by dozens of suppliers spread across the globe. These offices are responsible for building and maintaining sites in their region. Most equipment and supplies first arrive in Boulder, where they are tagged and entered into a UNAVCO-wide equipment database, assembled and quality checked as necessary, and sent on to the appropriate regional office. Larger items which are costly to store and ship from Boulder, such as batteries or long sections of stainless steel pipe and bar required for monuments, are shipped directly from the supplier to each region as needed. These supplies and equipment are also tracked through the ordering, delivery, installation, and maintenance cycle via Earned Value Management techniques which allow us to meet NSF and other Federal procurement rules. Early prototypes and assembly configurations aid the development of material and supply budgets. A thorough understanding of Federal procurement rules at project start up is critical as the project moves forward.

The Future of the United States Antarctic Program

NASA Astrophysics Data System (ADS)

Thom, J. E.; Weidner, G. A.; Lazzara, M. A.; Knuth, S. L.; Cassano, J. J.

2009-04-01

The last three decades have seen Antarctic surface meteorological observations augmented by an increasing number of automated weather stations (AWS). Since 1980, the University of Wisconsin-Madison has managed an expanding array of AWS in Antarctica that are funded through the United States' National Science Foundation. The AWS network began with six stations and has grown to approximately 60 stations. The majority of the AWS use a custom electronics package designed in the 1970s and modified over approximately 20 years. However, dramatic changes in the electronics industry have led the UW-Madison to transition its AWS to commercial-off-the-shelf (COTS) components capable of integrating on-station storage, varied sensors, multiple data telemetry options, and a flexible operating system. Among the important technical issues arising from adopting a COTS-based AWS system are limited temperature certification for Antarctic conditions; non-standard integration of the varied telecommunications equipment; potentially inflexible data acquisition schemes; and frequent product upgrades, changes, and obsolescence. The UW-Madison presents the current status of its AWS system; its recent experience with new data loggers, sensors, and communication options; and its attempts to obtain a standardized AWS. The intent is to encourage the development of a forum where groups can document their experiences with varied AWS systems in the extreme polar climate. Recent events have added another challenge within the United States Antarctic Program, as it has become clear that budgetary and logistic limitations will drastically impact the AWS program. With logistical costs playing a bigger factor in funding AWS operations, international coordination and cooperation will be important in deploying and maintaining the AWS networks (such as GCOS) that are critical to monitoring the world's climate.

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.

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

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.

Structured Analysis of the Logistic Support Analysis (LSA) Task, ’Integrated Logistic Support (ILS) Assessment Maintenance Planning E-1 Element’ (APJ 966-204)

DTIC Science & Technology

1988-10-01

Structured Analysis involves building a logical (non-physical) model of a system, using graphic techniques which enable users, analysts, and designers to... Design uses tools, especially graphic ones, to render systems readily understandable. 8 Ř. Structured Design offers a set of strategies for...in the overall systems design process, and an overview of the assessment procedures, as well as a guide to the overall assessment. 20. DISTRIBUTION

Matched samples logistic regression in case-control studies with missing values: when to break the matches.

PubMed

Hansson, Lisbeth; Khamis, Harry J

2008-12-01

Simulated data sets are used to evaluate conditional and unconditional maximum likelihood estimation in an individual case-control design with continuous covariates when there are different rates of excluded cases and different levels of other design parameters. The effectiveness of the estimation procedures is measured by method bias, variance of the estimators, root mean square error (RMSE) for logistic regression and the percentage of explained variation. Conditional estimation leads to higher RMSE than unconditional estimation in the presence of missing observations, especially for 1:1 matching. The RMSE is higher for the smaller stratum size, especially for the 1:1 matching. The percentage of explained variation appears to be insensitive to missing data, but is generally higher for the conditional estimation than for the unconditional estimation. It is particularly good for the 1:2 matching design. For minimizing RMSE, a high matching ratio is recommended; in this case, conditional and unconditional logistic regression models yield comparable levels of effectiveness. For maximizing the percentage of explained variation, the 1:2 matching design with the conditional logistic regression model is recommended.

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.

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.

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.

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.

Use and interpretation of logistic regression in habitat-selection studies

USGS Publications Warehouse

Keating, Kim A.; Cherry, Steve

2004-01-01

 Logistic regression is an important tool for wildlife habitat-selection studies, but the method frequently has been misapplied due to an inadequate understanding of the logistic model, its interpretation, and the influence of sampling design. To promote better use of this method, we review its application and interpretation under 3 sampling designs: random, case-control, and use-availability. Logistic regression is appropriate for habitat use-nonuse studies employing random sampling and can be used to directly model the conditional probability of use in such cases. Logistic regression also is appropriate for studies employing case-control sampling designs, but careful attention is required to interpret results correctly. Unless bias can be estimated or probability of use is small for all habitats, results of case-control studies should be interpreted as odds ratios, rather than probability of use or relative probability of use. When data are gathered under a use-availability design, logistic regression can be used to estimate approximate odds ratios if probability of use is small, at least on average. More generally, however, logistic regression is inappropriate for modeling habitat selection in use-availability studies. In particular, using logistic regression to fit the exponential model of Manly et al. (2002:100) does not guarantee maximum-likelihood estimates, valid probabilities, or valid likelihoods. We show that the resource selection function (RSF) commonly used for the exponential model is proportional to a logistic discriminant function. Thus, it may be used to rank habitats with respect to probability of use and to identify important habitat characteristics or their surrogates, but it is not guaranteed to be proportional to probability of use. Other problems associated with the exponential model also are discussed. We describe an alternative model based on Lancaster and Imbens (1996) that offers a method for estimating conditional probability of use in use-availability studies. Although promising, this model fails to converge to a unique solution in some important situations. Further work is needed to obtain a robust method that is broadly applicable to use-availability studies.

Logistics in a low carbon concept: Connotation and realization way

NASA Astrophysics Data System (ADS)

Zheng, Chaocheng; Qiu, Xiaoying; Mao, Jiarong

2017-01-01

Low-carbon logistics has become a trend for the logistics industry-as a high-energy consumption industry, continuation of its previous operating mode has been significantly behind the times. So logistics industry must release lower carbon emissions. This paper sort out the literature home and abroad from three aspects, that is, the definition of low-carbon logistics, low-carbon logistics implementation mechanisms or measures, and low carbon design quantitative models. The research shows: low-carbon logistics needed to implemented both in enterprise' macro and micro level, which means the government should provide relevant policy support and micro enterprises should be actively sought from all sectors of the logistics in energy saving. In practice, low-carbon logistics optimization models are effective tools for enterprises to implement emission reduction.

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

Information and material flows in complex networks

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Armbruster, Dieter; Mikhailov, Alexander S.; Lefeber, Erjen

2006-04-01

In this special issue, an overview of the Thematic Institute (TI) on Information and Material Flows in Complex Systems is given. The TI was carried out within EXYSTENCE, the first EU Network of Excellence in the area of complex systems. Its motivation, research approach and subjects are presented here. Among the various methods used are many-particle and statistical physics, nonlinear dynamics, as well as complex systems, network and control theory. The contributions are relevant for complex systems as diverse as vehicle and data traffic in networks, logistics, production, and material flows in biological systems. The key disciplines involved are socio-, econo-, traffic- and bio-physics, and a new research area that could be called “biologistics”.

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.

Reverse preferential spread in complex networks

NASA Astrophysics Data System (ADS)

Toyoizumi, Hiroshi; Tani, Seiichi; Miyoshi, Naoto; Okamoto, Yoshio

2012-08-01

Large-degree nodes may have a larger influence on the network, but they can be bottlenecks for spreading information since spreading attempts tend to concentrate on these nodes and become redundant. We discuss that the reverse preferential spread (distributing information inversely proportional to the degree of the receiving node) has an advantage over other spread mechanisms. In large uncorrelated networks, we show that the mean number of nodes that receive information under the reverse preferential spread is an upper bound among any other weight-based spread mechanisms, and this upper bound is indeed a logistic growth independent of the degree distribution.

The Senior Toronto Oncology Panel (STOP) Study: Research Participation for Older Adults With Cancer and Caregivers.

PubMed

Puts, Martine T E; Sattar, Schroder; Fossat, Takami; Fitch, Margaret I; Macdonald, Geraldine J; Hsu, Tina; Szumacher, Ewa; Stephens, Douglas A; Robinson, Joseph; Macdonald, David; Choate, Andrew S; Pitters, Eric; Liu, Barbara; Jeffs, Lianne; McGilton, Katherine S; Alibhai, Shabbir M H

2017-10-01

Background: Patient engagement in research may lead to better-designed studies and improved health outcomes. The objectives of this study were to identify the research priorities of older adults with cancer (OAWCs) and their caregivers and examine how to engage these individuals in research teams and what supports are needed. Methods: We conducted 3 public meetings and 7 focus groups to delineate research priorities and the supports needed to facilitate integration of OAWCs and their caregivers on research teams. Results: A total of 33 older adults and 19 caregivers attended a public meeting and 27 older adults and 17 caregivers participated in a focus group. Most of the OAWCs and their caregivers had never participated in research before. Three themes were identified from the focus groups: (1) motivation to be on a team; (2) ability to make meaningful contributions; and (3) logistical considerations to facilitate engagement. Most participants were motivated to be a research team member and be involved in all steps of research if it could benefit them or future patients and caregivers. OAWCs and their caregivers were highly motivated to improve outcomes. Required logistics included flexibility regarding time and location, accessibility to computer technology, transportation support, materials worded in lay language, and attending/having short training sessions, as well as the presence of peer support. Conclusions: OAWCs and their caregivers are very motivated and willing to participate in research and to be research team members. Logistics and the social aspects of being on a team are important. Copyright © 2017 by the National Comprehensive Cancer Network.

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,...

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.

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.

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.

Translating supportability requirements into design reality

NASA Astrophysics Data System (ADS)

Buche, J.; Cohen, I.

1986-10-01

This paper explores some of the principal issues in the integration of supportability into the design process. Roles of the contractor's design, supportability and management specialists and their government counterparts are discussed as they relate to logistics influence in design. Methods and processes by which weapon system logistics and readiness requirements are established, assessed, allocated to system elements and translated into specific design features are described. Tradeoff consideration, an approach to effective tradeoff criteria, and the progress of supportability issues through the program phases are identified with particular emphasis on the necessity for developing and maintaining an effective audit trail.

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

Moving beyond the Typologies of Managed Care: The Example of Health Plan Predictors of Screening Mammography

PubMed Central

Tye, Sherilyn; Phillips, Kathryn A; Liang, Su-Ying; Haas, Jennifer S

2004-01-01

Objectives To develop a framework of factors to characterize health plans, to identify how plan characteristics were measured in a national survey, and to apply our findings to an analysis of the predictors of screening mammography. Data Source The primary data were from the 1996 Medical Expenditure Panel Survey. Study Design Women ages 40+, with private insurance, and no history of breast cancer were included in the study (N=2,909). We used multivariate logistic regression to estimate mammography utilization in the past two years relative to health plan and demographic factors. Health plan measures included whether there is a defined provider network, whether coverage is restricted to a network, use of gatekeepers, level of cost containment, copayment and deductible amounts, coinsurance rate, and breadth of benefit coverage. Principal Findings We found no significant difference in reported mammography utilization using a dichotomous comparison of individuals enrolled in managed care versus indemnity plans. However, women in health plans with a defined provider network were more likely to report having received a mammogram in the past two years than those without networks (adjusted OR=1.21, 95 percent CI=1.07–1.36), and women in gatekeeper plans were more likely to report receiving mammography than those without gatekeepers (adjusted OR=1.18, 95 percent CI=1.03–1.36). Restricted out-of-network coverage, use of cost containment, enrollee cost sharing, and breadth of benefit coverage did not appear to affect mammography use. Conclusions It is important to examine the effect of individual health plan components on the utilization of health care, rather than use the traditional broader categorizations of managed versus nonmanaged care or simple health plan typologies. PMID:14965083

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.

Optimizing the US Navy’s Combat Logistics Force

DTIC Science & Technology

2008-01-01

Optimizing the US Navy’s Combat Logistics Force Gerald G. Brown, W. Matthew Carlyle Operations Research Department, Naval Postgraduate School...Wiley InterScience (www.interscience.wiley.com). Abstract: We study how changes to the composition and employment of the US Navy combat logistic force...evaluate new CLF ship designs, advise what number of ships in a new ship class would be needed, test concepts for forward at-sea logistics bases in lieu

Structured Analysis for the Logistic Support Analysis (LSA) Task and the Integrated Logistic Support (ILS) Element. Structured Analysis - ILS Assessment Element E11. Design Influence

DTIC Science & Technology

1989-01-01

format size of this report, the full identifying entry may well be forcibly shortened, thereby introducing the possibility of misunderstanding. Therefore...OF MATERIEL" 3d . "AR 570-9, "MANPOWER AND EQUIPMENT CONTROL - HOST NATION SUPPORT" 2. AR 700-9, "POLICIES OF THE ARMY LOGISTIC SYSTEM" 3. AR 700-82...PERSONNEL 4. TRAINING 5. SYSTEM SAFETY 6. HEALTH HAZARDS. TEE ASSESSMENT Or MANPRINT INFLUENCE ON DESIGNS IS ADDRESSED IN SIX (6) SPECIFIC AREAS IN

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

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.

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.

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)

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

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...

Effects of BMI on the risk and frequency of AIS 3+ injuries in motor-vehicle crashes.

PubMed

Rupp, Jonathan D; Flannagan, Carol A C; Leslie, Andrew J; Hoff, Carrie N; Reed, Matthew P; Cunningham, Rebecca M

2013-01-01

Determine the effects of BMI on the risk of serious-to-fatal injury (Abbreviated Injury Scale ≥ 3 or AIS 3+) to different body regions for adults in frontal, nearside, farside, and rollover crashes. Multivariate logistic regression analysis was applied to a probability sample of adult occupants involved in crashes generated by combining the National Automotive Sampling System (NASS-CDS) with a pseudoweighted version of the Crash Injury Research and Engineering Network database. Logistic regression models were applied to weighted data to estimate the change in the number of occupants with AIS 3+ injuries if no occupants were obese. Increasing BMI increased risk of lower-extremity injury in frontal crashes, decreased risk of lower-extremity injury in nearside impacts, increased risk of upper-extremity injury in frontal and nearside crashes, and increased risk of spine injury in frontal crashes. Several of these findings were affected by interactions with gender and vehicle type. If no occupants in frontal crashes were obese, 7% fewer occupants would sustain AIS 3+ upper-extremity injuries, 8% fewer occupants would sustain AIS 3+ lower-extremity injuries, and 28% fewer occupants would sustain AIS 3+ spine injuries. Results of this study have implications on the design and evaluation of vehicle safety systems. Copyright © 2013 The Obesity Society.

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.

41 CFR 101-30.303 - Responsibility.

Code of Federal Regulations, 2014 CFR

2014-07-01

... direct to the Defense Logistics Services Center (DLSC) in conformance with procedures set forth in the... cataloging activity designated to receive requests are in the GSA Handbook, Federal Catalog System-Logistics...

41 CFR 101-30.303 - Responsibility.

Code of Federal Regulations, 2012 CFR

2012-07-01

... direct to the Defense Logistics Services Center (DLSC) in conformance with procedures set forth in the... cataloging activity designated to receive requests are in the GSA Handbook, Federal Catalog System-Logistics...

41 CFR 101-30.303 - Responsibility.

Code of Federal Regulations, 2013 CFR

2013-07-01

... direct to the Defense Logistics Services Center (DLSC) in conformance with procedures set forth in the... cataloging activity designated to receive requests are in the GSA Handbook, Federal Catalog System-Logistics...

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

PubMed

Heidema, A Geert; Boer, Jolanda M A; Nagelkerke, Nico; Mariman, Edwin C M; van der A, Daphne L; Feskens, Edith J M

2006-04-21

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases.

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.

Social network composition of vascular patients and its associations with health behavior and clinical risk factors

PubMed Central

Heijmans, Naomi; van Lieshout, Jan; Wensing, Michel

2017-01-01

Background This study aimed to explore linkages of patients’ social network composition with health behaviors and clinical risk factors. Methods/Design This observational study was embedded in a project aimed at improving cardiovascular risk management (CRVM) in primary care. 657 vascular patients (227 with cardiovascular disease, 380 at high vascular risk), mean age 72.4 (SD 9.4) years, were recruited as were individuals patients considered important for dealing with their disease, so called alters (n = 487). Network composition was measured with structured patient questionnaires. Both patients and alters completed questionnaires to measure health behavior (habits for physical activity, diet, and smoking). Clinical risk factors (systolic blood pressure, LDL cholesterol level, and body mass index) were extracted from patients’ medical records. Six logistic regression analyses, using generalized estimating equations, were used to test three hypothesized effects of network composition (having alters with healthful behaviors, without depression, and with specialized knowledge) on six outcomes, adjusted for demographic, personal and psychological characteristics. Results Having alters with overall healthful behavior was related to healthful patient diet (OR 2.14, 95%CI: 1.52–3.02). Having non-smoking alters in networks was related to reduced odds for patient smoking (OR 0.17, 95%CI: 0.05–0.60). No effects of presence of non-depressed alters were found. Presence of alters with specialized knowledge on CVRM was inversely related to healthful diet habits of patients (OR 0.47, 95%CI 0.24–0.89). No significant associations between social network composition and clinical risk factors were found. Discussion Diet and smoking, but not physical exercise and clinical risk factors, were associated with social network composition of patients with vascular conditions. In this study of vascular patients, controlling for both personal and psychological factors, fewer network influences were found compared to previous research. Further research is needed to examine network structure characteristics as well as the role of psychological factors to enhance understanding health behavior of patients involved in CVRM. PMID:28957372

Design of Neural Networks for Fast Convergence and Accuracy

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1998-01-01

A novel procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed to provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component spacecraft design changes and measures of its performance. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The design algorithm attempts to avoid the local minima phenomenon that hampers the traditional network training. A numerical example is performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

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

The Automated Logistics Element Planning System (ALEPS)

NASA Technical Reports Server (NTRS)

Schwaab, Douglas G.

1991-01-01

The design and functions of ALEPS (Automated Logistics Element Planning System) is a computer system that will automate planning and decision support for Space Station Freedom Logistical Elements (LEs) resupply and return operations. ALEPS provides data management, planning, analysis, monitoring, interfacing, and flight certification for support of LE flight load planning activities. The prototype ALEPS algorithm development is described.

Structured Analysis of the Logistics Support Analysis (LSA) Task, and Integrated Logistic Support (ILS) Element, ’Standardization and Interoperability (S and I)’.

DTIC Science & Technology

1988-11-01

system, using graphic techniques which enable users, analysts, and designers to get a clear and common picture of the system and how its parts fit...boxes into hierarchies suitable for computer implementation. ŗ. Structured Design uses tools, especially graphic ones, to render systems readily...LSA, PROCESSES, DATA FLOWS, DATA STORES, EX"RNAL ENTITIES, OVERALL SYSTEMS DESIGN PROCESS, over 19, ABSTRACT (Continue on reverse if necessary and

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.

Information theory-based decision support system for integrated design of multivariable hydrometric networks

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin

2017-07-01

Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly.

Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges.

PubMed

Li, Shuangyan; Li, Xialian; Zhang, Dezhi; Zhou, Lingyun

2017-01-01

This study develops an optimization model to integrate facility location and inventory control for a three-level distribution network consisting of a supplier, multiple distribution centers (DCs), and multiple retailers. The integrated model addressed in this study simultaneously determines three types of decisions: (1) facility location (optimal number, location, and size of DCs); (2) allocation (assignment of suppliers to located DCs and retailers to located DCs, and corresponding optimal transport mode choices); and (3) inventory control decisions on order quantities, reorder points, and amount of safety stock at each retailer and opened DC. A mixed-integer programming model is presented, which considers the carbon emission taxes, multiple transport modes, stochastic demand, and replenishment lead time. The goal is to minimize the total cost, which covers the fixed costs of logistics facilities, inventory, transportation, and CO2 emission tax charges. The aforementioned optimal model was solved using commercial software LINGO 11. A numerical example is provided to illustrate the applications of the proposed model. The findings show that carbon emission taxes can significantly affect the supply chain structure, inventory level, and carbon emission reduction levels. The delay rate directly affects the replenishment decision of a retailer.

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.

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

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…

Space Station logistics policy - Risk management from the top down

NASA Technical Reports Server (NTRS)

Paules, Granville; Graham, James L., Jr.

1990-01-01

Considerations are presented in the area of risk management specifically relating to logistics and system supportability. These considerations form a basis for confident application of concurrent engineering principles to a development program, aiming at simultaneous consideration of support and logistics requirements within the engineering process as the system concept and designs develop. It is shown that, by applying such a process, the chances of minimizing program logistics and supportability risk in the long term can be improved. The problem of analyzing and minimizing integrated logistics risk for the Space Station Freedom Program is discussed.

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.

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

An investigation of the speeding-related crash designation through crash narrative reviews sampled via logistic regression.

PubMed

Fitzpatrick, Cole D; Rakasi, Saritha; Knodler, Michael A

2017-01-01

Speed is one of the most important factors in traffic safety as higher speeds are linked to increased crash risk and higher injury severities. Nearly a third of fatal crashes in the United States are designated as "speeding-related", which is defined as either "the driver behavior of exceeding the posted speed limit or driving too fast for conditions." While many studies have utilized the speeding-related designation in safety analyses, no studies have examined the underlying accuracy of this designation. Herein, we investigate the speeding-related crash designation through the development of a series of logistic regression models that were derived from the established speeding-related crash typologies and validated using a blind review, by multiple researchers, of 604 crash narratives. The developed logistic regression model accurately identified crashes which were not originally designated as speeding-related but had crash narratives that suggested speeding as a causative factor. Only 53.4% of crashes designated as speeding-related contained narratives which described speeding as a causative factor. Further investigation of these crashes revealed that the driver contributing code (DCC) of "driving too fast for conditions" was being used in three separate situations. Additionally, this DCC was also incorrectly used when "exceeding the posted speed limit" would likely have been a more appropriate designation. Finally, it was determined that the responding officer only utilized one DCC in 82% of crashes not designated as speeding-related but contained a narrative indicating speed as a contributing causal factor. The use of logistic regression models based upon speeding-related crash typologies offers a promising method by which all possible speeding-related crashes could be identified. Published by Elsevier Ltd.

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.

A conceptual model for the development process of confirmatory adaptive clinical trials within an emergency research network.

PubMed

Mawocha, Samkeliso C; Fetters, Michael D; Legocki, Laurie J; Guetterman, Timothy C; Frederiksen, Shirley; Barsan, William G; Lewis, Roger J; Berry, Donald A; Meurer, William J

2017-06-01

Adaptive clinical trials use accumulating data from enrolled subjects to alter trial conduct in pre-specified ways based on quantitative decision rules. In this research, we sought to characterize the perspectives of key stakeholders during the development process of confirmatory-phase adaptive clinical trials within an emergency clinical trials network and to build a model to guide future development of adaptive clinical trials. We used an ethnographic, qualitative approach to evaluate key stakeholders' views about the adaptive clinical trial development process. Stakeholders participated in a series of multidisciplinary meetings during the development of five adaptive clinical trials and completed a Strengths-Weaknesses-Opportunities-Threats questionnaire. In the analysis, we elucidated overarching themes across the stakeholders' responses to develop a conceptual model. Four major overarching themes emerged during the analysis of stakeholders' responses to questioning: the perceived statistical complexity of adaptive clinical trials and the roles of collaboration, communication, and time during the development process. Frequent and open communication and collaboration were viewed by stakeholders as critical during the development process, as were the careful management of time and logistical issues related to the complexity of planning adaptive clinical trials. The Adaptive Design Development Model illustrates how statistical complexity, time, communication, and collaboration are moderating factors in the adaptive design development process. The intensity and iterative nature of this process underscores the need for funding mechanisms for the development of novel trial proposals in academic settings.

The effects of designation and volume of neonatal care on mortality and morbidity outcomes of very preterm infants in England: retrospective population-based cohort study

PubMed Central

Watson, S I; Arulampalam, W; Petrou, S; Marlow, N; Morgan, A S; Draper, E S; Santhakumaran, S; Modi, N

2014-01-01

Objective To examine the effects of designation and volume of neonatal care at the hospital of birth on mortality and morbidity outcomes in very preterm infants in a managed clinical network setting. Design A retrospective, population-based analysis of operational clinical data using adjusted logistic regression and instrumental variables (IV) analyses. Setting 165 National Health Service neonatal units in England contributing data to the National Neonatal Research Database at the Neonatal Data Analysis Unit and participating in the Neonatal Economic, Staffing and Clinical Outcomes Project. Participants 20 554 infants born at <33 weeks completed gestation (17 995 born at 27–32 weeks; 2559 born at <27 weeks), admitted to neonatal care and either discharged or died, over the period 1 January 2009–31 December 2011. Intervention Tertiary designation or high-volume neonatal care at the hospital of birth. Outcomes Neonatal mortality, any in-hospital mortality, surgery for necrotising enterocolitis, surgery for retinopathy of prematurity, bronchopulmonary dysplasia and postmenstrual age at discharge. Results Infants born at <33 weeks gestation and admitted to a high-volume neonatal unit at the hospital of birth were at reduced odds of neonatal mortality (IV regression odds ratio (OR) 0.70, 95% CI 0.53 to 0.92) and any in-hospital mortality (IV regression OR 0.68, 95% CI 0.54 to 0.85). The effect of volume on any in-hospital mortality was most acute among infants born at <27 weeks gestation (IV regression OR 0.51, 95% CI 0.33 to 0.79). A negative association between tertiary-level unit designation and mortality was also observed with adjusted logistic regression for infants born at <27 weeks gestation. Conclusions High-volume neonatal care provided at the hospital of birth may protect against in-hospital mortality in very preterm infants. Future developments of neonatal services should promote delivery of very preterm infants at hospitals with high-volume neonatal units. PMID:25001393

Methodologic considerations in the design and analysis of nested case-control studies: association between cytokines and postoperative delirium.

PubMed

Ngo, Long H; Inouye, Sharon K; Jones, Richard N; Travison, Thomas G; Libermann, Towia A; Dillon, Simon T; Kuchel, George A; Vasunilashorn, Sarinnapha M; Alsop, David C; Marcantonio, Edward R

2017-06-06

The nested case-control study (NCC) design within a prospective cohort study is used when outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects. A NCC analysis with good matching procedures yields estimates that are as efficient and unbiased as estimates from the full cohort study. We present methodological considerations in a matched NCC design and analysis, which include the choice of match algorithms, analysis methods to evaluate the association of exposures of interest with outcomes, and consideration of overmatching. Matched, NCC design within a longitudinal observational prospective cohort study in the setting of two academic hospitals. Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery. The primary outcome was postoperative delirium from in-hospital interviews and medical record review. The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred. We used nonparametric signed ranked test to test for the median of the paired differences. We used conditional logistic regression to model the risk of IL-6 on delirium incidence. Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression. Partial R-square was used to assess the level of overmatching. We found that the optimal match algorithm yielded more matched pairs than the greedy algorithm. The choice of analytic strategy-whether to consider measured cytokine levels as the predictor or outcome-- yielded inferences that have different clinical interpretations but similar levels of statistical significance. Estimation results from NCC design using conditional logistic regression, and from simulated cohort design using unconditional logistic regression, were similar. We found minimal evidence for overmatching. Using a matched NCC approach introduces methodological challenges into the study design and data analysis. Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.

The application of virtual reality systems as a support of digital manufacturing and logistics

NASA Astrophysics Data System (ADS)

Golda, G.; Kampa, A.; Paprocka, I.

2016-08-01

Modern trends in development of computer aided techniques are heading toward the integration of design competitive products and so-called "digital manufacturing and logistics", supported by computer simulation software. All phases of product lifecycle: starting from design of a new product, through planning and control of manufacturing, assembly, internal logistics and repairs, quality control, distribution to customers and after-sale service, up to its recycling or utilization should be aided and managed by advanced packages of product lifecycle management software. Important problems for providing the efficient flow of materials in supply chain management of whole product lifecycle, using computer simulation will be described on that paper. Authors will pay attention to the processes of acquiring relevant information and correct data, necessary for virtual modeling and computer simulation of integrated manufacturing and logistics systems. The article describes possibilities of use an applications of virtual reality software for modeling and simulation the production and logistics processes in enterprise in different aspects of product lifecycle management. The authors demonstrate effective method of creating computer simulations for digital manufacturing and logistics and show modeled and programmed examples and solutions. They pay attention to development trends and show options of the applications that go beyond enterprise.

Feedstock Supply System Design and Economics for Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels Conversion Pathway: Fast Pyrolysis and Hydrotreating Bio-Oil Pathway "The 2017 Design Case"

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

Kevin L. Kenney; Kara G. Cafferty; Jacob J. Jacobson

The U.S. Department of Energy promotes the production of liquid fuels from lignocellulosic biomass feedstocks by funding fundamental and applied research that advances the state of technology in biomass sustainable supply, logistics, conversion, and overall system sustainability. As part of its involvement in this program, Idaho National Laboratory (INL) investigates the feedstock logistics economics and sustainability of these fuels. Between 2000 and 2012, INL quantified and the economics and sustainability of moving biomass from the field or stand to the throat of the conversion process using conventional equipment and processes. All previous work to 2012 was designed to improve themore » efficiency and decrease costs under conventional supply systems. The 2012 programmatic target was to demonstrate a biomass logistics cost of $55/dry Ton for woody biomass delivered to fast pyrolysis conversion facility. The goal was achieved by applying field and process demonstration unit-scale data from harvest, collection, storage, preprocessing, handling, and transportation operations into INL’s biomass logistics model.« less

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.

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.

Multi-Purpose Logistics Module (MPLM) Cargo Heat Exchanger

NASA Technical Reports Server (NTRS)

Zampiceni, John J.; Harper, Lon T.

2002-01-01

This paper describes the New Shuttle Orbiter's Multi- Purpose Logistics Modulo (MPLM) Cargo Heat Exchanger (HX) and associated MPLM cooling system. This paper presents Heat Exchanger (HX) design and performance characteristics of the system.

Identity Preserved Grain: Logistical Overview

DOT National Transportation Integrated Search

2000-01-01

This study was designed to be a resource for producers, shippers, and exporters seeking to diversify their markets through IP shipments. Included are examples of markets for IP grains, trends for containerized movements of grain, and general logistic...

Exploring the evolution of London's street network in the information space: A dual approach

NASA Astrophysics Data System (ADS)

Masucci, A. Paolo; Stanilov, Kiril; Batty, Michael

2014-01-01

We study the growth of London's street network in its dual representation, as the city has evolved over the past 224 years. The dual representation of a planar graph is a content-based network, where each node is a set of edges of the planar graph and represents a transportation unit in the so-called information space, i.e., the space where information is handled in order to navigate through the city. First, we discuss a novel hybrid technique to extract dual graphs from planar graphs, called the hierarchical intersection continuity negotiation principle. Then we show that the growth of the network can be analytically described by logistic laws and that the topological properties of the network are governed by robust log-normal distributions characterizing the network's connectivity and small-world properties that are consistent over time. Moreover, we find that the double-Pareto-like distributions for the connectivity emerge for major roads and can be modeled via a stochastic content-based network model using simple space-filling principles.

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.

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.

Development of the TLALOCNet GPS-Met Network in Northwestern Mexico: Supporting Continuous Water Vapor Observations of the North American Monsoon

NASA Astrophysics Data System (ADS)

Galetzka, J.; Feaux, K.; Cabral, E.; Salazar-Tlaczani, L.; Adams, D. K.; Serra, Y. L.; Mattioli, G. S.; Miller, M. M.

2014-12-01

TLALOCNet is a combined atmospheric and tectonic cGPS-Met network in Mexico designed for the investigation of climate, atmospheric processes, the earthquake cycle, and tectonics. While EarthScope-Plate Boundary Observatory (conterminous US, Alaska, Puerto Rico) is among the networks poised to become a nucleus for hemisphere-scale GPS observations, the completion of TLALOCNet at the end of 2015 will close a gap between PBO and other Latin American GPS networks that include COCONet (Central America, Caribbean, and Northern South America), CAnTO, CAP, and IGS extending from Alaska to Patagonia. The National Science Foundation funded the construction and operation of TLALOCNet, with significant matching funds and resources provided by the Universidad Nacional Autónoma de México (UNAM). The project will involve the construction or refurbishment of 38 cGPS-Met stations in Mexico built to PBO standards. The first three TLALOCNet stations were installed in the northern Mexican states of Sonora and Chihuahua in July 2014, following the North American Monsoon GPS Transect Experiment 2013. Together these observations better characterize critical components of water transport in the region. Data from these stations are now available through the UNAVCO data archive and can be downloaded from http://facility.unavco.org/data/dai2/app/dai2.html#. By the end of 2014, TLALOCNet data, together with complementary data from other regional cGPS networks in Mexico, will also be openly available through a Mexico-based data center. We will present the status of the project to date, including an overview of the station hardware, data communications, data flow, construction schedule, and science objectives. We will also present some of the challenges encountered, including regional logistics, shipping and importation, site security, and other issues associated with the construction and operation of a large continuous GPS network.

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.

Single and multiple objective biomass-to-biofuel supply chain optimization considering environmental impacts

NASA Astrophysics Data System (ADS)

Valles Sosa, Claudia Evangelina

Bioenergy has become an important alternative source of energy to alleviate the reliance on petroleum energy. Bioenergy offers diminishing climate change by reducing Green House Gas Emissions, as well as providing energy security and enhancing rural development. The Energy Independence and Security Act mandate the use of 21 billion gallons of advanced biofuels including 16 billion gallons of cellulosic biofuels by the year 2022. It is clear that Biomass can make a substantial contribution to supply future energy demand in a sustainable way. However, the supply of sustainable energy is one of the main challenges that mankind will face over the coming decades. For instance, many logistical challenges will be faced in order to provide an efficient and reliable supply of quality feedstock to biorefineries. 700 million tons of biomass will be required to be sustainably delivered to biorefineries annually to meet the projected use of biofuels by the year of 2022. Approaching this complex logistic problem as a multi-commodity network flow structure, the present work proposes the use of a genetic algorithm as a single objective optimization problem that considers the maximization of profit and the present work also proposes the use of a Multiple Objective Evolutionary Algorithm to simultaneously maximize profit while minimizing global warming potential. Most transportation optimization problems available in the literature have mostly considered the maximization of profit or the minimization of total travel time as potential objectives to be optimized. However, on this research work, we take a more conscious and sustainable approach for this logistic problem. Planners are increasingly expected to adopt a multi-disciplinary approach, especially due to the rising importance of environmental stewardship. The role of a transportation planner and designer is shifting from simple economic analysis to promoting sustainability through the integration of environmental objectives. To respond to these new challenges, the Modified Multiple Objective Evolutionary Algorithm for the design optimization of a biomass to bio-refinery logistic system that considers the simultaneous maximization of the total profit and the minimization of three environmental impacts is presented. Sustainability balances economic, social and environmental goals and objectives. There exist several works in the literature that have considered economic and environmental objectives for the presented supply chain problem. However, there is a lack of research performed in the social aspect of a sustainable logistics system. This work proposes a methodology to integrate social aspect assessment, based on employment creation. Finally, most of the assessment methodologies considered in the literature only contemplate deterministic values, when in realistic situations uncertainties in the supply chain are present. In this work, Value-at-Risk, an advanced risk measure commonly used in portfolio optimization is included to consider the uncertainties in biofuel prices, among the others.

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.

Logistics of Guinea Worm Disease Eradication in South Sudan

PubMed Central

Jones, Alexander H.; Becknell, Steven; Withers, P. Craig; Ruiz-Tiben, Ernesto; Hopkins, Donald R.; Stobbelaar, David; Makoy, Samuel Yibi

2014-01-01

From 2006 to 2012, the South Sudan Guinea Worm Eradication Program reduced new Guinea worm disease (dracunculiasis) cases by over 90%, despite substantial programmatic challenges. Program logistics have played a key role in program achievements to date. The program uses disease surveillance and program performance data and integrated technical–logistical staffing to maintain flexible and effective logistical support for active community-based surveillance and intervention delivery in thousands of remote communities. Lessons learned from logistical design and management can resonate across similar complex surveillance and public health intervention delivery programs, such as mass drug administration for the control of neglected tropical diseases and other disease eradication programs. Logistical challenges in various public health scenarios and the pivotal contribution of logistics to Guinea worm case reductions in South Sudan underscore the need for additional inquiry into the role of logistics in public health programming in low-income countries. PMID:24445199

Logistics of Guinea worm disease eradication in South Sudan.

PubMed

Jones, Alexander H; Becknell, Steven; Withers, P Craig; Ruiz-Tiben, Ernesto; Hopkins, Donald R; Stobbelaar, David; Makoy, Samuel Yibi

2014-03-01

From 2006 to 2012, the South Sudan Guinea Worm Eradication Program reduced new Guinea worm disease (dracunculiasis) cases by over 90%, despite substantial programmatic challenges. Program logistics have played a key role in program achievements to date. The program uses disease surveillance and program performance data and integrated technical-logistical staffing to maintain flexible and effective logistical support for active community-based surveillance and intervention delivery in thousands of remote communities. Lessons learned from logistical design and management can resonate across similar complex surveillance and public health intervention delivery programs, such as mass drug administration for the control of neglected tropical diseases and other disease eradication programs. Logistical challenges in various public health scenarios and the pivotal contribution of logistics to Guinea worm case reductions in South Sudan underscore the need for additional inquiry into the role of logistics in public health programming in low-income countries.

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.

A social network analysis of substance use among immigrant adolescents in six European cities.

PubMed

Lorant, Vincent; Soto Rojas, Victoria; Bécares, Laia; Kinnunen, Jaana M; Kuipers, Mirte A G; Moor, Irene; Roscillo, Gaetano; Alves, Joana; Grard, Adeline; Rimpelä, Arja; Federico, Bruno; Richter, Matthias; Perelman, Julian; Kunst, Anton E

2016-11-01

Social integration and the health of adolescents with a migration background is a major concern in multicultural societies. The literature, however, has paid little attention to the wider determinants of their health behaviours, including the composition of their social networks. The aim of this study was to describe the composition of adolescents' social networks according to migration background, and to examine how social networks are associated with substance use. In 2013, the SILNE study surveyed 11,015 secondary-school adolescents in 50 schools in six European cities in Belgium, Finland, Germany, Italy, the Netherlands, and Portugal, using a social network design. Each adolescent nominated up to five of their best and closest friends. Migration status was defined as first-generation migrants, second-generation migrants, and speaking another language at home. We computed two groups of network structural positions, the centrality of individual adolescents in networks, and the homophily of their social ties regarding migration (same-migration). Multilevel logistic regression was used to model the association between network structural position and smoking, alcohol use, and cannabis use. Compared with non-migrant adolescents, adolescents with migration backgrounds had similar relationship patterns. But almost half their social ties were with same-migration-background adolescents; non-migrants had few social ties to migrants. For adolescents with a migration background, a higher proportion of social ties with non-migrants was associated with increased use of cannabis (OR = 1.07, p = 0.03) and alcohol (OR = 1.08, p < 0.01), but not with increased smoking (p = 0.60). Popular migrant adolescents were at less risk of smoking, alcohol use, and cannabis use than popular non-migrant adolescents. Homophily of social ties by migration background is noticeable in European schools. The tendency of migrant adolescents to have same-migration social ties may isolate them from non-migrant adolescents, but also reduces their risky health behaviours, in particular cannabis and alcohol use. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Topology design and performance analysis of an integrated communication network

NASA Technical Reports Server (NTRS)

Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.

1985-01-01

A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.

Integrated Logistics Support approach: concept for the new big projects: E-ELT, SKA, CTA

NASA Astrophysics Data System (ADS)

Marchiori, G.; Rampini, F.; Formentin, F.

2014-08-01

The Integrated Logistic Support is a process supporting strategies and optimizing activities for a correct project management and system engineering development. From the design & engineering of complex technical systems, to the erection on site, acceptance and after-sales service, EIE GROUP covers all aspects of the Integrated Logistics Support (ILS) process that includes: costing process centered around the life cycle cost and Level of Repair Analyses; engineering process which influences the design via means of reliability, modularization, etc.; technical publishing process based on international specifications; ordering administration process for supply support. Through the ILS, EIE GROUP plans and directs the identification and development of logistics support and system requirements for its products, with the goal of creating systems that last longer and require less support, thereby reducing costs and increasing return on investments. ILS therefore, addresses these aspects of supportability not only during acquisition, but also throughout the operational life cycle of the system. The impact of the ILS is often measured in terms of metrics such as reliability, availability, maintainability and testability (RAMT), and System Safety (RAMS). Example of the criteria and approach adopted by EIE GROUP during the design, manufacturing and test of the ALMA European Antennas and during the design phase of the E-ELT telescope and Dome are presented.

Distributed Computer Networks in Support of Complex Group Practices

PubMed Central

Wess, Bernard P.

1978-01-01

The economics of medical computer networks are presented in context with the patient care and administrative goals of medical networks. Design alternatives and network topologies are discussed with an emphasis on medical network design requirements in distributed data base design, telecommunications, satellite systems, and software engineering. The success of the medical computer networking technology is predicated on the ability of medical and data processing professionals to design comprehensive, efficient, and virtually impenetrable security systems to protect data bases, network access and services, and patient confidentiality.

Designing Networks that are Capable of Self-Healing and Adapting

DTIC Science & Technology

2017-04-01

from statistical mechanics, combinatorics, boolean networks, and numerical simulations, and inspired by design principles from biological networks, we... principles for self-healing networks, and applications, and construct an all-possible-paths model for network adaptation. 2015-11-16 UNIT CONVERSION...combinatorics, boolean networks, and numerical simulations, and inspired by design principles from biological networks, we will undertake the fol

Airship logistics: The LTA vehicle; a total cargo system

NASA Technical Reports Server (NTRS)

Hackney, L. R. M.

1975-01-01

Design considerations for logistics are dealt with as they pertain to the large rigid LTA vehicle as either a commercial or military cargo carrier. Pertinent factors discussed are: (1) the basic mission; (2) types of payload; (3) the payload space in regards to configuration and sizing, its capacity, and its loadability. A logistic capability comparison of selected cargo airships versus jumbo jets is also made.

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…

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.

Accounting for Epistemic Uncertainty in Mission Supportability Assessment: A Necessary Step in Understanding Risk and Logistics Requirements

NASA Technical Reports Server (NTRS)

Owens, Andrew; De Weck, Olivier L.; Stromgren, Chel; Goodliff, Kandyce; Cirillo, William

2017-01-01

Future crewed missions to Mars present a maintenance logistics challenge that is unprecedented in human spaceflight. Mission endurance – defined as the time between resupply opportunities – will be significantly longer than previous missions, and therefore logistics planning horizons are longer and the impact of uncertainty is magnified. Maintenance logistics forecasting typically assumes that component failure rates are deterministically known and uses them to represent aleatory uncertainty, or uncertainty that is inherent to the process being examined. However, failure rates cannot be directly measured; rather, they are estimated based on similarity to other components or statistical analysis of observed failures. As a result, epistemic uncertainty – that is, uncertainty in knowledge of the process – exists in failure rate estimates that must be accounted for. Analyses that neglect epistemic uncertainty tend to significantly underestimate risk. Epistemic uncertainty can be reduced via operational experience; for example, the International Space Station (ISS) failure rate estimates are refined using a Bayesian update process. However, design changes may re-introduce epistemic uncertainty. Thus, there is a tradeoff between changing a design to reduce failure rates and operating a fixed design to reduce uncertainty. This paper examines the impact of epistemic uncertainty on maintenance logistics requirements for future Mars missions, using data from the ISS Environmental Control and Life Support System (ECLS) as a baseline for a case study. Sensitivity analyses are performed to investigate the impact of variations in failure rate estimates and epistemic uncertainty on spares mass. The results of these analyses and their implications for future system design and mission planning are discussed.

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.

Navy CALS Vision. Draft 2.0. Volume 25

DOT National Transportation Integrated Search

1990-10-01

Computer-aided Acquisition and Logistic Support (CALS) is a joint initiative between industry and the Department of Defense (DoD) that is targeted at: (1) Improving designs for weapon systems; (2) Reducing both acquisition and logistic support costs ...

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...

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 .

Towards a Framework for Evolvable Network Design

NASA Astrophysics Data System (ADS)

Hassan, Hoda; Eltarras, Ramy; Eltoweissy, Mohamed

The layered Internet architecture that had long guided network design and protocol engineering was an “interconnection architecture” defining a framework for interconnecting networks rather than a model for generic network structuring and engineering. We claim that the approach of abstracting the network in terms of an internetwork hinders the thorough understanding of the network salient characteristics and emergent behavior resulting in impeding design evolution required to address extreme scale, heterogeneity, and complexity. This paper reports on our work in progress that aims to: 1) Investigate the problem space in terms of the factors and decisions that influenced the design and development of computer networks; 2) Sketch the core principles for designing complex computer networks; and 3) Propose a model and related framework for building evolvable, adaptable and self organizing networks We will adopt a bottom up strategy primarily focusing on the building unit of the network model, which we call the “network cell”. The model is inspired by natural complex systems. A network cell is intrinsically capable of specialization, adaptation and evolution. Subsequently, we propose CellNet; a framework for evolvable network design. We outline scenarios for using the CellNet framework to enhance legacy Internet protocol stack.

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1997-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Design of neural networks for fast convergence and accuracy: dynamics and control.

PubMed

Maghami, P G; Sparks, D R

2000-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

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.

Resource constrained design of artificial neural networks using comparator neural network

NASA Technical Reports Server (NTRS)

Wah, Benjamin W.; Karnik, Tanay S.

1992-01-01

We present a systematic design method executed under resource constraints for automating the design of artificial neural networks using the back error propagation algorithm. Our system aims at finding the best possible configuration for solving the given application with proper tradeoff between the training time and the network complexity. The design of such a system is hampered by three related problems. First, there are infinitely many possible network configurations, each may take an exceedingly long time to train; hence, it is impossible to enumerate and train all of them to completion within fixed time, space, and resource constraints. Second, expert knowledge on predicting good network configurations is heuristic in nature and is application dependent, rendering it difficult to characterize fully in the design process. A learning procedure that refines this knowledge based on examples on training neural networks for various applications is, therefore, essential. Third, the objective of the network to be designed is ill-defined, as it is based on a subjective tradeoff between the training time and the network cost. A design process that proposes alternate configurations under different cost-performance tradeoff is important. We have developed a Design System which schedules the available time, divided into quanta, for testing alternative network configurations. Its goal is to select/generate and test alternative network configurations in each quantum, and find the best network when time is expended. Since time is limited, a dynamic schedule that determines the network configuration to be tested in each quantum is developed. The schedule is based on relative comparison of predicted training times of alternative network configurations using comparator network paradigm. The comparator network has been trained to compare training times for a large variety of traces of TSSE-versus-time collected during back-propagation learning of various applications.

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).

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.

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...

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…

42 CFR 405.2110 - Designation of ESRD networks.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Designation of ESRD networks. 405.2110 Section 405... End-Stage Renal Disease (ESRD) Services § 405.2110 Designation of ESRD networks. CMS designated ESRD networks in which the approved ESRD facilities collectively provide the necessary care for ESRD patients...

42 CFR 405.2110 - Designation of ESRD networks.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Designation of ESRD networks. 405.2110 Section 405... End-Stage Renal Disease (ESRD) Services § 405.2110 Designation of ESRD networks. CMS designated ESRD networks in which the approved ESRD facilities collectively provide the necessary care for ESRD patients...

A Review of Strategic Mobility Models and Analysis

DTIC Science & Technology

1991-01-01

Logistics Directorate of the Joint Staff, (JS-J-4) specifically by the Studies , Concepts, and Analysis Division (SCAD), which conducts long-range...their analysis objec- tives. This study was designed to assist the Logistics Directorate of the Joint Staff (JS/J-4) to understand and improve the...This study concentrated on resource planning, which is the type of planning performed by the Logistics Directorate’s Studies , Concepts, and Analysis

Research in network management techniques for tactical data communications networks

NASA Astrophysics Data System (ADS)

Boorstyn, R.; Kershenbaum, A.; Maglaris, B.; Sarachik, P.

1982-09-01

This is the final technical report for work performed on network management techniques for tactical data networks. It includes all technical papers that have been published during the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques, and local area networks.

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

PubMed

Golas, Sara Bersche; Shibahara, Takuma; Agboola, Stephen; Otaki, Hiroko; Sato, Jumpei; Nakae, Tatsuya; Hisamitsu, Toru; Kojima, Go; Felsted, Jennifer; Kakarmath, Sujay; Kvedar, Joseph; Jethwani, Kamal

2018-06-22

Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission. We used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system. Data from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital. Deep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

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.

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.

Passive Thermal Design Approach for the Space Communications and Navigation (SCaN) Testbed Experiment on the International Space Station (ISS)

NASA Technical Reports Server (NTRS)

Siamidis, John; Yuko, Jim

2014-01-01

The Space Communications and Navigation (SCaN) Program Office at NASA Headquarters oversees all of NASAs space communications activities. SCaN manages and directs the ground-based facilities and services provided by the Deep Space Network (DSN), Near Earth Network (NEN), and the Space Network (SN). Through the SCaN Program Office, NASA GRC developed a Software Defined Radio (SDR) testbed experiment (SCaN testbed experiment) for use on the International Space Station (ISS). It is comprised of three different SDR radios, the Jet Propulsion Laboratory (JPL) radio, Harris Corporation radio, and the General Dynamics Corporation radio. The SCaN testbed experiment provides an on-orbit, adaptable, SDR Space Telecommunications Radio System (STRS) - based facility to conduct a suite of experiments to advance the Software Defined Radio, Space Telecommunications Radio Systems (STRS) standards, reduce risk (Technology Readiness Level (TRL) advancement) for candidate Constellation future space flight hardware software, and demonstrate space communication links critical to future NASA exploration missions. The SCaN testbed project provides NASA, industry, other Government agencies, and academic partners the opportunity to develop and field communications, navigation, and networking technologies in the laboratory and space environment based on reconfigurable, software defined radio platforms and the STRS Architecture.The SCaN testbed is resident on the P3 Express Logistics Carrier (ELC) on the exterior truss of the International Space Station (ISS). The SCaN testbed payload launched on the Japanese Aerospace Exploration Agency (JAXA) H-II Transfer Vehicle (HTV) and was installed on the ISS P3 ELC located on the inboard RAM P3 site. The daily operations and testing are managed out of NASA GRC in the Telescience Support Center (TSC).

Study of earthquakes using a borehole seismic network at Koyna, India

NASA Astrophysics Data System (ADS)

Gupta, Harsh; Satyanarayana, Hari VS; Shashidhar, Dodla; Mallika, Kothamasu; Ranjan Mahato, Chitta; Shankar Maity, Bhavani

2017-04-01

Koyna, located near the west coast of India, is a classical site of artificial water reservoir triggered earthquakes. Triggered earthquakes started soon after the impoundment of the Koyna Dam in 1962. The activity has continued till now including the largest triggered earthquake of M 6.3 in 1967; 22 earthquakes of M ≥ 5 and several thousands smaller earthquakes. The latest significant earthquake of ML 3.7 occurred on 24th November 2016. In spite of having a network of 23 broad band 3-component seismic stations in the near vicinity of the Koyna earthquake zone, locations of earthquakes had errors of 1 km. The main reason was the presence of 1 km thick very heterogeneous Deccan Traps cover that introduced noise and locations could not be improved. To improve the accuracy of location of earthquakes, a unique network of eight borehole seismic stations surrounding the seismicity was designed. Six of these have been installed at depths varying from 981 m to 1522 m during 2015 and 2016, well below the Deccan Traps cover. During 2016 a total of 2100 earthquakes were located. There has been a significant improvement in the location of earthquakes and the absolute errors of location have come down to ± 300 m. All earthquakes of ML ≥ 0.5 are now located, compared to ML ≥1.0 earlier. Based on seismicity and logistics, a block of 2 km x 2 km area has been chosen for the 3 km deep pilot borehole. The installation of the borehole seismic network has further elucidated the correspondence between rate of water loading/unloading the reservoir and triggered seismicity.

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.

Design framework for entanglement-distribution switching networks

NASA Astrophysics Data System (ADS)

Drost, Robert J.; Brodsky, Michael

2016-09-01

The distribution of quantum entanglement appears to be an important component of applications of quantum communications and networks. The ability to centralize the sourcing of entanglement in a quantum network can provide for improved efficiency and enable a variety of network structures. A necessary feature of an entanglement-sourcing network node comprising several sources of entangled photons is the ability to reconfigurably route the generated pairs of photons to network neighbors depending on the desired entanglement sharing of the network users at a given time. One approach to such routing is the use of a photonic switching network. The requirements for an entanglement distribution switching network are less restrictive than for typical conventional applications, leading to design freedom that can be leveraged to optimize additional criteria. In this paper, we present a mathematical framework defining the requirements of an entanglement-distribution switching network. We then consider the design of such a switching network using a number of 2 × 2 crossbar switches, addressing the interconnection of these switches and efficient routing algorithms. In particular, we define a worst-case loss metric and consider 6 × 6, 8 × 8, and 10 × 10 network designs that optimize both this metric and the number of crossbar switches composing the network. We pay particular attention to the 10 × 10 network, detailing novel results proving the optimality of the proposed design. These optimized network designs have great potential for use in practical quantum networks, thus advancing the concept of quantum networks toward reality.

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.

Effects of road network on diversiform forest cover changes in the highest coverage region in China: An analysis of sampling strategies.

PubMed

Hu, Xisheng; Wu, Zhilong; Wu, Chengzhen; Ye, Limin; Lan, Chaofeng; Tang, Kun; Xu, Lu; Qiu, Rongzu

2016-09-15

Forest cover changes are of global concern due to their roles in global warming and biodiversity. However, many previous studies have ignored the fact that forest loss and forest gain are different processes that may respond to distinct factors by stressing forest loss more than gain or viewing forest cover change as a whole. It behooves us to carefully examine the patterns and drivers of the change by subdividing it into several categories. Our study includes areas of forest loss (4.8% of the study area), forest gain (1.3% of the study area) and forest loss and gain (2.0% of the study area) from 2000 to 2012 in Fujian Province, China. In the study area, approximately 65% and 90% of these changes occurred within 2000m of the nearest road and under road densities of 0.6km/km(2), respectively. We compared two sampling techniques (systematic sampling and random sampling) and four intensities for each technique to investigate the driving patterns underlying the changes using multinomial logistic regression. The results indicated the lack of pronounced differences in the regressions between the two sampling designs, although the sample size had a great impact on the regression outcome. The application of multi-model inference indicated that the low level road density had a negative significant association with forest loss and forest loss and gain, the expressway density had a positive significant impact on forest loss, and the road network was insignificantly related to forest gain. The model including socioeconomic and biophysical variables illuminated potentially different predictors of the different forest change categories. Moreover, the multiple comparisons tested by Fisher's least significant difference (LSD) were a good compensation for the multinomial logistic model to enrich the interpretation of the regression results. Copyright © 2016 Elsevier B.V. All rights reserved.

What is different about workers' compensation patients? Socioeconomic predictors of baseline disability status among patients with lumbar radiculopathy.

PubMed

Atlas, Steven J; Tosteson, Tor D; Hanscom, Brett; Blood, Emily A; Pransky, Glenn S; Abdu, William A; Andersson, Gunnar B; Weinstein, James N

2007-08-15

Combined analysis of 2 prospective clinical studies. To identify socioeconomic characteristics associated with workers' compensation in patients with an intervertebral disc herniation (IDH) or spinal stenosis (SpS). Few studies have compared socioeconomic differences between those receiving or not receiving workers' compensation with the same underlying clinical conditions. Patients were identified from the Spine Patient Outcomes Research Trial (SPORT) and the National Spine Network (NSN) practice-based outcomes study. Patients with IDH and SpS within NSN were identified satisfying SPORT eligibility criteria. Information on disability and work status at baseline evaluation was used to categorize patients into 3 groups: workers' compensation, other disability compensation, or work-eligible controls. Enrollment rates of patients with disability in a clinical efficacy trial (SPORT) and practice-based network (NSN) were compared. Independent socioeconomic predictors of baseline workers' compensation status were identified in multivariate logistic regression models controlling for clinical condition, study cohort, and initial treatment designation. Among 3759 eligible patients (1480 in SPORT and 2279 in NSN), 564 (15%) were receiving workers' compensation, 317 (8%) were receiving other disability compensation, and 2878 (77%) were controls. Patients receiving workers' compensation were less common in SPORT than NSN (9.2% vs. 18.8%, P < 0.001), but patients receiving other disability compensation were similarly represented (8.9% vs. 7.7%, P = 0.19). In univariate analyses, many socioeconomic characteristics significantly differed according to baseline workers' compensation status. In multiple logistic regression analyses, gender, educational level, work characteristics, legal action, and expectations about ability to work without surgery were independently associated with receiving workers' compensation. Clinical trials involving conditions commonly seen in patients with workers' compensation may need special efforts to ensure adequate representation. Socioeconomic characteristics markedly differed between patients receiving and not receiving workers' compensation. Identifying the independent effects of workers' compensation on outcomes will require controlling for these baseline characteristics and other clinical features associated with disability status.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

Networking for Teacher Learning: Toward a Theory of Effective Design.

ERIC Educational Resources Information Center

McDonald, Joseph P.; Klein, Emily J.

2003-01-01

Examines how teacher networks design for teacher learning, describing several dynamic tensions inherent in the designs of a sample of teacher networks and assessing the relationships of these tensions to teacher learning. The paper illustrates these design concepts with reference to the work of seven networks that aim to revamp teacher' knowledge…

Study on store-space assignment based on logistic AGV in e-commerce goods to person picking pattern

NASA Astrophysics Data System (ADS)

Xu, Lijuan; Zhu, Jie

2017-10-01

This paper studied on the store-space assignment based on logistic AGV in E-commerce goods to person picking pattern, and established the store-space assignment model based on the lowest picking cost, and design for store-space assignment algorithm after the cluster analysis based on similarity coefficient. And then through the example analysis, compared the picking cost between store-space assignment algorithm this paper design and according to item number and storage according to ABC classification allocation, and verified the effectiveness of the design of the store-space assignment algorithm.

Using Neural Networks in the Mapping of Mixed Discrete/Continuous Design Spaces With Application to Structural Design

DTIC Science & Technology

1994-02-01

desired that the problem to which the design space mapping techniques were applied be easily analyzed, yet provide a design space with realistic complexity...consistent fully stressed solution. 3 DESIGN SPACE MAPPING In order to reduce the computational expense required to optimize design spaces, neural networks...employed in this study. Some of the issues involved in using neural networks to do design space mapping are how to configure the neural network, how much

Research in Network Management Techniques for Tactical Data Communications Network.

DTIC Science & Technology

1982-09-01

the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques...contro!lers are designed to perform their limited tasks optimally. For the dynamic routing problem considered here, the local controllers are node...feedback to finding in optimum stead-o-state routing (static strategies) under non - control which can be easily implemented in real time. congested

Toward a framework for computer-mediated collaborative design in medical informatics.

PubMed

Patel, V L; Kaufman, D R; Allen, V G; Shortliffe, E H; Cimino, J J; Greenes, R A

1999-09-01

The development and implementation of enabling tools and methods that provide ready access to knowledge and information are among the central goals of medical informatics. The need for multi-institutional collaboration in the development of such tools and methods is increasingly being recognized. Collaboration involves communication, which typically involves individuals who work together at the same location. With the evolution of electronic modalities for communication, we seek to understand the role that such technologies can play in supporting collaboration, especially when the participants are geographically separated. Using the InterMed Collaboratory as a subject of study, we have analyzed their activities as an exercise in computer- and network-mediated collaborative design. We report on the cognitive, sociocultural, and logistical issues encountered when scientists from diverse organizations and backgrounds use communications technologies while designing and implementing shared products. Results demonstrate that it is important to match carefully the content with the mode of communication, identifying, for example, suitable uses of E-mail, conference calls, and face-to-face meetings. The special role of leaders in guiding and facilitating the group activities can also be seen, regardless of the communication setting in which the interactions occur. Most important is the proper use of technology to support the evolution of a shared vision of group goals and methods, an element that is clearly necessary before successful collaborative designs can proceed.

The challenge of logistics facilities development

NASA Technical Reports Server (NTRS)

Davis, James R.

1987-01-01

The paper discusses the experiences of a group of engineers and logisticians at John F. Kennedy Space center in the design, construction and activation of a consolidated logistics facility for support of Space Transportation System ground operations and maintenance. The planning, methodology and processes are covered, with emphasis placed on unique aspects and lessons learned. The project utilized a progressive design, baseline and build concept for each phase of construction, with the Government exercising funding and configuration oversight.

Global Spent Fuel Logistics Systems Study (GSFLS). Volume 3A. GSFLS technical analysis (appendix). Interim report

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

Kriger, A.

1978-01-31

This report is a part of the interim report documentation for the Global Spent Fuel Logistics System (GSFLS) study. The technical and financial considerations underlying a global spent fuel logistics systems have been studied and are reported. The Pacific Basin is used as a model throughout this report; however the stated methodology and, in many cases, considerations and conclusions are applicable to other global regions. Spent fuel discharge profiles for Pacific Basin Countries were used to determine the technical systems requirements for alternative concepts. Functional analyses and flows were generated to define both system design requirements and logistics parameters. Amore » technology review was made to ascertain the state-of-the-art of relevant GSFLS technical systems. Modular GSFLS facility designs were developed using the information generated from the functional analysis and technology review. The modular facility designs were used as a basis for siting and cost estimates for various GSFLS alternatives. Various GSFLS concepts were analyzed from a financial and economic perspective in order to provide total concepts costs and ascertain financial and economic sensitivities to key GSFLS variations. Results of the study include quantification of GSFLS facility and hardware requirements; drawings of relevant GSFLS facility designs; system cost estimates; financial reports - including user service charges; and comparative analyses of various GSFLS alternatives.« less

Principles of Biomimetic Vascular Network Design Applied to a Tissue-Engineered Liver Scaffold

PubMed Central

Hoganson, David M.; Pryor, Howard I.; Spool, Ira D.; Burns, Owen H.; Gilmore, J. Randall

2010-01-01

Branched vascular networks are a central component of scaffold architecture for solid organ tissue engineering. In this work, seven biomimetic principles were established as the major guiding technical design considerations of a branched vascular network for a tissue-engineered scaffold. These biomimetic design principles were applied to a branched radial architecture to develop a liver-specific vascular network. Iterative design changes and computational fluid dynamic analysis were used to optimize the network before mold manufacturing. The vascular network mold was created using a new mold technique that achieves a 1:1 aspect ratio for all channels. In vitro blood flow testing confirmed the physiologic hemodynamics of the network as predicted by computational fluid dynamic analysis. These results indicate that this biomimetic liver vascular network design will provide a foundation for developing complex vascular networks for solid organ tissue engineering that achieve physiologic blood flow. PMID:20001254

Principles of biomimetic vascular network design applied to a tissue-engineered liver scaffold.

PubMed

Hoganson, David M; Pryor, Howard I; Spool, Ira D; Burns, Owen H; Gilmore, J Randall; Vacanti, Joseph P

2010-05-01

Branched vascular networks are a central component of scaffold architecture for solid organ tissue engineering. In this work, seven biomimetic principles were established as the major guiding technical design considerations of a branched vascular network for a tissue-engineered scaffold. These biomimetic design principles were applied to a branched radial architecture to develop a liver-specific vascular network. Iterative design changes and computational fluid dynamic analysis were used to optimize the network before mold manufacturing. The vascular network mold was created using a new mold technique that achieves a 1:1 aspect ratio for all channels. In vitro blood flow testing confirmed the physiologic hemodynamics of the network as predicted by computational fluid dynamic analysis. These results indicate that this biomimetic liver vascular network design will provide a foundation for developing complex vascular networks for solid organ tissue engineering that achieve physiologic blood flow.

The effects of designation and volume of neonatal care on mortality and morbidity outcomes of very preterm infants in England: retrospective population-based cohort study.

PubMed

Watson, S I; Arulampalam, W; Petrou, S; Marlow, N; Morgan, A S; Draper, E S; Santhakumaran, S; Modi, N

2014-07-07

To examine the effects of designation and volume of neonatal care at the hospital of birth on mortality and morbidity outcomes in very preterm infants in a managed clinical network setting. A retrospective, population-based analysis of operational clinical data using adjusted logistic regression and instrumental variables (IV) analyses. 165 National Health Service neonatal units in England contributing data to the National Neonatal Research Database at the Neonatal Data Analysis Unit and participating in the Neonatal Economic, Staffing and Clinical Outcomes Project. 20 554 infants born at <33 weeks completed gestation (17 995 born at 27-32 weeks; 2559 born at <27 weeks), admitted to neonatal care and either discharged or died, over the period 1 January 2009-31 December 2011. Tertiary designation or high-volume neonatal care at the hospital of birth. Neonatal mortality, any in-hospital mortality, surgery for necrotising enterocolitis, surgery for retinopathy of prematurity, bronchopulmonary dysplasia and postmenstrual age at discharge. Infants born at <33 weeks gestation and admitted to a high-volume neonatal unit at the hospital of birth were at reduced odds of neonatal mortality (IV regression odds ratio (OR) 0.70, 95% CI 0.53 to 0.92) and any in-hospital mortality (IV regression OR 0.68, 95% CI 0.54 to 0.85). The effect of volume on any in-hospital mortality was most acute among infants born at <27 weeks gestation (IV regression OR 0.51, 95% CI 0.33 to 0.79). A negative association between tertiary-level unit designation and mortality was also observed with adjusted logistic regression for infants born at <27 weeks gestation. High-volume neonatal care provided at the hospital of birth may protect against in-hospital mortality in very preterm infants. Future developments of neonatal services should promote delivery of very preterm infants at hospitals with high-volume neonatal units. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

48 CFR 7.104 - General procedures.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., fiscal, legal, and technical personnel. If contract performance is to be in a designated operational area... shall review the plan and, if appropriate, revise it. (b) Requirements and logistics personnel should... planner should consult with requirements and logistics personnel who determine type, quality, quantity...

48 CFR 7.104 - General procedures.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., fiscal, legal, and technical personnel. If contract performance is to be in a designated operational area... shall review the plan and, if appropriate, revise it. (b) Requirements and logistics personnel should... planner should consult with requirements and logistics personnel who determine type, quality, quantity...

48 CFR 7.104 - General procedures.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., fiscal, legal, and technical personnel. If contract performance is to be in a designated operational area... shall review the plan and, if appropriate, revise it. (b) Requirements and logistics personnel should... planner should consult with requirements and logistics personnel who determine type, quality, quantity...

48 CFR 7.104 - General procedures.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., fiscal, legal, and technical personnel. If contract performance is to be in a designated operational area... shall review the plan and, if appropriate, revise it. (b) Requirements and logistics personnel should... planner should consult with requirements and logistics personnel who determine type, quality, quantity...

48 CFR 7.104 - General procedures.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., fiscal, legal, and technical personnel. If contract performance is to be in a designated operational area... shall review the plan and, if appropriate, revise it. (b) Requirements and logistics personnel should... planner should consult with requirements and logistics personnel who determine type, quality, quantity...

The positive role of social networks and social networking technology in the condom-using behaviors of homeless young people.

PubMed

Rice, Eric

2010-01-01

To examine the impact of condom-using peers in the social networks of homeless young people, differences in behaviors were assessed based on the social location of ties (home-based vs. street-based) and how those ties are maintained (face-to-face vs. via social networking technology). "Ego-centric" social network data were collected from 103 currently sexually active homeless young people aged 16-26 years in Los Angeles, California. Associations between condom use and the condom-using behaviors of social network influences were assessed using standard logistic regression. About 52% of respondents had a street-based peer who was a condom user. Having such a peer was associated with a 70% reduction in the odds of having unprotected sex at last intercourse. About 22% of respondents had a condom-using, home-based peer with whom they communicated only via social networking technology. Having such a peer was associated with a 90% reduction in risky sexual behavior and a 3.5 times increase in safer sex behavior. The study revealed several implications for new human immunodeficiency virus-prevention interventions that mobilize these networks and social networking technologies.

The influence of self-exempting beliefs and social networks on daily smoking: a mediation relationship explored.

PubMed

Yang, Xiaozhao Y; Kelly, Brian C; Yang, Tingzhong

2014-09-01

The decision to initiate, maintain, or quit cigarette smoking is structured by both social networks and health beliefs. Self-exempting beliefs affect people's decisions in favor of a behavior even when they recognize the harm associated with it. This study incorporated the literatures on social networks and self-exempting beliefs to study the problem of daily smoking by exploring their mediatory relationships and the mechanisms of how smoking behavior is developed and maintained. Specifically, this article hypothesizes that social networks affect daily smoking directly as well as indirectly by facilitating the formation of self-exempting beliefs. The sample comes from urban male residents in Hangzhou, China randomly selected and interviewed through multistage sampling in 2011. Using binary mediation analysis with logistic regression to test the hypotheses, the authors found that (a) daily smoking is associated with having smokers in several social network arenas and (b) self-exempting beliefs about smoking mediate the association between coworker network and daily smoking, but not for family network and friend network. The role of social network at work place in the creation and maintenance of self-exempting beliefs should be considered by policymakers, prevention experts, and interventionists.

The environmental control and life-support system for a lunar base: What drives its design

NASA Technical Reports Server (NTRS)

Hypes, Warren D.; Hall, John B., Jr.

1992-01-01

The purpose of this paper is to identify and briefly discuss some of the ground rules and mission scenario details that become drivers of the environmental control and life support (ECLS) system design and of the logistics related to the design. This paper is written for mission planners and non-ECLS system engineers to inform them of the details that will be important to the ECLS engineer when the design phase is reached. In addition, examples illustrate the impact of some selected mission characteristics on the logistics associated with ECLS systems. The last section of this paper focuses on the ECLS system technology development sequence and highlights specific portions that need emphasis.

Multipurpose Cargo Transfer Bag

NASA Technical Reports Server (NTRS)

Broyan, James; Baccus, Shelley

2014-01-01

The Logistics Reduction (LR) project within the Advanced Exploration Systems (AES) program is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) have been designed such that they can serve the same purpose as a Cargo Transfer Bag, the suitcase-shaped common logistics carrying bag for Shuttle and the International Space Station. After use as a cargo carrier, a regular CTB becomes trash, whereas the MCTB can be unzipped, unsnapped, and unfolded to be reused. Reuse ideas that have been investigated include partitions, crew quarters, solar radiation storm shelters, acoustic blankets, and forward osmosis water processing.

Analysis of logistic distribution performance of good supply from PT. Mentari Trans Nusantara distribution center to branches using Smart PLS 3.0

NASA Astrophysics Data System (ADS)

Endrawati, Titin; Siregar, M. Tirtana

2018-03-01

PT Mentari Trans Nusantara is a company engaged in the distribution of goods from the manufacture of the product to the distributor branch of the customer so that the product distribution must be controlled directly from the PT Mentari Trans Nusantara Center for faster delivery process. Problems often occur on the expedition company which in charge in sending the goods although it has quite extensive networking. The company is less control over logistics management. Meanwhile, logistics distribution management control policy will affect the company's performance in distributing products to customer distributor branches and managing product inventory in distribution center. PT Mentari Trans Nusantara is an expedition company which engaged in good delivery, including in Jakarta. Logistics management performance is very important due to its related to the supply of goods from the central activities to the branches based oncustomer demand. Supply chain management performance is obviously depends on the location of both the distribution center and branches, the smoothness of transportation in the distribution and the availability of the product in the distribution center to meet the demand in order to avoid losing sales. This study concluded that the company could be more efficient and effective in minimizing the risks of loses by improve its logistic management.

Design and implementation of interface units for high speed fiber optics local area networks and broadband integrated services digital networks

NASA Technical Reports Server (NTRS)

Tobagi, Fouad A.; Dalgic, Ismail; Pang, Joseph

1990-01-01

The design and implementation of interface units for high speed Fiber Optic Local Area Networks and Broadband Integrated Services Digital Networks are discussed. During the last years, a number of network adapters that are designed to support high speed communications have emerged. This approach to the design of a high speed network interface unit was to implement package processing functions in hardware, using VLSI technology. The VLSI hardware implementation of a buffer management unit, which is required in such architectures, is described.

Social support network characteristics and sexual risk taking among a racially/ethnically diverse sample of young, urban men who have sex with men

PubMed Central

Kapadia, F; Siconolfi, DE; Barton, S; Olivieri, B; Lombardo, L; Halkitis, PN

2013-01-01

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. PMID:23553346

The impact of tiered physician networks on patient choices.

PubMed

Sinaiko, Anna D; Rosenthal, Meredith B

2014-08-01

To assess whether patient choice of physician or health plan was affected by physician tier-rankings. Administrative claims and enrollment data on 171,581 nonelderly beneficiaries enrolled in Massachusetts Group Insurance Commission health plans that include a tiered physician network and who had an office visit with a tiered physician. We estimate the impact of tier-rankings on physician market share within a plan of new patients and on the percent of a physician's patients who switch to other physicians with fixed effects regression models. The effect of tiering on consumer plan choice is estimated using logistic regression and a pre-post study design. Physicians in the bottom (least-preferred) tier, particularly certain specialist physicians, had lower market share of new patient visits than physicians with higher tier-rankings. Patients whose physician was in the bottom tier were more likely to switch health plans. There was no effect of tier-ranking on patients switching away from physicians whom they have seen previously. The effect of tiering appears to be among patients who choose new physicians and at the lower end of the distribution of tiered physicians, rather than moving patients to the "best" performers. These findings suggest strong loyalty of patients to physicians more likely to be considered their personal doctor. © Health Research and Educational Trust.

Association of school social networks' influence and mass media factors with cigarette smoking among asthmatic students.

PubMed

Kanamori, Mariano; Beck, Kenneth H; Carter-Pokras, Olivia

2015-03-01

Around 10% of adolescent students under 18 years have current asthma. Asthmatic adolescents smoke as much or more than non-asthmatic adolescents. We explored the association between exposure to mass media and social networks' influence with asthmatic student smoking, and variations of these exposures by sex. This study included 9755 asthmatic and 38,487 non-asthmatic middle and high school students. Secondary data analysis incorporated the complex sample design; and univariate, bivariate, and logistic regression statistics. Asthmatic students had greater odds of smoking than non-asthmatic students. Asthmatic female students were more likely than asthmatic male students to have been exposed to secondhand smoke in rooms or cars and to smoking actors, but less likely to associate smoking with intent to wear tobacco-marketing products, or with looking cool/fitting in. Asthmatic male and female students, who have smoking friends, were exposed to secondhand smoke in rooms (only girls) or cars, intended to smoke if best friends offered cigarettes, or received/bought tobacco marketing products had greater odds of smoking than other asthmatic students. The observed associations suggest the need for general interventions to reduce middle and high school students' cigarette smoking as well as targeted interventions for asthmatic adolescent students. © 2015, American School Health Association.

Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges

PubMed Central

Li, Shuangyan; Li, Xialian; Zhang, Dezhi; Zhou, Lingyun

2017-01-01

This study develops an optimization model to integrate facility location and inventory control for a three-level distribution network consisting of a supplier, multiple distribution centers (DCs), and multiple retailers. The integrated model addressed in this study simultaneously determines three types of decisions: (1) facility location (optimal number, location, and size of DCs); (2) allocation (assignment of suppliers to located DCs and retailers to located DCs, and corresponding optimal transport mode choices); and (3) inventory control decisions on order quantities, reorder points, and amount of safety stock at each retailer and opened DC. A mixed-integer programming model is presented, which considers the carbon emission taxes, multiple transport modes, stochastic demand, and replenishment lead time. The goal is to minimize the total cost, which covers the fixed costs of logistics facilities, inventory, transportation, and CO2 emission tax charges. The aforementioned optimal model was solved using commercial software LINGO 11. A numerical example is provided to illustrate the applications of the proposed model. The findings show that carbon emission taxes can significantly affect the supply chain structure, inventory level, and carbon emission reduction levels. The delay rate directly affects the replenishment decision of a retailer. PMID:28103246

Cyberbullying: a 21st Century Health Care Phenomenon.

PubMed

Carter, Jemica M; Wilson, Feleta L

2015-01-01

This study examined bullying and cyberbullying prevalence among 367 adolescents 10 to 18 years of age who were attending schools and community organizations in suburban and urban neighborhoods in the Midwest United States. The correlational design investigated adolescents' daily use of technology that could be used to cyberbully peers, such as cell phones, computers, email, and the Internet. Results showed that 30% of participants had been bullied during school, and 17% had been cyberbullied, with online social networking sites the most common media employed (68%). The majority of participants owned or had access to computers (92%), email accounts (88%), social networking accounts (e.g., Facebook or MySpace) (82%), and cell phones (79%). Daily technology use included an average of two hours on a computer and a median of 71 text messages per day. Logistic regression analysis revealed no significant differences in bullying or cyberbullying prevalence based on location (urban or suburban) or demographic characteristics. Given the substantial presence of cyberbullying and the increase in technology use among adolescents in the 21st century, nurses need knowledge of the phenomenon to plan assessments in clinical practice. Early identification and assessment of cyberbullying victims and perpetrators, and development and implementation of effective interventions are needed to reduce this form of bullying among adolescents.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Kim, Y.; Hwang, T.; Vose, J. M.; Martin, K. L.; Band, L. E.

2016-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Keum, J.; Coulibaly, P. D.

2017-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Carter, David; Wetzel, Scott

2000-01-01

The NASA SLR Operational Center is responsible for: 1) NASA SLR network control, sustaining engineering, and logistics; 2) ILRS mission operations; and 3) ILRS and NASA SLR data operations. NASA SLR network control and sustaining engineering tasks include technical support, daily system performance monitoring, system scheduling, operator training, station status reporting, system relocation, logistics and support of the ILRS Networks and Engineering Working Group. These activities ensure the NASA SLR systems are meeting ILRS and NASA mission support requirements. ILRS mission operations tasks include mission planning, mission analysis, mission coordination, development of mission support plans, and support of the ILRS Missions Working Group. These activities ensure than new mission and campaign requirements are coordinated with the ILRS. Global Normal Points (NP) data, NASA SLR FullRate (FR) data, and satellite predictions are managed as part of data operations. Part of this operation includes supporting the ILRS Data Formats and Procedures Working Group. Global NP data operations consist of receipt, format and data integrity verification, archiving and merging. This activity culminates in the daily electronic transmission of NP files to the CDDIS. Currently of all these functions are automated. However, to ensure the timely and accurate flow of data, regular monitoring and maintenance of the operational software systems, computer systems and computer networking are performed. Tracking statistics between the stations and the data centers are compared periodically to eliminate lost data. Future activities in this area include sub-daily (i.e., hourly) NP data management, more stringent data integrity tests, and automatic station notification of format and data integrity issues.

Integrating biology, field logistics, and simulations to optimize parameter estimation for imperiled species

USGS Publications Warehouse

Lanier, Wendy E.; Bailey, Larissa L.; Muths, Erin L.

2016-01-01

Conservation of imperiled species often requires knowledge of vital rates and population dynamics. However, these can be difficult to estimate for rare species and small populations. This problem is further exacerbated when individuals are not available for detection during some surveys due to limited access, delaying surveys and creating mismatches between the breeding behavior and survey timing. Here we use simulations to explore the impacts of this issue using four hypothetical boreal toad (Anaxyrus boreas boreas) populations, representing combinations of logistical access (accessible, inaccessible) and breeding behavior (synchronous, asynchronous). We examine the bias and precision of survival and breeding probability estimates generated by survey designs that differ in effort and timing for these populations. Our findings indicate that the logistical access of a site and mismatch between the breeding behavior and survey design can greatly limit the ability to yield accurate and precise estimates of survival and breeding probabilities. Simulations similar to what we have performed can help researchers determine an optimal survey design(s) for their system before initiating sampling efforts.

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

PubMed Central

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

2011-01-01

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

Social networks and alcohol use disorders: findings from a nationally representative sample

PubMed Central

Mowbray, Orion; Quinn, Adam; Cranford, James A.

2014-01-01

Background While some argue that social network ties of individuals with alcohol use disorders (AUD) are robust, there is evidence to suggest that individuals with AUDs have few social network ties, which are a known risk factor for health and wellness. Objectives Social network ties to friends, family, co-workers and communities of individuals are compared among individuals with a past-year diagnosis of alcohol dependence or alcohol abuse to individuals with no lifetime diagnosis of AUD. Method Respondents from Wave 2 of the National Epidemiologic Survey on Alcohol Related Conditions (NESARC) were assessed for the presence of past-year alcohol dependence or past-year alcohol abuse, social network ties, sociodemographics and clinical characteristics. Results Bivariate analyses showed that both social network size and social network diversity was significantly smaller among individuals with alcohol dependence, compared to individuals with alcohol abuse or no AUD. When social and clinical factors related to AUD status were controlled, multinomial logistic models showed that social network diversity remained a significant predictor of AUD status, while social network size did not differ among AUD groups. Conclusion Social networks of individuals with AUD may be different than individuals with no AUD, but this claim is dependent on specific AUD diagnosis and how social networks are measured. PMID:24405256

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

A robotic system for automation of logistics functions on the Space Station

NASA Technical Reports Server (NTRS)

Martin, J. C.; Purves, R. B.; Hosier, R. N.; Krein, B. A.

1988-01-01

Spacecraft inventory management is currently performed by the crew and as systems become more complex, increased crew time will be required to perform routine logistics activities. If future spacecraft are to function effectively as research labs and production facilities, the efficient use of crew time as a limited resource for performing mission functions must be employed. The use of automation and robotics technology, such as automated warehouse and materials handling functions, can free the crew from many logistics tasks and provide more efficient use of crew time. Design criteria for a Space Station Automated Logistics Inventory Management System is focused on through the design and demonstration of a mobile two armed terrestrial robot. The system functionally represents a 0 gravity automated inventory management system and the problems associated with operating in such an environment. Features of the system include automated storage and retrieval, item recognition, two armed robotic manipulation, and software control of all inventory item transitions and queries.

Link and Network Layers Design for Ultra-High-Speed Terahertz-Band Communications Networks

DTIC Science & Technology

2017-01-01

throughput, and identify the optimal parameter values for their design (Sec. 6.2.3). Moreover, we validate and test the scheme with experimental data obtained...LINK AND NETWORK LAYERS DESIGN FOR ULTRA-HIGH- SPEED TERAHERTZ-BAND COMMUNICATIONS NETWORKS STATE UNIVERSITY OF NEW YORK (SUNY) AT BUFFALO JANUARY...TYPE FINAL TECHNICAL REPORT 3. DATES COVERED (From - To) FEB 2015 – SEP 2016 4. TITLE AND SUBTITLE LINK AND NETWORK LAYERS DESIGN FOR ULTRA-HIGH

Supply Chain Sustainability Analysis of Indirect Liquefaction of Blended Biomass to Produce High Octane Gasoline

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

Cai, Hao; Canter, Christina E.; Dunn, Jennifer B.

The Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) aims at developing and deploying technologies to transform renewable biomass resources into commercially viable, high-performance biofuels, bioproducts and biopower through public and private partnerships (DOE, 2015). BETO also performs a supply chain sustainability analysis (SCSA). This report describes the SCSA of the production of renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of lignocellulosic biomass. This SCSA was developed for the 2017 design case for feedstock logistics (INL, 2014) and for the 2022 target case for HOG production via IDL (Tan et al., 2015). The design includes advancements that aremore » likely and targeted to be achieved by 2017 for the feedstock logistics and 2022 for the IDL conversion process. The 2017 design case for feedstock logistics demonstrated a delivered feedstock cost of $80 per dry U.S. short ton by the year 2017 (INL, 2014). The 2022 design case for the conversion process, as modeled in Tan et al. (2015), uses the feedstock 2017 design case blend of biomass feedstocks consisting of pulpwood, wood residue, switchgrass, and construction and demolition waste (C&D) with performance properties consistent with a sole woody feedstock type (e.g., pine or poplar). The HOG SCSA case considers the 2017 feedstock design case (the blend) as well as individual feedstock cases separately as alternative scenarios when the feedstock blend ratio varies as a result of a change in feedstock availability. These scenarios could be viewed as bounding SCSA results because of distinctive requirements for energy and chemical inputs for the production and logistics of different components of the blend feedstocks.« less

Designing Industrial Networks Using Ecological Food Web Metrics.

PubMed

Layton, Astrid; Bras, Bert; Weissburg, Marc

2016-10-18

Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

78 FR 8686 - Establishment of the National Freight Network

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-06

... Network AGENCY: Federal Highway Administration (FHWA), DOT. ACTION: Notice. SUMMARY: This notice defines the planned process for the designation of the national freight network as required by Section 1115 of... the initial designation of the primary freight network, the designation of additional miles critical...

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…

Scaling and calibration of a core validation site for the soil moisture active passive mission

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated due to the logistics of installing a long term soil moisture monitoring network in an active landscape. It is more efficient to locate these stations along agricultural field boundaries, but unfortunately this oft...

Combat Ration Network for Technology Implementation. CORANET Demonstration Site: Results and Accomplishments

DTIC Science & Technology

2010-01-01

School of Enviromental and Biological Sciences New Brunswick, NJ 08903 FTR 214 Defense Logistics Agency 8725 John J. Kingsman Rd Fort Belvoir, VA...Precision Automation X Injection Mold 1100 Rack Stock America X Injection Mold 1400 Rack AllPax X Enviromental Chamber Model: 11-679-25C Fisher

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

Movement of Fuel Ashore: Storage, Capacity, Throughput, and Distribution Analysis

DTIC Science & Technology

2015-12-01

89  ix LIST OF FIGURES Figure 1.  Principles of Operational Maneuver from the Sea ........................... 7  Figure 2.  Compositing and...30  Table 2.  Force Mix Composition ...procedures, and force composition . Such alterations represent an acceptance of operational risk to buy down the foundational risk that the logistics network

Facilitating Collegial Exchange among Science Teachers: An Experiment in Computer-Based Conferencing. Technical Report 86-14.

ERIC Educational Resources Information Center

Katz, Mary Maxwell; And Others

Teacher isolation is a significant problem in the science teaching profession. Traditional inservice solutions are often plagued by logistical difficulties or occur too infrequently to build ongoing teacher networks. Educational Technology Center (ETC) researchers reasoned that computer-based conferencing might promote collegial exchange among…

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

Space Station logistic support by Aries

NASA Astrophysics Data System (ADS)

Cougnet, C.; Groepper, P.

1987-10-01

The architecture and functions of Aries, a low-cost expendable vehicle, are discussed. The Aries design is based on the Ariane 5 L5 and VEB. The major components of Aries are upgraded L5 and VEB and a payload adaptor; the design and operations of these components are described. The avionics and propulsion system for Aries are examined. Aries is to be employed for logistic support, assembly, and the placement of satellites. An example of a mission scenario and diagrams of Aries are provided.

Robust Network Design - Connectivity and Beyond

DTIC Science & Technology

2015-01-15

utilize a heterogeneous set of physical links (RF, Optical/Laser and SATCOM), for interconnecting a set of terrestrial, space and highly mobile airborne...design of mobility patterns of airborne platforms to provide stable operating conditions,  the design of networks that enable graceful performance...research effort, Airborne Network research was primarily directed towards Mobile Ad-hoc Networks (MANET). From our experience in design and

NASA Space Exploration Logistics Workshop Proceedings

NASA Technical Reports Server (NTRS)

deWeek, Oliver; Evans, William A.; Parrish, Joe; James, Sarah

2006-01-01

As NASA has embarked on a new Vision for Space Exploration, there is new energy and focus around the area of manned space exploration. These activities encompass the design of new vehicles such as the Crew Exploration Vehicle (CEV) and Crew Launch Vehicle (CLV) and the identification of commercial opportunities for space transportation services, as well as continued operations of the Space Shuttle and the International Space Station. Reaching the Moon and eventually Mars with a mix of both robotic and human explorers for short term missions is a formidable challenge in itself. How to achieve this in a safe, efficient and long-term sustainable way is yet another question. The challenge is not only one of vehicle design, launch, and operations but also one of space logistics. Oftentimes, logistical issues are not given enough consideration upfront, in relation to the large share of operating budgets they consume. In this context, a group of 54 experts in space logistics met for a two-day workshop to discuss the following key questions: 1. What is the current state-of the art in space logistics, in terms of architectures, concepts, technologies as well as enabling processes? 2. What are the main challenges for space logistics for future human exploration of the Moon and Mars, at the intersection of engineering and space operations? 3. What lessons can be drawn from past successes and failures in human space flight logistics? 4. What lessons and connections do we see from terrestrial analogies as well as activities in other areas, such as U.S. military logistics? 5. What key advances are required to enable long-term success in the context of a future interplanetary supply chain? These proceedings summarize the outcomes of the workshop, reference particular presentations, panels and breakout sessions, and record specific observations that should help guide future efforts.

Design, innovation, and rural creative places: Are the arts the cherry on top, or the secret sauce?

PubMed

Wojan, Timothy R; Nichols, Bonnie

2018-01-01

Creative class theory explains the positive relationship between the arts and commercial innovation as the mutual attraction of artists and other creative workers by an unobserved creative milieu. This study explores alternative theories for rural settings, by analyzing establishment-level survey data combined with data on the local arts scene. The study identifies the local contextual factors associated with a strong design orientation, and estimates the impact that a strong design orientation has on the local economy. Data on innovation and design come from a nationally representative sample of establishments in tradable industries. Latent class analysis allows identifying unobserved subpopulations comprised of establishments with different design and innovation orientations. Logistic regression allows estimating the association between an establishment's design orientation and local contextual factors. A quantile instrumental variable regression allows assessing the robustness of the logistic regression results with respect to endogeneity. An estimate of design orientation at the local level derived from the survey is used to examine variation in economic performance during the period of recovery from the Great Recession (2010-2014). Three distinct innovation (substantive, nominal, and non-innovators) and design orientations (design-integrated, "design last finish," and no systematic approach to design) are identified. Innovation- and design-intensive establishments were identified in both rural and urban areas. Rural design-integrated establishments tended to locate in counties with more highly educated workforces and containing at least one performing arts organization. A quantile instrumental variable regression confirmed that the logistic regression result is robust to endogeneity concerns. Finally, rural areas characterized by design-integrated establishments experienced faster growth in wages relative to rural areas characterized by establishments using no systematic approach to design.

Design, innovation, and rural creative places: Are the arts the cherry on top, or the secret sauce?

PubMed Central

Nichols, Bonnie

2018-01-01

Objective Creative class theory explains the positive relationship between the arts and commercial innovation as the mutual attraction of artists and other creative workers by an unobserved creative milieu. This study explores alternative theories for rural settings, by analyzing establishment-level survey data combined with data on the local arts scene. The study identifies the local contextual factors associated with a strong design orientation, and estimates the impact that a strong design orientation has on the local economy. Method Data on innovation and design come from a nationally representative sample of establishments in tradable industries. Latent class analysis allows identifying unobserved subpopulations comprised of establishments with different design and innovation orientations. Logistic regression allows estimating the association between an establishment’s design orientation and local contextual factors. A quantile instrumental variable regression allows assessing the robustness of the logistic regression results with respect to endogeneity. An estimate of design orientation at the local level derived from the survey is used to examine variation in economic performance during the period of recovery from the Great Recession (2010–2014). Results Three distinct innovation (substantive, nominal, and non-innovators) and design orientations (design-integrated, “design last finish,” and no systematic approach to design) are identified. Innovation- and design-intensive establishments were identified in both rural and urban areas. Rural design-integrated establishments tended to locate in counties with more highly educated workforces and containing at least one performing arts organization. A quantile instrumental variable regression confirmed that the logistic regression result is robust to endogeneity concerns. Finally, rural areas characterized by design-integrated establishments experienced faster growth in wages relative to rural areas characterized by establishments using no systematic approach to design. PMID:29489884

Enhanced three-dimensional stochastic adjustment for combined volcano geodetic networks

NASA Astrophysics Data System (ADS)

Del Potro, R.; Muller, C.

2009-12-01

Volcano geodesy is unquestionably a necessary technique in studies of physical volcanology and for eruption early warning systems. However, as every volcano geodesist knows, obtaining measurements of the required resolution using traditional campaigns and techniques is time consuming and requires a large manpower. Moreover, most volcano geodetic networks worldwide use a combination of data from traditional techniques; levelling, electronic distance measurements (EDM), triangulation and Global Navigation Satellite Systems (GNSS) but, in most cases, these data are surveyed, analysed and adjusted independently. This then leaves it to the authors’ criteria to decide which technique renders the most realistic results in each case. Herein we present a way of solving the problem of inter-methodology data integration in a cost-effective manner following a methodology were all the geodetic data of a redundant, combined network (e.g. surveyed by GNSS, levelling, distance, angular data, INSAR, extensometers, etc.) is adjusted stochastically within a single three-dimensional referential frame. The adjustment methodology is based on the least mean square method and links the data with its geometrical component providing combined, precise, three-dimensional, displacement vectors, relative to external reference points as well as stochastically-quantified, benchmark-specific, uncertainty ellipsoids. Three steps in the adjustment allow identifying, and hence dismissing, flagrant measurement errors (antenna height, atmospheric effects, etc.), checking the consistency of external reference points and a final adjustment of the data. Moreover, since the statistical indicators can be obtained from expected uncertainties in the measurements of the different geodetic techniques used (i.e. independent of the measured data), it is possible to run a priori simulations of a geodetic network in order to constrain its resolution, and reduce logistics, before the network is even built. In this work we present a first effort to apply this technique to a new volcano geodetic network on Arenal volcano in Costa Rica, using triangulation, EDM and GNSS data from four campaigns. An a priori simulation, later confirmed by field measurements, of the movement detection capacity of different benchmarks within the network, shows how the network design is optimised to detect smaller displacement at the points where these are expected. Data from the four campaigns also proves the repeatability and consistency of the statistical indicators. A preliminary interpretation of the geodetic data relative to Arenal’s volcanic activity could indicate a correlation between displacement velocity and direction with the location and thickness of the recent lava flow field. This then suggests that a deflation caused by the weight of the lava field could be obscuring the effects of possible deep magmatic sources. Although this study is specific to Arenal volcano and its regional tectonic setting, we suggest that the cost-effective, high-quality results we present, prove the methodology’s potential to be incorporated into the design and analysis of volcano geodetic networks worldwide.

Design of a ground-water-quality monitoring network for the Salinas River basin, California

USGS Publications Warehouse

Showalter, P.K.; Akers, J.P.; Swain, L.A.

1984-01-01

A regional ground-water quality monitoring network for the entire Salinas River drainage basin was designed to meet the needs of the California State Water Resources Control Board. The project included phase 1--identifying monitoring networks that exist in the region; phase 2--collecting information about the wells in each network; and phase 3--studying the factors--such as geology, land use, hydrology, and geohydrology--that influence the ground-water quality, and designing a regional network. This report is the major product of phase 3. Based on the authors ' understanding of the ground-water-quality monitoring system and input from local offices, an ideal network was designed. The proposed network includes 317 wells and 8 stream-gaging stations. Because limited funds are available to implement the monitoring network, the proposed network is designed to correspond to the ideal network insofar as practicable, and is composed mainly of 214 wells that are already being monitored by a local agency. In areas where network wells are not available, arrangements will be made to add wells to local networks. The data collected by this network will be used to assess the ground-water quality of the entire Salinas River drainage basin. After 2 years of data are collected, the network will be evaluated to test whether it is meeting the network objectives. Subsequent network evaluations will be done very 5 years. (USGS)

State feedback controller design for the synchronization of Boolean networks with time delays

NASA Astrophysics Data System (ADS)

Li, Fangfei; Li, Jianning; Shen, Lijuan

2018-01-01

State feedback control design to make the response Boolean network synchronize with the drive Boolean network is far from being solved in the literature. Motivated by this, this paper studies the feedback control design for the complete synchronization of two coupled Boolean networks with time delays. A necessary condition for the existence of a state feedback controller is derived first. Then the feedback control design procedure for the complete synchronization of two coupled Boolean networks is provided based on the necessary condition. Finally, an example is given to illustrate the proposed design procedure.

Engineering a Functional Small RNA Negative Autoregulation Network with Model-Guided Design.

PubMed

Hu, Chelsea Y; Takahashi, Melissa K; Zhang, Yan; Lucks, Julius B

2018-05-22

RNA regulators are powerful components of the synthetic biology toolbox. Here, we expand the repertoire of synthetic gene networks built from these regulators by constructing a transcriptional negative autoregulation (NAR) network out of small RNAs (sRNAs). NAR network motifs are core motifs of natural genetic networks, and are known for reducing network response time and steady state signal. Here we use cell-free transcription-translation (TX-TL) reactions and a computational model to design and prototype sRNA NAR constructs. Using parameter sensitivity analysis, we design a simple set of experiments that allow us to accurately predict NAR function in TX-TL. We transfer successful network designs into Escherichia coli and show that our sRNA transcriptional network reduces both network response time and steady-state gene expression. This work broadens our ability to construct increasingly sophisticated RNA genetic networks with predictable function.

Optimal cost design of water distribution networks using a decomposition approach

NASA Astrophysics Data System (ADS)

Lee, Ho Min; Yoo, Do Guen; Sadollah, Ali; Kim, Joong Hoon

2016-12-01

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

Method for Constructing Composite Response Surfaces by Combining Neural Networks with other Interpolation or Estimation Techniques

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor); Madavan, Nateri K. (Inventor)

2003-01-01

A method and system for design optimization that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits is used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.

78 FR 75442 - Designation of the Primary Freight Network

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-11

...] Designation of the Primary Freight Network AGENCY: Federal Highway Administration (FHWA), DOT. ACTION: Notice... period for the Designation of the highway Primary Freight Network (PFN) notice, which was published on... the complete National Freight Network (NFN), and to solicit comments on aspects of the NFN. The five...

Intergenerational Social Networks and Health Behaviors Among Children Living in Public Housing

PubMed Central

Schwartz, Heather; Thornton, Rachel Johnson; Griffin, Beth Ann; Green, Harold D.; Kennedy, David P.; Burkhauser, Susan; Pollack, Craig Evan

2015-01-01

Objectives. In a survey of families living in public housing, we investigated whether caretakers’ social networks are linked with children’s health status. Methods. 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). Results. 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. Conclusions. 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. PMID:26378821

S-curve networks and an approximate method for estimating degree distributions of complex networks

NASA Astrophysics Data System (ADS)

Guo, Jin-Li

2010-12-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

Family networks and health among Métis aged 45 or older.

PubMed

Ramage-Morin, Pamela L; Bougie, Evelyne

2017-12-20

Social networks are important for promoting and maintaining health and well-being. Social networks, including family and friendship ties, are sources of emotional, practical and other support that enhance social participation and help combat isolation and loneliness. Aboriginal seniors have been identified as a population at risk of social isolation. The data are from the 2012 Aboriginal Peoples Survey, a national survey of First Nations people living off reserve, Métis, and Inuit. Frequencies, cross-tabulations, and logistic regression models were used to look at family networks and self-perceived general and mental health among Métis aged 45 or older. An estimated 48% of Métis men and 60% of Métis women aged 45 or older had strong family networks. Older age, lower education, and non-participation in the labour force were associated with strong networks. Métis men and women with strong family networks had higher odds than did those with weak networks of reporting positive mental health, even when potential confounders were taken into account. Among Métis men, a relationship between strong family networks and positive general health was also observed. Strong family networks are associated with positive self-perceived general and mental health among Métis adults. In addition to individual behaviours, family well-being is important for general health promotion.

Social network effects on post-traumatic stress disorder (PTSD) in female North Korean immigrants.

PubMed

Lee, Byungkyu; Youm, Yoosik

2011-09-01

The goal of this paper is to examine the social network effects on post-traumatic sdress disorder (PTSD) in female North Korean immigrants who entered South Korea in 2007. Specifically, it attempts to verify if the density and composition of networks make a difference after controlling for the network size. A multivariate logistic regression is used to probe the effects of social networks using the North Korean Immigrant Panel data set. Because the data set had only completed its initial survey when this paper was written, the analysis was cross-sectional. The size of the support networks was systematically related to PTSD. Female North Korean immigrants with more supporting ties were less likely to develop PTSD, even after controlling for other risk factors (odds-ratio for one more tie was 0.8). However, once we control for the size of the network, neither the density nor the composition of the networks remains statistically significant. The prevalence of the PTSD among female North Korean immigrants is alarmingly high, and regardless of the characteristics of supporting network members, the size of the supporting networks provides substantial protection. This implies that a simple strategy that focuses on increasing the number of supporting ties will be effective among North Korean immigrants who entered South Korea in recent years.

In-space propellant logistics. Volume 4: Project planning data

NASA Technical Reports Server (NTRS)

1972-01-01

The prephase A conceptual project planning data as it pertains to the development of the selected logistics module configuration transported into earth orbit by the space shuttle orbiter. The data represents the test, implementation, and supporting research and technology requirements for attaining the propellant transfer operational capability for early 1985. The plan is based on a propellant module designed to support the space-based tug with cryogenic oxygen-hydrogen propellants. A logical sequence of activities that is required to define, design, develop, fabricate, test, launch, and flight test the propellant logistics module is described. Included are the facility and ground support equipment requirements. The schedule of activities are based on the evolution and relationship between the R and T, the development issues, and the resultant test program.

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

PubMed

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

A Human-Centered Approach to Sense and Respond Logistics

DTIC Science & Technology

2009-04-10

United States Transportation Command (USTRANSCOM), a human-centered research initiative consisting of eight distinct research efforts designed to...27  2.5  Experimental Design ...120  6.3.6  Auction design parameters

Application of artificial neural networks to the design optimization of aerospace structural components

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Patnaik, Surya N.; Murthy, Pappu L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated by using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network with the code NETS. Optimum designs for new design conditions were predicted by using the trained network. Neural net prediction of optimum designs was found to be satisfactory for most of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Optimum Design of Aerospace Structural Components Using Neural Networks

NASA Technical Reports Server (NTRS)

Berke, L.; Patnaik, S. N.; Murthy, P. L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires a trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network using the code NETS. Optimum designs for new design conditions were predicted using the trained network. Neural net prediction of optimum designs was found to be satisfactory for the majority of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Delay-induced cluster patterns in coupled Cayley tree networks

NASA Astrophysics Data System (ADS)

Singh, A.; Jalan, S.

2013-07-01

We study effects of delay in diffusively coupled logistic maps on the Cayley tree networks. We find that smaller coupling values exhibit sensitiveness to value of delay, and lead to different cluster patterns of self-organized and driven types. Whereas larger coupling strengths exhibit robustness against change in delay values, and lead to stable driven clusters comprising nodes from last generation of the Cayley tree. Furthermore, introduction of delay exhibits suppression as well as enhancement of synchronization depending upon coupling strength values. To the end we discuss the importance of results to understand conflicts and cooperations observed in family business.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Butterfly Encryption Scheme for Resource-Constrained Wireless Networks †

PubMed Central

Sampangi, Raghav V.; Sampalli, Srinivas

2015-01-01

Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID) and Wireless Body Area Networks (WBAN) that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG), and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis. PMID:26389899

Supply support of NASA tracking networks

NASA Technical Reports Server (NTRS)

1973-01-01

The extent which supply support for Jet Propulsion Laboratory's Deep Space Network and Goddard Space Flight Center's Space Flight Tracking and Data Network should be consolidated is considered along with the Identification of opportunities for improvements in each of the supply systems without regard to consolidation. There is a considerable amount of commonality between the items in the stock catalogs at the two network depots, 58% for federal stock number items and 30% overall. The workload at the DSIF Supply Depot (DSD) is small (less than 20%) compared to the Network Logistics Depot (NLD). A number of important benefits in supply support would result from a consolidation of DSD into NLD. LMI found that a consolidation as is, without any changes in inventory management techniques, would reduce annual operating costs by from $208,000 to $358,000. However, if the consolidation were coupled with a change to use of economic order quantities, the annual operating cost reduction would range from $930,000 to $1,078,000.

Butterfly Encryption Scheme for Resource-Constrained Wireless Networks.

PubMed

Sampangi, Raghav V; Sampalli, Srinivas

2015-09-15

Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID) and Wireless Body Area Networks (WBAN) that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG), and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis.

Associations between social support network characteristics and receipt of emotional and material support among a sample of male sexual minority youth

PubMed Central

Kapadia, Farzana; Halkitis, Perry; Barton, Staci; Siconolfi, Daniel; Figueroa, Rafael Perez

2014-01-01

Few studies have examined how social support network characteristics are related to perceived receipt of social support among male sexual minority youth. Using egocentric network data collected from a study of male sexual minority youth (n=592), multivariable logistic regression analyses examined distinct associations between individual and social network characteristics with receipt of (1) emotional and (2) material support. In multivariable models, frequent communication and having friends in one’s network yielded a two-fold increase in the likelihood of receiving emotional support whereas frequent communication was associated with an almost three-fold higher likelihood of perceived material support. Finally, greater internalized homophobia and personal experiences of gay-related stigma were inversely associated with perceived receipt of emotional and material support, respectively. Understanding the evolving social context and social interactions of this new generation of male sexual minority youth is warranted in order to understand the broader, contextual factors associated with their overall health and well-being. PMID:25214756

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

A Decision Processing Algorithm for CDC Location Under Minimum Cost SCM Network

NASA Astrophysics Data System (ADS)

Park, N. K.; Kim, J. Y.; Choi, W. Y.; Tian, Z. M.; Kim, D. J.

Location of CDC in the matter of network on Supply Chain is becoming on the high concern these days. Present status of methods on CDC has been mainly based on the calculation manually by the spread sheet to achieve the goal of minimum logistics cost. This study is focused on the development of new processing algorithm to overcome the limit of present methods, and examination of the propriety of this algorithm by case study. The algorithm suggested by this study is based on the principle of optimization on the directive GRAPH of SCM model and suggest the algorithm utilizing the traditionally introduced MST, shortest paths finding methods, etc. By the aftermath of this study, it helps to assess suitability of the present on-going SCM network and could be the criterion on the decision-making process for the optimal SCM network building-up for the demand prospect in the future.

Supply chain optimization: a practitioner's perspective on the next logistics breakthrough.

PubMed

Schlegel, G L

2000-08-01

The objective of this paper is to profile a practitioner's perspective on supply chain optimization and highlight the critical elements of this potential new logistics breakthrough idea. The introduction will briefly describe the existing distribution network, and business environment. This will include operational statistics, manufacturing software, and hardware configurations. The first segment will cover the critical success factors or foundations elements that are prerequisites for success. The second segment will give you a glimpse of a "working game plan" for successful migration to supply chain optimization. The final segment will briefly profile "bottom-line" benefits to be derived from the use of supply chain optimization as a strategy, tactical tool, and competitive advantage.

The O-Buoy Chemical Network

NASA Astrophysics Data System (ADS)

Matrai, P. A.; Williams, C. R.; Rauschenberg, C. D.

2012-12-01

Autonomous, sea ice-tethered buoys ("O-Buoys") are being deployed across the Arctic sea ice for long-term atmospheric measurements, with several O-Buoys having been deployed within the Hudson Bay, Beaufort Sea, and the North Pole. These buoys provide in-situ measurements of ozone, CO_{2} and BrO, as well as meteorological parameters, over the frozen ocean. O-Buoys were designed to transmit daily data over a period of 2 years while deployed in sea ice, as part of automated ice-drifting stations. Due to the logistical challenges of measurements over the Arctic Ocean region, most long term,in-situ observations of atmospheric chemistry have been made at coastal sites or islands near the coast, leaving large spatial and temporal gaps that O-Buoys can overcome. The significant uncertainty that remains in our understanding of the temporal and spatial variability in these parameters as well as the magnitude and/or frequency of long (CO_{2}) and short (ozone depletion) patterns can be overcome. Advances in floatation, communications, power management, and sensor hardware have been made to the original design to overcome the challenges of diminished Arctic sea ice which have resulted in our longest deployments into the summer so far.

A Study in Instructional Design: A Multi-Modal Approach to Business Logistics.

ERIC Educational Resources Information Center

Griffin, Robert E.; And Others

Pennsylvania State University provided financial grants and support services to faculty members for improvement of instruction. Funds were provided for released time for faculty, audiovisual production materials, and research and evaluation. An extension course in business logistics was developed using these funds. Lecture presentations were…

Enabling parallel simulation of large-scale HPC network systems

DOE PAGES

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; ...

2016-04-07

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Enabling parallel simulation of large-scale HPC network systems

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

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Using turbidity for designing water networks.

PubMed

Castaño, J A; Higuita, J C

2016-05-01

Some methods to design water networks with minimum fresh water consumption are based on the selection of a key contaminant. In most of these "single contaminant methods", a maximum allowable concentration of contaminants must be established in water demands and water sources. Turbidity is not a contaminant concentration but is a property that represents the "sum" of other contaminants, with the advantage that it can be cheaper and easily measured than biological oxygen demand, chemical oxygen demand, suspended solids, dissolved solids, among others. The objective of this paper is to demonstrate that turbidity can be used directly in the design of water networks just like any other contaminant concentration. A mathematical demonstration is presented and in order to validate the mathematical results, the design of a water network for a guava fudge production process is performed. The material recovery pinch diagram and nearest neighbors algorithm were used for the design of the water network. Nevertheless, this water network could be designed using other single contaminant methodologies. The maximum error between the expected and the real turbidity values in the water network was 3.3%. These results corroborate the usefulness of turbidity in the design of water networks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Women's social networks and use of facility delivery services for uncomplicated births in North West Ethiopia: a community-based case-control study.

PubMed

Asrese, Kerebih; Adamek, Margaret E

2017-12-28

High maternal mortality has remained an unmet public health challenge in the developing world. Maternal mortality in Ethiopia is among the highest in the world. Since most maternal deaths occur during labor, delivery, and the immediate postpartum period, facility delivery with skilled birth attendants is recommended to reduce maternal mortality. Nonetheless, the majority of women in Ethiopia give birth at home. Individual attributes and availability and accessibility of services deter service utilization. The role of social networks that may facilitate or constrain service use is not well studied. Community-based case-control study was conducted between February and March 2014 in Jabi Tehinan District, North West Ethiopia. Retrospective data were collected from 134 women who had uncomplicated births at health facilities and 140 women who had uncomplicated births at home within a year preceding the survey. Interviews were held with eight women who had uncomplicated births at health facilities and 11 who had uncomplicated births at home. The quantitative data were entered and analyzed using SPSS for Windows versions 16.0 and hierarchical logistic regression model was used for analysis. The qualitative data were transcribed verbatim and data were used to substantiate the quantitative data. The results indicated that social network variables were significantly associated with the use of health facilities for delivery. Taking social networks into account improved the explanation of facility use for delivery services over women's individual attributes. Women embedded within homogeneous network members (Adjusted OR 2.53; 95% CI: 1.26-5.06) and embedded within high SBA endorsement networks (Adjusted OR 7.97; 95% CI: 4.07-12.16) were more likely to deliver at health facilities than their counterparts. Women living in urban areas (Adjusted OR 3.32; 95% CI: 1.37-8.05) and had better knowledge of obstetric complications (Adjusted OR 3.01; 95% CI: 1.46-6.18) were more likely to deliver at health facilities. Social networks facilitate SBA utilization by serving as a reference for the behavior to deliver at health facilities. These findings inform health professionals and other stakeholders regarding the importance of considering women's social networks in designing intervention to increase the proportion of women who deliver at health facilities.

Multidisciplinary Design Optimization for Aeropropulsion Engines and Solid Modeling/Animation via the Integrated Forced Methods

NASA Technical Reports Server (NTRS)

2004-01-01

The grant closure report is organized in the following four chapters: Chapter describes the two research areas Design optimization and Solid mechanics. Ten journal publications are listed in the second chapter. Five highlights is the subject matter of chapter three. CHAPTER 1. The Design Optimization Test Bed CometBoards. CHAPTER 2. Solid Mechanics: Integrated Force Method of Analysis. CHAPTER 3. Five Highlights: Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft. Neural Network and Regression Soft Model Extended for PX-300 Aircraft Engine. Engine with Regression and Neural Network Approximators Designed. Cascade Optimization Strategy with Neural network and Regression Approximations Demonstrated on a Preliminary Aircraft Engine Design. Neural Network and Regression Approximations Used in Aircraft Design.

Nationwide SIP Telephony Network Design to Prevent Congestion Caused by Disaster

NASA Astrophysics Data System (ADS)

Satoh, Daisuke; Ashitagawa, Kyoko

We present a session initiation protocol (SIP) network design for a voice-over-IP network to prevent congestion caused by people calling friends and family after a disaster. The design increases the capacity of SIP servers in a network by using all of the SIP servers equally. It takes advantage of the fact that equipment for voice data packets is different from equipment for signaling packets in SIP networks. Furthermore, the design achieves simple routing on the basis of telephone numbers. We evaluated the performance of our design in preventing congestion through simulation. We showed that the proposed design has roughly 20 times more capacity, which is 57 times the normal load, than the conventional design if a disaster were to occur in Niigata Prefecture struck by the Chuetsu earthquake in 2004.

Feasibility of conducting wetfall chemistry investigations around the Bowen Power Plant

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

Chen, N.C.J.; Patrinos, A.A.N.

1979-10-01

The feasibility of expanding the Meteorological Effects of Thermal Energy Releases - Oak Ridge National Laboratory (METER-ORNL) research at Bower Power Plant, a coal-fired power plant in northwest Georgia, to include wetfall chemistry is evaluated using results of similar studies around other power plants, several atmospheric washout models, analysis of spatial variability in precipitation, and field logistical considerations. An optimal wetfall chemistry network design is proposed, incorporating the inner portion of the existing rain-gauge network and augmented by additional sites to ensure adequate coverage of probable target areas. The predicted sulfate production rate differs by about four orders of magnitudemore » among the models reviewed with a pH of 3. No model can claim superiority over any other model without substantive data verification. The spatial uniformity in rain amount is evaluated using four storms that occurred at the METER-ORNL network. Values of spatial variability ranged from 8 to 31% and decreased as the mean rainfall increased. The field study of wetfall chemistry will require a minimum of 5 persons to operate the approximately 50 collectors covering an area of 740 km/sup 2/. Preliminary wetfall-only samples collected on an event basis showed lower pH and higher electrical conductivity of precipitation collected about 5 km downwind of the power plant relative to samples collected upwind. Wetfall samples collected on a weekly basis using automatic samplers, however, showed variable results, with no consistent pattern. This suggests the need for event sampling to minimize variable rain volume and multiple-source effects often associated with weekly samples.« less

Emergency Department Frequent Utilization for Non-Emergent Presentments: Results from a Regional Urban Trauma Center Study

PubMed Central

2016-01-01

Objectives First, to test a model of the drivers of frequent emergency department utilization conceptualized as falling within predisposing, enabling, and need dimensions. Second, to extend the model to include social networks and service quality as predictors of frequent utilization. Third, to illustrate the variation in thresholds that define frequent utilization in terms of the number of emergency department encounters by the predictors within the model. Data Source Primary data collection over an eight week period within a level-1 trauma urban hospital’s emergency department. Study Design Representative randomized sample of 1,443 adult patients triaged ESI levels 4–5. Physicians and research staff interviewed patients as they received services. Relationships with the outcome variable, utilization, were tested using logistic regression to establish odds-ratios. Principal Findings 70.6 percent of patients have two or more, 48.3 percent have three or more, 25.3 percent have four or more, and 14.9 percent have five or more emergency department visits within 12 months. Factors associated with frequent utilization include gender, race, poor mental health, mental health drugs, prescription drug abuse, social networks, employment, perceptions of service quality, seriousness of condition, persistence of condition, and previous hospital admittance. Conclusions Interventions targeting associated factors will change global emergency department encounters, although the mutability varies. Policy interventions to address predisposing factors such as substance abuse or access to mental health treatment as well as interventions that speak to enabling factors such as promoting the resiliency of social networks may result in decreased frequency of emergency department utilization. PMID:26784515

Designing Secure Library Networks.

ERIC Educational Resources Information Center

Breeding, Michael

1997-01-01

Focuses on designing a library network to maximize security. Discusses UNIX and file servers; connectivity to campus, corporate networks and the Internet; separation of staff from public servers; controlling traffic; the threat of network sniffers; hubs that eliminate eavesdropping; dividing the network into subnets; Switched Ethernet;…

Methodology for designing and implementing a class for service for the transmission of medical images over a common network

NASA Astrophysics Data System (ADS)

Dimond, David A.; Burgess, Robert; Barrios, Nolan; Johnson, Neil D.

2000-05-01

Traditionally, to guarantee the network performance of medical image data transmission, imaging traffic was isolated on a separate network. Organizations are depending on a new generation of multi-purpose networks to transport both normal information and image traffic as they expand access to images throughout the enterprise. These organi want to leverage their existing infrastructure for imaging traffic, but are not willing to accept degradations in overall network performance. To guarantee 'on demand' network performance for image transmissions anywhere at any time, networks need to be designed with the ability to 'carve out' bandwidth for specific applications and to minimize the chances of network failures. This paper will present the methodology Cincinnati Children's Hospital Medical Center (CHMC) used to enhance the physical and logical network design of the existing hospital network to guarantee a class of service for imaging traffic. PACS network designs should utilize the existing enterprise local area network i.e. (LAN) infrastructure where appropriate. Logical separation or segmentation provides the application independence from other clinical and administrative applications as required, ensuring bandwidth and service availability.

Next-Generation WDM Network Design and Routing

NASA Astrophysics Data System (ADS)

Tsang, Danny H. K.; Bensaou, Brahim

2003-08-01

Call for Papers The Editors of JON are soliciting papers on WDM Network Design and Routing. The aim in this focus issue is to publish original research on topics including - but not limited to - the following: - WDM network architectures and protocols - GMPLS network architectures - Wavelength converter placement in WDM networks - Routing and wavelength assignment (RWA) in WDM networks - Protection and restoration strategies and algorithms in WDM networks - Traffic grooming in WDM networks - Dynamic routing strategies and algorithms - Optical Burst Switching - Support of Multicast - Protection and restoration in WDM networks - Performance analysis and optimization in WDM networks Manuscript Submission To submit to this special issue, follow the normal procedure for submission to JON, indicating "WDM Network Design" in the "Comments" field of the online submission form. For all other questions relating to this focus issue, please send an e-mail to jon@osa.org, subject line "WDM Network Design." Additional information can be found on the JON website: http://www.osa-jon.org/submission/. Schedule Paper Submission Deadline: November 1, 2003 Notification to Authors: January 15, 2004 Final Manuscripts to Publisher: February 15, 2004 Publication of Focus Issue: February/March 2004

Next-Generation WDM Network Design and Routing

NASA Astrophysics Data System (ADS)

Tsang, Danny H. K.; Bensaou, Brahim

2003-10-01

Call for Papers The Editors of JON are soliciting papers on WDM Network Design and Routing. The aim in this focus issue is to publish original research on topics including - but not limited to - the following: - WDM network architectures and protocols - GMPLS network architectures - Wavelength converter placement in WDM networks - Routing and wavelength assignment (RWA) in WDM networks - Protection and restoration strategies and algorithms in WDM networks - Traffic grooming in WDM networks - Dynamic routing strategies and algorithms - Optical burst switching - Support of multicast - Protection and restoration in WDM networks - Performance analysis and optimization in WDM networks Manuscript Submission To submit to this special issue, follow the normal procedure for submission to JON, indicating "WDM Network Design" in the "Comments" field of the online submission form. For all other questions relating to this focus issue, please send an e-mail to jon@osa.org, subject line "WDM Network Design." Additional information can be found on the JON website: http://www.osa-jon.org/submission/. Schedule - Paper Submission Deadline: November 1, 2003 - Notification to Authors: January 15, 2004 - Final Manuscripts to Publisher: February 15, 2004 - Publication of Focus Issue: February/March 2004

Next-Generation WDM Network Design and Routing

NASA Astrophysics Data System (ADS)

Tsang, Danny H. K.; Bensaou, Brahim

2003-09-01

Call for Papers The Editors of JON are soliciting papers on WDM Network Design and Routing. The aim in this focus issue is to publish original research on topics including - but not limited to - the following: - WDM network architectures and protocols - GMPLS network architectures - Wavelength converter placement in WDM networks - Routing and wavelength assignment (RWA) in WDM networks - Protection and restoration strategies and algorithms in WDM networks - Traffic grooming in WDM networks - Dynamic routing strategies and algorithms - Optical burst switching - Support of multicast - Protection and restoration in WDM networks - Performance analysis and optimization in WDM networks Manuscript Submission To submit to this special issue, follow the normal procedure for submission to JON, indicating "WDM Network Design" in the "Comments" field of the online submission form. For all other questions relating to this focus issue, please send an e-mail to jon@osa.org, subject line "WDM Network Design." Additional information can be found on the JON website: http://www.osa-jon.org/submission/. Schedule - Paper Submission Deadline: November 1, 2003 - Notification to Authors: January 15, 2004 - Final Manuscripts to Publisher: February 15, 2004 - Publication of Focus Issue: February/March 2004

Launch Control Network Engineer

NASA Technical Reports Server (NTRS)

Medeiros, Samantha

2017-01-01

The Spaceport Command and Control System (SCCS) is being built at the Kennedy Space Center in order to successfully launch NASA’s revolutionary vehicle that allows humans to explore further into space than ever before. During my internship, I worked with the Network, Firewall, and Hardware teams that are all contributing to the huge SCCS network project effort. I learned the SCCS network design and the several concepts that are running in the background. I also updated and designed documentation for physical networks that are part of SCCS. This includes being able to assist and build physical installations as well as configurations. I worked with the network design for vehicle telemetry interfaces to the Launch Control System (LCS); this allows the interface to interact with other systems at other NASA locations. This network design includes the Space Launch System (SLS), Interim Cryogenic Propulsion Stage (ICPS), and the Orion Multipurpose Crew Vehicle (MPCV). I worked on the network design and implementation in the Customer Avionics Interface Development and Analysis (CAIDA) lab.

MED34/448: The Networked Health-Care Environment of the Future: Requirements for new human abilities

PubMed Central

Patel, V; Shortliffe, E; Kaufman, D

1999-01-01

The implications of the Internet for health care are increasingly understood as scientists, health workers, patients, and health administrators envision new applications, new means for communicating about health issues, and new ways of accessing pertinent health information at the point of care. It is important to study not only the new technologies themselves, but also to recognize that the optimal use of these technologies requires new skills by users. Not only must both patients and health professionals be taught the basic skills related to use of networking technologies, but those who develop future systems must understand the new human abilities that are implied by the remarkable changes that are envisioned. We describe the results of research that have implications for effectively exploiting networking technology in order to enhance creativity, collaboration, and communication. The development and implementation of enabling tools and methods that provide ready access to knowledge and information are among the central goals of medical informatics. Given the immensity of this challenge, the need for multi-institutional collaboration is increasingly being recognized. Collaboration has typically involved individuals who work together at the same location. With the evolution of electronic communication modalities, workers at Harvard, Columbia, McGill, and Stanford Universities jointly investigated the role that networking technologies can play in supporting research collaboration at a distance. All communications among the workers from the other three institutions were observed in order to gain insights into the limitations and successes of communications technology in supporting this distributed creative process. We analyzed the activities of the Intermed team as they sought to develop a common representation for clinical guidelines, known as the GuideLine Interchange Format (GLIF). These activities can be described as a process of computer-mediated collaborative design. We report here on the cognitive, socio-cultural, and logistical issues encountered when scientists from diverse organizations and backgrounds use communications technologies while designing and implementing shared products. Results demonstrate that the effectiveness of communication modalities is predicated on the specific objectives of the task. We identify suitable uses of email, conference calls, and face-to-face meetings. The leaders play an integral role in guiding and facilitating the group activities across modalities. Most important was the proper use of technology to support the evolution of a shared vision of group goals and methods, an element that is clearly necessary before successful collaborative designs can proceed. We interpret these research findings as they relate to the scientific collaboration via the Internet with specific focus on changes in skills required with these new media of communication.

Exploring Student Characteristics of Retention That Lead to Graduation in Higher Education Using Data Mining Models

ERIC Educational Resources Information Center

Raju, Dheeraj; Schumacker, Randall

2015-01-01

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

76 FR 58433 - Proposal To Revise Service Standards for First-Class Mail, Periodicals, and Standard Mail

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-21

... sharp revenue declines associated with falling volumes, as well as other statutorily mandated costs, the... and to bring operating costs in line with revenues, will for the most part be unachievable without a... effectively managed on the workroom floors of a complex logistical network.'' Modern Service Standards for...

Time, Space and Structure in an E-Learning and E-Mentoring Project

ERIC Educational Resources Information Center

Loureiro-Koechlin, Cecilia; Allan, Barbara

2010-01-01

This study focuses on a project, "EMPATHY Net-Works," which developed a learning community as a means of encouraging women to progress into employment and management positions in the logistics and supply chain industries (LaSCI). Learning activities were organised in the form of a taught module containing face-to-face and online elements and…

Development and Validation of an Instrument for Early Assessment of Management Potential in a Mid-Size Chemical Company

ERIC Educational Resources Information Center

Zehner, Robert L.; Holton, Elwood F., III

2004-01-01

This study reports on development and concurrent validation of a competency instrument to identify potential leaders in a mid-size chemical company. Four competencies were identified: courageous problem solving, perceived energy, networking, and perceived motivation. Four different comparison groups were examined in logistic regression analyses.…

Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output.

PubMed

Nochomovitz, Yigal D; Li, Hao

2006-03-14

Deciphering the design principles for regulatory networks is fundamental to an understanding of biological systems. We have explored the mapping from the space of network topologies to the space of dynamical phenotypes for small networks. Using exhaustive enumeration of a simple model of three- and four-node networks, we demonstrate that certain dynamical phenotypes can be generated by an atypically broad spectrum of network topologies. Such dynamical outputs are highly designable, much like certain protein structures can be designed by an unusually broad spectrum of sequences. The network topologies that encode a highly designable dynamical phenotype possess two classes of connections: a fully conserved core of dedicated connections that encodes the stable dynamical phenotype and a partially conserved set of variable connections that controls the transient dynamical flow. By comparing the topologies and dynamics of the three- and four-node network ensembles, we observe a large number of instances of the phenomenon of "mutational buffering," whereby addition of a fourth node suppresses phenotypic variation amongst a set of three-node networks.

Childhood ADHD Symptoms: Association with Parental Social Networks and Mental Health Service Use during Adolescence.

PubMed

Bussing, Regina; Meyer, Johanna; Zima, Bonnie T; Mason, Dana M; Gary, Faye A; Garvan, Cynthia Wilson

2015-09-22

This study examines the associations of childhood attention-deficit/hyperactivity disorder (ADHD) risk status with subsequent parental social network characteristics and caregiver strain in adolescence; and examines predictors of adolescent mental health service use. Baseline ADHD screening identified children at high risk (n = 207) and low risk (n = 167) for ADHD. At eight-year follow-up, parents reported their social network characteristics, caregiver strain, adolescents' psychopathology and mental health service utilization, whereas adolescents self-reported their emotional status and ADHD stigma perceptions. Analyses were conducted using ANOVAs and nested logistic regression modeling. Parents of youth with childhood ADHD reported support networks consisting of fewer spouses but more healthcare professionals, and lower levels of support than control parents. Caregiver strain increased with adolescent age and psychopathology. Increased parental network support, youth ADHD symptoms, and caregiver strain, but lower youth stigma perceptions were independently associated with increased service use. Raising children with ADHD appears to significantly impact parental social network experiences. Reduced spousal support and overall lower network support levels may contribute to high caregiver strain commonly reported among parents of ADHD youth. Parental social network experiences influence adolescent ADHD service use. With advances in social networking technology, further research is needed to elucidate ways to enhance caregiver support during ADHD care.

Social networks and mental health in post-conflict Mitrovica, Kosova.

PubMed

Nakayama, Risa; Koyanagi, Ai; Stickley, Andrew; Kondo, Tetsuo; Gilmour, Stuart; Arenliu, Aliriza; Shibuya, Kenji

2014-11-17

To investigate the relation between social networks and mental health in the post-conflict municipality of Mitrovica, Kosovo. Using a three-stage stratified sampling method, 1239 respondents aged 16 years or above were recruited in the Greater Mitrovica region. Social network depth was measured by the frequency of contacts with friends, relatives and strangers. Depression and anxiety were measured using the Hospital Anxiety and Depression Scale (HADS). Multivariate logistic regression was used to examine the association between social network depth and mental health. The analytical sample consisted of 993 respondents. The prevalence of depression (54.3%) and anxiety (64.4%) were extremely high. In multiple regression analysis, a lower depth of social network (contact with friends) was associated with higher levels of both depression and anxiety. This study has shown that only one variety of social network--contact with friends--was important in terms of mental health outcomes in a population living in an area heavily affected by conflict. This suggests that the relation between social networks and mental health may be complex in that the effects of different forms of social network on mental health are not uniform and may depend on the way social networks are operationalised and the particular context in which the relationship is examined.

Network Exposure and Homicide Victimization in an African American Community

PubMed Central

Wildeman, Christopher

2014-01-01

Objectives. We estimated the association of an individual’s exposure to homicide in a social network and the risk of individual homicide victimization across a high-crime African American community. Methods. Combining 5 years of homicide and police records, we analyzed a network of 3718 high-risk individuals that was created by instances of co-offending. We used logistic regression to model the odds of being a gunshot homicide victim by individual characteristics, network position, and indirect exposure to homicide. Results. Forty-one percent of all gun homicides occurred within a network component containing less than 4% of the neighborhood’s population. Network-level indicators reduced the association between individual risk factors and homicide victimization and improved the overall prediction of individual victimization. Network exposure to homicide was strongly associated with victimization: the closer one is to a homicide victim, the greater the risk of victimization. Regression models show that exposure diminished with social distance: each social tie removed from a homicide victim decreased one’s odds of being a homicide victim by 57%. Conclusions. Risk of homicide in urban areas is even more highly concentrated than previously thought. We found that most of the risk of gun violence was concentrated in networks of identifiable individuals. Understanding these networks may improve prediction of individual homicide victimization within disadvantaged communities. PMID:24228655

Network exposure and homicide victimization in an African American community.

PubMed

Papachristos, Andrew V; Wildeman, Christopher

2014-01-01

We estimated the association of an individual's exposure to homicide in a social network and the risk of individual homicide victimization across a high-crime African American community. Combining 5 years of homicide and police records, we analyzed a network of 3718 high-risk individuals that was created by instances of co-offending. We used logistic regression to model the odds of being a gunshot homicide victim by individual characteristics, network position, and indirect exposure to homicide. Forty-one percent of all gun homicides occurred within a network component containing less than 4% of the neighborhood's population. Network-level indicators reduced the association between individual risk factors and homicide victimization and improved the overall prediction of individual victimization. Network exposure to homicide was strongly associated with victimization: the closer one is to a homicide victim, the greater the risk of victimization. Regression models show that exposure diminished with social distance: each social tie removed from a homicide victim decreased one's odds of being a homicide victim by 57%. Risk of homicide in urban areas is even more highly concentrated than previously thought. We found that most of the risk of gun violence was concentrated in networks of identifiable individuals. Understanding these networks may improve prediction of individual homicide victimization within disadvantaged communities.

Optimization of Turbine Blade Design for Reusable Launch Vehicles

NASA Technical Reports Server (NTRS)

Shyy, Wei

1998-01-01

To facilitate design optimization of turbine blade shape for reusable launching vehicles, appropriate techniques need to be developed to process and estimate the characteristics of the design variables and the response of the output with respect to the variations of the design variables. The purpose of this report is to offer insight into developing appropriate techniques for supporting such design and optimization needs. Neural network and polynomial-based techniques are applied to process aerodynamic data obtained from computational simulations for flows around a two-dimensional airfoil and a generic three- dimensional wing/blade. For the two-dimensional airfoil, a two-layered radial-basis network is designed and trained. The performances of two different design functions for radial-basis networks, one based on the accuracy requirement, whereas the other one based on the limit on the network size. While the number of neurons needed to satisfactorily reproduce the information depends on the size of the data, the neural network technique is shown to be more accurate for large data set (up to 765 simulations have been used) than the polynomial-based response surface method. For the three-dimensional wing/blade case, smaller aerodynamic data sets (between 9 to 25 simulations) are considered, and both the neural network and the polynomial-based response surface techniques improve their performance as the data size increases. It is found while the relative performance of two different network types, a radial-basis network and a back-propagation network, depends on the number of input data, the number of iterations required for radial-basis network is less than that for the back-propagation network.

Neural networks: What non-linearity to choose

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik YA.; Quintana, Chris

1991-01-01

Neural networks are now one of the most successful learning formalisms. Neurons transform inputs (x(sub 1),...,x(sub n)) into an output f(w(sub 1)x(sub 1) + ... + w(sub n)x(sub n)), where f is a non-linear function and w, are adjustable weights. What f to choose? Usually the logistic function is chosen, but sometimes the use of different functions improves the practical efficiency of the network. The problem of choosing f as a mathematical optimization problem is formulated and solved under different optimality criteria. As a result, a list of functions f that are optimal under these criteria are determined. This list includes both the functions that were empirically proved to be the best for some problems, and some new functions that may be worth trying.

Boosting Classification Accuracy of Diffusion MRI Derived Brain Networks for the Subtypes of Mild Cognitive Impairment Using Higher Order Singular Value Decomposition

PubMed Central

Zhan, L.; Liu, Y.; Zhou, J.; Ye, J.; Thompson, P.M.

2015-01-01

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and Alzheimer's disease (AD), and around 10-15% of people with MCI develop AD each year. More recently, MCI has been further subdivided into early and late stages, and there is interest in identifying sensitive brain imaging biomarkers that help to differentiate stages of MCI. Here, we focused on anatomical brain networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying early versus late MCI. PMID:26413202

Risk factors associated with cognitions for late-onset depression based on anterior and posterior default mode sub-networks.

PubMed

Liu, Rui; Yue, Yingying; Hou, Zhenghua; Yuan, Yonggui; Wang, Qiao

2018-08-01

Abnormal functional connectivity (FC) in the default mode network (DMN) plays an important role in late-onset depression (LOD) patients. In this study, the risk predictors of LOD based on anterior and posterior DMN are explored. A total of 27 LOD patients and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging and cognitive assessments. Firstly, FCs within DMN sub-networks were determined by placing seeds in the ventral medial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC). Secondly, multivariable logistic regression was used to identify risk factors for LOD patients. Finally, correlation analysis was performed to investigate the relationship between risk factors and the cognitive value. Multivariable logistic regression showed that the FCs between the vmPFC and right middle temporal gyrus (MTG) (vmPFC-MTG_R), FCs between the vmPFC and left precuneus (PCu), and FCs between the PCC and left PCu (PCC-PCu_L) were the risk factors for LOD. Furthermore, FCs of the vmPFC-MTG_R and PCC-PCu_L correlated with processing speed (R = 0.35, P = 0.002; R = 0.32, P = 0.009), and FCs of the vmPFC-MTG_R correlated with semantic memory (R = 0.41, P = 0.001). The study was a cross-sectional study. The results may be potentially biased because of a small sample. In this study, we confirmed that LOD patients mainly present cognitive deficits in processing speed and semantic memory. Moreover, our findings further suggested that FCs within DMN sub-networks associated with cognitions were risk factors, which may be used for the prediction of LOD. Copyright © 2018 Elsevier B.V. All rights reserved.

Using artificial intelligence to predict the risk for posterior capsule opacification after phacoemulsification.

PubMed

Mohammadi, Seyed-Farzad; Sabbaghi, Mostafa; Z-Mehrjardi, Hadi; Hashemi, Hassan; Alizadeh, Somayeh; Majdi, Mercede; Taee, Farough

2012-03-01

To apply artificial intelligence models to predict the occurrence of posterior capsule opacification (PCO) after phacoemulsification. Farabi Eye Hospital, Tehran, Iran. Clinical-based cross-sectional study. The posterior capsule status of eyes operated on for age-related cataract and the need for laser capsulotomy were determined. After a literature review, data polishing, and expert consultation, 10 input variables were selected. The QUEST algorithm was used to develop a decision tree. Three back-propagation artificial neural networks were constructed with 4, 20, and 40 neurons in 2 hidden layers and trained with the same transfer functions (log-sigmoid and linear transfer) and training protocol with randomly selected eyes. They were then tested on the remaining eyes and the networks compared for their performance. Performance indices were used to compare resultant models with the results of logistic regression analysis. The models were trained using 282 randomly selected eyes and then tested using 70 eyes. Laser capsulotomy for clinically significant PCO was indicated or had been performed 2 years postoperatively in 40 eyes. A sample decision tree was produced with accuracy of 50% (likelihood ratio 0.8). The best artificial neural network, which showed 87% accuracy and a positive likelihood ratio of 8, was achieved with 40 neurons. The area under the receiver-operating-characteristic curve was 0.71. In comparison, logistic regression reached accuracy of 80%; however, the likelihood ratio was not measurable because the sensitivity was zero. A prototype artificial neural network was developed that predicted posterior capsule status (requiring capsulotomy) with reasonable accuracy. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Variation in hospital mortality in an Australian neonatal intensive care unit network.

PubMed

Abdel-Latif, Mohamed E; Nowak, Gen; Bajuk, Barbara; Glass, Kathryn; Harley, David

2018-07-01

Studying centre-to-centre (CTC) variation in mortality rates is important because inferences about quality of care can be made permitting changes in practice to improve outcomes. However, comparisons between hospitals can be misleading unless there is adjustment for population characteristics and severity of illness. We sought to report the risk-adjusted CTC variation in mortality among preterm infants born <32 weeks and admitted to all eight tertiary neonatal intensive care units (NICUs) in the New South Wales and the Australian Capital Territory Neonatal Network (NICUS), Australia. We analysed routinely collected prospective data for births between 2007 and 2014. Adjusted mortality rates for each NICU were produced using a multiple logistic regression model. Output from this model was used to construct funnel plots. A total of 7212 live born infants <32 weeks gestation were admitted consecutively to network NICUs during the study period. NICUs differed in their patient populations and severity of illness.The overall unadjusted hospital mortality rate for the network was 7.9% (n=572 deaths). This varied from 5.3% in hospital E to 10.4% in hospital C. Adjusted mortality rates showed little CTC variation. No hospital reached the +99.8% control limit level on adjusted funnel plots. Characteristics of infants admitted to NICUs differ, and comparing unadjusted mortality rates should be avoided. Logistic regression-derived risk-adjusted mortality rates plotted on funnel plots provide a powerful visual graphical tool for presenting quality performance data. CTC variation is readily identified, permitting hospitals to appraise their practices and start timely intervention. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Sensitivity study of Space Station Freedom operations cost and selected user resources

NASA Technical Reports Server (NTRS)

Accola, Anne; Fincannon, H. J.; Williams, Gregory J.; Meier, R. Timothy

1990-01-01

The results of sensitivity studies performed to estimate probable ranges for four key Space Station parameters using the Space Station Freedom's Model for Estimating Space Station Operations Cost (MESSOC) are discussed. The variables examined are grouped into five main categories: logistics, crew, design, space transportation system, and training. The modification of these variables implies programmatic decisions in areas such as orbital replacement unit (ORU) design, investment in repair capabilities, and crew operations policies. The model utilizes a wide range of algorithms and an extensive trial logistics data base to represent Space Station operations. The trial logistics data base consists largely of a collection of the ORUs that comprise the mature station, and their characteristics based on current engineering understanding of the Space Station. A nondimensional approach is used to examine the relative importance of variables on parameters.

Closed-loop supply chain models with considering the environmental impact.

PubMed

Mohajeri, Amir; Fallah, Mohammad

2014-01-01

Global warming and climate changes created by large scale emissions of greenhouse gases are a worldwide concern. Due to this, the issue of green supply chain management has received more attention in the last decade. In this study, a closed-loop logistic concept which serves the purposes of recycling, reuse, and recovery required in a green supply chain is applied to integrate the environmental issues into a traditional logistic system. Here, we formulate a comprehensive closed-loop model for the logistics planning considering profitability and ecological goals. In this way, we can achieve the ecological goal reducing the overall amount of CO2 emitted from journeys. Moreover, the profitability criterion can be supported in the cyclic network with the minimum costs and maximum service level. We apply three scenarios and develop problem formulations for each scenario corresponding to the specified regulations and investigate the effect of the regulation on the preferred transport mode and the emissions. To validate the models, some numerical experiments are worked out and a comparative analysis is investigated.

Tradeoff Analysis for Combat Service Support Wireless Communications Alternatives

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

Burnette, John R.; Thibodeau, Christopher C.; Greitzer, Frank L.

2002-02-28

As the Army moves toward more mobile and agile forces and continued sustainment of numerous high-cost legacy logistics management systems, the requirement for wireless connectivity and a wireless network to supporting organizations has become ever more critical. There are currently several Army communications initiatives underway to resolve this wireless connectivity issue. However, to fully appreciate and understand the value of these initiatives, a Tradeoff Analysis is needed. The present study seeks to identify and assess solutions. The analysis identified issues that impede Interim Brigade Combat Team (IBCT) communication system integration and outlined core requirements for sharing of logistics data betweenmore » the field and Army battle command systems. Then, the analysis examined wireless communication alternatives as possible solutions for IBCT logistics communications problems. The current baseline system was compared with possible alternatives involving tactical radio systems, wireless/near term digital radio, cellular satellite, and third-generation (3G) wireless technologies. Cellular satellite and 3G wireless technologies offer clear advantages and should be considered for later IBCTs.« less

Position-Specific HIV Risk in a Large Network of Homeless Youths

PubMed Central

Barman-Adhikari, Anamika; Milburn, Norweeta G.; Monro, William

2012-01-01

Objectives. We examined interconnections among runaway and homeless youths (RHYs) and how aggregated network structure position was associated with HIV risk in this population. Methods. We collected individual and social network data from 136 RHYs. On the basis of these data, we generated a sociomatrix, accomplished network visualization with a “spring embedder,” and examined k-cores. We used multivariate logistic regression models to assess associations between peripheral and nonperipheral network position and recent unprotected sexual intercourse. Results. Small numbers of nominations at the individual level aggregated into a large social network with a visible core, periphery, and small clusters. Female youths were more likely to be in the core, as were youths who had been homeless for 2 years or more. Youths at the periphery were less likely to report unprotected intercourse and had been homeless for a shorter duration. Conclusions. HIV risk was a function of risk-taking youths' connections with one another and was associated with position in the overall network structure. Social network–based prevention programs, young women's housing and health programs, and housing-first programs for peripheral youths could be effective strategies for preventing HIV among this population. PMID:22095350

Chaos in the fractional order logistic delay system: Circuit realization and synchronization

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

Baskonus, Haci Mehmet; Hammouch, Zakia; Mekkaoui, Toufik

2016-06-08

In this paper, we present a numerical study and a circuit design to prove existence of chaos in the fractional order Logistic delay system. In addition, we investigate an active control synchronization scheme in this system. Numerical and cicruit simulations show the effectiveness and feasibility of this method.