HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP MODEL

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Chun Meng Tang

2015-12-01

Full Text Available Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly competitive. To maintain the current user base and continue to attract new users, how should social networking sites design their sites? Marketers spend a fairly large percent of their marketing budget on social media marketing. To formulate an effective social media strategy, how much do marketers understand the users of social networking sites? Learning from website evaluation studies, this study intends to provide some answers to these questions by examining how university students decide between two popular social networking sites, Facebook and Twitter. We first developed an analytic hierarchy process (AHP model of four main selection criteria and 12 sub-criteria, and then administered a questionnaire to a group of university students attending a course at a Malaysian university. AHP analyses of the responses from 12 respondents provided an insight into the decision-making process involved in students’ selection of social networking sites. It seemed that of the four main criteria, privacy was the top concern, followed by functionality, usability, and content. The sub-criteria that were of key concern to the students were apps, revenue-generating opportunities, ease of use, and information security. Between Facebook and Twitter, the students thought that Facebook was the better choice. This information is useful for social networking site designers to design sites that are more relevant to their users’ needs, and for marketers to craft more effective

A Novel Analytical Model for Network-on-Chip using Semi-Markov Process

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WANG, J.

2011-02-01

Full Text Available Network-on-Chip (NoC communication architecture is proposed to resolve the bottleneck of Multi-processor communication in a single chip. In this paper, a performance analytical model using Semi-Markov Process (SMP is presented to obtain the NoC performance. More precisely, given the related parameters, SMP is used to describe the behavior of each channel and the header flit routing time on each channel can be calculated by analyzing the SMP. Then, the average packet latency in NoC can be calculated. The accuracy of our model is illustrated through simulation. Indeed, the experimental results show that the proposed model can be used to obtain NoC performance and it performs better than the state-of-art models. Therefore, our model can be used as a useful tool to guide the NoC design process.

Green supply chain management strategy selection using analytic network process: case study at PT XYZ

Science.gov (United States)

Adelina, W.; Kusumastuti, R. D.

2017-01-01

This study is about business strategy selection for green supply chain management (GSCM) for PT XYZ by using Analytic Network Process (ANP). GSCM is initiated as a response to reduce environmental impacts from industrial activities. The purposes of this study are identifying criteria and sub criteria in selecting GSCM Strategy, and analysing a suitable GSCM strategy for PT XYZ. This study proposes ANP network with 6 criteria and 29 sub criteria, which are obtained from the literature and experts’ judgements. One of the six criteria contains GSCM strategy options, namely risk-based strategy, efficiency-based strategy, innovation-based strategy, and closed loop strategy. ANP solves complex GSCM strategy-selection by using a more structured process and considering green perspectives from experts. The result indicates that innovation-based strategy is the most suitable green supply chain management strategy for PT XYZ.

A Multi-Criteria Analysis for the Evaluation of Social Housing Proposals: from the Analytic Hierarchy Process (AHP to the Analytic Network Process (ANP

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Barbara Ferri

2017-02-01

Full Text Available Social housing requires appropriate evaluation models of projects, considering them from multiple perspectives: architectural, technical, environmental, economic, financial, paying particular attention to social aspects. The study proposes the use of a multi criteria evaluation model, based on the hierarchical (AHP and network (ANP analysis, as support in decision-making to guide practitioners and policy on the choice among alternative interventions. These methods allow to consider the overall effect of projects on urban system and the different points of view of those concerned, in an integrated and participatory approach. Interesting research perspectives concern the application of these evaluation approaches to case studies related to neighborhoods in which urban planning provides for social housing. The analysis will address the recent proposals for social housing in the city of Pescara (Italy, and in particular the urban transformation that is expected to achieve by means of the Integrated Urban Development Programme on the south-west of the city, whose regeneration was started by the Community Programme Urban 2.   Un’Analisi Multi Criteri per la Valutazione delle Proposte di Housing Sociale: dall’Analytic Hierarchy Process (AHP all’Analytic Network Process (ANP I modelli insediativi di social housing richiedono idonei strumenti valutativi degli interventi immobiliari, considerandoli da molteplici punti di vista: architettonici, urbanistici, ambientali, economici, finanziari, con particolare attenzione agli aspetti sociali. Lo studio propone l’impiego di un modello valutativo multicriteri basato sull’analisi gerarchica (AHP e a rete (ANP, come supporto ai processi decisionali riguardanti la scelta tra interventi alternativi di edilizia residenziale sociale, considerando il loro effetto complessivo sul sistema urbano secondo un approccio integrato e partecipativo. Parole Chiave: analisi multicriteri, edilizia residenziale sociale

Prioritizing of effective factors on development of medicinal plants cultivation using analytic network process

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Ghorbanali Rassam

2014-07-01

Full Text Available For the overall development of medicinal plants cultivation in Iran, there is a need to identify various effective factors on medicinal plant cultivation. A proper method for identifying the most effective factor on the development of the medicinal plants cultivation is essential. This research conducted in order to prioritizing of the effective criteria for the development of medicinal plant cultivation in North Khorasan province in Iran using Analytical Network Process (ANP method. The multi-criteria decision making (MCDM is suggested to be a viable method for factor selection and the analytic network process (ANP has been used as a tool for MCDM. For this purpose a list of effective factors offered to expert group. Then pair wise comparison questionnaires were distributed between relevant researchers and local producer experts of province to get their opinions about the priority of criteria and sub- criteria. The questionnaires were analyzed using Super Decision software. We illustrated the use of the ANP by ranking main effective factors such as economic, educational-extension services, cultural-social and supportive policies on development of medicinal plants. The main objective of the present study was to develop ANP as a decision making tool for prioritizing factors affecting the development of medicinal plants cultivation. Results showed that the ANP methodology was perfectly suited to tackling the complex interrelations involved in selection factor in this case. Also the results of the process revealed that among the factors, supporting the cultivation of medicinal plants, build the infrastructure for marketing support, having educated farmer and easy access to production input have most impact on the development of medicinal plant cultivation.

Manufacturing plant location selection in logistics network using Analytic Hierarchy Process

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Ping-Yu Chang

2015-11-01

Full Text Available Purpose: In recent years, numerous companies have moved their manufacturing plants to China to capitalize on lower cost and tax. Plant location has such an impact on cost, stocks, and logistics network but location selection in the company is usually based on subjective preference of high ranking managers. Such a decision-making process might result in selecting a location with a lower fixed cost but a higher operational cost. Therefore, this research adapts real data from an electronics company to develop a framework that incorporates both quantitative and qualitative factors for selecting new plant locations. Design/methodology/approach: In-depth interviews were conducted with 12 high rank managers (7 of them are department manager, 2 of them are vice-president, 1 of them is senior engineer, and 2 of them are plant manager in the departments of construction, finance, planning, production, and warehouse to determine the important factors. A questionnaire survey is then conducted for comparing factors which are analyzed using the Analytic Hierarchy Process (AHP. Findings: Results show that the best location chosen by the developed framework coincides well with the company’s primal production base. The results have been presented to the company’s high ranking managers for realizing the accuracy of the framework. Positive responses of the managers indicate usefulness of implementing the proposed model into reality, which adds to the value of this research. Practical implications: The proposed framework can save numerous time-consuming meetings called to compromise opinions and conflictions from different departments in location selection. Originality/value: This paper adapts the Analytic Hierarchy Process (AHP to incorporate quantitative and qualitative factors which are obtained through in-depth interviews with high rank managers in a company into the location decision.

Evaluation of options for energy recovery from municipal solid waste in India using the hierarchical analytical network process

International Nuclear Information System (INIS)

Nixon, J.D.; Dey, P.K.; Ghosh, S.K.; Davies, P.A.

2013-01-01

In this paper a Hierarchical Analytical Network Process (HANP) model is demonstrated for evaluating alternative technologies for generating electricity from MSW in India. The technological alternatives and evaluation criteria for the HANP study are characterised by reviewing the literature and consulting experts in the field of waste management. Technologies reviewed in the context of India include landfill, anaerobic digestion, incineration, pelletisation and gasification. To investigate the sensitivity of the result, we examine variations in expert opinions and carry out an Analytical Hierarchy Process (AHP) analysis for comparison. We find that anaerobic digestion is the preferred technology for generating electricity from MSW in India. Gasification is indicated as the preferred technology in an AHP model due to the exclusion of criteria dependencies and in an HANP analysis when placing a high priority on net output and retention time. We conclude that HANP successfully provides a structured framework for recommending which technologies to pursue in India, and the adoption of such tools is critical at a time when key investments in infrastructure are being made. Therefore the presented methodology is thought to have a wider potential for investors, policy makers, researchers and plant developers in India and elsewhere. - Highlights: • We evaluate alternative technologies for generating electricity from waste. • The methodology we develop is based on the analytical network process. • Assessment is made against technical, financial, environmental and risk criteria. • Anaerobic digestion and gasification are the preferred technologies for India. • The method reduces risk and ensures sustainability in energy project planning

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

Science.gov (United States)

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

2017-11-01

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

Customer Intelligence Analytics on Social Networks

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Brano MARKIĆ

2016-08-01

Full Text Available Discovering needs, habits and consumer behavior is the primary task of marketing analytics. It is necessary to integrate marketing and analytical skills with IT skills. Such knowledge integration allows access to data (structured and unstructured, their analysis and finding out information about the opinions, attitudes, needs and behavior of customers. In the paper is set the hypothesis that software tools can collect data (messages from social networks, analyze the content of messages and get to know the attitudes of customers about a product, service, tourist destination with the ultimate goal of improving customer relations. Experimental results are based on the analysis of the content of social network Facebook by using the package and function R language. This language showed a satisfactory application and development power in analysis of textual data on social networks for marketing analytics.

Analytical reasoning task reveals limits of social learning in networks.

Science.gov (United States)

Rahwan, Iyad; Krasnoshtan, Dmytro; Shariff, Azim; Bonnefon, Jean-François

2014-04-06

Social learning-by observing and copying others-is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is its ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of laboratory-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias', which limits their social learning to the output, rather than the process, of their peers' reasoning-even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behaviour through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning.

PERMASALAHAN PENGEMBANGAN SUKUK KORPORASI DI INDONESIA MENGGUNAKAN METODE ANALYTICAL NETWORK PROCESS (ANP

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Endri Endri

2017-03-01

Full Text Available This paper analyzed the problem of developing corporate sukuk in Indonesia using AnalyticNetwork Process (ANP methodology, proceeded by literature survey and in-depth interviewwith scholars, practitioners, and regulator of Islamic capital market to fully understand the problemand to develop an appropriate ANP network. The cause of this problem could be grouped into fouraspects, namely 1 market player; 2 product characteristic; 3 regulation; and 4 government. Thisresearch found that the problems of developing corporate sukuk in Indonesia could be summed upinto two main causes from market player and regulation aspects, namely the lack of market playerunderstanding and quality of human resource which involved in Islamic capital market, and alsothe uncertainty of tax regulations. The suggested solution was to increase understanding of marketplayer by promoting Islamic capital market intensively, and then providing quality of human resourceby training and education comprehensively, revising tax regulation to avoid double taxation becomethe next solution. Other suggested solution from government aspect was to give support throughissuance sovereign sukuk. Moreover, the most effective policy strategy to overcome the problems ofIslamic capital market, specially in developing corporate sukuk market was by implementing marketdriven strategy, where policies were intended to make market mechanism running well.

Analytic network process model for sustainable lean and green manufacturing performance indicator

Science.gov (United States)

Aminuddin, Adam Shariff Adli; Nawawi, Mohd Kamal Mohd; Mohamed, Nik Mohd Zuki Nik

2014-09-01

Sustainable manufacturing is regarded as the most complex manufacturing paradigm to date as it holds the widest scope of requirements. In addition, its three major pillars of economic, environment and society though distinct, have some overlapping among each of its elements. Even though the concept of sustainability is not new, the development of the performance indicator still needs a lot of improvement due to its multifaceted nature, which requires integrated approach to solve the problem. This paper proposed the best combination of criteria en route a robust sustainable manufacturing performance indicator formation via Analytic Network Process (ANP). The integrated lean, green and sustainable ANP model can be used to comprehend the complex decision system of the sustainability assessment. The finding shows that green manufacturing is more sustainable than lean manufacturing. It also illustrates that procurement practice is the most important criteria in the sustainable manufacturing performance indicator.

A Performance Analytical Strategy for Network-on-Chip Router with Input Buffer Architecture

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WANG, J.

2012-11-01

Full Text Available In this paper, a performance analytical strategy is proposed for Network-on-Chip router with input buffer architecture. First, an analytical model is developed based on semi-Markov process. For the non-work-conserving router with small buffer size, the model can be used to analyze the schedule delay and the average service time for each buffer when given the related parameters. Then, the packet average delay in router is calculated by using the model. Finally, we validate the effectiveness of our strategy by simulation. By comparing our analytical results to simulation results, we show that our strategy successfully captures the Network-on-Chip router performance and it performs better than the state-of-art technology. Therefore, our strategy can be used as an efficiency performance analytical tool for Network-on-Chip design.

Evaluating the performance of free-formed surface parts using an analytic network process

Science.gov (United States)

Qian, Xueming; Ma, Yanqiao; Liang, Dezhi

2018-03-01

To successfully design parts with a free-formed surface, the critical issue of how to evaluate and select a favourable evaluation strategy before design is raised. The evaluation of free-formed surface parts is a multiple criteria decision-making (MCDM) problem that requires the consideration of a large number of interdependent factors. The analytic network process (ANP) is a relatively new MCDM method that can systematically deal with all kinds of dependences. In this paper, the factors, which come from the life-cycle and influence the design of free-formed surface parts, are proposed. After analysing the interdependence among these factors, a Hybrid ANP (HANP) structure for evaluating the part’s curved surface is constructed. Then, a HANP evaluation of an impeller is presented to illustrate the application of the proposed method.

Modelling and assessment of dependent performance shaping factors through Analytic Network Process

International Nuclear Information System (INIS)

De Ambroggi, Massimiliano; Trucco, Paolo

2011-01-01

Despite continuous progresses in research and applications, one of the major weaknesses of current HRA methods dwells in their limited capability of modelling the mutual influences between performance shaping factors (PSFs). Indeed at least two types of dependencies between PSFs can be defined: (i) dependency between the states of the PSFs; (ii) dependency between the influences (impacts) of the PSFs on the human performance. This paper introduces a method, based on Analytic Network Process (ANP), for the quantification of the latter, where the overall contribution of each PSF (weight) to the human error probability (HEP) is eventually returned. The core of the method is the modelling process, articulated into two steps: firstly, a qualitative network of dependencies between PSFs is identified, then, the importance of each PSF is quantitatively assessed using ANP. The model allows to distinguish two components of the PSF influence: direct influence that is the influence that the considered PSF is able to express by itself, notwithstanding the presence of other PSFs and indirect influence that is the incremental influence of the considered PSF through its influence on other PSFs. A case study in Air Traffic Control is presented where the proposed approach is integrated into the cognitive simulator PROCOS. The results demonstrated a significant modification of the influence of PSFs over the operator performance when dependencies are taken into account, underlining the importance of considering not only the possible correlation between the states of PSFs but also their mutual dependency in affecting human performance in complex systems.

Supercritical boiler material selection using fuzzy analytic network process

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Saikat Ranjan Maity

2012-08-01

Full Text Available The recent development of world is being adversely affected by the scarcity of power and energy. To survive in the next generation, it is thus necessary to explore the non-conventional energy sources and efficiently consume the available sources. For efficient exploitation of the existing energy sources, a great scope lies in the use of Rankin cycle-based thermal power plants. Today, the gross efficiency of Rankin cycle-based thermal power plants is less than 28% which has been increased up to 40% with reheating and regenerative cycles. But, it can be further improved up to 47% by using supercritical power plant technology. Supercritical power plants use supercritical boilers which are able to withstand a very high temperature (650-720˚C and pressure (22.1 MPa while producing superheated steam. The thermal efficiency of a supercritical boiler greatly depends on the material of its different components. The supercritical boiler material should possess high creep rupture strength, high thermal conductivity, low thermal expansion, high specific heat and very high temperature withstandability. This paper considers a list of seven supercritical boiler materials whose performance is evaluated based on seven pivotal criteria. Given the intricacy and difficulty of this supercritical boiler material selection problem having interactions and interdependencies between different criteria, this paper applies fuzzy analytic network process to select the most appropriate material for a supercritical boiler. Rene 41 is the best supercritical boiler material, whereas, Haynes 230 is the worst preferred choice.

xQuake: A Modern Approach to Seismic Network Analytics

Science.gov (United States)

Johnson, C. E.; Aikin, K. E.

2017-12-01

While seismic networks have expanded over the past few decades, and social needs for accurate and timely information has increased dramatically, approaches to the operational needs of both global and regional seismic observatories have been slow to adopt new technologies. This presentation presents the xQuake system that provides a fresh approach to seismic network analytics based on complexity theory and an adaptive architecture of streaming connected microservices as diverse data (picks, beams, and other data) flow into a final, curated catalog of events. The foundation for xQuake is the xGraph (executable graph) framework that is essentially a self-organizing graph database. An xGraph instance provides both the analytics as well as the data storage capabilities at the same time. Much of the analytics, such as synthetic annealing in the detection process and an evolutionary programing approach for event evolution, draws from the recent GLASS 3.0 seismic associator developed by and for the USGS National Earthquake Information Center (NEIC). In some respects xQuake is reminiscent of the Earthworm system, in that it comprises processes interacting through store and forward rings; not surprising as the first author was the lead architect of the original Earthworm project when it was known as "Rings and Things". While Earthworm components can easily be integrated into the xGraph processing framework, the architecture and analytics are more current (e.g. using a Kafka Broker for store and forward rings). The xQuake system is being released under an unrestricted open source license to encourage and enable sthe eismic community support in further development of its capabilities.

Multidimensional epidemic thresholds in diffusion processes over interdependent networks

International Nuclear Information System (INIS)

Salehi, Mostafa; Siyari, Payam; Magnani, Matteo; Montesi, Danilo

2015-01-01

Highlights: •We propose a new concept of multidimensional epidemic threshold for interdependent networks. •We analytically derive and numerically illustrate the conditions for multilayer epidemics. •We study the evolution of infection density and diffusion dynamics. -- Abstract: Several systems can be modeled as sets of interdependent networks where each network contains distinct nodes. Diffusion processes like the spreading of a disease or the propagation of information constitute fundamental phenomena occurring over such coupled networks. In this paper we propose a new concept of multidimensional epidemic threshold characterizing diffusion processes over interdependent networks, allowing different diffusion rates on the different networks and arbitrary degree distributions. We analytically derive and numerically illustrate the conditions for multilayer epidemics, i.e., the appearance of a giant connected component spanning all the networks. Furthermore, we study the evolution of infection density and diffusion dynamics with extensive simulation experiments on synthetic and real networks

A proposal framework for investigating website success in the context of e-banking:an analytic network process approach

OpenAIRE

Salehi, Mona; Keramati, Abbas

2009-01-01

This study proposes a framework to investigate website success factors, and their relative importance in selecting the most preferred e-banking website. For one thing, Updated Delone and Mclean IS success model is chosen to extract significant website success factors in the context of e-banking in Iran. Secondly, Updated Delone and McLean IS success model is extended through applying an analytic network process (ANP) approach in order to investigate the relative importance of each factor and ...

Analisis Masalah Pengembangan Perbankan Syariah di Indonesia: Aplikasi Metode Analytic Network Process

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Aam Slamet Rusydiana

2016-09-01

Full Text Available The Development Problems Analysis of Islamic Banking in Indonesia: Application Analytic Network Process MethodThis study would try to address the problems that faced by Islamic banking institutions in Indonesia. The results showed that the problems that arise in the development of Islamic banks in Indonesia consists of four important aspects, namely: human, technical, legal/structural aspect, and market/communal aspect. Decomposition of problem as a whole gains the priorities: 1 There is not enough of Islamic banks capital yet; 2 Lack of understanding of Islamic bank practitioners; 3 Lack of government support; 4 the trust and public interest to Islamic banks tend to be low.While the priority of policy strategies that are considered able to resolve the problems of Islamic banking industry in Indonesia consists of: 1 strengthen the capital and business scale and improve the efficiency level; 2 improve the quantity and quality of human resources, and also information systems and technologies; Furthermore, 3 improve the structure of Islamic bank funds and harmonization of regulation and supervision. DOI: 10.15408/ess.v6i2.3573

A Project Strategic Index proposal for portfolio selection in electrical company based on the Analytic Network Process

Energy Technology Data Exchange (ETDEWEB)

Smith-Perera, Aida [Universidad Metropolitana de Caracas, Departamento de Gestion Tecnologica, Caracas 1071, Edo Miranda (Venezuela); Garcia-Melon, Monica; Poveda-Bautista, Rocio; Pastor-Ferrando, Juan-Pascual [Universidad Politecnica de Valencia, Departamento de Proyectos de Ingenieria, Camino de vera s/n 46022 Valencia (Spain)

2010-08-15

In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. It is based on strategic objectives of the company and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity which seeks to assist managers of a big Electrical Company of Venezuela to distribute the annual budget among the possible improvement actions to be conducted on the electrical network of Caracas. A total of 15 network improvement actions grouped into three clusters according to the strategic objectives of the company have been analyzed using the Project Strategic Index (PSI) proposed. The approach combines the use of the Analytic Network Process (ANP) method with the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts' judgments on each of the indicators used into one Project Strategic Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts' estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional budget distribution techniques. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods. (author)

A Project Strategic Index proposal for portfolio selection in electrical company based on the Analytic Network Process

International Nuclear Information System (INIS)

Smith-Perera, Aida; Garcia-Melon, Monica; Poveda-Bautista, Rocio; Pastor-Ferrando, Juan-Pascual

2010-01-01

In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. It is based on strategic objectives of the company and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity which seeks to assist managers of a big Electrical Company of Venezuela to distribute the annual budget among the possible improvement actions to be conducted on the electrical network of Caracas. A total of 15 network improvement actions grouped into three clusters according to the strategic objectives of the company have been analyzed using the Project Strategic Index (PSI) proposed. The approach combines the use of the Analytic Network Process (ANP) method with the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts' judgments on each of the indicators used into one Project Strategic Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts' estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional budget distribution techniques. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods. (author)

Network Monitoring as a Streaming Analytics Problem

KAUST Repository

Gupta, Arpit

2016-11-02

Programmable switches make it easier to perform flexible network monitoring queries at line rate, and scalable stream processors make it possible to fuse data streams to answer more sophisticated queries about the network in real-time. Unfortunately, processing such network monitoring queries at high traffic rates requires both the switches and the stream processors to filter the traffic iteratively and adaptively so as to extract only that traffic that is of interest to the query at hand. Others have network monitoring in the context of streaming; yet, previous work has not closed the loop in a way that allows network operators to perform streaming analytics for network monitoring applications at scale. To achieve this objective, Sonata allows operators to express a network monitoring query by considering each packet as a tuple and efficiently partitioning each query between the switches and the stream processor through iterative refinement. Sonata extracts only the traffic that pertains to each query, ensuring that the stream processor can scale traffic rates of several terabits per second. We show with a simple example query involving DNS reflection attacks and traffic traces from one of the world\\'s largest IXPs that Sonata can capture 95% of all traffic pertaining to the query, while reducing the overall data rate by a factor of about 400 and the number of required counters by four orders of magnitude. Copyright 2016 ACM.

Sistem Informasi Manajemen Rantai Pasok Pariwisata Untuk Pembuatan Produk Wisata Pada Agen Tour dan Travel dengan Analisis Swot dan Metode Analytic Network Process

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Dwi Mustika Kusumawardani

2016-12-01

Full Text Available The development of services company in tourism is increasing. Therefore each tour & travel agent should be able to improve the quality of attractive and competitive products. This research builds a system analysis of supply chain management in the manufacturing of tour packages with SWOT analysis and Analytic Network Process (ANP. SWOT analysis is one way to decide marketing strategy for the company to able to face global competition. In this study, a SWOT analysis is used to select the best suppliers in tourism sector. Suppliers include: hotels, restaurants, attractions and accommodations. Combination of the best suppliers used as in one product of tour package. While the method of Analytic Network Process is used to rank the tour package has been obtained previously. In addition, this method is applied because it can provide information about the most influential of criteria in making tour package. This method conducted by looking at dependency relationship between among criteria. Then give them weight among criteria, sub-criteria and alternatives. The criteria used in the method of Analytic Network Process are: product, price, place and promotion. The results obtained from this research is the system analysis of supply chain management of tourism which capable of producing an attractive and competitive tour packages form of tour packages 1 with a value of 0.53. In addition, this information system provides information that the most influential criteria in making tour package is the product criteria with a value of 0.30. The next criterion which affects the making of attractive and competitive tour packages is price of criteria with a value of 0.28.

The Analytical Hierarchy Process

DEFF Research Database (Denmark)

Barfod, Michael Bruhn

2007-01-01

The technical note gathers the theory behind the Analytical Hierarchy Process (AHP) and present its advantages and disadvantages in practical use.......The technical note gathers the theory behind the Analytical Hierarchy Process (AHP) and present its advantages and disadvantages in practical use....

Analytical maximum-likelihood method to detect patterns in real networks

International Nuclear Information System (INIS)

Squartini, Tiziano; Garlaschelli, Diego

2011-01-01

In order to detect patterns in real networks, randomized graph ensembles that preserve only part of the topology of an observed network are systematically used as fundamental null models. However, the generation of them is still problematic. Existing approaches are either computationally demanding and beyond analytic control or analytically accessible but highly approximate. Here, we propose a solution to this long-standing problem by introducing a fast method that allows one to obtain expectation values and standard deviations of any topological property analytically, for any binary, weighted, directed or undirected network. Remarkably, the time required to obtain the expectation value of any property analytically across the entire graph ensemble is as short as that required to compute the same property using the adjacency matrix of the single original network. Our method reveals that the null behavior of various correlation properties is different from what was believed previously, and is highly sensitive to the particular network considered. Moreover, our approach shows that important structural properties (such as the modularity used in community detection problems) are currently based on incorrect expressions, and provides the exact quantities that should replace them.

Implementation of a communication and control network for the instruments of a nuclear analytical laboratory

International Nuclear Information System (INIS)

Cunya, Eduardo; Baltuano, Oscar; Bedregal, Patricia

2013-01-01

This paper describes the implementation of a communication network and control for a conventional laboratory instruments and nuclear analytical processes based on CAN open field bus to control devices and machines. Hardware components and software developed as well as installation and configuration tools for incorporating new instruments to the network re presented. (authors).

A Fuzzy analytical hierarchy process approach in irrigation networks maintenance

Science.gov (United States)

Riza Permana, Angga; Rintis Hadiani, Rr.; Syafi'i

2017-11-01

Ponorogo Regency has 440 Irrigation Area with a total area of 17,950 Ha. Due to the limited budget and lack of maintenance cause decreased function on the irrigation. The aim of this study is to make an appropriate system to determine the indices weighted of the rank prioritization criteria for irrigation network maintenance using a fuzzy-based methodology. The criteria that are used such as the physical condition of irrigation networks, area of service, estimated maintenance cost, and efficiency of irrigation water distribution. 26 experts in the field of water resources in the Dinas Pekerjaan Umum were asked to fill out the questionnaire, and the result will be used as a benchmark to determine the rank of irrigation network maintenance priority. The results demonstrate that the physical condition of irrigation networks criterion (W1) = 0,279 has the greatest impact on the assessment process. The area of service (W2) = 0,270, efficiency of irrigation water distribution (W4) = 0,249, and estimated maintenance cost (W3) = 0,202 criteria rank next in effectiveness, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess maintenance priority on irrigation network.

Evaluation of power plants in Turkey using Analytic Network Process (ANP)

International Nuclear Information System (INIS)

Atmaca, Ediz; Basar, Hasan Burak

2012-01-01

Energy is one of the most important parameters of the development of societies. Low cost, clean and secure energy supply is a common issue for all countries. Every country spends commercial and political effort to avoid not having sufficient energy and to ensure an uninterrupted energy supply. This study attempts to determine the suitability of existing power plants in Turkey and the plants that are being considered for establishment in the near future. The alternatives which are being considered are natural gas, wind, geothermal, hydroelectric, and coal/lignite energy plants as well as nuclear energy plants. By using the multi-criteria decision making technique of Analytic Network Process (ANP), a multi-criteria evaluations of six different energy plants were performed with respect to the major criteria such as technology and sustainability, economical suitability, life quality and socio-economic impacts. -- Highlights: ► The study attempted to lay out the criteria based on which power plant investments are evaluated. ► In the energy industry in Turkey and in the world, it is considerably difficult to access data on energy. ► This study will provide significant support for people working in the energy area and related decision makers in Turkey. ► The study is also thought to provide benefit decision makers in the world energy industry. ► It can provide great benefit in ensuring the security of the energy to be produced from power plant investments.

Predicting tax avoidance by means of social network analytics

NARCIS (Netherlands)

Jasmien, Lismont; Cardinaels, Eddy; Bruynseels, L.M.L.; De Groote, Sander; Baesens, B.; Lemahieu, W.; Vanthienen, J.

This study predicts tax avoidance by means of social network analytics. We extend previous literature by being the first to build a predictive model including a larger variation of network features. We construct a network of firms connected through shared board membership. Then, we apply three

Bilişsel Haritalama ve Analitik Serim Süreci (ASS Entegrasyonu(The Integration of Cognitive Mapping and Analytic Network Process

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Aşkın ÖZDAĞOĞLU

2010-01-01

Full Text Available The type of variables (qualitative or quantitative directly affect the construction of the model. Gaining the quantitative data for decision making problems may not be possible. Therefore, only the qualitative data are had to be considered within decision making process. Another problem is to make a decision by considering many interactive factors. Analytic Network Process (ANP is a technique which finds the most appropriate alternative in the multicriteria decision problems that have many options. In this study, concept mapping is used for determining the relationships among the main components that affect the product in a frozen foods company and ANP structure is created with the help of concept mapping. During the solving process, the importance levels of the criteria are obtained.

Distributed data networks: a blueprint for Big Data sharing and healthcare analytics.

Science.gov (United States)

Popovic, Jennifer R

2017-01-01

This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large-scale, multisite, healthcare-related distributed data network, the U.S. Food and Drug Administration-sponsored Sentinel Initiative. Analytic infrastructure-development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources. © 2016 New York Academy of Sciences.

PEMILIHAN STRATEGI PEMASARAN PADA PT. NYONYA MENEER DENGAN MENGGUNAKAN PENDEKATAN METODE ANALYTICAL NETWORK PROCESS (ANP DAN TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO AN IDEAL SOLUTION (TOPSIS

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Ary Arvianto

2014-01-01

Full Text Available Dalam mencapai suatu keunggulan kompetitif, suatu perusahaan membutuhkan suatu strategi pemasaran untuk membedakan dan memiliki nilai yang berbeda dari kompetitornya. Karena krusialnya peran strategi pemasaran dalam kelangsungan perusahaan, pihak manajemen akan mengalami kesulitan dalam memilih strategi pemasaran terbaik dari pilihan strategi yang ada. PT. Nyonya Meneer memproduksi banyak jenis produk, salah satu jenis produk unggulannya adalah produk jamu untuk wanita. Penjualan produk jamu wanita tidak menunjukkan peningkatan yang sesuai dengan target, bahkan cenderung stagnan. Kondisi ini menunjukkan bahwa strategi pemasaran yang selama ini diterapkan belum memberikan hasil yang maksimal karena tidak tercapainya target penjualan yang ada. Oleh karena itu, perlu adanya suatu pemilihan strategi pemasaran PT. Nyonya Meneer dengan melihat kriteria-kriteria yang mempengaruhi dalam proses pemilihan strategi pemasaran dengan menggunakan metode Analytical Network Process (ANP dan TOPSIS. Alternatif strategi pemasaran pada penelitian ini berdasarkan strategi generik Porter. Hasil dari penelitian ini adalah bahwa strategi terpilih bagi PT. Nyonya Meneer adalah strategi segmentasi. Segmen yang direkomendasikan adalah wanita remaja hingga dewasa dengan pendapatan menengah dan menengah ke atas. Kata Kunci : analytical network process (ANP, pemilihan strategi pemasaran, strategi generik porter, TOPSIS Abstract In achieving competitive advantage, a company need a marketing strategy in order to differentiate from its competitor. A marketing strategy decision making is essential for marketing strategist to determine the most appropriate marketing strategy in effecient manner. PT. Nyonya Meneer is one of the biggest company that produce jamu in Indonesia. Jamu for women is the most popular product of PT. Nyonya Meneer. Sales of jamu for women does not show desirable increase, even tend to stagnan. It indicates  that current marketing strategy does not give

A novel analytical characterization for short-term plasticity parameters in spiking neural networks.

Science.gov (United States)

O'Brien, Michael J; Thibeault, Corey M; Srinivasa, Narayan

2014-01-01

Short-term plasticity (STP) is a phenomenon that widely occurs in the neocortex with implications for learning and memory. Based on a widely used STP model, we develop an analytical characterization of the STP parameter space to determine the nature of each synapse (facilitating, depressing, or both) in a spiking neural network based on presynaptic firing rate and the corresponding STP parameters. We demonstrate consistency with previous work by leveraging the power of our characterization to replicate the functional volumes that are integral for the previous network stabilization results. We then use our characterization to predict the precise transitional point from the facilitating regime to the depressing regime in a simulated synapse, suggesting in vitro experiments to verify the underlying STP model. We conclude the work by integrating our characterization into a framework for finding suitable STP parameters for self-sustaining random, asynchronous activity in a prescribed recurrent spiking neural network. The systematic process resulting from our analytical characterization improves the success rate of finding the requisite parameters for such networks by three orders of magnitude over a random search.

A Hybrid Approach for Reliability Analysis Based on Analytic Hierarchy Process and Bayesian Network

International Nuclear Information System (INIS)

Zubair, Muhammad

2014-01-01

By using analytic hierarchy process (AHP) and Bayesian Network (BN) the present research signifies the technical and non-technical issues of nuclear accidents. The study exposed that the technical faults was one major reason of these accidents. Keep an eye on other point of view it becomes clearer that human behavior like dishonesty, insufficient training, and selfishness are also play a key role to cause these accidents. In this study, a hybrid approach for reliability analysis based on AHP and BN to increase nuclear power plant (NPP) safety has been developed. By using AHP, best alternative to improve safety, design, operation, and to allocate budget for all technical and non-technical factors related with nuclear safety has been investigated. We use a special structure of BN based on the method AHP. The graphs of the BN and the probabilities associated with nodes are designed to translate the knowledge of experts on the selection of best alternative. The results show that the improvement in regulatory authorities will decrease failure probabilities and increase safety and reliability in industrial area.

Cutaneous leishmaniasis susceptibility mapping using multi-criteria decision-making techniques, analytic hierarchy process (AHP and analytic network process (ANP

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SEYED VAHID RAZAVI TERMEH

2018-02-01

Full Text Available Background & objective:Cutaneous leech is one of the six major diseases and an example of epidemic diseases in tropical regions. Prevalence and spread of this disease is affected by environmental factors and climatic conditions as well as economic, social and cultural issues. In this research, Analytic Hierarchy Process and network analyzes are used to prepare susceptible cutaneous leeches map. Considering high incidence of cutaneous leech in Khuzestan province, Izeh city was selected as a case study.   Materials & Methods: For this purpose, the number of patients affected by this disease in Izeh was obtained from the Provincial Health Center from 2009 to 2014. Information layers of elevation, rainfall, temperature, humidity, distance from river, distance from rural areas and land use were identified as effective parameter and their maps were prepared in GIS environment. Parameters were compared in pairs by using AHP and ANP and weight of each factors determining their impacts was calculated in Expert Choice and Super Decision software. Then these parameters were combined based on their obtained weights in ArcGIS software and the final cutaneous leech map was prepared. Evaluation of these methods was performed using relative operation curve (ROC and 16 points related to leech disease. Result: The results of weighting effective parameters using AHP and ANP showed that the highest weight is related to elevation, temperature and rainfall parameters, respectively. The results of ROC assessment showed that in preparing the map, ANP had an accuracy of 87.8% and AHP had an accuracy of 68.9%. Conclusion:The results of ANP showed that this model had suitable accuracy in preparing susceptible cutaneous leech map and AHP had moderate accuracy in preparing susceptible cutaneous leech map.

Epidemic processes in complex networks

Science.gov (United States)

Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

2015-07-01

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

Product design planning with the analytic hierarchy process in inter-organizational networks

NARCIS (Netherlands)

Hummel, J. Marjan; van Rossum, Wouter; Verkerke, Gijsbertus Jacob; Rakhorst, Gerhard

2002-01-01

In the second half of inter–organizational product development, the new product is likely to face significant design changes. Our study focused on the adequacy of the analytic hierarchy process (AHP) to support the collaborative partners to steer and align the accompanying design activities. It

Product design planning with the analytic hierarchy process in inter-organizational networks

NARCIS (Netherlands)

Hummel, J.M.; van Rossum, Wouter; Verkerke, Bart; Rakhorst, G

2002-01-01

In the second half of inter-organizational product developments the new product is likely to face significant design changes. Our study focused on the adequacy of the analytic hierarchy process (AHP) to support the collaborative partners to steer and align the accompanying design activities. It

Using Streaming Analytics for Effective Real Time Network Visibility -

Science.gov (United States)

on in your network right now. Certainly the other thing that we talked about on the big data side was [inaudible] data. So now we'll drill into - so this is all the traffic from the internal network to the taking a streaming analytics approach to network traffic analysis. So we can go to the next - there we go

Evaluation of soil erosion risk using Analytic Network Process and GIS: a case study from Spanish mountain olive plantations.

Science.gov (United States)

Nekhay, Olexandr; Arriaza, Manuel; Boerboom, Luc

2009-07-01

The study presents an approach that combined objective information such as sampling or experimental data with subjective information such as expert opinions. This combined approach was based on the Analytic Network Process method. It was applied to evaluate soil erosion risk and overcomes one of the drawbacks of USLE/RUSLE soil erosion models, namely that they do not consider interactions among soil erosion factors. Another advantage of this method is that it can be used if there are insufficient experimental data. The lack of experimental data can be compensated for through the use of expert evaluations. As an example of the proposed approach, the risk of soil erosion was evaluated in olive groves in Southern Spain, showing the potential of the ANP method for modelling a complex physical process like soil erosion.

Meta-analytically informed network analysis of resting state FMRI reveals hyperconnectivity in an introspective socio-affective network in depression.

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Leonhard Schilbach

Full Text Available Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.

Selecting the most appropriate maintenance strategies using fuzzy Analytic Network Process: A case study of Saipa vehicle industry

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Mina Rahimi

2014-04-01

Full Text Available It is necessary for companies and industries to select the most appropriate maintenance strategy to increase the reliability and safety level with reasonable cost. The primary objective of this paper is to assess different maintenance strategies and to select the best and the most appropriate alternatives for Saipa vehicle industry in Tehran, Iran. For this purpose, we simultaneously consider numerous conflicting objectives and constraints. In this study to counter with this conflicting and to consider the dependency among the qualitative and quantitative criteria and sub-criteria, an integration of Analytic Network Process (ANP and fuzzy set theory are considered. Therefore, factors playing important role in selecting the best maintenance strategy are determined by reviewing the research literature and interviewing with the experts by Delphi technique. Considering the relations among different factors, a network with 4 criteria and 28 sub-criteria are proposed. In the next step, ANP technique is applied for ranking effective factors in evolution of appropriate maintenance strategy. Results reveal that the best maintenance strategy for fixture body of pride (setter is corrective maintenance.

Generalized epidemic process on modular networks.

Science.gov (United States)

Chung, Kihong; Baek, Yongjoo; Kim, Daniel; Ha, Meesoon; Jeong, Hawoong

2014-05-01

Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.

Visual analytics for multimodal social network analysis: a design study with social scientists.

Science.gov (United States)

Ghani, Sohaib; Kwon, Bum Chul; Lee, Seungyoon; Yi, Ji Soo; Elmqvist, Niklas

2013-12-01

Social network analysis (SNA) is becoming increasingly concerned not only with actors and their relations, but also with distinguishing between different types of such entities. For example, social scientists may want to investigate asymmetric relations in organizations with strict chains of command, or incorporate non-actors such as conferences and projects when analyzing coauthorship patterns. Multimodal social networks are those where actors and relations belong to different types, or modes, and multimodal social network analysis (mSNA) is accordingly SNA for such networks. In this paper, we present a design study that we conducted with several social scientist collaborators on how to support mSNA using visual analytics tools. Based on an openended, formative design process, we devised a visual representation called parallel node-link bands (PNLBs) that splits modes into separate bands and renders connections between adjacent ones, similar to the list view in Jigsaw. We then used the tool in a qualitative evaluation involving five social scientists whose feedback informed a second design phase that incorporated additional network metrics. Finally, we conducted a second qualitative evaluation with our social scientist collaborators that provided further insights on the utility of the PNLBs representation and the potential of visual analytics for mSNA.

Optimal Information Processing in Biochemical Networks

Science.gov (United States)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

An Analytic Network Process approach for the environmental aspect selection problem — A case study for a hand blender

Energy Technology Data Exchange (ETDEWEB)

Bereketli Zafeirakopoulos, Ilke, E-mail: ibereketli@gsu.edu.tr; Erol Genevois, Mujde, E-mail: merol@gsu.edu.tr

2015-09-15

Life Cycle Assessment is a tool to assess, in a systematic way, the environmental aspects and its potential environmental impacts and resources used throughout a product's life cycle. It is widely accepted and considered as one of the most powerful tools to support decision-making processes used in ecodesign and sustainable production in order to learn about the most problematic parts and life cycle phases of a product and to have a projection for future improvements. However, since Life Cycle Assessment is a cost and time intensive method, companies do not intend to carry out a full version of it, except for large corporate ones. Especially for small and medium sized enterprises, which do not have enough budget for and knowledge on sustainable production and ecodesign approaches, focusing only on the most important possible environmental aspect is unavoidable. In this direction, finding the right environmental aspect to work on is crucial for the companies. In this study, a multi-criteria decision-making methodology, Analytic Network Process is proposed to select the most relevant environmental aspect. The proposed methodology aims at providing a simplified environmental assessment to producers. It is applied for a hand blender, which is a member of the Electrical and Electronic Equipment family. The decision criteria for the environmental aspects and relations of dependence are defined. The evaluation is made by the Analytic Network Process in order to create a realistic approach to inter-dependencies among the criteria. The results are computed via the Super Decisions software. Finally, it is observed that the procedure is completed in less time, with less data, with less cost and in a less subjective way than conventional approaches. - Highlights: • We present a simplified environmental assessment methodology to support LCA. • ANP is proposed to select the most relevant environmental aspect. • ANP deals well with the interdependencies between aspects

An Analytic Network Process approach for the environmental aspect selection problem — A case study for a hand blender

International Nuclear Information System (INIS)

Bereketli Zafeirakopoulos, Ilke; Erol Genevois, Mujde

2015-01-01

Life Cycle Assessment is a tool to assess, in a systematic way, the environmental aspects and its potential environmental impacts and resources used throughout a product's life cycle. It is widely accepted and considered as one of the most powerful tools to support decision-making processes used in ecodesign and sustainable production in order to learn about the most problematic parts and life cycle phases of a product and to have a projection for future improvements. However, since Life Cycle Assessment is a cost and time intensive method, companies do not intend to carry out a full version of it, except for large corporate ones. Especially for small and medium sized enterprises, which do not have enough budget for and knowledge on sustainable production and ecodesign approaches, focusing only on the most important possible environmental aspect is unavoidable. In this direction, finding the right environmental aspect to work on is crucial for the companies. In this study, a multi-criteria decision-making methodology, Analytic Network Process is proposed to select the most relevant environmental aspect. The proposed methodology aims at providing a simplified environmental assessment to producers. It is applied for a hand blender, which is a member of the Electrical and Electronic Equipment family. The decision criteria for the environmental aspects and relations of dependence are defined. The evaluation is made by the Analytic Network Process in order to create a realistic approach to inter-dependencies among the criteria. The results are computed via the Super Decisions software. Finally, it is observed that the procedure is completed in less time, with less data, with less cost and in a less subjective way than conventional approaches. - Highlights: • We present a simplified environmental assessment methodology to support LCA. • ANP is proposed to select the most relevant environmental aspect. • ANP deals well with the interdependencies between aspects

An environmental pressure index proposal for urban development planning based on the analytic network process

International Nuclear Information System (INIS)

Gomez-Navarro, Tomas; Garcia-Melon, Monica; Acuna-Dutra, Silvia; Diaz-Martin, Diego

2009-01-01

This paper introduces a new approach to prioritize urban planning projects according to their environmental pressure in an efficient and reliable way. It is based on the combination of three procedures: (i) the use of environmental pressure indicators, (ii) the aggregation of the indicators in an Environmental Pressure Index by means of the Analytic Network Process method (ANP) and (iii) the interpretation of the information obtained from the experts during the decision-making process. The method has been applied to a proposal for urban development of La Carlota airport in Caracas (Venezuela). There are three options which are currently under evaluation. They include a Health Club, a Residential Area and a Theme Park. After a selection process the experts chose the following environmental pressure indicators as ANP criteria for the project life cycle: used land area, population density, energy consumption, water consumption and waste generation. By using goal-oriented questionnaires designed by the authors, the experts determined the importance of the criteria, the relationships among criteria, and the relationships between the criteria and the urban development alternatives. The resulting data showed that water consumption is the most important environmental pressure factor, and the Theme Park project is by far the urban development alternative which exerts the least environmental pressure on the area. The participating experts coincided in appreciating the technique proposed in this paper is useful and, for ranking ordering these alternatives, an improvement from traditional techniques such as environmental impact studies, life-cycle analysis, etc.

RISIKO RANTAI PASOK KAKAO DI INDONESIA DENGAN METODE ANALYTIC NETWORK PROCESS DAN FAILURE MODE EFFECT ANALYSIS TERINTEGRASI

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Harumi Aini

2015-03-01

Full Text Available Cocoa is one of the plantation commodities whose role is quite important for the national economy of Indonesia. However, the cocoa industry faces several problems including the various risks involved in the cocoa supply chain. The aim of this study were: 1 Identify the various risks involved in the cocoa supply chain, 2 analyze and evaluate the supply chain actors members with the highest risk in the cocoa supply chain management, and 3 understand how to evaluate and mitigate the highest risk in the cocoa supply chain effectively and efficiently. An Integrated Analytic Network Process (ANP and Weighted Failure Mode Effect Analysis (WFMEA method will be used to determine and analyze the highest risk in the cocoa supply chain. The results of the priority of the members of the value chain in the cocoa supply chain risk management are the farmer (0.408 with the risk of having the greatest priority is production risk (0.221. Risk control could be done by improving the productivity and competitiveness of cocoa.Keywords: ANP, FMEA, cocoa, risk management, supply chainABSTRAKKakao merupakan salah satu komoditas perkebunan yang peranannya cukup penting bagi perekonomian Indonesia. Industri kakao menghadapi beberapa masalah termasuk berbagai risiko yang timbul dalam rantai pasokan kakao. Tujuan penelitian ini adalah 1 mengidentifikasi macam-macam risiko pada rantai pasok kakao, 2 menganalisis dan mengevaluasi anggota pelaku rantai pasok dengan risiko tertinggi dalam manajemen rantai pasok kakao, dan 3 mengetahui cara mengevaluasi dan memitigasi risiko tertinggi pada rantai pasok kakao dengan efektif dan efisien. Metode Analytic Network Process (ANP dan Weighted Failure Mode Effect Analysis (WFMEA terintegrasi digunakan untuk mengetahui dan menganalisis risiko tertinggi dalam rantai pasokan kakao. Hasil prioritas anggota pelaku rantai pasok dalam manajemen risiko rantai pasokan kakao petani (0,408 dengan risiko yang memiliki prioritas terbesar adalah

The governance of regional networks in the process of European integration

OpenAIRE

Cappellin, Riccardo

2001-01-01

The paper illustrates the model of territorial networks and it investigates the role of institutions in a bottom-up approach of economic and institutional integration aiming to tackle the negative impacts of the globalization process on the economic development. The first chapter illustrates in analytical terms the model of territorial networks and the multidimen-sional nature of the process of integration, in a regional and international setting and it contrasts it with the traditional neocl...

Supplier selection in supply chain management using analytical network process for Indonesian cement industry

Science.gov (United States)

Ismail, A. H.; Mahardika, R. Z. Z.

2017-12-01

Supply chain management has increased more significance with the impact of globalization. In the present worldwide market, well-managed supply chain is a standout amongst the most vital requirement to be more competitive in the market. For any organization incorporate cement industry, the most critical decision in initial process of supply chain management is to buy products, materials or services from suppliers. So the role of suppliers is irrefutable important in the global aggressive markets. Appropriate decision of supplier selection can lead to reducing cost in supply chain management. However, it is becoming more complex because of existing various criteria and involving the suitable experts in the company to make valid decision in accordance with its criteria. In this study, the supplier selection of an Indonesia’s leading cement company is analyzed by using one of the popular multi-criteria decision making method, Saaty’s analytical network process (ANP). It is employed for the selection of the best alternative among three suppliers of pasted bag. Supplier with the highest rank comes from several major steps from building the relationship between various criteria to rating the alternatives with the help of experts from the company. The results show that, Communication capability, Flexible payment terms, Ability to meet delivery quantities are the most important criteria in the pasted bag supplier selection in Indonesian cement industry with 0.155, 0.110 and 0.1 ANP coefficient respectively. And based on the ANP coefficient values in limit supermatrix, the A2 or supplier 2 had the highest score with 64.7% or 0.13 ANP coefficient.

What is Impulse Buying? An analytical network processing framework for prioritizing factors affecting impulse buying

Directory of Open Access Journals (Sweden)

Javad Siahkali Moradi

2012-08-01

Full Text Available One of the most important issues affecting profitability is to determine the impact of different factors influencing purchasing activities. In this paper, we perform an extensive literature survey to detect different purchasing factors influencing customers' behavior. The factors are categorized in three different groups and they are ranked using analytical network process. The results of our survey indicate that three factors of personal, product and situational play important roles in purchasing impulse. The personal item includes different factors where demographic characteristic factors receive the highest ranking (35% followed by other factors are feelings, excitement and fun, self identify, education and novelty. There are also three sub-factors associated with demographic characteristics including gender, age and race and the weights are 0.46748, 0.42668 and 0.10584, respectively, which means gender is the most important factor followed by age and race. Finally, the other factor is associated with situational factors' group, which includes presence of others, culture, design of store, time available, local market condition, sales staff and self service with the relative importance of 0.04296, 0.08733, 0.12130, 0.22217, 0.05643, 0.15346 and 0.31635, respectively.

Tourism infrastructure development prioritization in Sabang Island using analytic network process methods

Science.gov (United States)

Rani, Hafnidar A.; Afifuddin, Moch.; Akbar, Herry

2017-11-01

Indonesia has been widely known as an archipelago country, with its geographical location is at the equator, which make this country as a tropical country. It has the topography of diverse islands which consist of lakes, mountains, and one of countries which have the longest coastline. This condition cause Indonesia has various beautiful tourism objects and become the attraction to the international tourists to come. Indonesia still has the other islands which are as beautiful as Bali Island offering different beauties. One of them is an island located in the most western island of Indonesia, which becomes the zero point of the country. It is Sabang Island in Aceh Province. Sabang Island is the small volcanic island located in the most western island of Sumatra. Infrastructure becomes the basic device in supporting this tourism aspect, which the buildings and service institutions play the important role in appropriate managing of economic and community needs. The problem in this study is how to determine the priority of tourism infrastructure development in Sabang Island. The objective of this study is to determine the priority rank of tourism infrastructure development and the priority rank of the potential investment in Sabang Island to be developed. The ranking results of the Analytic Network Process (ANP) calculations of tourism locations/zones and tourism supporting infrastructure found that Teupin Layeu and Gapang, and Rubiah Island have the highest priority to be developed in the hotel/accommodation infrastructure which scores are 0.02589 and 0.02120. Then followed by parking infrastructure in Teupin Layeu and access road to Km 0 which became as the main priority determined by Sabang government which scores are 0.01750 and 0.01618.

The analyst's participation in the analytic process.

Science.gov (United States)

Levine, H B

1994-08-01

The analyst's moment-to-moment participation in the analytic process is inevitably and simultaneously determined by at least three sets of considerations. These are: (1) the application of proper analytic technique; (2) the analyst's personally-motivated responses to the patient and/or the analysis; (3) the analyst's use of him or herself to actualise, via fantasy, feeling or action, some aspect of the patient's conflicts, fantasies or internal object relationships. This formulation has relevance to our view of actualisation and enactment in the analytic process and to our understanding of a series of related issues that are fundamental to our theory of technique. These include the dialectical relationships that exist between insight and action, interpretation and suggestion, empathy and countertransference, and abstinence and gratification. In raising these issues, I do not seek to encourage or endorse wild analysis, the attempt to supply patients with 'corrective emotional experiences' or a rationalisation for acting out one's countertransferences. Rather, it is my hope that if we can better appreciate and describe these important dimensions of the analytic encounter, we can be better prepared to recognise, understand and interpret the continual streams of actualisation and enactment that are embedded in the analytic process. A deeper appreciation of the nature of the analyst's participation in the analytic process and the dimensions of the analytic process to which that participation gives rise may offer us a limited, although important, safeguard against analytic impasse.

Socio-semantic Networks of Research Publications in the Learning Analytics Community

NARCIS (Netherlands)

Fazeli, Soude; Drachsler, Hendrik; Sloep, Peter

2013-01-01

Fazeli, S., Drachsler, H., & Sloep, P. B. (2013). Socio-semantic Networks of Research Publications in the Learning Analytics Community. In M. d'Aquin, S. Dietze, H. Drachsler, E. Herder, & D. Taibi (Eds.), Linked data challenge, Learning Analytic and Knowledge (LAK13) (pp. 6-10). Vol. 974, Leuven,

A Visual Analytics Technique for Identifying Heat Spots in Transportation Networks

Directory of Open Access Journals (Sweden)

Marian Sorin Nistor

2016-12-01

Full Text Available The decision takers of the public transportation system, as part of urban critical infrastructures, need to increase the system resilience. For doing so, we identified analysis tools for biological networks as an adequate basis for visual analytics in that domain. In the paper at hand we therefore translate such methods for transportation systems and show the benefits by applying them on the Munich subway network. Here, visual analytics is used to identify vulnerable stations from different perspectives. The applied technique is presented step by step. Furthermore, the key challenges in applying this technique on transportation systems are identified. Finally, we propose the implementation of the presented features in a management cockpit to integrate the visual analytics mantra for an adequate decision support on transportation systems.

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

Science.gov (United States)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

Process analytical technology (PAT) for biopharmaceuticals

DEFF Research Database (Denmark)

Glassey, Jarka; Gernaey, Krist; Clemens, Christoph

2011-01-01

Process analytical technology (PAT), the regulatory initiative for building in quality to pharmaceutical manufacturing, has a great potential for improving biopharmaceutical production. The recommended analytical tools for building in quality, multivariate data analysis, mechanistic modeling, novel...

Modern Adaptive Analytics Approach to Lowering Seismic Network Detection Thresholds

Science.gov (United States)

Johnson, C. E.

2017-12-01

Modern seismic networks present a number of challenges, but perhaps most notably are those related to 1) extreme variation in station density, 2) temporal variation in station availability, and 3) the need to achieve detectability for much smaller events of strategic importance. The first of these has been reasonably addressed in the development of modern seismic associators, such as GLASS 3.0 by the USGS/NEIC, though some work still remains to be done in this area. However, the latter two challenges demand special attention. Station availability is impacted by weather, equipment failure or the adding or removing of stations, and while thresholds have been pushed to increasingly smaller magnitudes, new algorithms are needed to achieve even lower thresholds. Station availability can be addressed by a modern, adaptive architecture that maintains specified performance envelopes using adaptive analytics coupled with complexity theory. Finally, detection thresholds can be lowered using a novel approach that tightly couples waveform analytics with the event detection and association processes based on a principled repicking algorithm that uses particle realignment for enhanced phase discrimination.

The Use of Analytic Network Process for Risk Assessment in Production of Renewable Energy from Agriculture Biomass in Latvia

Directory of Open Access Journals (Sweden)

Sandija Rivza

2013-02-01

Full Text Available Risk assessment is an important factor for successful and sustainable entrepreneurship of bioenergy production that has become one of the priorities in energy sector of Latvia. Promotion of the use of renewable energy is included as one of the strategic goals for European Union (EU and Latvia. As this field of energy production in Latvia is rather new and scantily explored there are many risk factors arising in different stages of production, starting with planning and building of a bioreactor and ending with production and further use and distribution of energy. The present research focuses on risk assessment in renewable energy production form biomass as this kind of energy is seen as a perspective source for renewable energy under the conditions of Latvia. A risk assessment module for renewable energy production made by using the Analytic Network Process (ANP software is described in the paper.

Evaluation methodology for comparing memory and communication of analytic processes in visual analytics

Energy Technology Data Exchange (ETDEWEB)

Ragan, Eric D [ORNL; Goodall, John R [ORNL

2014-01-01

Provenance tools can help capture and represent the history of analytic processes. In addition to supporting analytic performance, provenance tools can be used to support memory of the process and communication of the steps to others. Objective evaluation methods are needed to evaluate how well provenance tools support analyst s memory and communication of analytic processes. In this paper, we present several methods for the evaluation of process memory, and we discuss the advantages and limitations of each. We discuss methods for determining a baseline process for comparison, and we describe various methods that can be used to elicit process recall, step ordering, and time estimations. Additionally, we discuss methods for conducting quantitative and qualitative analyses of process memory. By organizing possible memory evaluation methods and providing a meta-analysis of the potential benefits and drawbacks of different approaches, this paper can inform study design and encourage objective evaluation of process memory and communication.

Evaluating water management strategies in watersheds by new hybrid Fuzzy Analytical Network Process (FANP) methods

Science.gov (United States)

RazaviToosi, S. L.; Samani, J. M. V.

2016-03-01

Watersheds are considered as hydrological units. Their other important aspects such as economic, social and environmental functions play crucial roles in sustainable development. The objective of this work is to develop methodologies to prioritize watersheds by considering different development strategies in environmental, social and economic sectors. This ranking could play a significant role in management to assign the most critical watersheds where by employing water management strategies, best condition changes are expected to be accomplished. Due to complex relations among different criteria, two new hybrid fuzzy ANP (Analytical Network Process) algorithms, fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy max-min set methods are used to provide more flexible and accurate decision model. Five watersheds in Iran named Oroomeyeh, Atrak, Sefidrood, Namak and Zayandehrood are considered as alternatives. Based on long term development goals, 38 water management strategies are defined as subcriteria in 10 clusters. The main advantage of the proposed methods is its ability to overcome uncertainty. This task is accomplished by using fuzzy numbers in all steps of the algorithms. To validate the proposed method, the final results were compared with those obtained from the ANP algorithm and the Spearman rank correlation coefficient is applied to find the similarity in the different ranking methods. Finally, the sensitivity analysis was conducted to investigate the influence of cluster weights on the final ranking.

Laser-based analytical monitoring in nuclear-fuel processing plants

International Nuclear Information System (INIS)

Hohimer, J.P.

1978-09-01

The use of laser-based analytical methods in nuclear-fuel processing plants is considered. The species and locations for accountability, process control, and effluent control measurements in the Coprocessing, Thorex, and reference Purex fuel processing operations are identified and the conventional analytical methods used for these measurements are summarized. The laser analytical methods based upon Raman, absorption, fluorescence, and nonlinear spectroscopy are reviewed and evaluated for their use in fuel processing plants. After a comparison of the capabilities of the laser-based and conventional analytical methods, the promising areas of application of the laser-based methods in fuel processing plants are identified

Network performance and fault analytics for LTE wireless service providers

CERN Document Server

Kakadia, Deepak; Gilgur, Alexander

2017-01-01

 This book is intended to describe how to leverage emerging technologies big data analytics and SDN, to address challenges specific to LTE and IP network performance and fault management data in order to more efficiently manage and operate an LTE wireless networks. The proposed integrated solutions permit the LTE network service provider to operate entire integrated network, from RAN to Core , from UE to application service, as one unified system and correspondingly collect and align disparate key metrics and data, using an integrated and holistic approach to network analysis. The LTE wireless network performance and fault involves the network performance and management of network elements in EUTRAN, EPC and IP transport components, not only as individual components, but also as nuances of inter-working of these components. The key metrics for EUTRAN include radio access network accessibility, retainability, integrity, availability and mobility. The key metrics for EPC include MME accessibility, mobility and...

Data Analytics in CRM Processes: A Literature Review

Directory of Open Access Journals (Sweden)

Gončarovs Pāvels

2017-12-01

Full Text Available Nowadays, the data scarcity problem has been supplanted by the data deluge problem. Marketers and Customer Relationship Management (CRM specialists have access to rich data on consumer behaviour. The current challenge is effective utilisation of these data in CRM processes and selection of appropriate data analytics techniques. Data analytics techniques help find hidden patterns in data. The present paper explores the characteristics of data analytics as the integrated tool in CRM for sales managers. The paper aims at analysing some of the different analytics methods and tools which can be used for continuous improvement of CRM processes. A systematic literature has been conducted to achieve this goal. The results of the review highlight the most frequently considered CRM processes in the context of data analytics.

Statistically qualified neuro-analytic failure detection method and system

Science.gov (United States)

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

2002-03-02

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

Application of on-line analytical processing technique in accelerator

International Nuclear Information System (INIS)

Xie Dong; Li Weimin; He Duohui; Liu Gongfa; Xuan Ke

2005-01-01

A method of application of the on-line analytical processing technique in accelerator is described, which includes data pre-processing, the process of constructing of data warehouse and on-line analytical processing. (authors)

A geovisual analytic approach to understanding geo-social relationships in the international trade network.

Science.gov (United States)

Luo, Wei; Yin, Peifeng; Di, Qian; Hardisty, Frank; MacEachren, Alan M

2014-01-01

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly 'balkanized' (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

Mapping debris flow susceptibility using analytical network process in Kodaikkanal Hills, Tamil Nadu (India)

Science.gov (United States)

Sujatha, Evangelin Ramani; Sridhar, Venkataramana

2017-12-01

Rapid debris flows, a mixture of unconsolidated sediments and water travelling at speeds > 10 m/s are the most destructive water related mass movements that affect hill and mountain regions. The predisposing factors setting the stage for the event are the availability of materials, type of materials, stream power, slope gradient, aspect and curvature, lithology, land use and land cover, lineament density, and drainage. Rainfall is the most common triggering factor that causes debris flow in the Palar subwatershed and seismicity is not considered as it is a stable continental region and moderate seismic zone. Also, there are no records of major seismic activities in the past. In this study, one of the less explored heuristic methods known as the analytical network process (ANP) is used to map the spatial propensity of debris flow. This method is based on top-down decision model and is a multi-criteria, decision-making tool that translates subjective assessment of relative importance to weights or scores and is implemented in the Palar subwatershed which is part of the Western Ghats in southern India. The results suggest that the factors influencing debris flow susceptibility in this region are the availability of material on the slope, peak flow, gradient of the slope, land use and land cover, and proximity to streams. Among all, peak discharge is identified as the chief factor causing debris flow. The use of micro-scale watersheds demonstrated in this study to develop the susceptibility map can be very effective for local level planning and land management.

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

Science.gov (United States)

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

Social Sensor Analytics: Making Sense of Network Models in Social Media

Energy Technology Data Exchange (ETDEWEB)

Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.; Sego, Landon H.; Corley, Courtney D.

2015-07-27

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

Analytical Model based on Green Criteria for Optical Backbone Network Interconnection

DEFF Research Database (Denmark)

Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Pedersen, Jens Myrup

2011-01-01

Key terms such as Global warming, Green House Gas emissions, or Energy efficiency are currently on the scope of scientific research. Regarding telecommunications networks, wireless applications, routing protocols, etc. are being designed following this new “Green” trend. This work contributes...... to the evaluation of the environmental impact of networks from physical interconnection point of view. Networks deployment, usage, and disposal are analyzed as contributing elements to ICT’s (Information and Communications Technology) CO2 emissions. This paper presents an analytical model for evaluating...

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

KAUST Repository

Alfadly, Modar

2018-01-01

Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

KAUST Repository

Alfadly, Modar M.

2018-04-12

Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks.

Science.gov (United States)

Harris, Daniel R; Baus, Adam D; Harper, Tamela J; Jarrett, Traci D; Pollard, Cecil R; Talbert, Jeffery C

2016-08-01

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

Fast analytical scatter estimation using graphics processing units.

Science.gov (United States)

Ingleby, Harry; Lippuner, Jonas; Rickey, Daniel W; Li, Yue; Elbakri, Idris

2015-01-01

To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

PT. Tira Austenite, Tbk dan Analisis Kinerja Perusahaan Ekspedisi dalam Perspektif Supply Chain dan Metode Analytic Network Process (ANP

Directory of Open Access Journals (Sweden)

Khristian Edi Nugroho Soebandrija

2015-06-01

Full Text Available PT. TIRA AUSTENITE, Tbk (PTATbk and other companies in the field of supply chain require coordination pertaining cross functional and cross collaboration. The mentioned collaboration is required especially for Expedition Company. The performance analysis of Expedition Company, including PTATbk is needed to face the global competition. Company contribution generally, and in particular for Empirical Study toward PTATBK can lead to the problem solving and performance improvement, which covers selecting optimal expedition company and efficient time to dispatch product from existing route to be integrated into the core essence of this research pertaining PTATbk. The mentioned research refers to Empirical Study dan Managerial Implications through books and journals as reference in the Research Methodology. The focus of this researchmethodology is the Analytic Network Process (ANP; criteria of Price and Service; and other important criteria that support the performance analysis within PTATbk. Software ARENA Simulation plays vital role in this research that has the conclusion and recommendation toward problem solving and performance improvement that are translated into benefits versus risks and its form of % and the currency of IDR and/or USD.

Analytic information processing style in epilepsy patients.

Science.gov (United States)

Buonfiglio, Marzia; Di Sabato, Francesco; Mandillo, Silvia; Albini, Mariarita; Di Bonaventura, Carlo; Giallonardo, Annateresa; Avanzini, Giuliano

2017-08-01

Relevant to the study of epileptogenesis is learning processing, given the pivotal role that neuroplasticity assumes in both mechanisms. Recently, evoked potential analyses showed a link between analytic cognitive style and altered neural excitability in both migraine and healthy subjects, regardless of cognitive impairment or psychological disorders. In this study we evaluated analytic/global and visual/auditory perceptual dimensions of cognitive style in patients with epilepsy. Twenty-five cryptogenic temporal lobe epilepsy (TLE) patients matched with 25 idiopathic generalized epilepsy (IGE) sufferers and 25 healthy volunteers were recruited and participated in three cognitive style tests: "Sternberg-Wagner Self-Assessment Inventory", the C. Cornoldi test series called AMOS, and the Mariani Learning style Questionnaire. Our results demonstrate a significant association between analytic cognitive style and both IGE and TLE and respectively a predominant auditory and visual analytic style (ANOVA: p values <0,0001). These findings should encourage further research to investigate information processing style and its neurophysiological correlates in epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimization of hot water transport and distribution networks by analytical method: OPTAL program

International Nuclear Information System (INIS)

Barreau, Alain; Caizergues, Robert; Moret-Bailly, Jean

1977-06-01

This report presents optimization studies of hot water transport and distribution network by minimizing operating cost. Analytical optimization is used: Lagrange's method of undetermined multipliers. Optimum diameter of each pipe is calculated for minimum network operating cost. The characteristics of the computer program used for calculations, OPTAL, are given in this report. An example of network is calculated and described: 52 branches and 27 customers. Results are discussed [fr

Interacting Social Processes on Interconnected Networks.

Directory of Open Access Journals (Sweden)

Lucila G Alvarez-Zuzek

Full Text Available We propose and study a model for the interplay between two different dynamical processes -one for opinion formation and the other for decision making- on two interconnected networks A and B. The opinion dynamics on network A corresponds to that of the M-model, where the state of each agent can take one of four possible values (S = -2,-1, 1, 2, describing its level of agreement on a given issue. The likelihood to become an extremist (S = ±2 or a moderate (S = ±1 is controlled by a reinforcement parameter r ≥ 0. The decision making dynamics on network B is akin to that of the Abrams-Strogatz model, where agents can be either in favor (S = +1 or against (S = -1 the issue. The probability that an agent changes its state is proportional to the fraction of neighbors that hold the opposite state raised to a power β. Starting from a polarized case scenario in which all agents of network A hold positive orientations while all agents of network B have a negative orientation, we explore the conditions under which one of the dynamics prevails over the other, imposing its initial orientation. We find that, for a given value of β, the two-network system reaches a consensus in the positive state (initial state of network A when the reinforcement overcomes a crossover value r*(β, while a negative consensus happens for r βc. We develop an analytical mean-field approach that gives an insight into these regimes and shows that both dynamics are equivalent along the crossover line (r*, β*.

Prioritization of pavement maintenance sections using objective based Analytic Hierarchy Process

Directory of Open Access Journals (Sweden)

Sarfaraz Ahmed

2017-03-01

Full Text Available The application of Analytic Hierarchy Process (AHP method for the prioritization of pavement maintenance sections is widespread now-a-days. Although the evaluation of pavement maintenance section through AHP method is simple, where the relative importance (on Saaty’s scale assigned to each parameter in the hierarchy varies between the experts (transportation professionals consulted, which leads to discrepancies in the final rankings of the sections’, due to the subjectivity in the process. Further, experts base their decisions solely on their experience while consideration is not given to the actual quantitative physical condition of the roads. To overcome these difficulties an objective based AHP method is proposed in this study, where pairwise comparison values are assigned based on the collected field data from a road network in Mumbai city, consisting of 28 road sections. The final ranking list of candidate sections takes into consideration the priority weight of alternatives, which reflect the road conditions. The solution of priority ratings of AHP method is compared with the corresponding solution of road condition index method, a traditional pavement maintenance procedure. The findings of the present study suggest that objective based AHP method is more suitable for the prioritization of pavement maintenance of roads. Keywords: Prioritization, Analytic Hierarchy Process, Road condition index, Objective method, Rating and ranking

The Theory of Ratio Scale Estimation: Saaty's Analytic Hierarchy Process

OpenAIRE

Patrick T. Harker; Luis G. Vargas

1987-01-01

The Analytic Hierarchy Process developed by Saaty (Saaty, T. L. 1980. The Analytic Hierarchy Process. McGraw-Hill, New York.) has proven to be an extremely useful method for decision making and planning. However, some researchers in these areas have raised concerns over the theoretical basis underlying this process. This paper addresses currently debated issues concerning the theoretical foundations of the Analytic Hierarchy Process. We also illustrate through proof and through examples the v...

Communication Theoretic Data Analytics

OpenAIRE

Chen, Kwang-Cheng; Huang, Shao-Lun; Zheng, Lizhong; Poor, H. Vincent

2015-01-01

Widespread use of the Internet and social networks invokes the generation of big data, which is proving to be useful in a number of applications. To deal with explosively growing amounts of data, data analytics has emerged as a critical technology related to computing, signal processing, and information networking. In this paper, a formalism is considered in which data is modeled as a generalized social network and communication theory and information theory are thereby extended to data analy...

Power Distribution Analysis For Electrical Usage In Province Area Using Olap (Online Analytical Processing

Directory of Open Access Journals (Sweden)

Samsinar Riza

2018-01-01

Full Text Available The distribution network is the closest power grid to the customer Electric service providers such as PT. PLN. The dispatching center of power grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. Specific methods for online analytics information systems resulting from data warehouse processing with OLAP are chart and query reporting. The information in the form of chart reporting consists of the load distribution chart based on the repetition of time, distribution chart on the area, the substation region chart and the electric load usage chart. The results of the OLAP process show the development of electric load distribution, as well as the analysis of information on the load of electric power consumption and become an alternative in presenting information related to peak load.

Power Distribution Analysis For Electrical Usage In Province Area Using Olap (Online Analytical Processing)

Science.gov (United States)

Samsinar, Riza; Suseno, Jatmiko Endro; Widodo, Catur Edi

2018-02-01

The distribution network is the closest power grid to the customer Electric service providers such as PT. PLN. The dispatching center of power grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. Specific methods for online analytics information systems resulting from data warehouse processing with OLAP are chart and query reporting. The information in the form of chart reporting consists of the load distribution chart based on the repetition of time, distribution chart on the area, the substation region chart and the electric load usage chart. The results of the OLAP process show the development of electric load distribution, as well as the analysis of information on the load of electric power consumption and become an alternative in presenting information related to peak load.

PEMILIHAN STRATEGI PEMASARAN DI KAMPOENG KOPI BANARAN MENGGUNAKAN PENDEKATAN METODE ANALYTICAL NETWORK PROCESS (ANP DAN TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO AN IDEAL SOLUTION (TOPSIS

Directory of Open Access Journals (Sweden)

Aries Susanty

2014-09-01

untuk pemasaran Kampoeng Kopi Banaran adalah Strategi Segmentasi   Kata Kunci : strategi pemasaran; kampoeng kopi banaran; analytical network process (ANP; TOPSIS Abstract Kampoeng Kopi Banaran can’t achieve a return in accordance with the targets set. Hypothesized, this is the case because of the increasing number of competitors with similar business, such as Cimory, Kampoeng Rawa, Tlogo Plantation, Salib Putih, and Umbul Sidomukti and have not had a proper marketing strategy by Kampoeng Kopi Banaran. During this time, Kampoeng Kopi Banaran has been promote its products by using the website, brochures, and word of mouth. According to this condition, this study aimed to identify the appropriate criteria and sub-criteria for the formulation of a marketing strategy for Kampoeng Kopi Banaran, determine the weight of each criteria and sub-criteria, as well as proposing specific marketing strategies based on the criteria and sub-criteria. In this study, there are eight criteria used as a basis to develop a marketing strategy for Kampoeng Kopi Banaran, namely Managerial Capabilities (MC, Market Innovation Capabilities (MIC, Customer Linking Capabilities (CLC, Human Resource Assetes (HRA, Reputational assets (RA, Competition (C, Economy (E, and Social and cultural (SC. Meanwhile, the eight criterias will be further elaborated into a number of sub-criterias. The method is used to calculate weights of criteria and sub-criteria was Analytical Network Process (ANP whereas the method is used for the preparation of a marketing strategy was Technique for Others Reference by Similarity to Ideal Solution (TOPSIS. Data for this study were obtain by distributing questionnaires for managers and marketing section at Kampoeng Kopi Banaran. The results of data was processing show that the criteria with the highest weight in the marketing strategy for the preparation at Kampoeng Kopi Banaran is Managerial Capabilities (MC (0.1897 and sub-criteria with the highest weight is brand or

Analytic models for the evolution of semilocal string networks

International Nuclear Information System (INIS)

Nunes, A. S.; Martins, C. J. A. P.; Avgoustidis, A.; Urrestilla, J.

2011-01-01

We revisit previously developed analytic models for defect evolution and adapt them appropriately for the study of semilocal string networks. We thus confirm the expectation (based on numerical simulations) that linear scaling evolution is the attractor solution for a broad range of model parameters. We discuss in detail the evolution of individual semilocal segments, focusing on the phenomenology of segment growth, and also provide a preliminary comparison with existing numerical simulations.

Process analytical chemistry applied to actinide waste streams

International Nuclear Information System (INIS)

Day, R.S.

1994-01-01

The Department of Energy is being called upon to clean up it's legacy of waste from the nuclear complex generated during the cold war period. Los Alamos National Laboratory is actively involved in waste minimization and waste stream polishing activities associated with this clean up. The Advanced Testing Line for Actinide Separations (ATLAS) at Los Alamos serves as a developmental test bed for integrating flow sheet development of nitric acid waste streams with process analytical chemistry and process control techniques. The wastes require processing in glove boxes because of the radioactive components, thus adding to the difficulties of making analytical measurements. Process analytical chemistry methods provide real-time chemical analysis in support of existing waste stream operations and enhances the development of new waste stream polishing initiatives. The instrumentation and methods being developed on ATLAS are designed to supply near-real time analyses on virtually all of the chemical parameters found in nitric acid processing of actinide waste. These measurements supply information on important processing parameters including actinide oxidation states, free acid concentration, interfering anions and metal impurities

The Application of Fuzzy Analytical Network Process (FANP Approach for Appropriate Location Selection of Health Centers: case study in ramsar cite

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Dariush Mohammadi Zanjirani

2012-06-01

Full Text Available Background: Appropriate location selection for health Services unites is a Strategic decision which is based on gathering information and also exact analysis of related alternatives. It's clear that result of this decision is really important and will led to long time improvement in all dimensions including economic, social, and etc. Otherwise, the most studies of location have done in background manufacturing rather than service area and there are just few articles which have focused in field of healthcare. This study attempted to solve this stock of researches. Methods: By using an almost comprehensive literatures review, objective and subjective criteria are identified. After finalizing criteria's, Are used from decision-makers’ assessments for collection data. Fuzzy Analytical Network Process is used for analyzing the data. Results: The finding indicates that the criteria's of proposed model are high validity and reliability for appropriate location selection of Health Centers. Conclusion: The analyzing of data indicates that lamtar locate is selected appropriate location.

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

Science.gov (United States)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-31

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

Science.gov (United States)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-01

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

Two analytical models for evaluating performance of Gigabit Ethernet Hosts

International Nuclear Information System (INIS)

Salah, K.

2006-01-01

Two analytical models are developed to study the impact of interrupt overhead on operating system performance of network hosts when subjected to Gigabit network traffic. Under heavy network traffic, the system performance will be negatively affected due to interrupt overhead caused by incoming traffic. In particular, excessive latency and significant degradation in system throughput can be experienced. Also user application may livelock as the CPU power is mostly consumed by interrupt handling and protocol processing. In this paper we present and compare two analytical models that capture host behavior and evaluate its performance. The first model is based Markov processes and queuing theory, while the second, which is more accurate but more complex is a pure Markov process. For the most part both models give mathematically-equivalent closed-form solutions for a number of important system performance metrics. These metrics include throughput, latency and stability condition, CPU utilization of interrupt handling and protocol processing and CPU availability for user applications. The analysis yields insight into understanding and predicting the impact of system and network choices on the performance of interrupt-driven systems when subjected to light and heavy network loads. More, importantly, our analytical work can also be valuable in improving host performance. The paper gives guidelines and recommendations to address design and implementation issues. Simulation and reported experimental results show that our analytical models are valid and give a good approximation. (author)

PENGGUNAAN METODE ANALYTICAL HIERARCHY PROCESS DALAM PEMILIHAN LOKASI MANGROVE PARK

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Mustika Mustika

2017-02-01

Full Text Available Demak district is a district that has quite a lot of mangrove forests, beautiful expanse of mangrove is a natural potential that can be developed as a regional tourism assets. Mangrove Park is one of the utilization of conservation area into tourism areas of education and recreation The Selection of Planning site locations required an appropriate location in the terms of land use, The appropriate land is a land that has a Mangrove area which still leafy, natural (unprocessed and intended as a tourism area, an easy accessibility, the network infrastructure is also needed in the election of location in order to support the available facilities in the building. In addition, the view of the inside and outside of the site that will be a tourism place attraction. Decision Support System can be used as a tool to help the site selection process that involves many criteria. Analytical Hierarchy Process (AHP can be used to analyze which support the decision to choose a location. Phases of AHP used in this research is the identification of causes, preparation of hierarchy, prioritization, consistency, and the priority weight. From the Implementation of the method on the study case successfully find the best location for mangrove park, it is in the village Bedono it has the highest total global priorities 1.2349. Keywords: Site Location, Analytical Hierarchy Process, Mangrove Park Kabupaten Demak adalah kabupaten yang memiliki hutan mangrove yang cukup banyak, hamparan mangrove yang indah merupakan potensi alam yang dapat dikembangkan sebagai aset pariwisata daerah. Mangrove Park adalah salah satu bentuk pemanfaatan kawasan konservasi menjadi kawasan wisata edukasi dan rekreasi. Pemilihan lokasi tapak perencanaan diperlukan sebuah lokasi yang tepat dari segi peruntukan lahan, lahan yang tepat adalah lahan yang memiliki area Mangrove yang masih rimbun, alami (belum diolah dan diperuntukkan sebagai kawasan wisata, aksebilitas yang mudah dijangkau, jaringan

Role of the IAEA's ALMERA network in harmonization of analytical procedures applicable worldwide for radiological emergencies

International Nuclear Information System (INIS)

Pitois, A.; Osvath, I.; Tarjan, S.; Groening, M.; Osborn, D.; )

2016-01-01

The International Atomic Energy Agency (IAEA) coordinates and provides analytical support to the worldwide network of Analytical Laboratories for the Measurement of Environmental Radioactivity (ALMERA), consisting at the end of 2015 of 154 laboratories in 85 countries. This network, established by the IAEA in 1995, has for aim to provide timely and reliable measurement results of environmental radioactivity in routine monitoring and emergency situations. The IAEA supports the ALMERA laboratories in their routine and emergency response environmental monitoring activities by organizing proficiency tests and inter-laboratory comparison exercises, developing validated analytical procedures for environmental radioactivity measurement, and organizing training courses and workshops. The network also acts as a forum for sharing knowledge and expertise. The aim of this paper is to describe the current status of ALMERA analytical method development activities for radiological emergencies and the plans for further development in the field

Facing mixed emotions: Analytic and holistic perception of facial emotion expressions engages separate brain networks.

Science.gov (United States)

Meaux, Emilie; Vuilleumier, Patrik

2016-11-01

The ability to decode facial emotions is of primary importance for human social interactions; yet, it is still debated how we analyze faces to determine their expression. Here we compared the processing of emotional face expressions through holistic integration and/or local analysis of visual features, and determined which brain systems mediate these distinct processes. Behavioral, physiological, and brain responses to happy and angry faces were assessed by presenting congruent global configurations of expressions (e.g., happy top+happy bottom), incongruent composite configurations (e.g., angry top+happy bottom), and isolated features (e.g. happy top only). Top and bottom parts were always from the same individual. Twenty-six healthy volunteers were scanned using fMRI while they classified the expression in either the top or the bottom face part but ignored information in the other non-target part. Results indicate that the recognition of happy and anger expressions is neither strictly holistic nor analytic Both routes were involved, but with a different role for analytic and holistic information depending on the emotion type, and different weights of local features between happy and anger expressions. Dissociable neural pathways were engaged depending on emotional face configurations. In particular, regions within the face processing network differed in their sensitivity to holistic expression information, which predominantly activated fusiform, inferior occipital areas and amygdala when internal features were congruent (i.e. template matching), whereas more local analysis of independent features preferentially engaged STS and prefrontal areas (IFG/OFC) in the context of full face configurations, but early visual areas and pulvinar when seen in isolated parts. Collectively, these findings suggest that facial emotion recognition recruits separate, but interactive dorsal and ventral routes within the face processing networks, whose engagement may be shaped by

Network analytical tool for monitoring global food safety highlights China.

Directory of Open Access Journals (Sweden)

Tamás Nepusz

Full Text Available BACKGROUND: The Beijing Declaration on food safety and security was signed by over fifty countries with the aim of developing comprehensive programs for monitoring food safety and security on behalf of their citizens. Currently, comprehensive systems for food safety and security are absent in many countries, and the systems that are in place have been developed on different principles allowing poor opportunities for integration. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a user-friendly analytical tool based on network approaches for instant customized analysis of food alert patterns in the European dataset from the Rapid Alert System for Food and Feed. Data taken from alert logs between January 2003-August 2008 were processed using network analysis to i capture complexity, ii analyze trends, and iii predict possible effects of interventions by identifying patterns of reporting activities between countries. The detector and transgressor relationships are readily identifiable between countries which are ranked using i Google's PageRank algorithm and ii the HITS algorithm of Kleinberg. The program identifies Iran, China and Turkey as the transgressors with the largest number of alerts. However, when characterized by impact, counting the transgressor index and the number of countries involved, China predominates as a transgressor country. CONCLUSIONS/SIGNIFICANCE: This study reports the first development of a network analysis approach to inform countries on their transgressor and detector profiles as a user-friendly aid for the adoption of the Beijing Declaration. The ability to instantly access the country-specific components of the several thousand annual reports will enable each country to identify the major transgressors and detectors within its trading network. Moreover, the tool can be used to monitor trading countries for improved detector/transgressor ratios.

A Geovisual Analytic Approach to Understanding Geo-Social Relationships in the International Trade Network

OpenAIRE

Luo, Wei; Yin, Peifeng; Di, Qian; Hardisty, Frank; MacEachren, Alan M.

2014-01-01

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social...

Analytical control in metallurgical processes

International Nuclear Information System (INIS)

Coedo, A.G.; Dorado, M.T.; Padilla, I.

1998-01-01

This paper illustrates the role of analysis in enabling metallurgical industry to meet quality demands. For example, for the steel industry the demands by the automotive, aerospace, power generation, tinplate packaging industries and issue of environment near steel plants. Although chemical analysis technology continues to advance, achieving improved speed, precision and accuracy at lower levels of detection, the competitiveness of manufacturing industry continues to drive property demands at least at the same rate. Narrower specification ranges, lower levels of residual elements and economic pressures prescribe faster process routes, all of which lead to increased demands on the analytical function. These damands are illustrated by examples from several market sectors in which customer issues are considered together with ther analytical implications. (Author) 5 refs

Geo-social visual analytics

Directory of Open Access Journals (Sweden)

Wei Luo

2014-06-01

Full Text Available Spatial analysis and social network analysis typically consider social processes in their own specific contexts, either geographical or network space. Both approaches demonstrate strong conceptual overlaps. For example, actors close to each other tend to have greater similarity than those far apart; this phenomenon has different labels in geography (spatial autocorrelation and in network science (homophily. In spite of those conceptual and observed overlaps, the integration of geography and social network context has not received the attention needed in order to develop a comprehensive understanding of their interaction or their impact on outcomes of interest, such as population health behaviors, information dissemination, or human behavior in a crisis. In order to address this gap, this paper discusses the integration of geographic with social network perspectives applied to understanding social processes in place from two levels: the theoretical level and the methodological level. At the theoretical level, this paper argues that the concepts of nearness and relationship in terms of a possible extension of the First Law of Geography are a matter of both geographical and social network distance, relationship, and interaction. At the methodological level, the integration of geography and social network contexts are framed within a new interdisciplinary field:~visual analytics, in which three major application-oriented subfields (data exploration, decision-making, and predictive analysis are used to organize discussion. In each subfield, this paper presents a theoretical framework first, and then reviews what has been achieved regarding geo-social visual analytics in order to identify potential future research.

Heuristic and analytic processing in online sports betting.

Science.gov (United States)

d'Astous, Alain; Di Gaspero, Marc

2015-06-01

This article presents the results of two studies that examine the occurrence of heuristic (i.e., intuitive and fast) and analytic (i.e., deliberate and slow) processes among people who engage in online sports betting on a regular basis. The first study was qualitative and was conducted with a convenience sample of 12 regular online sports gamblers who described the processes by which they arrive at a sports betting decision. The results of this study showed that betting online on sports events involves a mix of heuristic and analytic processes. The second study consisted in a survey of 161 online sports gamblers where performance in terms of monetary gains, experience in online sports betting, propensity to collect and analyze relevant information prior to betting, and use of bookmaker odds were measured. This study showed that heuristic and analytic processes act as mediators of the relationship between experience and performance. The findings stemming of these two studies give some insights into gamblers' modes of thinking and behaviors in an online sports betting context and show the value of the dual mediation process model for research that looks at gambling activities from a judgment and decision making perspective.

Contagion processes on the static and activity-driven coupling networks

Science.gov (United States)

Lei, Yanjun; Jiang, Xin; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming

2016-03-01

The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated as either static or time-varying, supposing the whole network is observed in the same time window. In this paper, we consider the epidemics spreading on a network which has both static and time-varying structures. Meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and activity-driven coupling (SADC) network model to characterize the coupling between the static ("strong") structure and the dynamic ("weak") structure. Epidemic thresholds of the SIS and SIR models are studied using the SADC model both analytically and numerically under various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from the SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that a weak structure might make the epidemic threshold low in homogeneous networks but high in heterogeneous cases. Furthermore, we show that the weak structure has a substantive effect on the outbreak of the epidemics. This result might be useful in designing some efficient control strategies for epidemics spreading in networks.

Analytical transport network theory to guide the design of 3-D microstructural networks in energy materials: Part 1. Flow without reactions

Science.gov (United States)

Cocco, Alex P.; Nakajo, Arata; Chiu, Wilson K. S.

2017-12-01

We present a fully analytical, heuristic model - the "Analytical Transport Network Model" - for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a microstructural network's topology and the morphology of its channels to an effective material transport coefficient (a general term meant to encompass, e.g., conductivity or diffusion coefficient). The model's transport coefficient predictions agree well with those from electrochemical fin (ECF) theory and finite element analysis (FEA), but are computed 0.5-1.5 and 5-6 orders of magnitude faster, respectively. In addition, the theory explicitly relates a number of morphological and topological parameters directly to the transport coefficient, whereby the distributions that characterize the structure are readily available for further analysis. Furthermore, ATN's explicit development provides insight into the nature of the tortuosity factor and offers the potential to apply theory from network science and to consider the optimization of a network's effective resistance in a mathematically rigorous manner. The ATN model's speed and relative ease-of-use offer the potential to aid in accelerating the design (with respect to transport), and thus reducing the cost, of energy materials.

Comparison of Analytical and Measured Performance Results on Network Coding in IEEE 802.11 Ad-Hoc Networks

DEFF Research Database (Denmark)

Zhao, Fang; Médard, Muriel; Hundebøll, Martin

2012-01-01

CATWOMAN that can run on standard WiFi hardware. We present an analytical model to evaluate the performance of COPE in simple networks, and our results show the excellent predictive quality of this model. By closely examining the performance in two simple topologies, we observe that the coding gain results...

Networking in the Desert - Operational and Analytical Challenges for MINUSMA in Mali

DEFF Research Database (Denmark)

Haugegaard, Rikke

This paper will initiate a discussion of the operational and analytical challenges in understanding network dynamics in Mali, and how these dynamics can be seen as one source of conflict in Mali. The paper is based on a field visit to Mali in 2014....

A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems

Directory of Open Access Journals (Sweden)

Takanori Fujiwara

2018-03-01

Full Text Available The overall efficiency of an extreme-scale supercomputer largely relies on the performance of its network interconnects. Several of the state of the art supercomputers use networks based on the increasingly popular Dragonfly topology. It is crucial to study the behavior and performance of different parallel applications running on Dragonfly networks in order to make optimal system configurations and design choices, such as job scheduling and routing strategies. However, in order to study these temporal network behavior, we would need a tool to analyze and correlate numerous sets of multivariate time-series data collected from the Dragonfly’s multi-level hierarchies. This paper presents such a tool–a visual analytics system–that uses the Dragonfly network to investigate the temporal behavior and optimize the communication performance of a supercomputer. We coupled interactive visualization with time-series analysis methods to help reveal hidden patterns in the network behavior with respect to different parallel applications and system configurations. Our system also provides multiple coordinated views for connecting behaviors observed at different levels of the network hierarchies, which effectively helps visual analysis tasks. We demonstrate the effectiveness of the system with a set of case studies. Our system and findings can not only help improve the communication performance of supercomputing applications, but also the network performance of next-generation supercomputers. Keywords: Supercomputing, Parallel communication network, Dragonfly networks, Time-series data, Performance analysis, Visual analytics

Determinants of Customers` Churn Decision in the Nigeria Telecommunication Industry: An Analytic Hierarchy Process Approach

Directory of Open Access Journals (Sweden)

Sulaimon Olanrewaju Adebiyi

2015-10-01

Full Text Available This paper describes the application of Analytic Hierarchy Process (AHP for unraveling customers’ motivation for churn of telecommunication network in Nigeria. By identifying, modeling and measuring of customers` churn motivations across four mobile telecommunication service providers in Nigeria. AHP was used to design a hierarchical model of seven criteria for customers` churning of network and investigates the relative priorities of the criteria through a pairwise comparison. The questionnaire were administered through convenient sampling to 480 mobile telecommunication customers and was completed and returned by 438 mobile phone subscribers in Lagos state, Nigeria, but only 408 copies were useful for the analysis of this study. The result shows that six out of the seven criteria have weight above 10% in their individual contribution to motivating customer churn behavior in the Nigeria telecommunication industry. The inefficient data/ internet plan criterion has the highest weight of 18.81% relative to the churn decision. Thus, AHP effectively supported modeling and analyzing subscribers` motivation toward good marketing decision for both the individual and the organization. It helps in developing an analytic and intelligible framework of decision-making on complex problem of customer churn in an emerging market like Nigeria

A network analytical approach to the study of labour market mobility

DEFF Research Database (Denmark)

Toubøl, Jonas; Larsen, Anton Grau; Jensen, Carsten Strøby

(RR), which enable us to identify clusters of inter-mobile categories. We apply the method to data of the labour market mobility in Denmark 2000-2007 and demonstrate how this new method can overcome some long standing obstacles to the advance of labour market segmentation theory: Instead...... of the typical theory driven definition of the labour market segments, the use of social network analysis enable a data driven definition of the segments based on the direct observation of mobility between job-positions, which reveals a number of new findings.......The aim of this paper is to present a new network analytical method for analysis of social mobility between categories like occupations or industries. The method consists of two core components; the algorithm MONECA (Mobility Network Clustering Algorithm), and the intensity measure of Relative Risk...

HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP) MODEL

OpenAIRE

Chun Meng Tang; Miang Hong Ngerng

2015-01-01

Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly co...

Analytical approach to cross-layer protocol optimization in wireless sensor networks

Science.gov (United States)

Hortos, William S.

2008-04-01

In the distributed operations of route discovery and maintenance, strong interaction occurs across mobile ad hoc network (MANET) protocol layers. Quality of service (QoS) requirements of multimedia service classes must be satisfied by the cross-layer protocol, along with minimization of the distributed power consumption at nodes and along routes to battery-limited energy constraints. In previous work by the author, cross-layer interactions in the MANET protocol are modeled in terms of a set of concatenated design parameters and associated resource levels by multivariate point processes (MVPPs). Determination of the "best" cross-layer design is carried out using the optimal control of martingale representations of the MVPPs. In contrast to the competitive interaction among nodes in a MANET for multimedia services using limited resources, the interaction among the nodes of a wireless sensor network (WSN) is distributed and collaborative, based on the processing of data from a variety of sensors at nodes to satisfy common mission objectives. Sensor data originates at the nodes at the periphery of the WSN, is successively transported to other nodes for aggregation based on information-theoretic measures of correlation and ultimately sent as information to one or more destination (decision) nodes. The "multimedia services" in the MANET model are replaced by multiple types of sensors, e.g., audio, seismic, imaging, thermal, etc., at the nodes; the QoS metrics associated with MANETs become those associated with the quality of fused information flow, i.e., throughput, delay, packet error rate, data correlation, etc. Significantly, the essential analytical approach to MANET cross-layer optimization, now based on the MVPPs for discrete random events occurring in the WSN, can be applied to develop the stochastic characteristics and optimality conditions for cross-layer designs of sensor network protocols. Functional dependencies of WSN performance metrics are described in

Analytical methods and laboratory facility for the Defense Waste Processing Facility

International Nuclear Information System (INIS)

Coleman, C.J.; Dewberry, R.A.; Lethco, A.J.; Denard, C.D.

1985-01-01

This paper describes the analytical methods, instruments, and laboratory that will support vitrification of defense waste. The Defense Waste Processing Facility (DWPF) is now being constructed at Savannah River Plant (SRP). Beginning in 1989, SRP high-level defense waste will be immobilized in borosilicate glass for disposal in a federal repository. The DWPF will contain an analytical laboratory for performing process control analyses. Additional analyses will be performed for process history and process diagnostics. The DWPF analytical facility will consist of a large shielded sampling cell, three shielded analytical cells, a laboratory for instrumental analysis and chemical separations, and a counting room. Special instrumentation is being designed for use in the analytical cells, including microwave drying/dissolution apparatus, and remote pipetting devices. The instrumentation laboratory will contain inductively coupled plasma, atomic absorption, Moessbauer spectrometers, a carbon analyzer, and ion chromatography equipment. Counting equipment will include intrinsic germanium detectors, scintillation counters, Phoswich alpha, beta, gamma detectors, and a low-energy photon detector

Analytical Bounds on the Threads in IXP1200 Network Processor

OpenAIRE

Ramakrishna, STGS; Jamadagni, HS

2003-01-01

Increasing link speeds have placed enormous burden on the processing requirements and the processors are expected to carry out a variety of tasks. Network Processors (NP) [1] [2] is the blanket name given to the processors, which are traded for flexibility and performance. Network Processors are offered by a number of vendors; to take the main burden of processing requirement of network related operations from the conventional processors. The Network Processors cover a spectrum of design trad...

Critical regimes driven by recurrent mobility patterns of reaction-diffusion processes in networks

Science.gov (United States)

Gómez-Gardeñes, J.; Soriano-Paños, D.; Arenas, A.

2018-04-01

Reaction-diffusion processes1 have been widely used to study dynamical processes in epidemics2-4 and ecology5 in networked metapopulations. In the context of epidemics6, reaction processes are understood as contagions within each subpopulation (patch), while diffusion represents the mobility of individuals between patches. Recently, the characteristics of human mobility7, such as its recurrent nature, have been proven crucial to understand the phase transition to endemic epidemic states8,9. Here, by developing a framework able to cope with the elementary epidemic processes, the spatial distribution of populations and the commuting mobility patterns, we discover three different critical regimes of the epidemic incidence as a function of these parameters. Interestingly, we reveal a regime of the reaction-diffussion process in which, counter-intuitively, mobility is detrimental to the spread of disease. We analytically determine the precise conditions for the emergence of any of the three possible critical regimes in real and synthetic networks.

Interactive network analytical tool for instantaneous bespoke interrogation of food safety notifications.

Science.gov (United States)

Nepusz, Tamás; Petróczi, Andrea; Naughton, Declan P

2012-01-01

The globalization of food supply necessitates continued advances in regulatory control measures to ensure that citizens enjoy safe and adequate nutrition. The aim of this study was to extend previous reports on network analysis relating to food notifications by including an optional filter by type of notification and in cases of contamination, by type of contaminant in the notified foodstuff. A filter function has been applied to enable processing of selected notifications by contaminant or type of notification to i) capture complexity, ii) analyze trends, and iii) identify patterns of reporting activities between countries. The program rapidly assesses nations' roles as transgressor and/or detector for each category of contaminant and for the key class of border rejection. In the open access demonstration version, the majority of notifications in the Rapid Alert System for Food and Feed were categorized by contaminant type as mycotoxin (50.4%), heavy metals (10.9%) or bacteria (20.3%). Examples are given demonstrating how network analytical approaches complement, and in some cases supersede, descriptive statistics such as frequency counts, which may give limited or potentially misleading information. One key feature is that network analysis takes the relationship between transgressor and detector countries, along with number of reports and impact simultaneously into consideration. Furhermore, the indices that compliment the network maps and reflect each country's transgressor and detector activities allow comparisons to be made between (transgressing vs. detecting) as well as within (e.g. transgressing) activities. This further development of the network analysis approach to food safety contributes to a better understanding of the complexity of the effort ensuring food is safe for consumption in the European Union. The unique patterns of the interplay between detectors and transgressors, instantly revealed by our approach, could supplement the intelligence

Interactive network analytical tool for instantaneous bespoke interrogation of food safety notifications.

Directory of Open Access Journals (Sweden)

Tamás Nepusz

Full Text Available The globalization of food supply necessitates continued advances in regulatory control measures to ensure that citizens enjoy safe and adequate nutrition. The aim of this study was to extend previous reports on network analysis relating to food notifications by including an optional filter by type of notification and in cases of contamination, by type of contaminant in the notified foodstuff.A filter function has been applied to enable processing of selected notifications by contaminant or type of notification to i capture complexity, ii analyze trends, and iii identify patterns of reporting activities between countries. The program rapidly assesses nations' roles as transgressor and/or detector for each category of contaminant and for the key class of border rejection. In the open access demonstration version, the majority of notifications in the Rapid Alert System for Food and Feed were categorized by contaminant type as mycotoxin (50.4%, heavy metals (10.9% or bacteria (20.3%. Examples are given demonstrating how network analytical approaches complement, and in some cases supersede, descriptive statistics such as frequency counts, which may give limited or potentially misleading information. One key feature is that network analysis takes the relationship between transgressor and detector countries, along with number of reports and impact simultaneously into consideration. Furhermore, the indices that compliment the network maps and reflect each country's transgressor and detector activities allow comparisons to be made between (transgressing vs. detecting as well as within (e.g. transgressing activities.This further development of the network analysis approach to food safety contributes to a better understanding of the complexity of the effort ensuring food is safe for consumption in the European Union. The unique patterns of the interplay between detectors and transgressors, instantly revealed by our approach, could supplement the

A method for risk-informed safety significance categorization using the analytic hierarchy process and bayesian belief networks

International Nuclear Information System (INIS)

Ha, Jun Su; Seong, Poong Hyun

2004-01-01

A risk-informed safety significance categorization (RISSC) is to categorize structures, systems, or components (SSCs) of a nuclear power plant (NPP) into two or more groups, according to their safety significance using both probabilistic and deterministic insights. In the conventional methods for the RISSC, the SSCs are quantitatively categorized according to their importance measures for the initial categorization. The final decisions (categorizations) of SSCs, however, are qualitatively made by an expert panel through discussions and adjustments of opinions by using the probabilistic insights compiled in the initial categorization process and combining the probabilistic insights with the deterministic insights. Therefore, owing to the qualitative and linear decision-making process, the conventional methods have the demerits as follows: (1) they are very costly in terms of time and labor, (2) it is not easy to reach the final decision, when the opinions of the experts are in conflict and (3) they have an overlapping process due to the linear paradigm (the categorization is performed twice - first, by the engineers who propose the method, and second, by the expert panel). In this work, a method for RISSC using the analytic hierarchy process (AHP) and bayesian belief networks (BBN) is proposed to overcome the demerits of the conventional methods and to effectively arrive at a final decision (or categorization). By using the AHP and BBN, the expert panel takes part in the early stage of the categorization (that is, the quantification process) and the safety significance based on both probabilistic and deterministic insights is quantified. According to that safety significance, SSCs are quantitatively categorized into three categories such as high safety significant category (Hi), potentially safety significant category (Po), or low safety significant category (Lo). The proposed method was applied to the components such as CC-V073, CV-V530, and SI-V644 in Ulchin Unit

Reconfigurable network processing platforms

NARCIS (Netherlands)

Kachris, C.

2007-01-01

This dissertation presents our investigation on how to efficiently exploit reconfigurable hardware to design flexible, high performance, and power efficient network devices capable to adapt to varying processing requirements of network applications and traffic. The proposed reconfigurable network

Analytic and heuristic processes in the detection and resolution of conflict.

Science.gov (United States)

Ferreira, Mário B; Mata, André; Donkin, Christopher; Sherman, Steven J; Ihmels, Max

2016-10-01

Previous research with the ratio-bias task found larger response latencies for conflict trials where the heuristic- and analytic-based responses are assumed to be in opposition (e.g., choosing between 1/10 and 9/100 ratios of success) when compared to no-conflict trials where both processes converge on the same response (e.g., choosing between 1/10 and 11/100). This pattern is consistent with parallel dual-process models, which assume that there is effective, rather than lax, monitoring of the output of heuristic processing. It is, however, unclear why conflict resolution sometimes fails. Ratio-biased choices may increase because of a decline in analytical reasoning (leaving heuristic-based responses unopposed) or to a rise in heuristic processing (making it more difficult for analytic processes to override the heuristic preferences). Using the process-dissociation procedure, we found that instructions to respond logically and response speed affected analytic (controlled) processing (C), leaving heuristic processing (H) unchanged, whereas the intuitive preference for large nominators (as assessed by responses to equal ratio trials) affected H but not C. These findings create new challenges to the debate between dual-process and single-process accounts, which are discussed.

Recent developments in analytical detection methods for radiation processed foods

International Nuclear Information System (INIS)

Wu Jilan

1993-01-01

A short summary of the programmes of 'ADMIT' (FAO/IAEA) and the developments in analytical detection methods for radiation processed foods has been given. It is suggested that for promoting the commercialization of radiation processed foods and controlling its quality, one must pay more attention to the study of analytical detection methods of irradiated food

Signal Processing and Neural Network Simulator

Science.gov (United States)

Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

1995-04-01

The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

Assessment of Learning in Digital Interactive Social Networks: A Learning Analytics Approach

Science.gov (United States)

Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen

2016-01-01

This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable…

Nonlinear signal processing using neural networks: Prediction and system modelling

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.; Farber, R.

1987-06-01

The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

An analytical approach to managing complex process problems

Energy Technology Data Exchange (ETDEWEB)

Ramstad, Kari; Andersen, Espen; Rohde, Hans Christian; Tydal, Trine

2006-03-15

The oil companies are continuously investing time and money to ensure optimum regularity on their production facilities. High regularity increases profitability, reduces workload on the offshore organisation and most important; - reduces discharge to air and sea. There are a number of mechanisms and tools available in order to achieve high regularity. Most of these are related to maintenance, system integrity, well operations and process conditions. However, for all of these tools, they will only be effective if quick and proper analysis of fluids and deposits are carried out. In fact, analytical backup is a powerful tool used to maintain optimised oil production, and should as such be given high priority. The present Operator (Hydro Oil and Energy) and the Chemical Supplier (MI Production Chemicals) have developed a cooperation to ensure that analytical backup is provided efficiently to the offshore installations. The Operator's Research and Development (R and D) departments and the Chemical Supplier have complementary specialties in both personnel and equipment, and this is utilized to give the best possible service when required from production technologists or operations. In order for the Operator's Research departments, Health, Safety and Environment (HSE) departments and Operations to approve analytical work performed by the Chemical Supplier, a number of analytical tests are carried out following procedures agreed by both companies. In the present paper, three field case examples of analytical cooperation for managing process problems will be presented. 1) Deposition in a Complex Platform Processing System. 2) Contaminated Production Chemicals. 3) Improved Monitoring of Scale Inhibitor, Suspended Solids and Ions. In each case the Research Centre, Operations and the Chemical Supplier have worked closely together to achieve fast solutions and Best Practice. (author) (tk)

METODE ANALYTICAL HIERARCHY PROCESS: SISTEM REKOMENDER DATABASE SOFTWARE

Directory of Open Access Journals (Sweden)

Doni Purnama Alam Syah

2014-09-01

Full Text Available Abstract - Rekomender electoral system is a database software application that can be used to look for alternative software database selection strategy, the method of analytical hierarchy process (AHP. Rekomender systems needed by companies that have a large enough data processing such as the Bureau of Bina Sarana IT Information, expensive investments in the provision of Information Technology (IT makes IT Bina Sarana Information Bureau to be more careful in determining the selection of database software. This study focuses on research of database software selection system with the method of analytical hierarchy process (AHP, a case study of IT Bureau Bina Sarana Infromatika with the observation unit administrator. The results of the study found that there are two (2 main criteria, namely the selection of technology and a user with an alternative strategy My SQL, Oracle and SQL Server. Having tested the system rekomender My SQL result that the top priority in the selection of database software with a 41% weighting, followed by SQL Server and Oracle 39% 21%. The end result of a system that has been created rekomender concluded that the Bureau of Bina Sarana Informatics IT can define strategy alternatives before determining database software to be used more effectively and efficiently. Abstrak¬¬ - Sistem rekomender pemilihan database software merupakan aplikasi yang dapat digunakan untuk mencari alternatif strategi pemilihan database software, dengan metode analytical hierarchy process (AHP. Sistem rekomender dibutuhkan oleh perusahaan yang memiliki pengolahan data yang cukup besar seperti Biro TI Bina Sarana Informatika, mahalnya investasi pada penyediaan Teknologi Informasi (TI membuat Biro TI Bina Sarana Informatika lebih berhati-hati dalam menentukan pemilihan database software. Penelitian ini berfokus kepada penetilian tentang sistem pemilihan database sofware dengan metode analytical hierarchy process (AHP, studi kasus Biro TI Bina Sarana

Classification of user interfaces for graph-based online analytical processing

Science.gov (United States)

Michaelis, James R.

2016-05-01

In the domain of business intelligence, user-oriented software for conducting multidimensional analysis via Online- Analytical Processing (OLAP) is now commonplace. In this setting, datasets commonly have well-defined sets of dimensions and measures around which analysis tasks can be conducted. However, many forms of data used in intelligence operations - deriving from social networks, online communications, and text corpora - will consist of graphs with varying forms of potential dimensional structure. Hence, enabling OLAP over such data collections requires explicit definition and extraction of supporting dimensions and measures. Further, as Graph OLAP remains an emerging technique, limited research has been done on its user interface requirements. Namely, on effective pairing of interface designs to different types of graph-derived dimensions and measures. This paper presents a novel technique for pairing of user interface designs to Graph OLAP datasets, rooted in Analytic Hierarchy Process (AHP) driven comparisons. Attributes of the classification strategy are encoded through an AHP ontology, developed in our alternate work and extended to support pairwise comparison of interfaces. Specifically, according to their ability, as perceived by Subject Matter Experts, to support dimensions and measures corresponding to Graph OLAP dataset attributes. To frame this discussion, a survey is provided both on existing variations of Graph OLAP, as well as existing interface designs previously applied in multidimensional analysis settings. Following this, a review of our AHP ontology is provided, along with a listing of corresponding dataset and interface attributes applicable toward SME recommendation structuring. A walkthrough of AHP-based recommendation encoding via the ontology-based approach is then provided. The paper concludes with a short summary of proposed future directions seen as essential for this research area.

Redesign of the Attention Process of Patients with Rheumatologic Diseases: Assessing the Performance with Analytic Hierarchy Process

OpenAIRE

Gorbanev, Iouri; Cortes, Ariel; Agudelo-Londoño, Sandra

2017-01-01

Objective. To compare the Business process management and the analytic hierarchy process as the tools of process performance assessment. Instruments and Methods. Case study of the attention process of rheumatology patients. Business process management and analytic hierarchy process were applied to assess the redesign of the attention process. The two methods were compared. The data were obtained through personal observations, an interview with a Colombian health insurer’s senior executive, an...

Disaster risk management in prospect mining area Blitar district, East Java, using microtremor analysis and ANP (analytical network processing) approach

Energy Technology Data Exchange (ETDEWEB)

Parwatiningtyas, Diyan, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com; Ambarsari, Erlin Windia, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com; Marlina, Dwi, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com; Wiratomo, Yogi, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com [Department of Physics, Faculty of Engineering, Mathematics and Natural Sciences, Indraprasta PGRI University, Nangka Street No. 58C Tanjung Barat, South Jakarta (Indonesia)

2014-03-24

Indonesia has a wealth of natural assets is so large to be managed and utilized, either from its own local government and local communities, especially in the mining sector. However, mining activities can change the state of the surface layer of the earth that have a high impact disaster risk. This could threaten the safety and disrupt human life, environmental damage, loss of property, and the psychological impact, sulking to the rule of law no 24 of 2007. That's why we strive to manage and minimize the risk of mine disasters in the region, how to use the method of calculation of Amplification Factor (AF) from the analysis based microtremor sulking Kanai and Nakamura, and decision systems were tested by analysis of ANP. Based on the amplification factor and Analytical Network Processing (ANP) obtained, some points showed instability in the surface layer of a mining area include the site of the TP-7, TP-8, TP-9, TP-10, (Birowo2). If in terms of structure, location indicated unstable due to have a sloping surface layer, resulting in the occurrence of landslides and earthquake risk is high. In the meantime, other areas of the mine site can be said to be a stable area.

Disaster risk management in prospect mining area Blitar district, East Java, using microtremor analysis and ANP (analytical network processing) approach

International Nuclear Information System (INIS)

Parwatiningtyas, Diyan; Ambarsari, Erlin Windia; Marlina, Dwi; Wiratomo, Yogi

2014-01-01

Indonesia has a wealth of natural assets is so large to be managed and utilized, either from its own local government and local communities, especially in the mining sector. However, mining activities can change the state of the surface layer of the earth that have a high impact disaster risk. This could threaten the safety and disrupt human life, environmental damage, loss of property, and the psychological impact, sulking to the rule of law no 24 of 2007. That's why we strive to manage and minimize the risk of mine disasters in the region, how to use the method of calculation of Amplification Factor (AF) from the analysis based microtremor sulking Kanai and Nakamura, and decision systems were tested by analysis of ANP. Based on the amplification factor and Analytical Network Processing (ANP) obtained, some points showed instability in the surface layer of a mining area include the site of the TP-7, TP-8, TP-9, TP-10, (Birowo2). If in terms of structure, location indicated unstable due to have a sloping surface layer, resulting in the occurrence of landslides and earthquake risk is high. In the meantime, other areas of the mine site can be said to be a stable area

Analytical connection between thresholds and immunization strategies of SIS model in random networks

Science.gov (United States)

Zhou, Ming-Yang; Xiong, Wen-Man; Liao, Hao; Wang, Tong; Wei, Zong-Wen; Fu, Zhong-Qian

2018-05-01

Devising effective strategies for hindering the propagation of viruses and protecting the population against epidemics is critical for public security and health. Despite a number of studies based on the susceptible-infected-susceptible (SIS) model devoted to this topic, we still lack a general framework to compare different immunization strategies in completely random networks. Here, we address this problem by suggesting a novel method based on heterogeneous mean-field theory for the SIS model. Our method builds the relationship between the thresholds and different immunization strategies in completely random networks. Besides, we provide an analytical argument that the targeted large-degree strategy achieves the best performance in random networks with arbitrary degree distribution. Moreover, the experimental results demonstrate the effectiveness of the proposed method in both artificial and real-world networks.

Defense Waste Processing Facility prototypic analytical laboratory

International Nuclear Information System (INIS)

Policke, T.A.; Bryant, M.F.; Spencer, R.B.

1991-01-01

The Defense Waste Processing Technology (DWPT) Analytical Laboratory is a relatively new laboratory facility at the Savannah River Site (SRS). It is a non-regulated, non-radioactive laboratory whose mission is to support research and development (R ampersand D) and waste treatment operations by providing analytical and experimental services in a way that is safe, efficient, and produces quality results in a timely manner so that R ampersand D personnel can provide quality technical data and operations personnel can efficiently operate waste treatment facilities. The modules are sample receiving, chromatography I, chromatography II, wet chemistry and carbon, sample preparation, and spectroscopy

Cooperative spreading processes in multiplex networks.

Science.gov (United States)

Wei, Xiang; Chen, Shihua; Wu, Xiaoqun; Ning, Di; Lu, Jun-An

2016-06-01

This study is concerned with the dynamic behaviors of epidemic spreading in multiplex networks. A model composed of two interacting complex networks is proposed to describe cooperative spreading processes, wherein the virus spreading in one layer can penetrate into the other to promote the spreading process. The global epidemic threshold of the model is smaller than the epidemic thresholds of the corresponding isolated networks. Thus, global epidemic onset arises in the interacting networks even though an epidemic onset does not arise in each isolated network. Simulations verify the analysis results and indicate that cooperative spreading processes in multiplex networks enhance the final infection fraction.

Big Data Analytics for Industrial Process Control

DEFF Research Database (Denmark)

Khan, Abdul Rauf; Schioler, Henrik; Kulahci, Murat

2017-01-01

Today, in modern factories, each step in manufacturing produces a bulk of valuable as well as highly precise information. This provides a great opportunity for understanding the hidden statistical dependencies in the process. Systematic analysis and utilization of advanced analytical methods can...

Big data analytics for the virtual network topology reconfiguration use case

OpenAIRE

Gifre Renom, Lluís; Morales Alcaide, Fernando; Velasco Esteban, Luis Domingo; Ruiz Ramírez, Marc

2016-01-01

ABNO's OAM Handler is extended with big data analytics capabilities to anticipate traffic changes in volume and direction. Predicted traffic is used to trigger virtual network topology re-optimization. When the virtual topology needs to be reconfigured, predicted and current traffic matrices are used to find the optimal topology. A heuristic algorithm to adapt current virtual topology to meet both actual demands and expected traffic matrix is proposed. Experimental assessment is carried ou...

Trends in Process Analytical Technology: Present State in Bioprocessing.

Science.gov (United States)

Jenzsch, Marco; Bell, Christian; Buziol, Stefan; Kepert, Felix; Wegele, Harald; Hakemeyer, Christian

2017-08-04

Process analytical technology (PAT), the regulatory initiative for incorporating quality in pharmaceutical manufacturing, is an area of intense research and interest. If PAT is effectively applied to bioprocesses, this can increase process understanding and control, and mitigate the risk from substandard drug products to both manufacturer and patient. To optimize the benefits of PAT, the entire PAT framework must be considered and each elements of PAT must be carefully selected, including sensor and analytical technology, data analysis techniques, control strategies and algorithms, and process optimization routines. This chapter discusses the current state of PAT in the biopharmaceutical industry, including several case studies demonstrating the degree of maturity of various PAT tools. Graphical Abstract Hierarchy of QbD components.

Extending the applicability of the analytic hierarchy process

NARCIS (Netherlands)

Huizingh, K.R.E.; Vrolijk, H.C.J.

The Analytic Hierarchy Process (AHP) has often been used to support decisions that only have to be made once. in this study, we explore whether the AHP can be applied to repetitive decision-making. We suggest a variant of the process to elicit implicit decision models that evaluate alternatives not

Analytical solution of a stochastic content-based network model

International Nuclear Information System (INIS)

Mungan, Muhittin; Kabakoglu, Alkan; Balcan, Duygu; Erzan, Ayse

2005-01-01

We define and completely solve a content-based directed network whose nodes consist of random words and an adjacency rule involving perfect or approximate matches for an alphabet with an arbitrary number of letters. The analytic expression for the out-degree distribution shows a crossover from a leading power law behaviour to a log-periodic regime bounded by a different power law decay. The leading exponents in the two regions have a weak dependence on the mean word length, and an even weaker dependence on the alphabet size. The in-degree distribution, on the other hand, is much narrower and does not show any scaling behaviour

Using Analytic Hierarchy Process in Textbook Evaluation

Science.gov (United States)

Kato, Shigeo

2014-01-01

This study demonstrates the application of the analytic hierarchy process (AHP) in English language teaching materials evaluation, focusing in particular on its potential for systematically integrating different components of evaluation criteria in a variety of teaching contexts. AHP is a measurement procedure wherein pairwise comparisons are made…

Prioritizing factors affecting the hospital employees' productivity from the hospital managers' viewpoint using integrated decision-making trial and evaluation laboratory and analytic network process

Directory of Open Access Journals (Sweden)

Ardalan Feili

2018-01-01

Full Text Available Objectives: This study aimed to identify and prioritize factors affecting the hospital employees' productivity from the viewpoint of hospital managers working in the teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences, in 2017. Materials and Methods: This was an applied, cross-sectional, and descriptive-analytical study conducted in 2017 in all teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences. After identifying factors affecting hospital employees' productivity using the results of previous studies, all hospital managers (56 managers were selected as the study population using census method to prioritize the factors. The decision-making trial and evaluation laboratory (DEMATEL and analytic network process (ANP techniques were used for analyzing the collected data through Excel 2010 and Super Decision 2.8. Results: Fifteen factors affecting employees' productivity were determined using the results of previous studies which were classified into four clusters. The results of DEMATEL technique showed that “employees' attitude toward the organization” was the most affecting factor (r = 11.928 and also the most affected factor (c = 12.120, as well as the most important factor affecting the employees' productivity (r + c = 24.048. In addition, the results of ANP showed that the cluster of “leadership and management styles” (relative weight [RW] = 0.274 and its factors, especially “involving employees in the decision-making processes” (L1 (RW = 0.102 and “delegation of authority to the employees” (L2 (RW = 0.100 were the most important factors affecting the employees' productivity. Conclusion: According to the results, adopting an appropriate leadership style and providing participatory management, involving the employees in the hospital decision-making processes, etc., had significant effects on the increases in the employees' motivation and productivity.

Quantum Processes and Dynamic Networks in Physical and Biological Systems.

Science.gov (United States)

Dudziak, Martin Joseph

, by virtue of mathematical and computational models that may be transferred from the macroscopic domain to the microscopic. A consequence of this multi-faceted thesis is that there may be mature analytical tools and techniques that have heretofore not been adequately recognized for their value to quantum physics. These may include adaptations of neural networks, cellular automata, chaotic attractors, and parallel processing systems. Conceptual and practical architectures are presented for the development of software and hardware environments to employ massively parallel computing for the modeling of large populations of dynamic processes.

Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling.

Science.gov (United States)

Kornecki, Martin; Strube, Jochen

2018-03-16

Productivity improvements of mammalian cell culture in the production of recombinant proteins have been made by optimizing cell lines, media, and process operation. This led to enhanced titers and process robustness without increasing the cost of the upstream processing (USP); however, a downstream bottleneck remains. In terms of process control improvement, the process analytical technology (PAT) initiative, initiated by the American Food and Drug Administration (FDA), aims to measure, analyze, monitor, and ultimately control all important attributes of a bioprocess. Especially, spectroscopic methods such as Raman or near-infrared spectroscopy enable one to meet these analytical requirements, preferably in-situ. In combination with chemometric techniques like partial least square (PLS) or principal component analysis (PCA), it is possible to generate soft sensors, which estimate process variables based on process and measurement models for the enhanced control of bioprocesses. Macroscopic kinetic models can be used to simulate cell metabolism. These models are able to enhance the process understanding by predicting the dynamic of cells during cultivation. In this article, in-situ turbidity (transmission, 880 nm) and ex-situ Raman spectroscopy (785 nm) measurements are combined with an offline macroscopic Monod kinetic model in order to predict substrate concentrations. Experimental data of Chinese hamster ovary cultivations in bioreactors show a sufficiently linear correlation (R² ≥ 0.97) between turbidity and total cell concentration. PLS regression of Raman spectra generates a prediction model, which was validated via offline viable cell concentration measurement (RMSE ≤ 13.82, R² ≥ 0.92). Based on these measurements, the macroscopic Monod model can be used to determine different process attributes, e.g., glucose concentration. In consequence, it is possible to approximately calculate (R² ≥ 0.96) glucose concentration based on online cell

Network Monitoring as a Streaming Analytics Problem

KAUST Repository

Gupta, Arpit; Birkner, Rü diger; Canini, Marco; Feamster, Nick; Mac-Stoker, Chris; Willinger, Walter

2016-01-01

, processing such network monitoring queries at high traffic rates requires both the switches and the stream processors to filter the traffic iteratively and adaptively so as to extract only that traffic that is of interest to the query at hand. Others have

Networked business process management

NARCIS (Netherlands)

Grefen, P.W.P.J.

2013-01-01

In the current economy, a shift can be seen from stand-alone business organizations to networks of tightly collaborating business organizations. To allow this tight collaboration, business process management in these collaborative networks is becoming increasingly important. This paper discusses

Integration fuzzy analytic network process (ANP) and SWOT business strategy for the development of small and medium enterprises (SME)

Science.gov (United States)

Khotimah, Bain Khusnul; Irhamni, Firli; Kustiyahningsih, Yenny

2017-08-01

Business competition is one risk factor for Small and Medium Enterprises (SME) to set up good management in handling the risk of loss. This proposed research will look for criteria that influence the occurrence of damages based on data from by Cooperative and SME on Batik Madura. Method approach which used Fuzzy Analytic Network Process (FANP) as the weight of interest in decision support systems. Factor analysis of the level losses will influence the performance in the business sector. SWOT analysis combined with FANP method to determine the most appropriate development strategy to be applied industry. From the results of SWOT analysis and FANP, it was found the strategy of the best development to apply business strategy. The raw materials and human resources are available to increase the production capacity of the test results of SWOT analysis SME on Batik Madura. The result measurement of SME are always favourable the position, because the value is well resulted production and the amount is stable revenue which caused SME are in the first quadrant, so the power can exist take advantage of business opportunities. While the trial results of SWOT analysis on SME on Batik Madura in January and March are quadrant of second quadrant because of the number of defective products is quite produced, causing SME are under threat. But although SME suffer threats, SME still have strength on the amount of production and timely delivery.

The Analytic Hierarchy Process and Participatory Decisionmaking

Science.gov (United States)

Daniel L. Schmoldt; Daniel L. Peterson; Robert L. Smith

1995-01-01

Managing natural resource lands requires social, as well as biophysical, considerations. Unfortunately, it is extremely difficult to accurately assess and quantify changing social preferences, and to aggregate conflicting opinions held by diverse social groups. The Analytic Hierarchy Process (AHP) provides a systematic, explicit, rigorous, and robust mechanism for...

Numerical and semi-analytical modelling of the process induced distortions in pultrusion

DEFF Research Database (Denmark)

Baran, Ismet; Carlone, P.; Hattel, Jesper Henri

2013-01-01

, the transient distortions are inferred adopting a semi-analytical procedure, i.e. post processing numerical results by means of analytical methods. The predictions of the process induced distortion development using the aforementioned methods are found to be qualitatively close to each other...

Pattern-recalling processes in quantum Hopfield networks far from saturation

International Nuclear Information System (INIS)

Inoue, Jun-ichi

2011-01-01

As a mathematical model of associative memories, the Hopfield model was now well-established and a lot of studies to reveal the pattern-recalling process have been done from various different approaches. As well-known, a single neuron is itself an uncertain, noisy unit with a finite unnegligible error in the input-output relation. To model the situation artificially, a kind of 'heat bath' that surrounds neurons is introduced. The heat bath, which is a source of noise, is specified by the 'temperature'. Several studies concerning the pattern-recalling processes of the Hopfield model governed by the Glauber-dynamics at finite temperature were already reported. However, we might extend the 'thermal noise' to the quantum-mechanical variant. In this paper, in terms of the stochastic process of quantum-mechanical Markov chain Monte Carlo method (the quantum MCMC), we analytically derive macroscopically deterministic equations of order parameters such as 'overlap' in a quantum-mechanical variant of the Hopfield neural networks (let us call quantum Hopfield model or quantum Hopfield networks). For the case in which non-extensive number p of patterns are embedded via asymmetric Hebbian connections, namely, p/N → 0 for the number of neuron N → ∞ ('far from saturation'), we evaluate the recalling processes for one of the built-in patterns under the influence of quantum-mechanical noise.

The performance of the remote analytical laboratory during the first fluorinel dissolution process campaign

International Nuclear Information System (INIS)

Lewis, L.C.; Henscheid, J.P.

1989-01-01

The Remote Analytical Laboratory at the Idaho Chemical Processing Plant was designed to provide analytical chemistry support to the irradiated fuel processing and associated waste processing operations. The facility was put into radioactive operation on July 7, 1986, and operated for more than a year during the first fluorinel fuel dissolution process campaign. The facility incorporated a number of innovative features and was equipped with state-of-the-art analytical instrumentation. The success of the facility is a direct function of how well the remote analytical equipment performed. The performance is discussed in this article

Is a pre-analytical process for urinalysis required?

Science.gov (United States)

Petit, Morgane; Beaudeux, Jean-Louis; Majoux, Sandrine; Hennequin, Carole

2017-10-01

For the reliable urinary measurement of calcium, phosphate and uric acid, a pre-analytical process by adding acid or base to urine samples at laboratory is recommended in order to dissolve precipitated solutes. Several studies on different kind of samples and analysers have previously shown that a such pre-analytical treatment is useless. The objective was to study the necessity of pre-analytical treatment of urine on samples collected using the V-Monovette ® (Sarstedt) system and measured on the analyser Architect C16000 (Abbott Diagnostics). Sixty urinary samples of hospitalized patients were selected (n=30 for calcium and phosphate, and n=30 for uric acid). After acidification of urine samples for measurement of calcium and phosphate, and alkalinisation for measurement of uric acid respectively, differences between results before and after the pre-analytical treatment were compared to acceptable limits recommended by the French society of clinical biology (SFBC). No difference in concentration between before and after pre-analytical treatment of urine samples exceeded acceptable limits from SFBC for measurement of calcium and uric acid. For phosphate, only one sample exceeded these acceptable limits, showing a result paradoxically lower after acidification. In conclusion, in agreement with previous study, our results show that acidification or alkalinisation of urine samples from 24 h urines or from urination is not a pre-analytical necessity for measurement of calcium, phosphate and uric acid.

Green Degree Comprehensive Evaluation of Elevator Based on Fuzzy Analytic Hierarchy Process

Directory of Open Access Journals (Sweden)

Lizhen

2015-01-01

Full Text Available The green design of the elevator has many characteristics which contains many factors and the combination of qualitative and quantitative. In view of the fuzzy problem of evaluation index information, fuzzy analytic hierarchy process and fuzzy comprehensive evaluation model are combined to evaluate the green degree of elevator. In this method, the weights of the indexes are calculated by using the fuzzy analytic hierarchy process and the fuzzy analytic hierarchy process is used to calculate the weights of each level. The feasibility will be defined of using green degree evaluation of elevator system as an example to verify the method.

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

Directory of Open Access Journals (Sweden)

Wilten eNicola

2016-02-01

Full Text Available A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF. The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

Science.gov (United States)

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

Automatic-heuristic and executive-analytic processing during reasoning: Chronometric and dual-task considerations.

Science.gov (United States)

De Neys, Wim

2006-06-01

Human reasoning has been shown to overly rely on intuitive, heuristic processing instead of a more demanding analytic inference process. Four experiments tested the central claim of current dual-process theories that analytic operations involve time-consuming executive processing whereas the heuristic system would operate automatically. Participants solved conjunction fallacy problems and indicative and deontic selection tasks. Experiment 1 established that making correct analytic inferences demanded more processing time than did making heuristic inferences. Experiment 2 showed that burdening the executive resources with an attention-demanding secondary task decreased correct, analytic responding and boosted the rate of conjunction fallacies and indicative matching card selections. Results were replicated in Experiments 3 and 4 with a different secondary-task procedure. Involvement of executive resources for the deontic selection task was less clear. Findings validate basic processing assumptions of the dual-process framework and complete the correlational research programme of K. E. Stanovich and R. F. West (2000).

Quantitative high throughput analytics to support polysaccharide production process development.

Science.gov (United States)

Noyes, Aaron; Godavarti, Ranga; Titchener-Hooker, Nigel; Coffman, Jonathan; Mukhopadhyay, Tarit

2014-05-19

The rapid development of purification processes for polysaccharide vaccines is constrained by a lack of analytical tools current technologies for the measurement of polysaccharide recovery and process-related impurity clearance are complex, time-consuming, and generally not amenable to high throughput process development (HTPD). HTPD is envisioned to be central to the improvement of existing polysaccharide manufacturing processes through the identification of critical process parameters that potentially impact the quality attributes of the vaccine and to the development of de novo processes for clinical candidates, across the spectrum of downstream processing. The availability of a fast and automated analytics platform will expand the scope, robustness, and evolution of Design of Experiment (DOE) studies. This paper details recent advances in improving the speed, throughput, and success of in-process analytics at the micro-scale. Two methods, based on modifications of existing procedures, are described for the rapid measurement of polysaccharide titre in microplates without the need for heating steps. A simplification of a commercial endotoxin assay is also described that features a single measurement at room temperature. These assays, along with existing assays for protein and nucleic acids are qualified for deployment in the high throughput screening of polysaccharide feedstreams. Assay accuracy, precision, robustness, interference, and ease of use are assessed and described. In combination, these assays are capable of measuring the product concentration and impurity profile of a microplate of 96 samples in less than one day. This body of work relies on the evaluation of a combination of commercially available and clinically relevant polysaccharides to ensure maximum versatility and reactivity of the final assay suite. Together, these advancements reduce overall process time by up to 30-fold and significantly reduce sample volume over current practices. The

Neural networks in signal processing

International Nuclear Information System (INIS)

Govil, R.

2000-01-01

Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

A Process Management System for Networked Manufacturing

Science.gov (United States)

Liu, Tingting; Wang, Huifen; Liu, Linyan

With the development of computer, communication and network, networked manufacturing has become one of the main manufacturing paradigms in the 21st century. Under the networked manufacturing environment, there exist a large number of cooperative tasks susceptible to alterations, conflicts caused by resources and problems of cost and quality. This increases the complexity of administration. Process management is a technology used to design, enact, control, and analyze networked manufacturing processes. It supports efficient execution, effective management, conflict resolution, cost containment and quality control. In this paper we propose an integrated process management system for networked manufacturing. Requirements of process management are analyzed and architecture of the system is presented. And a process model considering process cost and quality is developed. Finally a case study is provided to explain how the system runs efficiently.

Adaptive cyclically dominating game on co-evolving networks: numerical and analytic results

Science.gov (United States)

Choi, Chi Wun; Xu, Chen; Hui, Pak Ming

2017-10-01

A co-evolving and adaptive Rock (R)-Paper (P)-Scissors (S) game (ARPS) in which an agent uses one of three cyclically dominating strategies is proposed and studied numerically and analytically. An agent takes adaptive actions to achieve a neighborhood to his advantage by rewiring a dissatisfying link with a probability p or switching strategy with a probability 1 - p. Numerical results revealed two phases in the steady state. An active phase for p pc has three separate clusters of agents using only R, P, and S, respectively with terminated adaptive actions. A mean-field theory based on the link densities in co-evolving network is formulated and the trinomial closure scheme is applied to obtain analytical solutions. The analytic results agree with simulation results on ARPS well. In addition, the different probabilities of winning, losing, and drawing a game among the agents are identified as the origin of the small discrepancy between analytic and simulation results. As a result of the adaptive actions, agents of higher degrees are often those being taken advantage of. Agents with a smaller (larger) degree than the mean degree have a higher (smaller) probability of winning than losing. The results are informative for future attempts on formulating more accurate theories.

Adverse Outcome Pathway Networks II: Network Analytics.

Science.gov (United States)

Villeneuve, Daniel L; Angrish, Michelle M; Fortin, Marie C; Katsiadaki, Ioanna; Leonard, Marc; Margiotta-Casaluci, Luigi; Munn, Sharon; O'Brien, Jason M; Pollesch, Nathan L; Smith, L Cody; Zhang, Xiaowei; Knapen, Dries

2018-02-28

Toxicological responses to stressors are more complex than the simple one biological perturbation to one adverse outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present paper introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using two example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses, or previously undefined emergent patterns of response, are introduced. Along with a companion article (Knapen et al. part I), these concepts set the stage for development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. Collectively, this work addresses one of the major themes identified through a SETAC Horizon Scanning effort focused on advancing the AOP framework. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

Developmental changes in analytic and holistic processes in face perception.

Science.gov (United States)

Joseph, Jane E; DiBartolo, Michelle D; Bhatt, Ramesh S

2015-01-01

Although infants demonstrate sensitivity to some kinds of perceptual information in faces, many face capacities continue to develop throughout childhood. One debate is the degree to which children perceive faces analytically versus holistically and how these processes undergo developmental change. In the present study, school-aged children and adults performed a perceptual matching task with upright and inverted face and house pairs that varied in similarity of featural or 2(nd) order configural information. Holistic processing was operationalized as the degree of serial processing when discriminating faces and houses [i.e., increased reaction time (RT), as more features or spacing relations were shared between stimuli]. Analytical processing was operationalized as the degree of parallel processing (or no change in RT as a function of greater similarity of features or spatial relations). Adults showed the most evidence for holistic processing (most strongly for 2(nd) order faces) and holistic processing was weaker for inverted faces and houses. Younger children (6-8 years), in contrast, showed analytical processing across all experimental manipulations. Older children (9-11 years) showed an intermediate pattern with a trend toward holistic processing of 2(nd) order faces like adults, but parallel processing in other experimental conditions like younger children. These findings indicate that holistic face representations emerge around 10 years of age. In adults both 2(nd) order and featural information are incorporated into holistic representations, whereas older children only incorporate 2(nd) order information. Holistic processing was not evident in younger children. Hence, the development of holistic face representations relies on 2(nd) order processing initially then incorporates featural information by adulthood.

Developmental changes in analytic and holistic processes in face perception

Directory of Open Access Journals (Sweden)

Jane Elizabeth Joseph

2015-08-01

Full Text Available Although infants demonstrate sensitivity to some kinds of perceptual information in faces, many face capacities continue to develop throughout childhood. One debate is the degree to which children perceive faces analytically versus holistically and how these processes undergo developmental change. In the present study, school-aged children and adults performed a perceptual matching task with upright and inverted face and house pairs that varied in similarity of featural or 2nd order configural information. Holistic processing was operationalized as the degree of serial processing when discriminating faces and houses (i.e., increased reaction time, RT, as more features or spacing relations were shared between stimuli. Analytical processing was operationalized as the degree of parallel processing (or no change in reaction time as a function of greater similarity of features or spatial relations. Adults showed the most evidence for holistic processing (most strongly for 2nd order faces and holistic processing was weaker for inverted faces and houses. Younger children (6-8 years, in contrast, showed analytical processing across all experimental manipulations. Older children (9-11 years showed an intermediate pattern with a trend toward holistic processing of 2nd order faces like adults, but parallel processing in other experimental conditions like younger children. These findings indicate that holistic face representations emerge around 10 years of age. In adults both 2nd order and featural information are incorporated into holistic representations, whereas older children only incorporate 2nd order information. Holistic processing was not evident in younger children. Hence, the development of holistic face representations relies on 2nd order processing initially then incorporates featural information by adulthood.

Developmental changes in analytic and holistic processes in face perception

Science.gov (United States)

Joseph, Jane E.; DiBartolo, Michelle D.; Bhatt, Ramesh S.

2015-01-01

Although infants demonstrate sensitivity to some kinds of perceptual information in faces, many face capacities continue to develop throughout childhood. One debate is the degree to which children perceive faces analytically versus holistically and how these processes undergo developmental change. In the present study, school-aged children and adults performed a perceptual matching task with upright and inverted face and house pairs that varied in similarity of featural or 2nd order configural information. Holistic processing was operationalized as the degree of serial processing when discriminating faces and houses [i.e., increased reaction time (RT), as more features or spacing relations were shared between stimuli]. Analytical processing was operationalized as the degree of parallel processing (or no change in RT as a function of greater similarity of features or spatial relations). Adults showed the most evidence for holistic processing (most strongly for 2nd order faces) and holistic processing was weaker for inverted faces and houses. Younger children (6–8 years), in contrast, showed analytical processing across all experimental manipulations. Older children (9–11 years) showed an intermediate pattern with a trend toward holistic processing of 2nd order faces like adults, but parallel processing in other experimental conditions like younger children. These findings indicate that holistic face representations emerge around 10 years of age. In adults both 2nd order and featural information are incorporated into holistic representations, whereas older children only incorporate 2nd order information. Holistic processing was not evident in younger children. Hence, the development of holistic face representations relies on 2nd order processing initially then incorporates featural information by adulthood. PMID:26300838

An integrated approach of analytical network process and fuzzy based spatial decision making systems applied to landslide risk mapping

Science.gov (United States)

Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar

2017-09-01

Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km2, is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.

Network Dynamics of Innovation Processes

Science.gov (United States)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

Evaluating Modeling Sessions Using the Analytic Hierarchy Process

NARCIS (Netherlands)

Ssebuggwawo, D.; Hoppenbrouwers, S.J.B.A.; Proper, H.A.; Persson, A.; Stirna, J.

2008-01-01

In this paper, which is methodological in nature, we propose to use an established method from the field of Operations Research, the Analytic Hierarchy Process (AHP), in the integrated, stakeholder- oriented evaluation of enterprise modeling sessions: their language, pro- cess, tool (medium), and

Network analysis literacy a practical approach to the analysis of networks

CERN Document Server

Zweig, Katharina A

2014-01-01

Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.

HOSPITAL SITE SELECTION USING TWO-STAGE FUZZY MULTI-CRITERIA DECISION MAKING PROCESS

Directory of Open Access Journals (Sweden)

Ali Soltani

2011-06-01

Full Text Available Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorbitant costs on city budget and damages the environment inevitably. Nowadays, multi-attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. Two well-known techniques, analytical hierarchal process and analytical network process are among multi-criteria decision making systems which can easily be consistent with both quantitative and qualitative criteria. These are also developed to be fuzzy analytical hierarchal process and fuzzy analytical network process systems which are capable of accommodating inherent uncertainty and vagueness in multi-criteria decision-making. This paper reports the process and results of a hospital site selection within the Region 5 of Shiraz metropolitan area, Iran using integrated fuzzy analytical network process systems with Geographic Information System (GIS. The weights of the alternatives were calculated using fuzzy analytical network process. Then a sensitivity analysis was conducted to measure the elasticity of a decision in regards to different criteria. This study contributes to planning practice by suggesting a more comprehensive decision making tool for site selection.

HOSPITAL SITE SELECTION USING TWO-STAGE FUZZY MULTI-CRITERIA DECISION MAKING PROCESS

Directory of Open Access Journals (Sweden)

Ali Soltani

2011-01-01

Full Text Available Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorbitant costs on city budget and damages the environment inevitably. Nowadays, multi-attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. Two well-known techniques, analytical hierarchal process and analytical network process are among multi-criteria decision making systems which can easily be consistent with both quantitative and qualitative criteria. These are also developed to be fuzzy analytical hierarchal process and fuzzy analytical network process systems which are capable of accommodating inherent uncertainty and vagueness in multi-criteria decision-making. This paper reports the process and results of a hospital site selection within the Region 5 of Shiraz metropolitan area, Iran using integrated fuzzy analytical network process systems with Geographic Information System (GIS. The weights of the alternatives were calculated using fuzzy analytical network process. Then a sensitivity analysis was conducted to measure the elasticity of a decision in regards to different criteria. This study contributes to planning practice by suggesting a more comprehensive decision making tool for site selection.

Partner Selection for Strategic Alliance in Networked Manufacturing

Institute of Scientific and Technical Information of China (English)

CHENYou-ping; YINYong; ZHOUZu-de

2004-01-01

Networked Manufacturing is the trend evolution for manufacture enterprise to gain core competence in the networked economy environment. In this paper, the definition of the strategic alliance is introduced and its life cycle is described. As the selection of suitable partners is of vital importance to the success for strategic alliance in Networked Manufacturing environment, also in this paper, the definition, criteria and process for partner selection are introduced. Then the fuzzy-AHP (Analytic Hierarchy Process) method, as a fuzzy extension of analytic hierarchical approach for partner selection, is given. In the end, a case study is provided.

Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

International Nuclear Information System (INIS)

Tsarouchas, D.; Markaki, A.E.

2011-01-01

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing.

Modelling dendritic ecological networks in space: anintegrated network perspective

Science.gov (United States)

Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within

Analytic Strategies of Streaming Data for eHealth.

Science.gov (United States)

Yoon, Sunmoo

2016-01-01

New analytic strategies for streaming big data from wearable devices and social media are emerging in ehealth. We face challenges to find meaningful patterns from big data because researchers face difficulties to process big volume of streaming data using traditional processing applications.1 This introductory 180 minutes tutorial offers hand-on instruction on analytics2 (e.g., topic modeling, social network analysis) of streaming data. This tutorial aims to provide practical strategies of information on reducing dimensionality using examples of big data. This tutorial will highlight strategies of incorporating domain experts and a comprehensive approach to streaming social media data.

Process and results of analytical framework and typology development for POINT

DEFF Research Database (Denmark)

Gudmundsson, Henrik; Lehtonen, Markku; Bauler, Tom

2009-01-01

POINT is a project about how indicators are used in practice; to what extent and in what way indicators actually influence, support, or hinder policy and decision making processes, and what could be done to enhance the positive role of indicators in such processes. The project needs an analytical......, a set of core concepts and associated typologies, a series of analytic schemes proposed, and a number of research propositions and questions for the subsequent empirical work in POINT....

Global analytic treatment of terrestrial photogrammetric networks

CERN Document Server

Mayoud, M

1980-01-01

In order to solve certain special CERN metrology problems, analytical terrestrial photogrammetry may have some advantages which are first discussed along with their drawbacks and limitations. In this application, it is necessary to carry out a rigorous and global adjustment of the observations and simultaneously process all the perspective ray bundles. The basic principles, the least squares solution and the stochastic analysis of the results are presented. However, for the CERN project, one wonders if the production of digital theodolites is going to reduce the advantages of the photogrammetric method. (12 refs).

Insights to Engineered Geothermal System Performance Using Gringarten-Witherspoon-Ohnishi Analytical Solutions and Fracture Network Models

Science.gov (United States)

Doe, T.; McLaren, R.; Finilla, A.

2017-12-01

An enduring legacy of Paul Witherspoon and his students and colleagues has been both the development of geothermal energy and the bases of modern fractured-rock hydrogeology. One of the seminal contributions to the geothermal field was Gringarten, Witherspoon, and Ohnishi's analytical models for enhanced geothermal systems. Although discrete fracture network (DFN) modeling developed somewhat independently in the late 1970s, Paul Witherspoon's foresight in promoting underground in situ testing at the Stripa Mine in Sweden was a major driver in Lawrence Berkeley Laboratory's contributions to its development.This presentation looks extensions of Gringarten's analytical model into discrete fracture network modeling as a basis for providing further insights into the challenges and opportunities of engineered geothermal systems. The analytical solution itself has many insightful applications beyond those presented in the original paper. The definition of dimensionless time by itself shows that thermal breakthrough has a second power dependence on surface area and on flow rate. The fracture intensity also plays a strong role, as it both increases the surface area and decrease his flow rate per fracture. The improvement of EGS performance with fracture intensity reaches a limit where thermal depletion of the rock lags only slightly behind the thermal breakthrough of cold water in the fracture network.Simple network models, which couple a DFN generator (FracMan) with a hydrothermally coupled flow solver (HydroGeoSphere) expand on Gringarten's concepts to show that realistic heterogeneity of spacing and transmissivity significantly degrades EGS performance. EGS production in networks of stimulated fractures initially follows Gringarten's type curves, with a later deviation is the smaller rock blocks thermally deplete and the entire stimulated volume acts as a single sink. Three-dimensional models of EGS performance show the critical importance of the relative magnitudes of

An Analytical Hierarchy Process Model for the Evaluation of College Experimental Teaching Quality

Science.gov (United States)

Yin, Qingli

2013-01-01

Taking into account the characteristics of college experimental teaching, through investigaton and analysis, evaluation indices and an Analytical Hierarchy Process (AHP) model of experimental teaching quality have been established following the analytical hierarchy process method, and the evaluation indices have been given reasonable weights. An…

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

Science.gov (United States)

Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Criminal Network Investigation: Processes, Tools, and Techniques

DEFF Research Database (Denmark)

Petersen, Rasmus Rosenqvist

important challenge for criminal network investigation, despite the massive attention it receives from research and media. Challenges such as the investigation process, the context of the investigation, human factors such as thinking and creativity, and political decisions and legal laws are all challenges...... that could mean the success or failure of criminal network investigations. % include commission reports as indications of process related problems .. to "play a little politics" !! Information, process, and human factors, are challenges we find to be addressable by software system support. Based on those......Criminal network investigations such as police investigations, intelligence analysis, and investigative journalism involve a range of complex knowledge management processes and tasks. Criminal network investigators collect, process, and analyze information related to a specific target to create...

Wireless network development for the automatic registration of parameters in laboratories of nuclear analytical techniques

International Nuclear Information System (INIS)

Tincopa, Jean Pierre; Baltuano, Oscar; Bedregal, Patricia

2015-01-01

This paper presents in detail the development of a low-cost wireless network for automatic recording of temperature and relative humidity parameters in the laboratory of nuclear analytical techniques. This prototype has a DHT22 sensor which gives us both parameters with high precision and are automatically read and displayed by a ATmega328P microcontroller. This data is then transmitted through transceivers Xbee Pro S2B forming a mesh network for real time storage using an RTC (Real Time Clock). We present the experimental results obtained in its implementation. (author)

ANALISIS PROBLEMATIKA ZAKAT PADA BAZNAS KOTA TASIKMALAYA:PENDEKATAN METODE ANALYTIC NETWORK PROCESS (ANP

Directory of Open Access Journals (Sweden)

Irman Firmansyah

2014-04-01

Full Text Available Zakat is an obligation that must be carried out by muzakki that not only aims to carry out obligations to Almighty but sharp-edged nature of social justice among mankind. Therefore charity must be managed properly by the board amilin especially by channeling zakat use specifically targeted at Tasikmalaya City Baznas charity board. The study was to examine the affairs of Baznas perzakatan at Tasikmalaya City. Analysis tool used namely Analysis Network Process (ANP is a qualitative-quantitative method using super decision software . The analysis showed that there is an internal problem which consists of lacking leadership and lacking performance OPZ performance. The problems consist of the absence of external PERDA about channeling zakat institutions and communities less know Baznas. As for an internal solution consisting of leadership and performance maximization of transparency and distribution, while the external solution consisted of socialization and support Baznas scholars. Kendall coefficient ( W ranged from 0.970 to 0.9975 means that all respondents have the same relative answer.

The analytic hierarchy process as a support for decision making

Directory of Open Access Journals (Sweden)

Filipović Milanka

2007-01-01

Full Text Available The first part of this text deals with a convention site selection as one of the most lucrative areas in the tourism industry. The second part gives a further description of a method for decision making - the analytic hierarchy process. The basic characteristics: hierarchy constructions and pair wise comparison on the given level of the hierarchy are allured. The third part offers an example of application. This example is solved using the Super - Decision software, which is developed as a computer support for the analytic hierarchy process. This indicates that the AHP approach is a useful tool to help support a decision of convention site selection. .

Quality-by-Design (QbD): An integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and process design space development.

Science.gov (United States)

Wu, Huiquan; White, Maury; Khan, Mansoor A

2011-02-28

The aim of this work was to develop an integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and design space development. A dynamic co-precipitation process by gradually introducing water to the ternary system of naproxen-Eudragit L100-alcohol was monitored at real-time in situ via Lasentec FBRM and PVM. 3D map of count-time-chord length revealed three distinguishable process stages: incubation, transition, and steady-state. The effects of high risk process variables (slurry temperature, stirring rate, and water addition rate) on both derived co-precipitation process rates and final chord-length-distribution were evaluated systematically using a 3(3) full factorial design. Critical process variables were identified via ANOVA for both transition and steady state. General linear models (GLM) were then used for parameter estimation for each critical variable. Clear trends about effects of each critical variable during transition and steady state were found by GLM and were interpreted using fundamental process principles and Nyvlt's transfer model. Neural network models were able to link process variables with response variables at transition and steady state with R(2) of 0.88-0.98. PVM images evidenced nucleation and crystal growth. Contour plots illustrated design space via critical process variables' ranges. It demonstrated the utility of integrated PAT approach for QbD development. Published by Elsevier B.V.

Analytical model of a burst assembly algorithm for the VBR in the OBS networks

International Nuclear Information System (INIS)

Shargabi, M.A.A.; Mellah, H.; Abid, A.

2008-01-01

This paper presents a proposed analytical model for the number of bursts aggregated in a period of time in OBS networks. The model considers the case of VBR traffic with two different sending rates, which are SCR and PCR. The model is validated using extensive simulations. Where results from simulations are in total agreement with the results obtained by the proposed model. (author)

Social network supported process recommender system.

Science.gov (United States)

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

Social Network Supported Process Recommender System

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Yanming Ye

2014-01-01

Full Text Available Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

Understanding Process in Group-Based Intervention Delivery: Social Network Analysis and Intra-entity Variability Methods as Windows into the "Black Box".

Science.gov (United States)

Molloy Elreda, Lauren; Coatsworth, J Douglas; Gest, Scott D; Ram, Nilam; Bamberger, Katharine

2016-11-01

Although the majority of evidence-based programs are designed for group delivery, group process and its role in participant outcomes have received little empirical attention. Data were collected from 20 groups of participants (94 early adolescents, 120 parents) enrolled in an efficacy trial of a mindfulness-based adaptation of the Strengthening Families Program (MSFP). Following each weekly session, participants reported on their relations to group members. Social network analysis and methods sensitive to intraindividual variability were integrated to examine weekly covariation between group process and participant progress, and to predict post-intervention outcomes from levels and changes in group process. Results demonstrate hypothesized links between network indices of group process and intervention outcomes and highlight the value of this unique analytic approach to studying intervention group process.

Big Data Analytics for Industrial Process Control

DEFF Research Database (Denmark)

Khan, Abdul Rauf; Schioler, Henrik; Kulahci, Murat

2017-01-01

Today, in modern factories, each step in manufacturing produces a bulk of valuable as well as highly precise information. This provides a great opportunity for understanding the hidden statistical dependencies in the process. Systematic analysis and utilization of advanced analytical methods can ...... lead towards more informed decisions. In this article we discuss some of the challenges related to big data analysis in manufacturing and relevant solutions to some of these challenges....

An analytically resolved model of a potato's thermal processing using Heun functions

Science.gov (United States)

Vargas Toro, Agustín.

2014-05-01

A potato's thermal processing model is solved analytically. The model is formulated using the equation of heat diffusion in the case of a spherical potato processed in a furnace, and assuming that the potato's thermal conductivity is radially modulated. The model is solved using the method of the Laplace transform, applying Bromwich Integral and Residue Theorem. The temperatures' profile in the potato is presented as an infinite series of Heun functions. All computations are performed with computer algebra software, specifically Maple. Using the numerical values of the thermal parameters of the potato and geometric and thermal parameters of the processing furnace, the time evolution of the temperatures in different regions inside the potato are presented analytically and graphically. The duration of thermal processing in order to achieve a specified effect on the potato is computed. It is expected that the obtained analytical results will be important in food engineering and cooking engineering.

Some applications of fuzzy sets and the analytical hierarchy process to decision making

OpenAIRE

Castro, Alberto Rosas

1984-01-01

Approved for public release; distribution unlimited This thesis examines the use of fuzzy set theory and the analytic hierarchy process in decision making. It begins by reviewing the insight of psychologists, social scientists and computer scientists to the decision making process. The Operations Research- Systems Analysis approach is discussed followed by a presentation of the basis of fuzzy set theory and the analytic hierarchy process. Two applications of these meth...

Improving drug manufacturing with process analytical technology.

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Rodrigues, Licinia O; Alves, Teresa P; Cardoso, Joaquim P; Menezes, José C

2006-01-01

Within the process analytical technology (PAT) framework, as presented in the US Food and Drug Administration guidelines, the aim is to design, develop and operate processes consistently to ensure a pre-defined level of quality at the end of the manufacturing process. Three PAT implementation scenarios can be envisaged. Firstly, PAT could be used in its most modest version (in an almost non-PAT manner) to simply replace an existing quality control protocol (eg, using near-infrared spectroscopy for an in-process quality control, such as moisture content). Secondly, the use of in-process monitoring and process analysis could be integrated to enhance process understanding and operation for an existing industrial process. Thirdly, PAT could be used extensively and exclusively throughout development, scale-up and full-scale production of a new product and process. Although the first type of implementations are well known, reports of the second and third types remain scarce. Herein, results obtained from PAT implementations of the second and third types are described for two industrial processes for preparing bulk active pharmaceutical ingredients, demonstrating the benefits in terms of increased process understanding and process control.

Penerapan Metode Analytic Network Process (ANP Untuk Pendukung Keputusan Pemilihan Tema Tugas Akhir (Studi Kasus: Program Studi S1 Informatika ST3 Telkom

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Dila Nurlaila

2017-07-01

Full Text Available Berdasarkan hasil dari survey yang dilakukan terhadap 30 mahasiswa Informatika yang akan mengambil mata kuliah tugas akhir, lebih dari 80% menjawab belum memiliki konsep Tugas Akhir, hal ini menjadi perhatian bahwa masih banyak dari mahasiswa yang belum mengetahui tema Tugas Akhir apa yang akan dambilnya nanti yang sesuai dengan minat dan kompetensinya. Dari hal tersebut akan dilakukan penelitian penerapan metode Analytic Network Process (ANP pada  Pendukung keputusan pemilihan tugas tema Tugas Akhir. ANP merupakan suatu metode dalam decision making yang mempertimbangkan hubungan antar kriteria. Penelitian ini bertujuan untuk menguji tingkat keberhasilan metode ANP dalam mengatasi masalah mahasiswa yang belum mengetahui konsep dari tugas akhir. Langkah pertama, ditentukan kriteria yang menjadi penentu dari pemilihan tema Tugas Akhir di prodi S1 Informatika. Kriteria ini akan dibuat model jaringan ANP menggunakan software super decision dan setiap kriteria akan dilakukan pairwised comparison (perbandingan berpasangan guna untuk mendapatkan pembobotan dari masing – masing kriteria dan sub kriteria. Yang menjadi expert judgement pada pengambil keputusan ini adalah ketua keahlian program studi ICM dan DESTI. Setelah melakukan pengujian dengan membandingkan pilihan secara manual dengan pilihan berdasarkan perhitungan ANP hasilnya sebesar 46,6% tema tugas akhir mahasiswa sesuai dan akurat, hilangnya 53,4% akurasi dikarenakan ketidak sesuaian jawaban mahasiswa saat menentukan nilai peminatan.

Literature Review on Processing and Analytical Methods for ...

Science.gov (United States)

Report The purpose of this report was to survey the open literature to determine the current state of the science regarding the processing and analytical methods currently available for recovery of F. tularensis from water and soil matrices, and to determine what gaps remain in the collective knowledge concerning F. tularensis identification from environmental samples.

Multiattribute Supplier Selection Using Fuzzy Analytic Hierarchy Process

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Serhat Aydin

2010-11-01

Full Text Available Supplier selection is a multiattribute decision making (MADM problem which contains both qualitative and quantitative factors. Supplier selection has vital importance for most companies. The aim of this paper is to provide an AHP based analytical tool for decision support enabling an effective multicriteria supplier selection process in an air conditioner seller firm under fuzziness. In this article, the Analytic Hierarchy Process (AHP under fuzziness is employed for its permissiveness to use an evaluation scale including linguistic expressions, crisp numerical values, fuzzy numbers and range numerical values. This scale provides a more flexible evaluation compared with the other fuzzy AHP methods. In this study, the modified AHP was used in supplier selection in an air conditioner firm. Three experts evaluated the suppliers according to the proposed model and the most appropriate supplier was selected. The proposed model enables decision makers select the best supplier among supplier firms effectively. We confirm that the modified fuzzy AHP is appropriate for group decision making in supplier selection problems.

Mining Heterogeneous Information Networks by Exploring the Power of Links

Science.gov (United States)

Han, Jiawei

Knowledge is power but for interrelated data, knowledge is often hidden in massive links in heterogeneous information networks. We explore the power of links at mining heterogeneous information networks with several interesting tasks, including link-based object distinction, veracity analysis, multidimensional online analytical processing of heterogeneous information networks, and rank-based clustering. Some recent results of our research that explore the crucial information hidden in links will be introduced, including (1) Distinct for object distinction analysis, (2) TruthFinder for veracity analysis, (3) Infonet-OLAP for online analytical processing of information networks, and (4) RankClus for integrated ranking-based clustering. We also discuss some of our on-going studies in this direction.

A convergent model for distributed processing of Big Sensor Data in urban engineering networks

Science.gov (United States)

Parygin, D. S.; Finogeev, A. G.; Kamaev, V. A.; Finogeev, A. A.; Gnedkova, E. P.; Tyukov, A. P.

2017-01-01

The problems of development and research of a convergent model of the grid, cloud, fog and mobile computing for analytical Big Sensor Data processing are reviewed. The model is meant to create monitoring systems of spatially distributed objects of urban engineering networks and processes. The proposed approach is the convergence model of the distributed data processing organization. The fog computing model is used for the processing and aggregation of sensor data at the network nodes and/or industrial controllers. The program agents are loaded to perform computing tasks for the primary processing and data aggregation. The grid and the cloud computing models are used for integral indicators mining and accumulating. A computing cluster has a three-tier architecture, which includes the main server at the first level, a cluster of SCADA system servers at the second level, a lot of GPU video cards with the support for the Compute Unified Device Architecture at the third level. The mobile computing model is applied to visualize the results of intellectual analysis with the elements of augmented reality and geo-information technologies. The integrated indicators are transferred to the data center for accumulation in a multidimensional storage for the purpose of data mining and knowledge gaining.

Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology.

Science.gov (United States)

Rüdt, Matthias; Briskot, Till; Hubbuch, Jürgen

2017-03-24

Process analytical technologies (PAT) for the manufacturing of biologics have drawn increased interest in the last decade. Besides being encouraged by the Food and Drug Administration's (FDA's) PAT initiative, PAT promises to improve process understanding, reduce overall production costs and help to implement continuous manufacturing. This article focuses on spectroscopic tools for PAT in downstream processing (DSP). Recent advances and future perspectives will be reviewed. In order to exploit the full potential of gathered data, chemometric tools are widely used for the evaluation of complex spectroscopic information. Thus, an introduction into the field will be given. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Raman spectroscopy as a process analytical technology for pharmaceutical manufacturing and bioprocessing.

Science.gov (United States)

Esmonde-White, Karen A; Cuellar, Maryann; Uerpmann, Carsten; Lenain, Bruno; Lewis, Ian R

2017-01-01

Adoption of Quality by Design (QbD) principles, regulatory support of QbD, process analytical technology (PAT), and continuous manufacturing are major factors effecting new approaches to pharmaceutical manufacturing and bioprocessing. In this review, we highlight new technology developments, data analysis models, and applications of Raman spectroscopy, which have expanded the scope of Raman spectroscopy as a process analytical technology. Emerging technologies such as transmission and enhanced reflection Raman, and new approaches to using available technologies, expand the scope of Raman spectroscopy in pharmaceutical manufacturing, and now Raman spectroscopy is successfully integrated into real-time release testing, continuous manufacturing, and statistical process control. Since the last major review of Raman as a pharmaceutical PAT in 2010, many new Raman applications in bioprocessing have emerged. Exciting reports of in situ Raman spectroscopy in bioprocesses complement a growing scientific field of biological and biomedical Raman spectroscopy. Raman spectroscopy has made a positive impact as a process analytical and control tool for pharmaceutical manufacturing and bioprocessing, with demonstrated scientific and financial benefits throughout a product's lifecycle.

Assessing Adult Learning Preferences Using the Analytic Hierarchy Process.

Science.gov (United States)

Lee, Doris; McCool, John; Napieralski, Laura

2000-01-01

Graduate students (n=134) used the analytic hierarchy process, which weights expressed preferences, to rate four learning activities: lectures, discussion/reflection, individual projects, and group projects. Their preferences for discussion/reflection and individual projects were independent of auditory, visual, and kinesthetic learning styles.…

Learning drifting concepts with neural networks

NARCIS (Netherlands)

Biehl, Michael; Schwarze, Holm

1993-01-01

The learning of time-dependent concepts with a neural network is studied analytically and numerically. The linearly separable target rule is represented by an N-vector, whose time dependence is modelled by a random or deterministic drift process. A single-layer network is trained online using

Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks

KAUST Repository

Elsawy, Hesham

2014-11-01

Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.

Technical Reviews on Pattern Recognition in Process Analytical Technology

International Nuclear Information System (INIS)

Kim, Jong Yun; Choi, Yong Suk; Ji, Sun Kyung; Park, Yong Joon; Song, Kyu Seok; Jung, Sung Hee

2008-12-01

Pattern recognition is one of the first and the most widely adopted chemometric tools among many active research area in chemometrics such as design of experiment(DoE), pattern recognition, multivariate calibration, signal processing. Pattern recognition has been used to identify the origin of a wine and the time of year that the vine was grown by using chromatography, cause of fire by using GC/MS chromatography, detection of explosives and land mines, cargo and luggage inspection in seaports and airports by using a prompt gamma-ray activation analysis, and source apportionment of environmental pollutant by using a stable isotope ratio mass spectrometry. Recently, pattern recognition has been taken into account as a major chemometric tool in the so-called 'process analytical technology (PAT)', which is a newly-developed concept in the area of process analytics proposed by US Food and Drug Administration (US FDA). For instance, identification of raw material by using a pattern recognition analysis plays an important role for the effective quality control of the production process. Recently, pattern recognition technique has been used to identify the spatial distribution and uniformity of the active ingredients present in the product such as tablet by transforming the chemical data into the visual information

Actor networks in strategic niche management : insights from social network theory

NARCIS (Netherlands)

Caniëls, M.C.J.; Romijn, H.A.

2008-01-01

This paper contributes to Strategic Niche Management (SNM), an analytical technique designed to facilitate the introduction and diffusion of radically new sustainable technologies through societal experiments. According to SNM, intensive networking among social actors is a crucial process for the

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics

Science.gov (United States)

2017-01-01

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

Science.gov (United States)

Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier

2017-10-21

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.

Designing Robust Process Analytical Technology (PAT) Systems for Crystallization Processes: A Potassium Dichromate Crystallization Case Study

DEFF Research Database (Denmark)

Abdul Samad, Noor Asma Fazli Bin; Sin, Gürkan

2013-01-01

The objective of this study is to test and validate a Process Analytical Technology (PAT) system design on a potassium dichromate crystallization process in the presence of input uncertainties using uncertainty and sensitivity analysis. To this end a systematic framework for managing uncertaintie...

Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities

Directory of Open Access Journals (Sweden)

Peyman Babashamsi

2016-03-01

Full Text Available Maintenance activities and pavement rehabilitation require the allocation of massive finances. Yet due to budget shortfalls, stakeholders and decision-makers must prioritize projects in maintenance and rehabilitation. This article addresses the prioritization of pavement maintenance alternatives by integrating the fuzzy analytic hierarchy process (AHP with the VIKOR method (which stands for ‘VlseKriterijumska Optimizacija I Kompromisno Resenje,’ meaning multi-criteria optimization and compromise solution for the process of multi-criteria decision analysis (MCDA by considering various pavement network indices. The indices selected include the pavement condition index (PCI, traffic congestion, pavement width, improvement and maintenance costs, and the time required to operate. In order to determine the weights of the indices, the fuzzy AHP is used. Subsequently, the alternatives’ priorities are ranked according to the indices weighted with the VIKOR model. The choice of these two independent methods was motivated by the fact that integrating fuzzy AHP with the VIKOR model can assist decision makers with solving MCDA problems. The case study was conducted on a pavement network within the same particular region in Tehran; three main streets were chosen that have an empirically higher maintenance demand. The most significant factors were evaluated and the project with the highest priority was selected for urgent maintenance. By comparing the index values of the alternative priorities, Delavaran Blvd. was revealed to have higher priority over the other streets in terms of maintenance and rehabilitation activities. Keywords: Maintenance and rehabilitation prioritization, Fuzzy analysis hierarchy process, VIKOR model, Pavement condition index, Multi-criteria decision analysis

Robust recurrent neural network modeling for software fault detection and correction prediction

International Nuclear Information System (INIS)

Hu, Q.P.; Xie, M.; Ng, S.H.; Levitin, G.

2007-01-01

Software fault detection and correction processes are related although different, and they should be studied together. A practical approach is to apply software reliability growth models to model fault detection, and fault correction process is assumed to be a delayed process. On the other hand, the artificial neural networks model, as a data-driven approach, tries to model these two processes together with no assumptions. Specifically, feedforward backpropagation networks have shown their advantages over analytical models in fault number predictions. In this paper, the following approach is explored. First, recurrent neural networks are applied to model these two processes together. Within this framework, a systematic networks configuration approach is developed with genetic algorithm according to the prediction performance. In order to provide robust predictions, an extra factor characterizing the dispersion of prediction repetitions is incorporated into the performance function. Comparisons with feedforward neural networks and analytical models are developed with respect to a real data set

Synthesis and Design of Integrated Process and Water Networks

DEFF Research Database (Denmark)

Handani, Zainatul B.; Quaglia, Alberto; Gani, Rafiqul

2015-01-01

This work presents the development of a systematic framework for a simultaneous synthesis and design of process and water networks using the superstructure-based optimization approach. In this framework, a new superstructure combining both networks is developed by attempting to consider all...... possible options with respect to the topology of the process and water networks, leading to Mixed Integer Non Linear Programming (MINLP) problem. A solution strategy to solve the multi-network problem accounts explicitly the interactions between the networks by selecting suitable technologies in order...... to transform raw materials into products and produce clean water to be reused in the process at the early stage of design. Since the connection between the process network and the wastewater treatment network is not a straight forward connection, a new converter interval is introduced in order to convert...

Efficient Online Processing for Advanced Analytics

OpenAIRE

El Seidy, Mohamed Elsayed Mohamed Ahmed

2017-01-01

With the advent of emerging technologies and the Internet of Things, the importance of online data analytics has become more pronounced. Businesses and companies are adopting approaches that provide responsive analytics to stay competitive in the global marketplace. Online analytics allow data analysts to promptly react to patterns or to gain preliminary insights from early results that aid in research, decision making, and effective strategy planning. The growth of data-velocity in a variety...

Framework for developing a spatial walkability index (SWI) for the light-rail transit (LRT) stations in Kuala Lumpur city centre using analytical network process (ANP) and GIS

Science.gov (United States)

Naharudin, Nabilah; Ahamad, Mohd Sanusi S.; Sadullah, Ahmad Farhan Mohd

2017-10-01

In support to the nation's goal of developing a liveable city, Malaysian government aims to improve the mobility in Kuala Lumpur by providing good quality transit services across the city. However, the public starts to demand for more than just a connectivity between two points. They want their transit journey to be comfortable and pleasant from the very first mile. The key here is the first and last mile (FLM) of the transit service which defines their journey to access the station itself. The question is, does the existing transit services' FLM satisfy public's needs? Therefore, many studies had emerged in attempt to assess the pedestrian-friendliness. While most of them did base on the pedestrian's perceptions, there were also studies that spatially measured the connectivity and accessibility to various landuses and point of interests. While both can be a good method, their integration could actually produce a better assessment. However, till date, only a few studies had attempted to do so. This paper proposes a framework to develop a Spatial Walkability Index (SWI) by integrating a multicriteria evaluation technique, Analytical Network Process (ANP) and network analysis on geographical information system (GIS) platform. First, ANP will aggregate the degree of importance for each walkability criteria based on the pedestrian's perceptions. Then, the network analysis will use the weighted criteria as attributes to find the walkable routes within half mile radius from each station. The index will be calculated by rationing the total length of walkable routes in respect to the available footpath. The final outcome is a percentage of walkable FLM transit routes for each station which will be named as the SWI. It is expected that the developed framework can be applied in other cities across the globe. It can also be improvised to suit the demand and purpose there.

Discrete event simulation of the Defense Waste Processing Facility (DWPF) analytical laboratory

International Nuclear Information System (INIS)

Shanahan, K.L.

1992-02-01

A discrete event simulation of the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) analytical laboratory has been constructed in the GPSS language. It was used to estimate laboratory analysis times at process analytical hold points and to study the effect of sample number on those times. Typical results are presented for three different simultaneous representing increasing levels of complexity, and for different sampling schemes. Example equipment utilization time plots are also included. SRS DWPF laboratory management and chemists found the simulations very useful for resource and schedule planning

Using the Analytic Hierarchy Process to Analyze Multiattribute Decisions.

Science.gov (United States)

Spires, Eric E.

1991-01-01

The use of the Analytic Hierarchy Process (AHP) in assisting researchers to analyze decisions is discussed. The AHP is compared with other decision-analysis techniques, including multiattribute utility measurement, conjoint analysis, and general linear models. Insights that AHP can provide are illustrated with data gathered in an auditing context.…

Optimizing an Immersion ESL Curriculum Using Analytic Hierarchy Process

Science.gov (United States)

Tang, Hui-Wen Vivian

2011-01-01

The main purpose of this study is to fill a substantial knowledge gap regarding reaching a uniform group decision in English curriculum design and planning. A comprehensive content-based course criterion model extracted from existing literature and expert opinions was developed. Analytical hierarchy process (AHP) was used to identify the relative…

Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

Science.gov (United States)

Ly, Cheng

2015-12-01

Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, we study how these two forms of heterogeneity lead to different distributions of excitatory firing rates. To analytically characterize how these types of heterogeneities affect the network, we employ a dimension reduction method that relies on a combination of Monte Carlo simulations and probability density function equations. We find that the relationship between intrinsic and network heterogeneity has a strong effect on the overall level of heterogeneity of the firing rates. Specifically, this relationship can lead to amplification or attenuation of firing rate heterogeneity, and these effects depend on whether the recurrent network is firing asynchronously or rhythmically firing. These observations are captured with the aforementioned reduction method, and furthermore simpler analytic descriptions based on this dimension reduction method are developed. The final analytic descriptions provide compact and descriptive formulas for how the relationship between intrinsic and network heterogeneity determines the firing rate heterogeneity dynamics in various settings.

Evaluation and selection of in-situ leaching mining method using analytic hierarchy process

International Nuclear Information System (INIS)

Zhao Heyong; Tan Kaixuan; Liu Huizhen

2007-01-01

According to the complicated conditions and main influence factors of in-situ leaching min- ing, a model and processes of analytic hierarchy are established for evaluation and selection of in-situ leaching mining methods based on analytic hierarchy process. Taking a uranium mine in Xinjiang of China for example, the application of this model is presented. The results of analyses and calculation indicate that the acid leaching is the optimum project. (authors)

Pre-processing for Triangulation of Probabilistic Networks

NARCIS (Netherlands)

Bodlaender, H.L.; Koster, A.M.C.A.; Eijkhof, F. van den; Gaag, L.C. van der

2001-01-01

The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a networks graph. In this paper, we show that pre-processing can help in finding good triangulations for probabilistic networks, that is, triangulations with a minimal maximum

What makes us think? A three-stage dual-process model of analytic engagement.

Science.gov (United States)

Pennycook, Gordon; Fugelsang, Jonathan A; Koehler, Derek J

2015-08-01

The distinction between intuitive and analytic thinking is common in psychology. However, while often being quite clear on the characteristics of the two processes ('Type 1' processes are fast, autonomous, intuitive, etc. and 'Type 2' processes are slow, deliberative, analytic, etc.), dual-process theorists have been heavily criticized for being unclear on the factors that determine when an individual will think analytically or rely on their intuition. We address this issue by introducing a three-stage model that elucidates the bottom-up factors that cause individuals to engage Type 2 processing. According to the model, multiple Type 1 processes may be cued by a stimulus (Stage 1), leading to the potential for conflict detection (Stage 2). If successful, conflict detection leads to Type 2 processing (Stage 3), which may take the form of rationalization (i.e., the Type 1 output is verified post hoc) or decoupling (i.e., the Type 1 output is falsified). We tested key aspects of the model using a novel base-rate task where stereotypes and base-rate probabilities cued the same (non-conflict problems) or different (conflict problems) responses about group membership. Our results support two key predictions derived from the model: (1) conflict detection and decoupling are dissociable sources of Type 2 processing and (2) conflict detection sometimes fails. We argue that considering the potential stages of reasoning allows us to distinguish early (conflict detection) and late (decoupling) sources of analytic thought. Errors may occur at both stages and, as a consequence, bias arises from both conflict monitoring and decoupling failures. Copyright © 2015 Elsevier Inc. All rights reserved.

Aplikasi Analytical Hierarchy Process Pada Pemilihan Metode Analisis Zat Organik Dalam Air

Directory of Open Access Journals (Sweden)

Dino Rimantho

2016-07-01

Full Text Available Water is one of the food products analyzed in water chemistry and environmental laboratories. One of the parameters analyzed are organic substances. The number of samples that were not comparable with the analytical skills can cause delays in test results. Analytical Hierarchy Process applied to evaluate the analytical methods used. Alternative methods tested include titrimetric method, spectrophotometry, and total organic carbon (TOC. Respondents consisted of deputy technical manager, laboratory coordinator, and two senior analysts. Alternative results obtained are methods of TOC. Proposed improvements alternative analytical method based on the results obtained, the method of the TOC with a 10-15 minute analysis time and use of CRM to the validity of the analysis results.

Improving Earth/Prediction Models to Improve Network Processing

Science.gov (United States)

Wagner, G. S.

2017-12-01

The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

Learning Analytics for Networked Learning Models

Science.gov (United States)

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

Combining Vertex-centric Graph Processing with SPARQL for Large-scale RDF Data Analytics

KAUST Repository

Abdelaziz, Ibrahim

2017-06-27

Modern applications, such as drug repositioning, require sophisticated analytics on RDF graphs that combine structural queries with generic graph computations. Existing systems support either declarative SPARQL queries, or generic graph processing, but not both. We bridge the gap by introducing Spartex, a versatile framework for complex RDF analytics. Spartex extends SPARQL to support programs that combine seamlessly generic graph algorithms (e.g., PageRank, Shortest Paths, etc.) with SPARQL queries. Spartex builds on existing vertex-centric graph processing frameworks, such as Graphlab or Pregel. It implements a generic SPARQL operator as a vertex-centric program that interprets SPARQL queries and executes them efficiently using a built-in optimizer. In addition, any graph algorithm implemented in the underlying vertex-centric framework, can be executed in Spartex. We present various scenarios where our framework simplifies significantly the implementation of complex RDF data analytics programs. We demonstrate that Spartex scales to datasets with billions of edges, and show that our core SPARQL engine is at least as fast as the state-of-the-art specialized RDF engines. For complex analytical tasks that combine generic graph processing with SPARQL, Spartex is at least an order of magnitude faster than existing alternatives.

Model and Analytic Processes for Export License Assessments

Energy Technology Data Exchange (ETDEWEB)

Thompson, Sandra E.; Whitney, Paul D.; Weimar, Mark R.; Wood, Thomas W.; Daly, Don S.; Brothers, Alan J.; Sanfilippo, Antonio P.; Cook, Diane; Holder, Larry

2011-09-29

This paper represents the Department of Energy Office of Nonproliferation Research and Development (NA-22) Simulations, Algorithms and Modeling (SAM) Program's first effort to identify and frame analytical methods and tools to aid export control professionals in effectively predicting proliferation intent; a complex, multi-step and multi-agency process. The report focuses on analytical modeling methodologies that alone, or combined, may improve the proliferation export control license approval process. It is a follow-up to an earlier paper describing information sources and environments related to international nuclear technology transfer. This report describes the decision criteria used to evaluate modeling techniques and tools to determine which approaches will be investigated during the final 2 years of the project. The report also details the motivation for why new modeling techniques and tools are needed. The analytical modeling methodologies will enable analysts to evaluate the information environment for relevance to detecting proliferation intent, with specific focus on assessing risks associated with transferring dual-use technologies. Dual-use technologies can be used in both weapons and commercial enterprises. A decision-framework was developed to evaluate which of the different analytical modeling methodologies would be most appropriate conditional on the uniqueness of the approach, data availability, laboratory capabilities, relevance to NA-22 and Office of Arms Control and Nonproliferation (NA-24) research needs and the impact if successful. Modeling methodologies were divided into whether they could help micro-level assessments (e.g., help improve individual license assessments) or macro-level assessment. Macro-level assessment focuses on suppliers, technology, consumers, economies, and proliferation context. Macro-level assessment technologies scored higher in the area of uniqueness because less work has been done at the macro level. An

A universal, fault-tolerant, non-linear analytic network for modeling and fault detection

International Nuclear Information System (INIS)

Mott, J.E.; King, R.W.; Monson, L.R.; Olson, D.L.; Staffon, J.D.

1992-01-01

The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system

A universal, fault-tolerant, non-linear analytic network for modeling and fault detection

Energy Technology Data Exchange (ETDEWEB)

Mott, J.E. [Advanced Modeling Techniques Corp., Idaho Falls, ID (United States); King, R.W.; Monson, L.R.; Olson, D.L.; Staffon, J.D. [Argonne National Lab., Idaho Falls, ID (United States)

1992-03-06

The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system.

OLAP – Online Analytical Processing

Directory of Open Access Journals (Sweden)

Azoumana Kamagate

2013-07-01

Full Text Available Este procesamiento analítico le da pautas al mundo empresarial, en permitir realizar análisis multidimensional de las bases de datos de gran volumen en las organizaciones, para realizar toma de decisiones de los mismos (que son el tema de consultas especiales. Un sistema OLAP debe cumplir las reglas del Dr. Codd: Se tiene que tener una visión multidimensional de los datos; Pensar en dimensiones y métricas de Negocio. No en tablas y en campos. Abstract This analytical process sets out the guidelines for the business world by carrying out a multidimensional analysis of high volume databases in organizations for decision-making. An OLAP system should obey the rules of Dr. Codd: you should have a multidimensional vision of the data: thinking in terms of the dimensions and metrics of business. Not tables and fields.

Gaussian process regression for sensor networks under localization uncertainty

Science.gov (United States)

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

Identifying and tracking dynamic processes in social networks

Science.gov (United States)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Future planning: default network activity couples with frontoparietal control network and reward-processing regions during process and outcome simulations.

Science.gov (United States)

Gerlach, Kathy D; Spreng, R Nathan; Madore, Kevin P; Schacter, Daniel L

2014-12-01

We spend much of our daily lives imagining how we can reach future goals and what will happen when we attain them. Despite the prevalence of such goal-directed simulations, neuroimaging studies on planning have mainly focused on executive processes in the frontal lobe. This experiment examined the neural basis of process simulations, during which participants imagined themselves going through steps toward attaining a goal, and outcome simulations, during which participants imagined events they associated with achieving a goal. In the scanner, participants engaged in these simulation tasks and an odd/even control task. We hypothesized that process simulations would recruit default and frontoparietal control network regions, and that outcome simulations, which allow us to anticipate the affective consequences of achieving goals, would recruit default and reward-processing regions. Our analysis of brain activity that covaried with process and outcome simulations confirmed these hypotheses. A functional connectivity analysis with posterior cingulate, dorsolateral prefrontal cortex and anterior inferior parietal lobule seeds showed that their activity was correlated during process simulations and associated with a distributed network of default and frontoparietal control network regions. During outcome simulations, medial prefrontal cortex and amygdala seeds covaried together and formed a functional network with default and reward-processing regions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An Analytic Hierarchy Process for School Quality and Inspection: Model Development and Application

Science.gov (United States)

Al Qubaisi, Amal; Badri, Masood; Mohaidat, Jihad; Al Dhaheri, Hamad; Yang, Guang; Al Rashedi, Asma; Greer, Kenneth

2016-01-01

Purpose: The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections. Design/methodology/approach: The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the…

The power of event-driven analytics in Large Scale Data Processing

CERN Multimedia

CERN. Geneva; Marques, Paulo

2011-01-01

FeedZai is a software company specialized in creating high-­‐throughput low-­‐latency data processing solutions. FeedZai develops a product called "FeedZai Pulse" for continuous event-­‐driven analytics that makes application development easier for end users. It automatically calculates key performance indicators and baselines, showing how current performance differ from previous history, creating timely business intelligence updated to the second. The tool does predictive analytics and trend analysis, displaying data on real-­‐time web-­‐based graphics. In 2010 FeedZai won the European EBN Smart Entrepreneurship Competition, in the Digital Models category, being considered one of the "top-­‐20 smart companies in Europe". The main objective of this seminar/workshop is to explore the topic for large-­‐scale data processing using Complex Event Processing and, in particular, the possible uses of Pulse in...

Evidential analytic hierarchy process dependence assessment methodology in human reliability analysis

International Nuclear Information System (INIS)

Chen, Lu Yuan; Zhou, Xinyi; Xiao, Fuyuan; Deng, Yong; Mahadevan, Sankaran

2017-01-01

In human reliability analysis, dependence assessment is an important issue in risky large complex systems, such as operation of a nuclear power plant. Many existing methods depend on an expert's judgment, which contributes to the subjectivity and restrictions of results. Recently, a computational method, based on the Dempster-Shafer evidence theory and analytic hierarchy process, has been proposed to handle the dependence in human reliability analysis. The model can deal with uncertainty in an analyst's judgment and reduce the subjectivity in the evaluation process. However, the computation is heavy and complicated to some degree. The most important issue is that the existing method is in a positive aspect, which may cause an underestimation of the risk. In this study, a new evidential analytic hierarchy process dependence assessment methodology, based on the improvement of existing methods, has been proposed, which is expected to be easier and more effective

Evidential Analytic Hierarchy Process Dependence Assessment Methodology in Human Reliability Analysis

Directory of Open Access Journals (Sweden)

Luyuan Chen

2017-02-01

Full Text Available In human reliability analysis, dependence assessment is an important issue in risky large complex systems, such as operation of a nuclear power plant. Many existing methods depend on an expert's judgment, which contributes to the subjectivity and restrictions of results. Recently, a computational method, based on the Dempster–Shafer evidence theory and analytic hierarchy process, has been proposed to handle the dependence in human reliability analysis. The model can deal with uncertainty in an analyst's judgment and reduce the subjectivity in the evaluation process. However, the computation is heavy and complicated to some degree. The most important issue is that the existing method is in a positive aspect, which may cause an underestimation of the risk. In this study, a new evidential analytic hierarchy process dependence assessment methodology, based on the improvement of existing methods, has been proposed, which is expected to be easier and more effective.

Evidential analytic hierarchy process dependence assessment methodology in human reliability analysis

Energy Technology Data Exchange (ETDEWEB)

Chen, Lu Yuan; Zhou, Xinyi; Xiao, Fuyuan; Deng, Yong [School of Computer and Information Science, Southwest University, Chongqing (China); Mahadevan, Sankaran [School of Engineering, Vanderbilt University, Nashville (United States)

2017-02-15

In human reliability analysis, dependence assessment is an important issue in risky large complex systems, such as operation of a nuclear power plant. Many existing methods depend on an expert's judgment, which contributes to the subjectivity and restrictions of results. Recently, a computational method, based on the Dempster-Shafer evidence theory and analytic hierarchy process, has been proposed to handle the dependence in human reliability analysis. The model can deal with uncertainty in an analyst's judgment and reduce the subjectivity in the evaluation process. However, the computation is heavy and complicated to some degree. The most important issue is that the existing method is in a positive aspect, which may cause an underestimation of the risk. In this study, a new evidential analytic hierarchy process dependence assessment methodology, based on the improvement of existing methods, has been proposed, which is expected to be easier and more effective.

EVALUATION THE SUPPLIERS USING ANALYTIC HIERARCHY PROCESS(AHP: AN APPLICATION IN THE TEXTILE FIRM

Directory of Open Access Journals (Sweden)

AHMET ÖZTÜRK

2013-06-01

Full Text Available Supplier selection is a complex multi-criteria problem which includes both qualitative and quantitative criteria.  In order to select the suppliers, it is necessary to make a tradeoff between these criteria some of which may conflict. Different approaches are suggested to solve the supplier selection problem in the literature. Especially, Saaty’s analytic hierarchy process (AHS is more useful approach for the problem, because of its inherent capability to handle qualitative and quantitative criteria.The main purpose of this study is to solve the supplier selection problem of the textile firm by using AHS.  The proposed model consists of a hierarchical network of connections among five alternatives, seven main and thirteen sub criteria. Twenty-one pairwise comparison matrices were obtained by using focus group methodology.  The results are presented and the sensitivity analyses are performed. Finally, some suggestions and important clues for the management are presented.

Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

International Nuclear Information System (INIS)

Sahoo, Satiprasad; Dhar, Anirban; Kar, Amlanjyoti

2016-01-01

Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. - Highlights: • Environmental vulnerability zone identification based on Grey Analytic Hierarchy Process (AHP) • The effectiveness evaluation by means of a grey clustering method with support from AHP • Use of grey approach eliminates the excessive dependency on the experience of experts.

Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

Energy Technology Data Exchange (ETDEWEB)

Sahoo, Satiprasad [School of Water Resources, Indian Institute of Technology Kharagpur (India); Dhar, Anirban, E-mail: anirban.dhar@gmail.com [Department of Civil Engineering, Indian Institute of Technology Kharagpur (India); Kar, Amlanjyoti [Central Ground Water Board, Bhujal Bhawan, Faridabad, Haryana (India)

2016-01-15

Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. - Highlights: • Environmental vulnerability zone identification based on Grey Analytic Hierarchy Process (AHP) • The effectiveness evaluation by means of a grey clustering method with support from AHP • Use of grey approach eliminates the excessive dependency on the experience of experts.

DAPNA: an architectural framework for data processing networks

NARCIS (Netherlands)

Sözer, Hasan; Nouta, Sander; Wombacher, Andreas; Perona, Paolo

2013-01-01

A data processing network is as a set of (software) components connected through communication channels to apply a series of operations on data. Realization and maintenance of large-scale data processing networks necessitate an architectural approach that supports analysis, verification,

Epidemic processes in complex networks

OpenAIRE

Pastor Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

2015-01-01

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The t...

INTEGRASI METODE ANALYTICAL NETWORK PROCESS (ANP DAN TECHNIQUE FOR OTHERS PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS DALAM MENENTUKAN PRIORITAS SUPPLIER BAHAN BAKU (Studi Kasus PT Nyonya Meneer Semarang

Directory of Open Access Journals (Sweden)

Dyah Ika Rinawati

2015-01-01

Full Text Available Salah satu faktor yang mempengaruhi performansi perusahaan adalah keberadaan supplier yang berperan sebagai penyedia bahan baku. Pemilihan supplier merupakan sebuah pengambilan keputusan multi kriteria, karena banyak faktor yang bersifat kualitatif maupun kuantitatif dapat mempengaruhi performansi supplier.  Sehingga tujuan dalam penelitian ini adalah untuk menentukan supplier yang diprioritaskan PT Nyonya Meneer Semarang dalam memenuhi kebutuhan bahan baku jahe, temulawak, kencur, sambiloto dan pegagan. Kemudian dilakukan pengelompokkan 5 item bahan baku dengan menggunakan model Kraljic Portfolio Matrix. Berdasarkan perhitungan diperoleh hasil yakni bahan baku jahe, kencur dan temulawak termasuk kedalam kategori kuadran critical. Metode Analytical Network Process (ANP dapat dijadikan alternatif untuk suatu permasalahan yang memiliki banyak subkriteria yang saling berkaitan atau berpengaruh dalam pengambilan keputusan dan untuk perankingan  supplier dengan metode Technique For Orders Preference by Similarity to Ideal Solution (TOPSIS. Terdapat 13 subkriteria yang digunakan dalam penentuan prioritas supplier. Berdasarkan pembobotan subkriteria dengan menggunakan ANP, subkriteria yang paling besar pengaruhnya dalam penentuan prioritas supplier adalah harga penawaran sebesar 0,2736. Selanjutnya untuk penentuan prioritas supplier dilakukan dengan menggunakan metode TOPSIS dimana bobot subkriteria diperoleh dari pengolahan metode ANP. Kata Kunci : penentuan prioritas supplier, kraljic portfolio matrix, ANP, TOPSIS   Abstract One of the factors that influence the company performance is the presence of suppliers which supplies raw materials. Selection of suppliers is a Multi-Criteria Decison Problem, because many factors are qualitative and quantitative data can affect the performance of suppliers. So the purpose of this research is to determine the priority supplier companies to meet the raw material needs of jahe, temulawak, kencur, sambiloto and

Analysis of land suitability for urban development in Ahwaz County in southwestern Iran using fuzzy logic and analytic network process (ANP).

Science.gov (United States)

Malmir, Maryam; Zarkesh, Mir Masoud Kheirkhah; Monavari, Seyed Masoud; Jozi, Seyed Ali; Sharifi, Esmail

2016-08-01

The ever-increasing development of cities due to population growth and migration has led to unplanned constructions and great changes in urban spatial structure, especially the physical development of cities in unsuitable places, which requires conscious guidance and fundamental organization. It is therefore necessary to identify suitable sites for future development of cities and prevent urban sprawl as one of the main concerns of urban managers and planners. In this study, to determine the suitable sites for urban development in the county of Ahwaz, the effective biophysical and socioeconomic criteria (including 27 sub-criteria) were initially determined based on literature review and interviews with certified experts. In the next step, a database of criteria and sub-criteria was prepared. Standardization of values and unification of scales in map layers were done using fuzzy logic. The criteria and sub-criteria were weighted by analytic network process (ANP) in the Super Decision software. Next, the map layers were overlaid using weighted linear combination (WLC) in the GIS software. According to the research findings, the final land suitability map was prepared with five suitability classes of very high (5.86 %), high (31.93 %), medium (38.61 %), low (17.65 %), and very low (5.95 %). Also, in terms of spatial distribution, suitable lands for urban development are mainly located in the central and southern parts of the Ahwaz County. It is expected that integration of fuzzy logic and ANP model will provide a better decision support tool compared with other models. The developed model can also be used in the land suitability analysis of other cities.

Perioperative and ICU Healthcare Analytics within a Veterans Integrated System Network: a Qualitative Gap Analysis.

Science.gov (United States)

Mudumbai, Seshadri; Ayer, Ferenc; Stefanko, Jerry

2017-08-01

Health care facilities are implementing analytics platforms as a way to document quality of care. However, few gap analyses exist on platforms specifically designed for patients treated in the Operating Room, Post-Anesthesia Care Unit, and Intensive Care Unit (ICU). As part of a quality improvement effort, we undertook a gap analysis of an existing analytics platform within the Veterans Healthcare Administration. The objectives were to identify themes associated with 1) current clinical use cases and stakeholder needs; 2) information flow and pain points; and 3) recommendations for future analytics development. Methods consisted of semi-structured interviews in 2 phases with a diverse set (n = 9) of support personnel and end users from five facilities across a Veterans Integrated Service Network. Phase 1 identified underlying needs and previous experiences with the analytics platform across various roles and operational responsibilities. Phase 2 validated preliminary feedback, lessons learned, and recommendations for improvement. Emerging themes suggested that the existing system met a small pool of national reporting requirements. However, pain points were identified with accessing data in several information system silos and performing multiple manual validation steps of data content. Notable recommendations included enhancing systems integration to create "one-stop shopping" for data, and developing a capability to perform trends analysis. Our gap analysis suggests that analytics platforms designed for surgical and ICU patients should employ approaches similar to those being used for primary care patients.

Multimodal processes scheduling in mesh-like network environment

Directory of Open Access Journals (Sweden)

Bocewicz Grzegorz

2015-06-01

Full Text Available Multimodal processes planning and scheduling play a pivotal role in many different domains including city networks, multimodal transportation systems, computer and telecommunication networks and so on. Multimodal process can be seen as a process partially processed by locally executed cyclic processes. In that context the concept of a Mesh-like Multimodal Transportation Network (MMTN in which several isomorphic subnetworks interact each other via distinguished subsets of common shared intermodal transport interchange facilities (such as a railway station, bus station or bus/tram stop as to provide a variety of demand-responsive passenger transportation services is examined. Consider a mesh-like layout of a passengers transport network equipped with different lines including buses, trams, metro, trains etc. where passenger flows are treated as multimodal processes. The goal is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multimodal transportation processes scheduling encompassing passenger flow itineraries. Then, the main objective is to provide conditions guaranteeing solvability of particular transport lines scheduling, i.e. guaranteeing the right match-up of local cyclic acting bus, tram, metro and train schedules to a given passengers flow itineraries.

Shape-Shifting Droplet Networks.

Science.gov (United States)

Zhang, T; Wan, Duanduan; Schwarz, J M; Bowick, M J

2016-03-11

We consider a three-dimensional network of aqueous droplets joined by single lipid bilayers to form a cohesive, tissuelike material. The droplets in these networks can be programed to have distinct osmolarities so that osmotic gradients generate internal stresses via local fluid flows to cause the network to change shape. We discover, using molecular dynamics simulations, a reversible folding-unfolding process by adding an osmotic interaction with the surrounding environment which necessarily evolves dynamically as the shape of the network changes. This discovery is the next important step towards osmotic robotics in this system. We also explore analytically and numerically how the networks become faceted via buckling and how quasi-one-dimensional networks become three dimensional.

An Analytical Network Process on Financial Access of the Small and Medium Enterprise in Sharia Banking in Tasikmalaya City

Directory of Open Access Journals (Sweden)

Asep Suryanto

2015-06-01

Full Text Available Small and Medium Enterprise (SME is one of the significant roles in national economic development. It is seemly followed by the rise of employment absorbent and equity in income distribution. The capital constraint and the impedance of banking financial access have become the main problem to the Small and Medium entrepreneurs. The objectives of this research are to identify the main factors as problems of Small and Medium Enterprises in having access to the financial institutions, and also to find out the solutions of the research problems. This research uses qualitative approach i.e. Analytic Network Process (ANP. Through applying this method, it is expected to help the researchers in making measurement and synthesis of some factors regarding on the topic analyzed as well as finding the solution for problems faced by the SMEs. The resources of the data is derived from questionnaires and in-depth interview with experts, practitioners, SMEs and regulators which then analyzed by the structure and hierarchy into homogen clusters of the SMEs problems and solutions, measuring into ratio scale and building synthesis. As the result, it becomes clear what factors impeding the financial access of the SMEs to banks. The results of this research show that the difficulties of SMEs in accessing financial support in Islamic financial institutions are internal problems of Islamic banking i.e. lack of financial assistance given to the SMEs, the functions of Islamic banking as business partners for SMEs is not optimal. Whereas the external problems in the SMEs are the disability in meeting the financial requirements asked by Islamic banking that are collateral and business history. The internal solutions are Islamic banking must give business mentoring to SMEs that have received financial supports to minimalize the bad credits level. The external solution is the government must also socialize Islamic financial mechanism to SMEs as part of education efforts.

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics.

Science.gov (United States)

Kotevska, Olivera; Kusne, A Gilad; Samarov, Daniel V; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today's cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County.

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics

Science.gov (United States)

Kotevska, Olivera; Kusne, A. Gilad; Samarov, Daniel V.; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today’s cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County. PMID:29250476

Epidemic spreading on interconnected networks.

Science.gov (United States)

Saumell-Mendiola, Anna; Serrano, M Ángeles; Boguñá, Marián

2012-08-01

Many real networks are not isolated from each other but form networks of networks, often interrelated in nontrivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop a heterogeneous mean-field approach that allows us to calculate the conditions for the emergence of an endemic state. Interestingly, a global endemic state may arise in the coupled system even though the epidemics is not able to propagate on each network separately and even when the number of coupling connections is small. Our analytic results are successfully confronted against large-scale numerical simulations.

Information governance in dynamic networked business process management

NARCIS (Netherlands)

Rasouli, M.; Eshuis, H.; Grefen, P.W.P.J.; Trienekens, J.J.M.; Kusters, R.J.

2016-01-01

Competition in today’s globalized markets forces organizations to collaborate within dynamic business networks to provide mass-customized integrated solutions for customers. The collaboration within dynamic business networks necessitates forming dynamic networked business processes (DNBPs).

Mapping social networks in software process improvement

DEFF Research Database (Denmark)

Tjørnehøj, Gitte; Nielsen, Peter Axel

2005-01-01

Software process improvement in small, agile organizations is often problematic. Model-based approaches seem to overlook problems. We have been seeking an alternative approach to overcome this through action research. Here we report on a piece of action research from which we developed an approach...... to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...... software process improvement....

Process analytical technology (PAT) tools for the cultivation step in biopharmaceutical production

NARCIS (Netherlands)

Streefland, M.; Martens, D.E.; Beuvery, E.C.; Wijffels, R.H.

2013-01-01

The process analytical technology (PAT) initiative is now 10 years old. This has resulted in the development of many tools and software packages dedicated to PAT application on pharmaceutical processes. However, most applications are restricted to small molecule drugs, mainly for the relatively

Mapping stochastic processes onto complex networks

International Nuclear Information System (INIS)

Shirazi, A H; Reza Jafari, G; Davoudi, J; Peinke, J; Reza Rahimi Tabar, M; Sahimi, Muhammad

2009-01-01

We introduce a method by which stochastic processes are mapped onto complex networks. As examples, we construct the networks for such time series as those for free-jet and low-temperature helium turbulence, the German stock market index (the DAX), and white noise. The networks are further studied by contrasting their geometrical properties, such as the mean length, diameter, clustering, and average number of connections per node. By comparing the network properties of the original time series investigated with those for the shuffled and surrogate series, we are able to quantify the effect of the long-range correlations and the fatness of the probability distribution functions of the series on the networks constructed. Most importantly, we demonstrate that the time series can be reconstructed with high precision by means of a simple random walk on their corresponding networks

Analytic and heuristic processing influences on adolescent reasoning and decision-making.

Science.gov (United States)

Klaczynski, P A

2001-01-01

The normative/descriptive gap is the discrepancy between actual reasoning and traditional standards for reasoning. The relationship between age and the normative/descriptive gap was examined by presenting adolescents with a battery of reasoning and decision-making tasks. Middle adolescents (N = 76) performed closer to normative ideals than early adolescents (N = 66), although the normative/descriptive gap was large for both groups. Correlational analyses revealed that (1) normative responses correlated positively with each other, (2) nonnormative responses were positively interrelated, and (3) normative and nonnormative responses were largely independent. Factor analyses suggested that performance was based on two processing systems. The "analytic" system operates on "decontextualized" task representations and underlies conscious, computational reasoning. The "heuristic" system operates on "contextualized," content-laden representations and produces "cognitively cheap" responses that sometimes conflict with traditional norms. Analytic processing was more clearly linked to age and to intelligence than heuristic processing. Implications for cognitive development, the competence/performance issue, and rationality are discussed.

Optimal design of nuclear mechanical dampers with analytical hierarchy process

International Nuclear Information System (INIS)

Zou Yuehua; Wen Bo; Xu Hongxiang; Qin Yonglie

2000-01-01

An optimal design with analytical hierarchy process on nuclear mechanical dampers manufactured by authors' university was described. By using fuzzy judgement matrix the coincidence was automatically satisfied without the need of coincidence test. The results obtained by this method have been put into the production practices

Modelling aspects of distributed processing in telecommunication networks

NARCIS (Netherlands)

Tomasgard, A; Audestad, JA; Dye, S; Stougie, L; van der Vlerk, MH; Wallace, SW

1998-01-01

The purpose of this paper is to formally describe new optimization models for telecommunication networks with distributed processing. Modem distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in

Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

Science.gov (United States)

Wenhui, Ma; Yu, Wang

2017-06-01

Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

Investigating physical properties of solid dosage forms during pharmaceutical processing : Process analytical applications of vibrational spectroscopy

OpenAIRE

Römer, Meike

2008-01-01

In order to improve and continuously develop the quality of pharmaceutical products, the process analytical technology (PAT) framework has been adopted by the US Food and Drug Administration. One of the aims of PAT is to identify critical process parameters and their effect on the quality of the final product. Real time analysis of the process data enables better control of the processes to obtain a high quality product. The main purpose of this work was to monitor crucial pharmaceutical...

INITIAL RESOURCE PROVISIONINGIN IAAS CLOUDS BASED ON THE ANALYTIC HIERARCHY PROCESS

Directory of Open Access Journals (Sweden)

Andrey A. Mikryukov

2015-01-01

Full Text Available The aim of this paper is to describe one possible solution of a problem of efficient initial resource provisioning in the Infrastructure-as-a-Service cloud environments using the Analytic Hierarchy Process.

Interestingness-Driven Diffusion Process Summarization in Dynamic Networks

DEFF Research Database (Denmark)

Qu, Qiang; Liu, Siyuan; Jensen, Christian S.

2014-01-01

The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key...... tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which...... render existing techniques inapplicable. We study the topic of dynamic network summarization: how to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or edges over time, and we address the problem by finding interestingness-driven diffusion processes...

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

Science.gov (United States)

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Data Farming Process and Initial Network Analysis Capabilities

Directory of Open Access Journals (Sweden)

Gary Horne

2016-01-01

Full Text Available Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics.

Process Analytical Technology (PAT): batch-to-batch reproducibility of fermentation processes by robust process operational design and control.

Science.gov (United States)

Gnoth, S; Jenzsch, M; Simutis, R; Lübbert, A

2007-10-31

The Process Analytical Technology (PAT) initiative of the FDA is a reaction on the increasing discrepancy between current possibilities in process supervision and control of pharmaceutical production processes and its current application in industrial manufacturing processes. With rigid approval practices based on standard operational procedures, adaptations of production reactors towards the state of the art were more or less inhibited for long years. Now PAT paves the way for continuous process and product improvements through improved process supervision based on knowledge-based data analysis, "Quality-by-Design"-concepts, and, finally, through feedback control. Examples of up-to-date implementations of this concept are presented. They are taken from one key group of processes in recombinant pharmaceutical protein manufacturing, the cultivations of genetically modified Escherichia coli bacteria.

Ranking stability and super-stable nodes in complex networks.

Science.gov (United States)

Ghoshal, Gourab; Barabási, Albert-László

2011-07-19

Pagerank, a network-based diffusion algorithm, has emerged as the leading method to rank web content, ecological species and even scientists. Despite its wide use, it remains unknown how the structure of the network on which it operates affects its performance. Here we show that for random networks the ranking provided by pagerank is sensitive to perturbations in the network topology, making it unreliable for incomplete or noisy systems. In contrast, in scale-free networks we predict analytically the emergence of super-stable nodes whose ranking is exceptionally stable to perturbations. We calculate the dependence of the number of super-stable nodes on network characteristics and demonstrate their presence in real networks, in agreement with the analytical predictions. These results not only deepen our understanding of the interplay between network topology and dynamical processes but also have implications in all areas where ranking has a role, from science to marketing.

Lyophilization: a useful approach to the automation of analytical processes?

OpenAIRE

de Castro, M. D. Luque; Izquierdo, A.

1990-01-01

An overview of the state-of-the-art in the use of lyophilization for the pretreatment of samples and standards prior to their storage and/or preconcentration is presented. The different analytical applications of this process are dealt with according to the type of material (reagent, standard, samples) and matrix involved.

Fuzzy analytical hierarchy process and GIS for predictive cu -au ...

African Journals Online (AJOL)

Mineral exploration generally starts on small scale (small areas) and, then progresses to large scale (small area). There are many methods for achieving this goal. To achieve this goal one of these methods is Fuzzy analytical hierarchy process (Fuzzy AHP) that is the most popular multi-criteria decision-making techniques.

Assessing the Importance of Treatment Goals in Patients with Psoriasis: Analytic Hierarchy Process vs. Likert Scales.

Science.gov (United States)

Gutknecht, Mandy; Danner, Marion; Schaarschmidt, Marthe-Lisa; Gross, Christian; Augustin, Matthias

2018-02-15

To define treatment benefit, the Patient Benefit Index contains a weighting of patient-relevant treatment goals using the Patient Needs Questionnaire, which includes a 5-point Likert scale ranging from 0 ("not important at all") to 4 ("very important"). These treatment goals have been assigned to five health dimensions. The importance of each dimension can be derived by averaging the importance ratings on the Likert scales of associated treatment goals. As the use of a Likert scale does not allow for a relative assessment of importance, the objective of this study was to estimate relative importance weights for health dimensions and associated treatment goals in patients with psoriasis by using the analytic hierarchy process and to compare these weights with the weights resulting from the Patient Needs Questionnaire. Furthermore, patients' judgments on the difficulty of the methods were investigated. Dimensions of the Patient Benefit Index and their treatment goals were mapped into a hierarchy of criteria and sub-criteria to develop the analytic hierarchy process questionnaire. Adult patients with psoriasis starting a new anti-psoriatic therapy in the outpatient clinic of the Institute for Health Services Research in Dermatology and Nursing at the University Medical Center Hamburg (Germany) were recruited and completed both methods (analytic hierarchy process, Patient Needs Questionnaire). Ratings of treatment goals on the Likert scales (Patient Needs Questionnaire) were summarized within each dimension to assess the importance of the respective health dimension/criterion. Following the analytic hierarchy process approach, consistency in judgments was assessed using a standardized measurement (consistency ratio). At the analytic hierarchy process level of criteria, 78 of 140 patients achieved the accepted consistency. Using the analytic hierarchy process, the dimension "improvement of physical functioning" was most important, followed by "improvement of social

A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

Science.gov (United States)

Mailloux, Shay; Halámek, Jan; Katz, Evgeny

2014-03-07

A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

Pellet manufacturing by extrusion-spheronization using process analytical technology

DEFF Research Database (Denmark)

Sandler, Niklas; Rantanen, Jukka; Heinämäki, Jyrki

2005-01-01

The aim of this study was to investigate the phase transitions occurring in nitrofurantoin and theophylline formulations during pelletization by extrusion-spheronization. An at-line process analytical technology (PAT) approach was used to increase the understanding of the solid-state behavior...... of the active pharmaceutical ingredients (APIs) during pelletization. Raman spectroscopy, near-infrared (NIR) spectroscopy, and X-ray powder diffraction (XRPD) were used in the characterization of polymorphic changes during the process. Samples were collected at the end of each processing stage (blending......, granulation, extrusion, spheronization, and drying). Batches were dried at 3 temperature levels (60 degrees C, 100 degrees C, and 135 degrees C). Water induced a hydrate formation in both model formulations during processing. NIR spectroscopy gave valuable real-time data about the state of water in the system...

An analytical study of various telecomminication networks using Markov models

International Nuclear Information System (INIS)

Ramakrishnan, M; Jayamani, E; Ezhumalai, P

2015-01-01

The main aim of this paper is to examine issues relating to the performance of various Telecommunication networks, and applied queuing theory for better design and improved efficiency. Firstly, giving an analytical study of queues deals with quantifying the phenomenon of waiting lines using representative measures of performances, such as average queue length (on average number of customers in the queue), average waiting time in queue (on average time to wait) and average facility utilization (proportion of time the service facility is in use). In the second, using Matlab simulator, summarizes the finding of the investigations, from which and where we obtain results and describing methodology for a) compare the waiting time and average number of messages in the queue in M/M/1 and M/M/2 queues b) Compare the performance of M/M/1 and M/D/1 queues and study the effect of increasing the number of servers on the blocking probability M/M/k/k queue model. (paper)

Big data and high-performance analytics in structural health monitoring for bridge management

Science.gov (United States)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

Towards the understanding of network information processing in biology

Science.gov (United States)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Target-Centric Network Modeling

DEFF Research Database (Denmark)

Mitchell, Dr. William L.; Clark, Dr. Robert M.

In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

Science.gov (United States)

Gao, Chao; Tang, Shaoting; Li, Weihua; Yang, Yaqian; Zheng, Zhiming

2018-04-01

Recently, the interplay between epidemic spreading and awareness diffusion has aroused the interest of many researchers, who have studied models mainly based on linear coupling relations between information and epidemic layers. However, in real-world networks the relation between two layers may be closely correlated with the property of individual nodes and exhibits nonlinear dynamical features. Here we propose a nonlinear coupled information-epidemic model (I-E model) and present a comprehensive analysis in a more generalized scenario where the upload rate differs from node to node, deletion rate varies between susceptible and infected states, and infection rate changes between unaware and aware states. In particular, we develop a theoretical framework of the intra- and inter-layer dynamical processes with a microscopic Markov chain approach (MMCA), and derive an analytic epidemic threshold. Our results suggest that the change of upload and deletion rate has little effect on the diffusion dynamics in the epidemic layer.

Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

Directory of Open Access Journals (Sweden)

Wenhui Ma

2017-06-01

Full Text Available Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

An Analytic Hierarchy Process Analysis: Application to Subscriber Retention Decisions in the Nigerian Mobile Telecommunications

Directory of Open Access Journals (Sweden)

Adebiyi Sulaimon Olanrewaju

2015-12-01

Full Text Available The introduction of mobile number portability (MNP in the Nigerian telecommunications industry has brought a new challenge for mobile operators. This study investigates the use of Analytic Hierarchy Process (AHP in customer retention decisions in the Nigerian telecommunication industry using a cross-sectional survey design. Primary data were obtained through questionnaires administered to 480 mobile telecommunications subscribers in six tertiary institutions located in Lagos State, Nigeria. These educational institutions were chosen using a multistage sampling technique. Of 438 questionnaires received from subscribers, 408 were valid. Based on this sample data an AHP model was built to assess the determinants of customer retention decisions. Next, eigen values, an eigen vector and maximum lambda (λMax were obtained using the AHP analysis for the matrices. This analysis shows that customers considered call quality as the important in the retention decision. We conclude that AHP is a meaningful tool for determining what motivates retention decisions, that can help network operators formulate effective customer retention strategies.

Percolation of interdependent network of networks

International Nuclear Information System (INIS)

Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

2015-01-01

Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

Parallel processing data network of master and slave transputers controlled by a serial control network

Science.gov (United States)

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

Synthesis of a parallel data stream processor from data flow process networks

NARCIS (Netherlands)

Zissulescu-Ianculescu, Claudiu

2008-01-01

In this talk, we address the problem of synthesizing Process Network specifications to FPGA execution platforms. The process networks we consider are special cases of Kahn Process Networks. We call them COMPAAN Data Flow Process Networks (CDFPN) because they are provided by a translator called the

Modelling of packet traffic with matrix analytic methods

DEFF Research Database (Denmark)

Andersen, Allan T.

1995-01-01

BISDN network. The heuristic formula did not seem to yield substantially better results than already available approximations. Finally, some results for the finite capacity BMAP/G/1 queue have been obtained. The steady state probability vector of the embedded chain is found by a direct method where...... process. A heuristic formula for the tail behaviour of a single server queue fed by a superposition of renewal processes has been evaluated. The evaluation was performed by applying Matrix Analytic methods. The heuristic formula has applications in the Call Admission Control (CAC) procedure of the future...

Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

Science.gov (United States)

Chiadamrong, N.; Piyathanavong, V.

2017-12-01

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

The Case for Adopting Server-side Analytics

Science.gov (United States)

Tino, C.; Holmes, C. P.; Feigelson, E.; Hurlburt, N. E.

2017-12-01

The standard method for accessing Earth and space science data relies on a scheme developed decades ago: data residing in one or many data stores must be parsed out and shipped via internet lines or physical transport to the researcher who in turn locally stores the data for analysis. The analyses tasks are varied and include visualization, parameterization, and comparison with or assimilation into physics models. In many cases this process is inefficient and unwieldy as the data sets become larger and demands on the analysis tasks become more sophisticated and complex. For about a decade, several groups have explored a new paradigm to this model. The names applied to the paradigm include "data analytics", "climate analytics", and "server-side analytics". The general concept is that in close network proximity to the data store there will be a tailored processing capability appropriate to the type and use of the data served. The user of the server-side analytics will operate on the data with numerical procedures. The procedures can be accessed via canned code, a scripting processor, or an analysis package such as Matlab, IDL or R. Results of the analytics processes will then be relayed via the internet to the user. In practice, these results will be at a much lower volume, easier to transport to and store locally by the user and easier for the user to interoperate with data sets from other remote data stores. The user can also iterate on the processing call to tailor the results as needed. A major component of server-side analytics could be to provide sets of tailored results to end users in order to eliminate the repetitive preconditioning that is both often required with these data sets and which drives much of the throughput challenges. NASA's Big Data Task Force studied this issue. This paper will present the results of this study including examples of SSAs that are being developed and demonstrated and suggestions for architectures that might be developed for

Complex networks: when random walk dynamics equals synchronization

International Nuclear Information System (INIS)

Kriener, Birgit; Anand, Lishma; Timme, Marc

2012-01-01

Synchrony prevalently emerges from the interactions of coupled dynamical units. For simple systems such as networks of phase oscillators, the asymptotic synchronization process is assumed to be equivalent to a Markov process that models standard diffusion or random walks on the same network topology. In this paper, we analytically derive the conditions for such equivalence for networks of pulse-coupled oscillators, which serve as models for neurons and pacemaker cells interacting by exchanging electric pulses or fireflies interacting via light flashes. We find that the pulse synchronization process is less simple, but there are classes of, e.g., network topologies that ensure equivalence. In particular, local dynamical operators are required to be doubly stochastic. These results provide a natural link between stochastic processes and deterministic synchronization on networks. Tools for analyzing diffusion (or, more generally, Markov processes) may now be transferred to pin down features of synchronization in networks of pulse-coupled units such as neural circuits. (paper)

A network perspective on the processes of empowered organizations.

Science.gov (United States)

Neal, Zachary P

2014-06-01

Organizational empowerment is a multi-faceted concept that involves processes occurring both within and between organizations that facilitate achievement of their goals. This paper takes a closer look at three interorganizational processes that lead to empowered organizations: building alliances, getting the word out, and capturing others' attention. These processes are located within the broader nomological network of empowerment and organizational empowerment, and are linked to particular patterns of interorganizational relationships that facilitate organizations' ability to engage in them. A new network-based measure, γ-centrality, is introduced to capture the particular network structure associated with each process to be assessed. It is demonstrated first in a hypothetical organizational network, then applied to take a closer look at organizational empowerment in the context of a coordinating council composed of human service agencies. The paper concludes with a discussion of the implications of relationships between these processes, and the potential for unintended consequences in the empowerment of organizations.

Numerical and analytical simulation of the production process of ZrO2 hollow particles

Science.gov (United States)

Safaei, Hadi; Emami, Mohsen Davazdah

2017-12-01

In this paper, the production process of hollow particles from the agglomerated particles is addressed analytically and numerically. The important parameters affecting this process, in particular, the initial porosity level of particles and the plasma gun types are investigated. The analytical model adopts a combination of quasi-steady thermal equilibrium and mechanical balance. In the analytical model, the possibility of a solid core existing in agglomerated particles is examined. In this model, a range of particle diameters (50μm ≤ D_{p0} ≤ 160 μ m) and various initial porosities ( 0.2 ≤ p ≤ 0.7) are considered. The numerical model employs the VOF technique for two-phase compressible flows. The production process of hollow particles from the agglomerated particles is simulated, considering an initial diameter of D_{p0} = 60 μm and initial porosity of p = 0.3, p = 0.5, and p = 0.7. Simulation results of the analytical model indicate that the solid core diameter is independent of the initial porosity, whereas the thickness of the particle shell strongly depends on the initial porosity. In both models, a hollow particle may hardly develop at small initial porosity values ( p disintegrates at high initial porosity values ( p > 0.6.

Collaborative In-Network Processing for Target Tracking

Directory of Open Access Journals (Sweden)

Juan Liu

2003-03-01

Full Text Available This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors—acoustic-amplitude sensors for target distance estimation and direction-of-arrival sensors for bearing estimation—and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: tracking is distributed, and the network is energy-efficient, activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.

Epidemics and rumours in complex networks

CERN Document Server

Draief, Moez

2009-01-01

Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling

Trust Transitivity in Social Networks

OpenAIRE

Richters, Oliver; Peixoto, Tiago P.

2011-01-01

Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical...

Competing Contact Processes on Homogeneous Networks with Tunable Clusterization

Science.gov (United States)

Rybak, Marcin; Kułakowski, Krzysztof

2013-03-01

We investigate two homogeneous networks: the Watts-Strogatz network with mean degree ⟨k⟩ = 4 and the Erdös-Rényi network with ⟨k⟩ = 10. In both kinds of networks, the clustering coefficient C is a tunable control parameter. The network is an area of two competing contact processes, where nodes can be in two states, S or D. A node S becomes D with probability 1 if at least two its mutually linked neighbors are D. A node D becomes S with a given probability p if at least one of its neighbors is S. The competition between the processes is described by a phase diagram, where the critical probability pc depends on the clustering coefficient C. For p > pc the rate of state S increases in time, seemingly to dominate in the whole system. Below pc, the majority of nodes is in the D-state. The numerical results indicate that for the Watts-Strogatz network the D-process is activated at the finite value of the clustering coefficient C, close to 0.3. On the contrary, for the Erdös-Rényi network the transition is observed at the whole investigated range of C.

Evaluation of feeds for melt and dilute process using an Analytical Hierarchy Process

International Nuclear Information System (INIS)

Krupa, J.F.

2000-01-01

WSRC was requested to evaluate whether nuclear materials other than aluminum-clad spent nuclear fuel should be considered for treatment to prepare them for disposal in the melt and dilute facility as part of the Treatment and Storage Facility (TSF) currently projected for construction in the L-Reactor process area. The Analytical Hierarchy Process using a ratings methodology was used to rank potential feed candidates for disposition through the Melt and Dilute facility proposed for disposition of Savannah River Site aluminum-clad spent nuclear fuel. Because of the scoping nature of this analysis, the expert team convened for this purpose concentrated on technical feasibility and potential cost impacts associated with using melt and dilute versus the current disposition option

Neural PID Control Strategy for Networked Process Control

Directory of Open Access Journals (Sweden)

Jianhua Zhang

2013-01-01

Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.

Application of analytic hierarchy process to extract the user's purpose of expert systems

International Nuclear Information System (INIS)

Gofuku, Akio; Wakabayashi, Jiro; Morimoto, Takashi.

1992-01-01

This paper deals with an application of analytic hierarchy process (AHP) to extract the user's purpose which must be input to expert systems. In the AHP, the process to obtain the weights for criteria by pairwise comparisons is interpreted as the extraction of the decision marker's idea about the importance of each criterion. With this interpretation, the analytic hierarchy process is applied to extract the analyst's idea of the weights of several factors to select constitutive equations suitable for a target analysis in a model selection support expert system under development for numerical simulation of nuclear thermal-hydraulics; the constitutive equations are ordinary introduced in a liquid-vapor two-phase flow analysis. Furthermore, an algorithm by applying the graph theory is shown to evaluate covering condition to obtain the weights from incomplete pairwise comparisons. (author)

Fluctuations and pseudo long range dependence in network flows: A non-stationary Poisson process model

International Nuclear Information System (INIS)

Yu-Dong, Chen; Li, Li; Yi, Zhang; Jian-Ming, Hu

2009-01-01

In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) (F i ) of the i-th node and its variance σ i as σ i α (F i ) α . Such scaling laws are found to be prevalent both in natural and man-made network systems, but the understanding of their origins still remains limited. This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon: the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaling phenomenon. (general)

Networked Identities

DEFF Research Database (Denmark)

Ryberg, Thomas; Larsen, Malene Charlotte

2008-01-01

of CoPs we shall argue that the metaphor or theory of networked learning is itself confronted with some central tensions and challenges that need to be addressed. We then explore these theoretical and analytic challenges to the network metaphor, through an analysis of a Danish social networking site. We......In this article we take up a critique of the concept of Communities of Practice (CoP) voiced by several authors, who suggest that networks may provide a better metaphor to understand social forms of organisation and learning. Through a discussion of the notion of networked learning and the critique...... argue that understanding meaning-making and ‘networked identities’ may be relevant analytic entry points in navigating the challenges....

Nonlinear identification of process dynamics using neural networks

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, A.F.; Chong, K.T.

1992-01-01

In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

H Canyon Processing In Correlation With FH Analytical Labs

International Nuclear Information System (INIS)

Weinheimer, E.

2012-01-01

Management of radioactive chemical waste can be a complicated business. H Canyon and F/H Analytical Labs are two facilities present at the Savannah River Site in Aiken, SC that are at the forefront. In fact H Canyon is the only large-scale radiochemical processing facility in the United States and this processing is only enhanced by the aid given from F/H Analytical Labs. As H Canyon processes incoming materials, F/H Labs provide support through a variety of chemical analyses. Necessary checks of the chemical makeup, processing, and accountability of the samples taken from H Canyon process tanks are performed at the labs along with further checks on waste leaving the canyon after processing. Used nuclear material taken in by the canyon is actually not waste. Only a small portion of the radioactive material itself is actually consumed in nuclear reactors. As a result various radioactive elements such as Uranium, Plutonium and Neptunium are commonly found in waste and may be useful to recover. Specific processing is needed to allow for separation of these products from the waste. This is H Canyon's specialty. Furthermore, H Canyon has the capacity to initiate the process for weapons-grade nuclear material to be converted into nuclear fuel. This is one of the main campaigns being set up for the fall of 2012. Once usable material is separated and purified of impurities such as fission products, it can be converted to an oxide and ultimately turned into commercial fuel. The processing of weapons-grade material for commercial fuel is important in the necessary disposition of plutonium. Another processing campaign to start in the fall in H Canyon involves the reprocessing of used nuclear fuel for disposal in improved containment units. The importance of this campaign involves the proper disposal of nuclear waste in order to ensure the safety and well-being of future generations and the environment. As processing proceeds in the fall, H Canyon will have a substantial

Analytic and Heuristic Processing Influences on Adolescent Reasoning and Decision-Making.

Science.gov (United States)

Klaczynski, Paul A.

2001-01-01

Examined the relationship between age and the normative/descriptive gap--the discrepancy between actual reasoning and traditional standards for reasoning. Found that middle adolescents performed closer to normative ideals than early adolescents. Factor analyses suggested that performance was based on two processing systems, analytic and heuristic…

NDA 2000 -- A modern, networked laboratory

International Nuclear Information System (INIS)

Thompson, K.A.; Ceo, R.N.

1996-01-01

As part of the modernization process, the Nondestructive Analysis (NDA) laboratory at Oak Ridge is undergoing changes to increase reliability, incorporate new analytical techniques, and improve quality assurance. The data system has been decentralized into a network, allowing any instrument to be controlled from any client, even remotely for trouble shooting purposes. By making the computers interchangeable, reliability increases. The software has been redesigned to function on a network, and incorporates several improvements to enhance accuracy and include quality assurance. The emphasis of this paper is directed at the actual hardware and software to integrate NDA 2000. Another paper (Reference 1) by the same authors presented at this symposium gives more details concerning new analytical and QA techniques

IoT Stream Processing and Analytics in The Fog

OpenAIRE

Yang, Shusen

2017-01-01

The emerging Fog paradigm has been attracting increasing interests from both academia and industry, due to the low-latency, resilient, and cost-effective services it can provide. Many Fog applications such as video mining and event monitoring, rely on data stream processing and analytics, which are very popular in the Cloud, but have not been comprehensively investigated in the context of Fog architecture. In this article, we present the general models and architecture of Fog data streaming, ...

A method of network topology optimization design considering application process characteristic

Science.gov (United States)

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.

A Visual Analytics Approach for Extracting Spatio-Temporal Urban Mobility Information from Mobile Network Traffic

Directory of Open Access Journals (Sweden)

Euro Beinat

2012-11-01

Full Text Available In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—served as a proxy for more than two months of mobility within four urban test areas in Northern Italy. In contrast to previous work, our approach relies entirely on visualization and mapping techniques, implemented in several software applications. We purposefully avoid statistical or probabilistic modeling and, nonetheless, reveal characteristic and exceptional mobility patterns. The results show, for example, surprising similarities and symmetries amongst the total mobility and people flows between the test areas. Moreover, the exceptional patterns detected can be associated to real-world events such as soccer matches. We conclude that the visual analytics approach presented can shed new light on large-scale collective urban mobility behavior and thus helps to better understand the “pulse” of dynamic urban systems.

Pre-analytic process control: projecting a quality image.

Science.gov (United States)

Serafin, Mark D

2006-09-26

Within the health-care system, the term "ancillary department" often describes the laboratory. Thus, laboratories may find it difficult to define their image and with it, customer perception of department quality. Regulatory requirements give laboratories who so desire an elegant way to address image and perception issues--a comprehensive pre-analytic system solution. Since large laboratories use such systems--laboratory service manuals--I describe and illustrate the process for the benefit of smaller facilities. There exist resources to help even small laboratories produce a professional service manual--an elegant solution to image and customer perception of quality.

Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making

Science.gov (United States)

Mohd, Wan Rosanisah Wan; Abdullah, Lazim

2017-11-01

A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.

Group Decision Making in Higher Education Using the Analytic Hierarchy Process.

Science.gov (United States)

Liberatore, Matthew J.; Nydick, Robert L.

1997-01-01

Examines application of the analytic hierarchy process (AHP) to group decision-making and evaluation situations in higher education. The approach is illustrated by (1) evaluation of academic research papers at Villanova University (Pennsylvania), and (2) a suggested adaptation for the more complex problem of institutionwide strategic planning.…

Uncertainty Reduction for Stochastic Processes on Complex Networks

Science.gov (United States)

Radicchi, Filippo; Castellano, Claudio

2018-05-01

Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.

Possibilities of Utilizing the Method of Analytical Hierarchy Process Within the Strategy of Corporate Social Business

Science.gov (United States)

Drieniková, Katarína; Hrdinová, Gabriela; Naňo, Tomáš; Sakál, Peter

2010-01-01

The paper deals with the analysis of the theory of corporate social responsibility, risk management and the exact method of analytic hierarchic process that is used in the decision-making processes. The Chapters 2 and 3 focus on presentation of the experience with the application of the method in formulating the stakeholders' strategic goals within the Corporate Social Responsibility (CSR) and simultaneously its utilization in minimizing the environmental risks. The major benefit of this paper is the application of Analytical Hierarchy Process (AHP).

Demonstrating the use of web analytics and an online survey to understand user groups of a national network of river level data

Science.gov (United States)

Macleod, Christopher Kit; Braga, Joao; Arts, Koen; Ioris, Antonio; Han, Xiwu; Sripada, Yaji; van der Wal, Rene

2016-04-01

The number of local, national and international networks of online environmental sensors are rapidly increasing. Where environmental data are made available online for public consumption, there is a need to advance our understanding of the relationships between the supply of and the different demands for such information. Understanding how individuals and groups of users are using online information resources may provide valuable insights into their activities and decision making. As part of the 'dot.rural wikiRivers' project we investigated the potential of web analytics and an online survey to generate insights into the use of a national network of river level data from across Scotland. These sources of online information were collected alongside phone interviews with volunteers sampled from the online survey, and interviews with providers of online river level data; as part of a larger project that set out to help improve the communication of Scotland's online river data. Our web analytics analysis was based on over 100 online sensors which are maintained by the Scottish Environmental Protection Agency (SEPA). Through use of Google Analytics data accessed via the R Ganalytics package we assessed: if the quality of data provided by Google Analytics free service is good enough for research purposes; if we could demonstrate what sensors were being used, when and where; how the nature and pattern of sensor data may affect web traffic; and whether we can identify and profile these users based on information from traffic sources. Web analytics data consists of a series of quantitative metrics which capture and summarize various dimensions of the traffic to a certain web page or set of pages. Examples of commonly used metrics include the number of total visits to a site and the number of total page views. Our analyses of the traffic sources from 2009 to 2011 identified several different major user groups. To improve our understanding of how the use of this national

Analytic Hierarchy Process Expansion for Innovation Performance Measurement Framework

Directory of Open Access Journals (Sweden)

Song-Kyoo Kim

2013-01-01

Full Text Available Innovation is a top strategic priority for the majority of companies. The need for innovation becomes more and more evident in the current corporate world, and the purpose of innovation is to create business value. The Analytic Hierarchy Process (AHP is a structured technique for organizing and analyzing complex decisions. This paper is targeting the framework design of the innovation performance criteria and provides the general guidelines to evaluate the relationship between the criteria by using AHP expansion.

Manufacturing Process Selection of Composite Bicycle’s Crank Arm using Analytical Hierarchy Process (AHP)

Science.gov (United States)

Luqman, M.; Rosli, M. U.; Khor, C. Y.; Zambree, Shayfull; Jahidi, H.

2018-03-01

Crank arm is one of the important parts in a bicycle that is an expensive product due to the high cost of material and production process. This research is aimed to investigate the potential type of manufacturing process to fabricate composite bicycle crank arm and to describe an approach based on analytical hierarchy process (AHP) that assists decision makers or manufacturing engineers in determining the most suitable process to be employed in manufacturing of composite bicycle crank arm at the early stage of the product development process to reduce the production cost. There are four types of processes were considered, namely resin transfer molding (RTM), compression molding (CM), vacuum bag molding and filament winding (FW). The analysis ranks these four types of process for its suitability in the manufacturing of bicycle crank arm based on five main selection factors and 10 sub factors. Determining the right manufacturing process was performed based on AHP process steps. Consistency test was performed to make sure the judgements are consistent during the comparison. The results indicated that the compression molding was the most appropriate manufacturing process because it has the highest value (33.6%) among the other manufacturing processes.

Evaluation of feeds for melt and dilute process using an analytical hierarchy process

Energy Technology Data Exchange (ETDEWEB)

Krupa, J.F.

2000-03-22

Westinghouse Savannah River Company was requested to evaluate whether nuclear materials other than aluminum-clad spent nuclear fuel should be considered for treatment to prepare them for disposal in the melt and dilute facility as part of the Treatment and Storage Facility currently projected for construction in the L-Reactor process area. The decision analysis process used to develop this analysis considered many variables and uncertainties, including repository requirements that are not yet finalized. The Analytical Hierarchy Process using a ratings methodology was used to rank potential feed candidates for disposition through the Melt and Dilute facility proposed for disposition of Savannah River Site aluminum-clad spent nuclear fuel. Because of the scoping nature of this analysis, the expert team convened for this purpose concentrated on technical feasibility and potential cost impacts associated with using melt and dilute versus the current disposition option. This report documents results of the decision analysis.

Evaluation of feeds for melt and dilute process using an analytical hierarchy process

International Nuclear Information System (INIS)

Krupa, J.F.

2000-01-01

Westinghouse Savannah River Company was requested to evaluate whether nuclear materials other than aluminum-clad spent nuclear fuel should be considered for treatment to prepare them for disposal in the melt and dilute facility as part of the Treatment and Storage Facility currently projected for construction in the L-Reactor process area. The decision analysis process used to develop this analysis considered many variables and uncertainties, including repository requirements that are not yet finalized. The Analytical Hierarchy Process using a ratings methodology was used to rank potential feed candidates for disposition through the Melt and Dilute facility proposed for disposition of Savannah River Site aluminum-clad spent nuclear fuel. Because of the scoping nature of this analysis, the expert team convened for this purpose concentrated on technical feasibility and potential cost impacts associated with using melt and dilute versus the current disposition option. This report documents results of the decision analysis

Process analysis of two-layered tube hydroforming with analytical and experimental verification

International Nuclear Information System (INIS)

Seyedkashi, S. M. Hossein; Panahizadeh R, Valiollah; Xu, Haibin; Kim, Sang Yun; Moon, Young Hoon

2013-01-01

Two-layered tubular joints are suitable for special applications. Designing and manufacturing of two layered components require enough knowledge about the tube material behavior during the hydroforming process. In this paper, hydroforming of two-layered tubes is investigated analytically, and the results are verified experimentally. The aim of this study is to derive an analytical model which can be used in the process design. Fundamental equations are written for both of the outer and inner tubes, and the total forming pressure is obtained from these equations. Hydroforming experiments are carried out on two different combinations of materials for inner and outer tubes; case 1: copper/aluminum and case 2: carbon steel/stainless steel. It is observed that experimental results are in good agreement with the theoretical model obtained for estimation of forming pressure able to avoid wrinkling.

A comparison of verbal and numerical judgments in the analytic hierarchy process

NARCIS (Netherlands)

Huizingh, EKRE; Vrolijk, HCJ

In the Analytic Hierarchy Process (AHP), decision makers make pairwise comparisons of alternatives and criteria. The AHP allows to make these pairwise comparisons verbally or numerically. Although verbal statements are intuitively attractive for preference elicitation, there is overwhelming evidence

Software/hardware distributed processing network supporting the Ada environment

Science.gov (United States)

Wood, Richard J.; Pryk, Zen

1993-09-01

A high-performance, fault-tolerant, distributed network has been developed, tested, and demonstrated. The network is based on the MIPS Computer Systems, Inc. R3000 Risc for processing, VHSIC ASICs for high speed, reliable, inter-node communications and compatible commercial memory and I/O boards. The network is an evolution of the Advanced Onboard Signal Processor (AOSP) architecture. It supports Ada application software with an Ada- implemented operating system. A six-node implementation (capable of expansion up to 256 nodes) of the RISC multiprocessor architecture provides 120 MIPS of scalar throughput, 96 Mbytes of RAM and 24 Mbytes of non-volatile memory. The network provides for all ground processing applications, has merit for space-qualified RISC-based network, and interfaces to advanced Computer Aided Software Engineering (CASE) tools for application software development.

Artificial neural networks in variable process control: application in particleboard manufacture

Energy Technology Data Exchange (ETDEWEB)

Esteban, L. G.; Garcia Fernandez, F.; Palacios, P. de; Conde, M.

2009-07-01

Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study two artificial neural networks were combined with the control process charts and it was checked whether the data obtained by the networks were valid for variable process control in particleboard manufacture. The networks made it possible to obtain the mean and standard deviation of the internal bond strength of the particleboard within acceptable margins using known data of thickness, density, moisture content, swelling and absorption. The networks obtained met the acceptance criteria for test values from non-standard test methods, as well as the criteria for using these values in statistical process control. (Author) 47 refs.

Comprehensive Sustainability Evaluation of High-Speed Railway (HSR Construction Projects Based on Unascertained Measure and Analytic Hierarchy Process

Directory of Open Access Journals (Sweden)

Yongzhi Chang

2018-02-01

Full Text Available This paper aims to evaluate the sustainability of high-speed railway (HSR construction projects in a comprehensive manner. To this end, the author established an index system, involving 4 primary indices, 9 secondary indices, and 32 tertiary indices. The analytic hierarchy process (AHP and the unascertained measure were introduced to calculate the weights of these indices. Then, the index system was applied to evaluate the sustainability of the China’s Harbin-Dalian Passenger Dedicated Line (PDL. The results show that the Harbin-Dalian PDL project achieved good results in terms of process, economic benefit, impact, and sustainability, and will bring long-term benefits in the fields of tourism, economy, and transport capacity, as well as many other fields. In spite of its good overall sustainability, the project needs to further increase its economic benefits and reduce its negative environmental impact. For this purpose, it is necessary to adopt the management mode of “separation between network and transportation” and apply noise prevention measures like noise barriers, tunnels, and overhead viaducts. This research lays a solid basis for the sustainability evaluation of HSR construction projects, and simplifies the modelling process for designers of HSR.

Modeling Aggregation Processes of Lennard-Jones particles Via Stochastic Networks

Science.gov (United States)

Forman, Yakir; Cameron, Maria

2017-07-01

We model an isothermal aggregation process of particles/atoms interacting according to the Lennard-Jones pair potential by mapping the energy landscapes of each cluster size N onto stochastic networks, computing transition probabilities from the network for an N-particle cluster to the one for N+1, and connecting these networks into a single joint network. The attachment rate is a control parameter. The resulting network representing the aggregation of up to 14 particles contains 6427 vertices. It is not only time-irreversible but also reducible. To analyze its transient dynamics, we introduce the sequence of the expected initial and pre-attachment distributions and compute them for a wide range of attachment rates and three values of temperature. As a result, we find the configurations most likely to be observed in the process of aggregation for each cluster size. We examine the attachment process and conduct a structural analysis of the sets of local energy minima for every cluster size. We show that both processes taking place in the network, attachment and relaxation, lead to the dominance of icosahedral packing in small (up to 14 atom) clusters.

User Behavior Analytics

Energy Technology Data Exchange (ETDEWEB)

Turcotte, Melissa [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Moore, Juston Shane [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-02-28

User Behaviour Analytics is the tracking, collecting and assessing of user data and activities. The goal is to detect misuse of user credentials by developing models for the normal behaviour of user credentials within a computer network and detect outliers with respect to their baseline.

Competing spreading processes and immunization in multiplex networks

International Nuclear Information System (INIS)

Gao, Bo; Deng, Zhenghong; Zhao, Dawei

2016-01-01

Epidemic spreading on physical contact network will naturally introduce the human awareness information diffusion on virtual contact network, and the awareness diffusion will in turn depress the epidemic spreading, thus forming the competing spreading processes of epidemic and awareness in a multiplex networks. In this paper, we study the competing dynamics of epidemic and awareness, both of which follow the SIR process, in a two-layer networks based on microscopic Markov chain approach and numerical simulations. We find that strong capacities of awareness diffusion and self-protection of individuals could lead to a much higher epidemic threshold and a smaller outbreak size. However, the self-awareness of individuals has no obvious effect on the epidemic threshold and outbreak size. In addition, the immunization of the physical contact network under the interplay between of epidemic and awareness spreading is also investigated. The targeted immunization is found performs much better than random immunization, and the awareness diffusion could reduce the immunization threshold for both type of random and targeted immunization significantly.

MULTIPLE CRITERA METHODS WITH FOCUS ON ANALYTIC HIERARCHY PROCESS AND GROUP DECISION MAKING

Directory of Open Access Journals (Sweden)

Lidija Zadnik-Stirn

2010-12-01

Full Text Available Managing natural resources is a group multiple criteria decision making problem. In this paper the analytic hierarchy process is the chosen method for handling the natural resource problems. The one decision maker problem is discussed and, three methods: the eigenvector method, data envelopment analysis method, and logarithmic least squares method are presented for the derivation of the priority vector. Further, the group analytic hierarchy process is discussed and six methods for the aggregation of individual judgments or priorities: weighted arithmetic mean method, weighted geometric mean method, and four methods based on data envelopment analysis are compared. The case study on land use in Slovenia is applied. The conclusions review consistency, sensitivity analyses, and some future directions of research.

Extending Practical Pre-Aggregation in On-Line Analytical Processing

DEFF Research Database (Denmark)

Pedersen, Torben Bach; Jensen, Christian Søndergaard; Dyreson, Curtis E.

On-Line Analytical Processing (OLAP) based on a dimensional view of data is being used increasingly in traditional business applications as well as in applications such as health care for the purpose of analyzing very large amounts of data. Pre-aggregation, the prior materialization of aggregate...... select combinations of aggregates and then re-use these for efficiently computing other aggregates. However, this re-use of aggregates is contingent on the dimension hierarchies and the relationships between facts and dimensions satisfying stringent constraints. This severely limits the scope...

Hazardous Waste Landfill Siting using GIS Technique and Analytical Hierarchy Process

Directory of Open Access Journals (Sweden)

Ozeair Abessi

2010-07-01

Full Text Available Disposal of large amount of generated hazardous waste in power plants, has always received communities' and authori¬ties attentions. In this paper using site screening method and Analytical Hierarchy Process (AHP a sophisticated approach for siting hazardous waste landfill in large areas is presented. This approach demonstrates how the evaluation criteria such as physical, socio-economical, technical, environmental and their regulatory sub criteria can be introduced into an over layer technique to screen some limited appropriate zones in the area. Then, in order to find the optimal site amongst the primary screened site utilizing a Multiple Criteria Decision Making (MCDM method for hierarchy computations of the process is recommended. Using the introduced method an accurate siting procedure for environmental planning of the landfills in an area would be enabled. In the study this approach was utilized for disposal of hazardous wastes of Shahid Rajaee thermal power plant located in Qazvin province west central part of Iran. As a result of this study 10 suitable zones were screened in the area at first, then using analytical hierarchy process a site near the power plant were chosen as the optimal site for landfilling of the hazardous wastes in Qazvin province.

Big Data Analytics Embedded Smart City Architecture for Performance Enhancement through Real-Time Data Processing and Decision-Making

Directory of Open Access Journals (Sweden)

Bhagya Nathali Silva

2017-01-01

Full Text Available The concept of the smart city is widely favored, as it enhances the quality of life of urban citizens, involving multiple disciplines, that is, smart community, smart transportation, smart healthcare, smart parking, and many more. Continuous growth of the complex urban networks is significantly challenged by real-time data processing and intelligent decision-making capabilities. Therefore, in this paper, we propose a smart city framework based on Big Data analytics. The proposed framework operates on three levels: (1 data generation and acquisition level collecting heterogeneous data related to city operations, (2 data management and processing level filtering, analyzing, and storing data to make decisions and events autonomously, and (3 application level initiating execution of the events corresponding to the received decisions. In order to validate the proposed architecture, we analyze a few major types of dataset based on the proposed three-level architecture. Further, we tested authentic datasets on Hadoop ecosystem to determine the threshold and the analysis shows that the proposed architecture offers useful insights into the community development authorities to improve the existing smart city architecture.

MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

Science.gov (United States)

Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming

2017-09-01

Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.

Fault detection and diagnosis for complex multivariable processes using neural networks

International Nuclear Information System (INIS)

Weerasinghe, M.

1998-06-01

Development of a reliable fault diagnosis method for large-scale industrial plants is laborious and often difficult to achieve due to the complexity of the targeted systems. The main objective of this thesis is to investigate the application of neural networks to the diagnosis of non-catastrophic faults in an industrial nuclear fuel processing plant. The proposed methods were initially developed by application to a simulated chemical process prior to further validation on real industrial data. The diagnosis of faults at a single operating point is first investigated. Statistical data conditioning methods of data scaling and principal component analysis are investigated to facilitate fault classification and reduce the complexity of neural networks. Successful fault diagnosis was achieved with significantly smaller networks than using all process variables as network inputs. Industrial processes often manufacture at various operating points, but demonstrated applications of neural networks for fault diagnosis usually only consider a single (primary) operating point. Developing a standard neural network scheme for fault diagnosis at all operating points would be usually impractical due to the unavailability of suitable training data for less frequently used (secondary) operating points. To overcome this problem, the application of a single neural network for the diagnosis of faults operating at different points is investigated. The data conditioning followed the same techniques as used for the fault diagnosis of a single operating point. The results showed that a single neural network could be successfully used to diagnose faults at operating points other than that it is trained for, and the data conditioning significantly improved the classification. Artificial neural networks have been shown to be an effective tool for process fault diagnosis. However, a main criticism is that details of the procedures taken to reach the fault diagnosis decisions are embedded in

Using the Analytic Hierarchy Process for Decision-Making in Ecosystem Management

Science.gov (United States)

Daniel L. Schmoldt; David L. Peterson

1997-01-01

Land management activities on public lands combine multiple objectives in order to create a plan of action over a finite time horizon. Because management activities are constrained by time and money, it is critical to make the best use of available agency resources. The Analytic Hierarchy Process (AHP) offers a structure for multi-objective decisionmaking so that...

Workflow-Oriented Cyberinfrastructure for Sensor Data Analytics

Science.gov (United States)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

Sensor streams comprise an increasingly large part of Earth Science data. Analytics based on sensor data require an easy way to perform operations such as acquisition, conversion to physical units, metadata linking, sensor fusion, analysis and visualization on distributed sensor streams. Furthermore, embedding real-time sensor data into scientific workflows is of growing interest. We have implemented a scalable networked architecture that can be used to dynamically access packets of data in a stream from multiple sensors, and perform synthesis and analysis across a distributed network. Our system is based on the integrated Rule Oriented Data System (irods.org), which accesses sensor data from the Antelope Real Time Data System (brtt.com), and provides virtualized access to collections of data streams. We integrate real-time data streaming from different sources, collected for different purposes, on different time and spatial scales, and sensed by different methods. iRODS, noted for its policy-oriented data management, brings to sensor processing features and facilities such as single sign-on, third party access control lists ( ACLs), location transparency, logical resource naming, and server-side modeling capabilities while reducing the burden on sensor network operators. Rich integrated metadata support also makes it straightforward to discover data streams of interest and maintain data provenance. The workflow support in iRODS readily integrates sensor processing into any analytical pipeline. The system is developed as part of the NSF-funded Datanet Federation Consortium (datafed.org). APIs for selecting, opening, reaping and closing sensor streams are provided, along with other helper functions to associate metadata and convert sensor packets into NetCDF and JSON formats. Near real-time sensor data including seismic sensors, environmental sensors, LIDAR and video streams are available through this interface. A system for archiving sensor data and metadata in Net

Work process, performance and professional profile of a Hearing Health Network: reference for satisfaction.

Science.gov (United States)

Escarce, Andrezza Gonzalez; Lemos, Stela Maris Aguiar; Carvalho, Sirley Alves da Silva

2016-01-01

To analyze the correlation between the satisfaction of professionals from the Hearing Health Care network in two micro-regions of Minas Gerais state and the sociodemographic profile, work process, and work performance in the health service. This is a cross-sectional, observational, analytic study with a non-probabilistic sample including 34 professionals from the Hearing Health Care services. Data collection occurred through individual interviews in the municipality of professional practice. Associations between the Professional Satisfaction variable and the explanatory variables Sociodemographic Data, Work Routine, and Developed Actions were conducted. Professionals with graduate studies were more satisfied with the human resources policy and the activities developed, whereas health civil servants showed more satisfaction with the wage policy and the work schedule. The correlation analysis between work process and satisfaction revealed a moderate positive correlation between items such as Health Promotion Actions, Satisfaction with Diagnostic Equipment, and Satisfaction with Maintenance Equipment. The present study revealed a higher level of satisfaction among professionals with graduate studies (human resources policy and activities developed) and civil servants (wage policy and work schedule). The relevance of this study lies on the important role that health professionals play on the Health Care Network. Additionally, the study of satisfaction level can provide a search for improvements, considering that satisfied professionals not only improve service quality, but also show greater creativity, commitment, and performance.

Reducing Post-Decision Dissonance in International Decisions: The Analytic Hierarchy Process Approach.

Science.gov (United States)

DuBois, Frank L.

1999-01-01

Describes use of the analytic hierarchy process (AHP) as a teaching tool to illustrate the complexities of decision making in an international environment. The AHP approach uses managerial input to develop pairwise comparisons of relevant decision criteria to efficiently generate an appropriate solution. (DB)

Two Distinct Scene-Processing Networks Connecting Vision and Memory.

Science.gov (United States)

Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

2016-01-01

A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

APPLICATION OF FUZZY ANALYTIC HIERARCHY PROCESS TO BUILDING RESEARCH TEAMS

Directory of Open Access Journals (Sweden)

Karol DĄBROWSKI

2016-01-01

Full Text Available Building teams has a fundamental impact for execution of research and development projects. The teams appointed for the needs of given projects are based on individuals from both inside and outside of the organization. Knowledge is not only a product available on the market but also an intangible resource affecting their internal and external processes. Thus it is vitally important for businesses and scientific research facilities to effectively manage knowledge within project teams. The article presents a proposal to use Fuzzy AHP (Analytic Hierarchy Process and ANFIS (Adaptive Neuro Fuzzy Inference System methods in working groups building for R&D projects on the basis of employees skills.

Application of Fuzzy Analytic Hierarchy Process to Building Research Teams

Science.gov (United States)

Dąbrowski, Karol; Skrzypek, Katarzyna

2016-03-01

Building teams has a fundamental impact for execution of research and development projects. The teams appointed for the needs of given projects are based on individuals from both inside and outside of the organization. Knowledge is not only a product available on the market but also an intangible resource affecting their internal and external processes. Thus it is vitally important for businesses and scientific research facilities to effectively manage knowledge within project teams. The article presents a proposal to use Fuzzy AHP (Analytic Hierarchy Process) and ANFIS (Adaptive Neuro Fuzzy Inference System) methods in working groups building for R&D projects on the basis of employees skills.

"Violent Intent Modeling: Incorporating Cultural Knowledge into the Analytical Process

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Nibbs, Faith G.

2007-08-24

While culture has a significant effect on the appropriate interpretation of textual data, the incorporation of cultural considerations into data transformations has not been systematic. Recognizing that the successful prevention of terrorist activities could hinge on the knowledge of the subcultures, Anthropologist and DHS intern Faith Nibbs has been addressing the need to incorporate cultural knowledge into the analytical process. In this Brown Bag she will present how cultural ideology is being used to understand how the rhetoric of group leaders influences the likelihood of their constituents to engage in violent or radicalized behavior, and how violent intent modeling can benefit from understanding that process.

Design of common heat exchanger network for batch processes

International Nuclear Information System (INIS)

Anastasovski, Aleksandar

2014-01-01

Heat integration of energy streams is very important for the efficient energy recovery in production systems. Pinch technology is a very useful tool for heat integration and maximizing energy efficiency. Creating of heat exchangers network as a common solution for systems in batch mode that will be applicable in all existing time slices is very difficult. This paper suggests a new methodology for design of common heat exchanger network for batch processes. Heat exchanger network designs were created for all determined repeatable and non-repeatable time periods – time slices. They are the basis for creating the common heat exchanger network. The common heat exchanger network as solution, satisfies all heat-transfer needs for each time period and for every existing combination of selected streams in the production process. This methodology use split of some heat exchangers into two or more heat exchange units or heat exchange zones. The reason for that is the multipurpose use of heat exchangers between different pairs of streams in different time periods. Splitting of large heat exchangers would maximize the total heat transfer usage of heat exchange units. Final solution contains heat exchangers with the minimum heat load as well as the minimum need of heat transfer area. The solution is applicable for all determined time periods and all existing stream combinations. - Highlights: •Methodology for design of energy efficient systems in batch processes. •Common Heat Exchanger Network solution based on designs with Pinch technology. •Multipurpose use of heat exchangers in batch processes

Network analysis applications in hydrology

Science.gov (United States)

Price, Katie

2017-04-01

Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

Application of process analytical technology in tablet process development using NIR spectroscopy : Blend uniformity, content uniformity and coating thickness measurements

NARCIS (Netherlands)

Moes, Johannes J; Ruijken, Marco M; Gout, Erik; Frijlink, Henderik W; Ugwoke, Michael I

2008-01-01

Near-infrared (NIR)spectroscopy was employed as a process analytical technique in three steps of tabletting process: to monitor the blend homogeneity, evaluate the content uniformity of tablets and determine the tablets coating thickness. A diode-array spectrometer mounted on a lab blender (SP15 NIR

Analytical bounds on the area spectral efficiency of uplink heterogeneous networks over generalized fading channels

KAUST Repository

Shakir, Muhammad

2014-06-01

Heterogeneous networks (HetNets) are envisioned to enable next-generation cellular networks by providing higher spectral and energy efficiency. A HetNet is typically composed of multiple radio access technologies where several low-power low-cost operators or user-deployed small-cell base stations (SBSs) complement the macrocell network. In this paper, we consider a two-tier HetNet where the SBSs are arranged around the edge of the reference macrocell such that the resultant configuration is referred to as cell-on-edge (COE). Each mobile user in a small cell is considered capable of adapting its uplink transmit power according to a location-based slow power control mechanism. The COE configuration is observed to increase the uplink area spectral efficiency (ASE) and energy efficiency while reducing the cochannel interference power. A moment-generating-function (MGF)-based approach has been exploited to derive the analytical bounds on the uplink ASE of the COE configuration. The derived expressions are generalized for any composite fading distribution, and closed-form expressions are presented for the generalized- K fading channels. Simulation results are included to support the analysis and to show the efficacy of the COE configuration. A comparative performance analysis is also provided to demonstrate the improvements in the performance of cell-edge users of the COE configuration compared with that of macro-only networks (MoNets) and other unplanned deployment strategies. © 2013 IEEE.

Application of Characterization, Modeling, and Analytics Towards Understanding Process Structure Linkages in Metallic 3D Printing (Postprint)

Science.gov (United States)

2017-08-01

METALLIC 3D PRINTING (POSTPRINT) M.A. Groeber, E. Schwalbach, S. Donegan, K. Chaput, T. Butler, and J. Miller AFRL/RX 27 JULY...MODELING, AND ANALYTICS TOWARDS UNDERSTANDING PROCESS- STRUCTURE LINKAGES IN METALLIC 3D PRINTING (POSTPRINT) 5a. CONTRACT NUMBER IN-HOUSE 5b...characterization, modelling, and analytics towards understanding process-structure linkages in metallic 3D printing M A Groeber, E Schwalbach, S Donegan, K

Use of evidence in a categorization task: analytic and holistic processing modes.

Science.gov (United States)

Greco, Alberto; Moretti, Stefania

2017-11-01

Category learning performance can be influenced by many contextual factors, but the effects of these factors are not the same for all learners. The present study suggests that these differences can be due to the different ways evidence is used, according to two main basic modalities of processing information, analytically or holistically. In order to test the impact of the information provided, an inductive rule-based task was designed, in which feature salience and comparison informativeness between examples of two categories were manipulated during the learning phases, by introducing and progressively reducing some perceptual biases. To gather data on processing modalities, we devised the Active Feature Composition task, a production task that does not require classifying new items but reproducing them by combining features. At the end, an explicit rating task was performed, which entailed assessing the accuracy of a set of possible categorization rules. A combined analysis of the data collected with these two different tests enabled profiling participants in regard to the kind of processing modality, the structure of representations and the quality of categorial judgments. Results showed that despite the fact that the information provided was the same for all participants, those who adopted analytic processing better exploited evidence and performed more accurately, whereas with holistic processing categorization is perfectly possible but inaccurate. Finally, the cognitive implications of the proposed procedure, with regard to involved processes and representations, are discussed.

On the network convergence process in RPL over IEEE 802.15.4 multihop networks: improvement and trade-offs.

Science.gov (United States)

Kermajani, Hamidreza; Gomez, Carles

2014-07-07

The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently developed by the Internet Engineering Task Force (IETF). Given its crucial role in enabling the Internet of Things, a significant amount of research effort has already been devoted to RPL. However, the RPL network convergence process has not yet been investigated in detail. In this paper we study the influence of the main RPL parameters and mechanisms on the network convergence process of this protocol in IEEE 802.15.4 multihop networks. We also propose and evaluate a mechanism that leverages an option available in RPL for accelerating the network convergence process. We carry out extensive simulations for a wide range of conditions, considering different network scenarios in terms of size and density. Results show that network convergence performance depends dramatically on the use and adequate configuration of key RPL parameters and mechanisms. The findings and contributions of this work provide a RPL configuration guideline for network convergence performance tuning, as well as a characterization of the related performance trade-offs.

On the Network Convergence Process in RPL over IEEE 802.15.4 Multihop Networks: Improvement and Trade-Offs

Directory of Open Access Journals (Sweden)

Hamidreza Kermajani

2014-07-01

Full Text Available The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL has been recently developed by the Internet Engineering Task Force (IETF. Given its crucial role in enabling the Internet of Things, a significant amount of research effort has already been devoted to RPL. However, the RPL network convergence process has not yet been investigated in detail. In this paper we study the influence of the main RPL parameters and mechanisms on the network convergence process of this protocol in IEEE 802.15.4 multihop networks. We also propose and evaluate a mechanism that leverages an option available in RPL for accelerating the network convergence process. We carry out extensive simulations for a wide range of conditions, considering different network scenarios in terms of size and density. Results show that network convergence performance depends dramatically on the use and adequate configuration of key RPL parameters and mechanisms. The findings and contributions of this work provide a RPL configuration guideline for network convergence performance tuning, as well as a characterization of the related performance trade-offs.

Methodological aspects of network assets accounting

Directory of Open Access Journals (Sweden)

Yuhimenko-Nazaruk I.A.

2017-08-01

Full Text Available The necessity of using innovative tools of processing and representation of information about network assets is substantiated. The suggestions for displaying network assets in accounts are presented. The main reasons for the need to display the network assets in the financial statements of all members of the network structure (the economic essence of network assets as the object of accounting; the non-additional model for the formation of the value of network assets; the internetworking mechanism for the formation of the value of network assets are identified. The stages of accounting valuation of network assets are allocated and substantiated. The analytical table for estimating the value of network assets and additional network capital in accounting is developed. The order of additional network capital reflection in accounting is developed. The method of revaluation of network assets in accounting in the broad sense is revealed. The order of accounting of network assets with increasing or decreasing the number of participants in the network structure is determined.

Load balancing prediction method of cloud storage based on analytic hierarchy process and hybrid hierarchical genetic algorithm.

Science.gov (United States)

Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian

2016-01-01

With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.

Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

Directory of Open Access Journals (Sweden)

Xi Jin

2015-01-01

Full Text Available The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

A Hybrid Fuzzy Analytic Network Process (FANP and Data Envelopment Analysis (DEA Approach for Supplier Evaluation and Selection in the Rice Supply Chain

Directory of Open Access Journals (Sweden)

Chia–Nan Wang

2018-06-01

Full Text Available In the market economy, competition is typically due to the difficulty in selecting the most suitable supplier, one that is capable to help a business to develop a profit to the highest value threshold and capable to meet sustainable development features. In addition, this research discusses a wide range of consequences from choosing an effective supplier, including reducing production cost, improving product quality, delivering the product on time, and responding flexibly to customer requirements. Therefore, the activities noted above are able to increase an enterprise’s competitiveness. It can be seen that selecting a supplier is complex in that decision-makers must have an understanding of the qualitative and quantitative features for assessing the symmetrical impact of the criteria to reach the most accurate result. In this research, the multi-criteria group decision-making (MCGDM approach was proposed to solve supplier selection problems. The authors collected data from 25 potential suppliers, and the four main criteria within contain 15 sub-criteria to define the most effective supplier, which has viewed factors, including financial efficiency guarantee, quality of materials, ability to deliver on time, and the conditioned response to the environment to improve the efficiency of the industry supply chain. Initially, fuzzy analytic network process (ANP is used to evaluate and rank these criteria, which are able to be utilized to clarify important criteria that directly affect the profitability of the business. Subsequently, data envelopment analysis (DEA models, including the Charnes Cooper Rhodes model (CCR model, Banker Charnes Cooper model (BCC model, and slacks-based measure model (SBM model, were proposed to rank suppliers. The result of the model has proposed 7/25 suppliers, which have a condition response to the enterprises’ supply requirements.

Processing horizontal networks measured by integrated terrestrial and GPS technologies

Directory of Open Access Journals (Sweden)

Vincent Jakub

2003-09-01

Full Text Available Local horizontal networks in which GPS and terrestrial measurements (TER are done are often established at present. Iin other networks, the previous terrestrial measurements can be completed with quantities from contemporary GPS observations (tunnel nets, mining nets with surface and underground parts and other long-shaped nets.The processing of such heterobeneous (GPS, TER networks whose terrestrial measurements are performed as point coordinate measurements (∆X, ∆Y using (geodetic total stationIn is presented in this paper. In such network structures it is then available:- the values ∆X, ∆Y from TER observations which are transformed in the plane of S-JTSK for adjustement,- the values ∆X, ∆Y in the plane S-JTSK that can be obtained by 3D transformation of WGS84 netpoint coordinates from GPS observations to corresponding coordinates S-JTSK.For common adjusting all the ∆X, ∆Y, some elements of the network geometry (e.g. distances should be measured by both methods (GPS, TER. This approach makes possible an effective homogenisation of both network parts what is equivalent to saying that an expressive influence reduction on local frame realizations of S-JTSK in the whole network can be made.Results of network processing obtained in proposed manner are acceptable in general and they are equivalent (accuracy, reliability to results of another processing methods.

Quality Measures in Pre-Analytical Phase of Tissue Processing: Understanding Its Value in Histopathology.

Science.gov (United States)

Rao, Shalinee; Masilamani, Suresh; Sundaram, Sandhya; Duvuru, Prathiba; Swaminathan, Rajendiran

2016-01-01

Quality monitoring in histopathology unit is categorized into three phases, pre-analytical, analytical and post-analytical, to cover various steps in the entire test cycle. Review of literature on quality evaluation studies pertaining to histopathology revealed that earlier reports were mainly focused on analytical aspects with limited studies on assessment of pre-analytical phase. Pre-analytical phase encompasses several processing steps and handling of specimen/sample by multiple individuals, thus allowing enough scope for errors. Due to its critical nature and limited studies in the past to assess quality in pre-analytical phase, it deserves more attention. This study was undertaken to analyse and assess the quality parameters in pre-analytical phase in a histopathology laboratory. This was a retrospective study done on pre-analytical parameters in histopathology laboratory of a tertiary care centre on 18,626 tissue specimens received in 34 months. Registers and records were checked for efficiency and errors for pre-analytical quality variables: specimen identification, specimen in appropriate fixatives, lost specimens, daily internal quality control performance on staining, performance in inter-laboratory quality assessment program {External quality assurance program (EQAS)} and evaluation of internal non-conformities (NC) for other errors. The study revealed incorrect specimen labelling in 0.04%, 0.01% and 0.01% in 2007, 2008 and 2009 respectively. About 0.04%, 0.07% and 0.18% specimens were not sent in fixatives in 2007, 2008 and 2009 respectively. There was no incidence of specimen lost. A total of 113 non-conformities were identified out of which 92.9% belonged to the pre-analytical phase. The predominant NC (any deviation from normal standard which may generate an error and result in compromising with quality standards) identified was wrong labelling of slides. Performance in EQAS for pre-analytical phase was satisfactory in 6 of 9 cycles. A low incidence

Analytical system availability techniques

NARCIS (Netherlands)

Brouwers, J.J.H.; Verbeek, P.H.J.; Thomson, W.R.

1987-01-01

Analytical techniques are presented to assess the probability distributions and related statistical parameters of loss of production from equipment networks subject to random failures and repairs. The techniques are based on a theoretical model for system availability, which was further developed

Big data and software defined networks

CERN Document Server

Taheri, Javid

2018-01-01

Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). This new book investigates areas where Big-Data and SDN can help each other in delivering more efficient services.

Dry sample storage system for an analytical laboratory supporting plutonium processing

International Nuclear Information System (INIS)

Treibs, H.A.; Hartenstein, S.D.; Griebenow, B.L.; Wade, M.A.

1990-01-01

The Special Isotope Separation (SIS) plant is designed to provide removal of undesirable isotopes in fuel grade plutonium by the atomic vapor laser isotope separation (AVLIS) process. The AVLIS process involves evaporation of plutonium metal, and passage of an intense beam of light from a laser through the plutonium vapor. The laser beam consists of several discrete wavelengths, tuned to the precise wavelength required to ionize the undesired isotopes. These ions are attracted to charged plates, leaving the bulk of the plutonium vapor enriched in the desired isotopes to be collected on a cold plate. Major portions of the process consist of pyrochemical processes, including direct reduction of the plutonium oxide feed material with calcium metal, and aqueous processes for purification of plutonium in residues. The analytical laboratory for the plant is called the Material and Process Control Laboratory (MPCL), and provides for the analysis of solid and liquid process samples

Network worlds : from link analysis to virtual places.

Energy Technology Data Exchange (ETDEWEB)

Joslyn, C. (Cliff)

2002-01-01

Significant progress is being made in knowledge systems through recent advances in the science of very large networks. Attention is now turning in many quarters to the potential impact on counter-terrorism methods. After reviewing some of these advances, we will discuss the difference between such 'network analytic' approaches, which focus on large, homogeneous graph strucures, and what we are calling 'link analytic' approaches, which focus on somewhat smaller graphs with heterogeneous link types. We use this venue to begin the process of rigorously defining link analysis methods, especially the concept of chaining of views of multidimensional databases. We conclude with some speculation on potential connections to virtual world architectures.

Understanding Customer Product Choices: A Case Study Using the Analytical Hierarchy Process

Science.gov (United States)

Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt

1996-01-01

The Analytical Hierarchy Process (AHP) was used to characterize the bridge material selection decisions of highway officials across the United States. Understanding product choices by utilizing the AHP allowed us to develop strategies for increasing the use of timber in bridge construction. State Department of Transportation engineers, private consulting engineers, and...

Elements of learning technologies designing of engineering networks heat

Directory of Open Access Journals (Sweden)

Sidorkina Irina G.

2016-01-01

Full Text Available Modern educational systems function as a medium fast analysis of shared information that defines them as analytical. The purpose of analytical information processing systems: working with distributed data on a global computer networks, mining and processing of semi structured information, knowledge. Existing mathematical and heuristic methods for the automated synthesis of electronic courses and their corresponding algorithms do not allow the full compliance of development realized in the form of adequate criteria for the totality of the properties distributed educational systems within acceptable time limits and characteristic. Therefore, the development of electronic educational applications must be accompanied by a variety of software support intelligent and adaptive functions. In addition, there is no theoretical justification for integrative aspects and their practical applications for intelligent and adaptive systems of designing distance learning courses. Currently, this type of problem may be considered as a potentially promising. The article presents the functionality of the e-learning course on the design engineering of thermal networks, process modeling in engineering networks with the solution of energy efficiency, detection of problem areas; identify the irrational layout of heaters and others.

Generalized master equations for non-Poisson dynamics on networks.

Science.gov (United States)

Hoffmann, Till; Porter, Mason A; Lambiotte, Renaud

2012-10-01

The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.

Analytical calculation of heavy quarkonia production processes in computer

International Nuclear Information System (INIS)

Braguta, V V; Likhoded, A K; Luchinsky, A V; Poslavsky, S V

2014-01-01

This report is devoted to the analytical calculation of heavy quarkonia production processes in modern experiments such as LHC, B-factories and superB-factories in computer. Theoretical description of heavy quarkonia is based on the factorization theorem. This theorem leads to special structure of the production amplitudes which can be used to develop computer algorithm which calculates these amplitudes automatically. This report is devoted to the description of this algorithm. As an example of its application we present the results of the calculation of double charmonia production in bottomonia decays and inclusive the χ cJ mesons production in pp-collisions

Perangkat Lunak Perhitungan Perubahan Jabatan Dengan Menggunakan Fuzzy Analytical Hierarchy Process (studi kasus : UIN Sunan Ampel Surabaya

Directory of Open Access Journals (Sweden)

Ilham .

2017-04-01

Full Text Available This study discusses the promotion in an institution by considering many factors, and the submission must be conducted objectively, not subjectively. To be able to give an objective assessment results in every employee by considering all the assessment criteria, one of the methods that can be used is the method of Fuzzy Analytical Hierarchy Process (AHP. From the results of research using Fuzzy Analytical Hierarchy Process method showed that the greatest weight virmansyah discount the value that is equal to 80.78 so a great opportunity to get a change or a promotion. Decision to change positions, it gives the rank order value candidates as a recommendation for promotion to employees. So with the Decision Support System with Analytical Hierarchy Process  method can help and facilitate career planning manager (sale or transfer to save time, costs, and more objective.

The diminishing role of hubs in dynamical processes on complex networks.

Science.gov (United States)

Quax, Rick; Apolloni, Andrea; Sloot, Peter M A

2013-11-06

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein-protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature.

Neural network training by Kalman filtering in process system monitoring

International Nuclear Information System (INIS)

Ciftcioglu, Oe.

1996-03-01

Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

Directory of Open Access Journals (Sweden)

Matteo Smerlak

Full Text Available The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network, and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

Science.gov (United States)

Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

2015-01-01

The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

Understanding Organizational Crisis Management Processes : an analytical framework drawn from a case study in a public company

OpenAIRE

Gand , Sébastien; Acquier , Aurélien; Szpirglas , Mathias

2005-01-01

International audience; This article investigates a case of crisis management in a French public company. Combining stakeholder management and a knowledge-based perspective, we propose an analytical framework of organizational crisis management processes. We will first show how the crisis can be analyzed as a collapse of existing frames of collective action, and then present the crisis management processes in details. Our analytical framework leads us to distinguish two kinds of actors who pl...

Impact of degree truncation on the spread of a contagious process on networks.

Science.gov (United States)

Harling, Guy; Onnela, Jukka-Pekka

2018-03-01

Understanding how person-to-person contagious processes spread through a population requires accurate information on connections between population members. However, such connectivity data, when collected via interview, is often incomplete due to partial recall, respondent fatigue or study design, e.g., fixed choice designs (FCD) truncate out-degree by limiting the number of contacts each respondent can report. Past research has shown how FCD truncation affects network properties, but its implications for predicted speed and size of spreading processes remain largely unexplored. To study the impact of degree truncation on predictions of spreading process outcomes, we generated collections of synthetic networks containing specific properties (degree distribution, degree-assortativity, clustering), and also used empirical social network data from 75 villages in Karnataka, India. We simulated FCD using various truncation thresholds and ran a susceptible-infectious-recovered (SIR) process on each network. We found that spreading processes propagated on truncated networks resulted in slower and smaller epidemics, with a sudden decrease in prediction accuracy at a level of truncation that varied by network type. Our results have implications beyond FCD to truncation due to any limited sampling from a larger network. We conclude that knowledge of network structure is important for understanding the accuracy of predictions of process spread on degree truncated networks.

Image processing with a cellular nonlinear network

International Nuclear Information System (INIS)

Morfu, S.

2005-01-01

A cellular nonlinear network (CNN) based on uncoupled nonlinear oscillators is proposed for image processing purposes. It is shown theoretically and numerically that the contrast of an image loaded at the nodes of the CNN is strongly enhanced, even if this one is initially weak. An image inversion can be also obtained without reconfiguration of the network whereas a gray levels extraction can be performed with an additional threshold filtering. Lastly, an electronic implementation of this CNN is presented

Definition and characterization of an extended social-affective default network.

Science.gov (United States)

Amft, Maren; Bzdok, Danilo; Laird, Angela R; Fox, Peter T; Schilbach, Leonhard; Eickhoff, Simon B

2015-03-01

Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the DMN. In this study, we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network). We first seeded meta-analytic connectivity modeling and resting-state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions, the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to introspective, socio-affective, that is, self- and other-related mental processes.

Default network activation during episodic and semantic memory retrieval: A selective meta-analytic comparison.

Science.gov (United States)

Kim, Hongkeun

2016-01-08

It remains unclear whether and to what extent the default network subregions involved in episodic memory (EM) and semantic memory (SM) processes overlap or are separated from one another. This study addresses this issue through a controlled meta-analysis of functional neuroimaging studies involving healthy participants. Various EM and SM task paradigms differ widely in the extent of default network involvement. Therefore, the issue at hand cannot be properly addressed without some control for this factor. In this regard, this study employs a two-stage analysis: a preliminary meta-analysis to select EM and SM task paradigms that recruit relatively extensive default network regions and a main analysis to compare the selected task paradigms. Based on a within-EM comparison, the default network contributed more to recollection/familiarity effects than to old/new effects, and based on a within-SM comparison, it contributed more to word/pseudoword effects than to semantic/phonological effects. According to a direct comparison of recollection/familiarity and word/pseudoword effects, each involving a range of default network regions, there were more overlaps than separations in default network subregions involved in these two effects. More specifically, overlaps included the bilateral posterior cingulate/retrosplenial cortex, left inferior parietal lobule, and left anteromedial prefrontal regions, whereas separations included only the hippocampal formation and the parahippocampal cortex region, which was unique to recollection/familiarity effects. These results indicate that EM and SM retrieval processes involving strong memory signals recruit extensive and largely overlapping default network regions and differ mainly in distinct contributions of hippocampus and parahippocampal regions to EM retrieval. Copyright © 2015 Elsevier Ltd. All rights reserved.

Advanced business process management in networked E-business scenarios

NARCIS (Netherlands)

Grefen, P.W.P.J.; Türetken, O.

2017-01-01

In the modern economy, we see a shift towards networked business scenarios. In many contemporary situations, the operation of multiple organizations is tightly coupled in collaborative business networks. To allow this tightly coupled collaboration, business process management (BPM) in these

Synthesis and Design of Processing Networks

DEFF Research Database (Denmark)

Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

2012-01-01

In this contribution, we propose an integrated business and engineering framework for synthesis and design of processing networks under uncertainty. In our framework, an adapted formulation of the transhipment problem is integrated with a superstructure, leading to a Stochastic Mixed Integer Non...... under market and technical uncertainty....

Materials, processes, and environmental engineering network

Science.gov (United States)

White, Margo M.

1993-01-01

The Materials, Processes, and Environmental Engineering Network (MPEEN) was developed as a central holding facility for materials testing information generated by the Materials and Processes Laboratory. It contains information from other NASA centers and outside agencies, and also includes the NASA Environmental Information System (NEIS) and Failure Analysis Information System (FAIS) data. Environmental replacement materials information is a newly developed focus of MPEEN. This database is the NASA Environmental Information System, NEIS, which is accessible through MPEEN. Environmental concerns are addressed regarding materials identified by the NASA Operational Environment Team, NOET, to be hazardous to the environment. An environmental replacement technology database is contained within NEIS. Environmental concerns about materials are identified by NOET, and control or replacement strategies are formed. This database also contains the usage and performance characteristics of these hazardous materials. In addition to addressing environmental concerns, MPEEN contains one of the largest materials databases in the world. Over 600 users access this network on a daily basis. There is information available on failure analysis, metals and nonmetals testing, materials properties, standard and commercial parts, foreign alloy cross-reference, Long Duration Exposure Facility (LDEF) data, and Materials and Processes Selection List data.

A study of the discovery process in 802.11 networks

OpenAIRE

Castignani , German; Arcia Moret , Andres Emilio; Montavont , Nicolas

2011-01-01

International audience; Today wireless communications are a synonym of mobility and resource sharing. These characteristics, proper of both infrastructure and ad-hoc networks, heavily relies on a general resource discovery process. The discovery process, being an unavoidable procedure, has to be fast and reliable to mitigate the effect of network disruptions. In this article, by means of simulations and a real testbed, our contribution is twofold. First we assess the discovery process focusin...

ANALISA PEMILIHAN SUPPLIER RAMAH LINGKUNGAN DENGAN METODE ANALYTICAL NETWORK PROCESS (ANP PADA PT KIMIA FARMA PLANT SEMARANG

Directory of Open Access Journals (Sweden)

Nia Budi Puspitasari

2016-02-01

Full Text Available Indonesia bersama Thailand dan Filipina menguasai pasar industri farmasi Asia Tenggara sebesar 80% serta diperkirakan pasar industri farmasi hingga 2016 akan mencapai nilai 96,1 miliar USD. Dalam menghadapi hal tersebut diperlukan beberapa hal dimana pada saat ini isu mengenai lingkungan sangat menjadi tren masyarakat. Regulasi pemerintah kepada industri mengenai lingkungan dan peningkatan jumlah masyarakat yang beralih kepada green product membuat industri untuk mulai memasukkan aspek lingkungan ke dalam proses industrinya. Pemilihan pemasok merupakan masalah pengambilan keputusan penting agar mendapatkan pemasok yang dapat meningkatkan daya saing perusahaan. Kriteria pemilihan pemasok umumnya hanya didasarkan pada aspek cost, delivery, dan kualitas. Hal tersebut belum sesuai dengan isu lingkungan dan regulasi pemerintah saat ini. Pemilihan green supplier dilakukan pada PT Kimia Farma plant Semarang. Hal tersebut dilakukan karena PT Kimia Farma plant Semarang berkeinginan mengarahkan produk yang dihasilkan ke arah green product. Saat ini PT Kimia Farma plant Semarang mengalami penurunan produksi dalam 2 tahun terakhir dimana pada jangka 5 tahun, PT Kimia Farma melakukan pergantian supplier sebanyak 5 kali. Analisa pemilihan green supplier tersebut dilakukan menggunakan metode Analytichal Network Process (ANP karena ANP merupakan salah satu metode yang mampu merepresentasikan tingkat kepentingan berbagai pihak dengan mempertimbangkan saling keterkaitan antar kriteria dan sub kriteria yang ada. . Pada pemilihan green supplier kriteria kualitas memiliki bobot 0,369, kriteria lingkungan memiliki bobot sebesar 0,246, kriteria harga memiliki bobot 0,159, kriteria pengiriman 0,11 kriteria pelayanan 0,072, dan kriteria hubungan pemasok 0,044. Rekomendasi supplier yang diberikan adalah PT Sejong karena memiliki bobot terbesar yaitu 0,271.     Abstract Indonesia with Thailand and Philippines now lead pharmaceutical industry market of sotheast asia by

Modelling dendritic ecological networks in space: An integrated network perspective

Science.gov (United States)

Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

Network Traffic Analysis With Query Driven VisualizationSC 2005HPC Analytics Results

Energy Technology Data Exchange (ETDEWEB)

Stockinger, Kurt; Wu, Kesheng; Campbell, Scott; Lau, Stephen; Fisk, Mike; Gavrilov, Eugene; Kent, Alex; Davis, Christopher E.; Olinger,Rick; Young, Rob; Prewett, Jim; Weber, Paul; Caudell, Thomas P.; Bethel,E. Wes; Smith, Steve

2005-09-01

Our analytics challenge is to identify, characterize, and visualize anomalous subsets of large collections of network connection data. We use a combination of HPC resources, advanced algorithms, and visualization techniques. To effectively and efficiently identify the salient portions of the data, we rely on a multi-stage workflow that includes data acquisition, summarization (feature extraction), novelty detection, and classification. Once these subsets of interest have been identified and automatically characterized, we use a state-of-the-art-high-dimensional query system to extract data subsets for interactive visualization. Our approach is equally useful for other large-data analysis problems where it is more practical to identify interesting subsets of the data for visualization than to render all data elements. By reducing the size of the rendering workload, we enable highly interactive and useful visualizations. As a result of this work we were able to analyze six months worth of data interactively with response times two orders of magnitude shorter than with conventional methods.

Quaternionic Multilayer Perceptron with Local Analyticity

Directory of Open Access Journals (Sweden)

Nobuyuki Matsui

2012-11-01

Full Text Available A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons’ states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights of the network.

A real-time data acquisition and processing system for the analytical laboratory automation of a HTR spent fuel reprocessing facility

International Nuclear Information System (INIS)

Watzlawik, K.H.

1979-12-01

A real-time data acquisition and processing system for the analytical laboratory of an experimental HTR spent fuel reprocessing facility is presented. The on-line open-loop system combines in-line and off-line analytical measurement procedures including data acquisition and evaluation as well as analytical laboratory organisation under the control of a computer-supported laboratory automation system. In-line measurements are performed for density, volume and temperature in process tanks and registration of samples for off-line measurements. Off-line computer-coupled experiments are potentiometric titration, gas chromatography and X-ray fluorescence analysis. Organisational sections like sample registration, magazining, distribution and identification, multiple data assignment and especially calibrations of analytical devices are performed by the data processing system. (orig.) [de

Revisit of analytical methods for the process and plant control analyses during reprocessing of fast reactor fuels

International Nuclear Information System (INIS)

Subba Rao, R.V.

2016-01-01

CORAL (COmpact facility for Reprocessing of Advanced fuels in Lead cell) is an experimental facility for demonstrating the reprocessing of irradiated fast reactor fuels discharged from the Fast Breeder Test Reactor (FBTR). The objective of the reprocessing plant is to achieve nuclear grade plutonium and uranium oxides with minimum process waste volumes. The process flow sheet for the reprocessing of spent Fast Reactor Fuel consists of Transport of spent fuel, Chopping, Dissolution, Feed conditioning, Solvent Extraction cycle, Partitioning Cycle and Re-conversion of Plutonium nitrate and uranium nitrate to respective oxides. The efficiency and performance of the plant to achieve desired objective depends on the analyses of various species in the different steps adopted during reprocessing of fuels. The analytical requirements in the plant can be broadly classified as 1. Process control Analyses (Analyses which effect the performance of the plant- PCA); 2. Plant control Analyses (Analyses which indicates efficiency of the plant-PLCA); 3. Nuclear Material Accounting samples (Analyses which has bearing on nuclear material accounting in the plant - NUMAC) and Quality control Analyses (Quality of the input bulk chemicals as well as products - QCA). The analytical methods selected are based on the duration of analyses, precision and accuracies required for each type analytical requirement classified earlier. The process and plant control analyses requires lower precision and accuracies as compared to NUMAC analyses, which requires very high precision accuracy. The time taken for analyses should be as lower as possible for process and plant control analyses as compared to NUMAC analyses. The analytical methods required for determining U and Pu in process and plant samples from FRFR will be different as compared to samples from TRFR (Thermal Reactor Fuel Reprocessing) due to higher Pu to U ratio in FRFR as compared TRFR and they should be such that they can be easily

Application of Network Analysis for Characterizing Service Modularity

DEFF Research Database (Denmark)

Frandsen, Thomas

2012-01-01

The purpose of this paper is to explore the potential of the application of network analytical techniques to identify and characterize modularity of service processes. Services can be conceptualized as systems of interrelated components which can be decomposed in order to achieve a modular design...

Understanding Business Analytics

Science.gov (United States)

2015-01-05

analytics have been used in organizations for a variety of reasons for quite some time; ranging from the simple (generating and understanding business analytics...process. understanding business analytics 3 How well these two components are orchestrated will determine the level of success an organization has in

Precision Scaling of Neural Networks for Efficient Audio Processing

OpenAIRE

Ko, Jong Hwan; Fromm, Josh; Philipose, Matthai; Tashev, Ivan; Zarar, Shuayb

2017-01-01

While deep neural networks have shown powerful performance in many audio applications, their large computation and memory demand has been a challenge for real-time processing. In this paper, we study the impact of scaling the precision of neural networks on the performance of two common audio processing tasks, namely, voice-activity detection and single-channel speech enhancement. We determine the optimal pair of weight/neuron bit precision by exploring its impact on both the performance and ...

Simulating the formation of keratin filament networks by a piecewise-deterministic Markov process.

Science.gov (United States)

Beil, Michael; Lück, Sebastian; Fleischer, Frank; Portet, Stéphanie; Arendt, Wolfgang; Schmidt, Volker

2009-02-21

Keratin intermediate filament networks are part of the cytoskeleton in epithelial cells. They were found to regulate viscoelastic properties and motility of cancer cells. Due to unique biochemical properties of keratin polymers, the knowledge of the mechanisms controlling keratin network formation is incomplete. A combination of deterministic and stochastic modeling techniques can be a valuable source of information since they can describe known mechanisms of network evolution while reflecting the uncertainty with respect to a variety of molecular events. We applied the concept of piecewise-deterministic Markov processes to the modeling of keratin network formation with high spatiotemporal resolution. The deterministic component describes the diffusion-driven evolution of a pool of soluble keratin filament precursors fueling various network formation processes. Instants of network formation events are determined by a stochastic point process on the time axis. A probability distribution controlled by model parameters exercises control over the frequency of different mechanisms of network formation to be triggered. Locations of the network formation events are assigned dependent on the spatial distribution of the soluble pool of filament precursors. Based on this modeling approach, simulation studies revealed that the architecture of keratin networks mostly depends on the balance between filament elongation and branching processes. The spatial distribution of network mesh size, which strongly influences the mechanical characteristics of filament networks, is modulated by lateral annealing processes. This mechanism which is a specific feature of intermediate filament networks appears to be a major and fast regulator of cell mechanics.

pn: A Tool for Improved Derivation of Process Networks

Directory of Open Access Journals (Sweden)

Sven Verdoolaege

2007-04-01

Full Text Available Current emerging embedded System-on-Chip platforms are increasingly becoming multiprocessor architectures. System designers experience significant difficulties in programming these platforms. The applications are typically specified as sequential programs that do not reveal the available parallelism in an application, thereby hindering the efficient mapping of an application onto a parallel multiprocessor platform. In this paper, we present our compiler techniques for facilitating the migration from a sequential application specification to a parallel application specification using the process network model of computation. Our work is inspired by a previous research project called Compaan. With our techniques we address optimization issues such as the generation of process networks with simplified topology and communication without sacrificing the process networks' performance. Moreover, we describe a technique for compile-time memory requirement estimation which we consider as an important contribution of this paper. We demonstrate the usefulness of our techniques on several examples.

Multiple-predators-based capture process on complex networks

International Nuclear Information System (INIS)

Sharafat, Rajput Ramiz; Pu Cunlai; Li Jie; Chen Rongbin; Xu Zhongqi

2017-01-01

The predator/prey (capture) problem is a prototype of many network-related applications. We study the capture process on complex networks by considering multiple predators from multiple sources. In our model, some lions start from multiple sources simultaneously to capture the lamb by biased random walks, which are controlled with a free parameter α . We derive the distribution of the lamb’s lifetime and the expected lifetime 〈 T 〉. Through simulation, we find that the expected lifetime drops substantially with the increasing number of lions. Moreover, we study how the underlying topological structure affects the capture process, and obtain that locating on small-degree nodes is better than on large-degree nodes to prolong the lifetime of the lamb. The dense or homogeneous network structures are against the survival of the lamb. We also discuss how to improve the capture efficiency in our model. (paper)

Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

NARCIS (Netherlands)

Veldhoen, S.; Hupkes, D.; Zuidema, W.

2016-01-01

We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

Using the analytic hierarchy process to support teams in defining new product objectives

NARCIS (Netherlands)

Hummel, J.M.; Verkerke, G.J.; van Rossum, W.; Rakhorst, G.; Hummel, J.M.

2001-01-01

Defining new product objectives is a critical problem solving activity to new product success. The analytic hierarchy process appears to be an adequate technique for multi-criteria decision analysis to support the definition of new product objectives. To illustrate this support, we applied this

Global tree network for computing structures enabling global processing operations

Science.gov (United States)

Blumrich; Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

2010-01-19

A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

Networks in Action: New Actors and Practices in Education Policy in Brazil

Science.gov (United States)

Shiroma, Eneida Oto

2014-01-01

This paper focuses on the role of networks in the policy-making process in education and discusses the potential of network analysis as an analytical tool for education policy research. Drawing on publically available data from personal or institutional websites, this paper reports the findings from research carried out between 2005 and 2011.…

Mashup Model and Verification Using Mashup Processing Network

Science.gov (United States)

Zahoor, Ehtesham; Perrin, Olivier; Godart, Claude

Mashups are defined to be lightweight Web applications aggregating data from different Web services, built using ad-hoc composition and being not concerned with long term stability and robustness. In this paper we present a pattern based approach, called Mashup Processing Network (MPN). The idea is based on Event Processing Network and is supposed to facilitate the creation, modeling and the verification of mashups. MPN provides a view of how different actors interact for the mashup development namely the producer, consumer, mashup processing agent and the communication channels. It also supports modeling transformations and validations of data and offers validation of both functional and non-functional requirements, such as reliable messaging and security, that are key issues within the enterprise context. We have enriched the model with a set of processing operations and categorize them into data composition, transformation and validation categories. These processing operations can be seen as a set of patterns for facilitating the mashup development process. MPN also paves a way for realizing Mashup Oriented Architecture where mashups along with services are used as building blocks for application development.

International Federation of Clinical Chemistry. Use of artificial intelligence in analytical systems for the clinical laboratory. IFCC Committee on Analytical Systems.

Science.gov (United States)

Place, J F; Truchaud, A; Ozawa, K; Pardue, H; Schnipelsky, P

1994-12-16

The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI) both as expert systems and as neural networks. This paper considers the role of software in system operation, control and automation and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel-processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system. In the second part of this paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories. It is concluded that AI constitutes a collective form of intellectual property and that there is a need for better documentation, evaluation and regulation of the systems already being used widely in clinical laboratories.

Google matrix analysis of directed networks

Science.gov (United States)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2015-10-01

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

Research prioritization using the Analytic Hierarchy Process: basic methods. Volume 1

International Nuclear Information System (INIS)

Vesely, W.E.; Shafaghi, A.; Gary, I. Jr.; Rasmuson, D.M.

1983-08-01

This report describes a systematic approach for prioritizing research needs and research programs. The approach is formally called the Analytic Hierarchy Process which was developed by T.L. Saaty and is described in several of his texts referenced in the report. The Analytic Hierarchy Process, or AHP for short, has been applied to a wide variety of prioritization problems and has a good record of success as documented in Saaty's texts. The report develops specific guidelines for constructing the hierarchy and for prioritizing the research programs. Specific examples are given to illustrate the steps in the AHP. As part of the work, a computer code has been developed and the use of the code is described. The code allows the prioritizations to be done in a codified and efficient manner; sensitivity and parametric studies can also be straightforwardly performed to gain a better understanding of the prioritization results. Finally, as an important part of the work, an approach is developed which utilizes probabilistic risk analyses (PRAs) to systematically identify and prioritize research needs and research programs. When utilized in an AHP framework, the PRA's which have been performed to date provide a powerful information source for focusing research on those areas most impacting risk and risk uncertainty

Large-scale functional networks connect differently for processing words and symbol strings.

Science.gov (United States)

Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

2018-01-01

Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

Renal fascial network in retroperitoneal extension of pathologic processes

International Nuclear Information System (INIS)

Raptopoulos, V.; Kleinman, P.K.; Marks, S.C. Jr.; Davidoff, A.

1987-01-01

The concept of the fascial network emerged after careful analysis of CT scans of 100 patients with a variety of retroperitoneal abnormalities, and after correlation of CT scans and anatomic dissections performed on eight unembalmed cadavers in which different-colored barium-mixed liquid latex was injected in various retroperitoneal compartments. Fat lobules are supported and connected with each other by surrounding thin layers of connective tissue. Thicker connective tissue lamellae (septa) connect and support organs and fascia. Thus, a fascial network infrastructure exists in which fat lobules act as mechanical barriers to the spread of pathologic processes, while these processes tend to take the course of least resistance by spreading along or dissecting within fascial and septal planes. The fascial network acts as a roadway, conduit, and barrier to spread in the retroperitoneum and fatty tissue in general. The insights afforded by the fascial network concept unwind the traditional views regarding the dynamics of retroperitoneal pathology

Recent advances on failure and recovery in networks of networks

International Nuclear Information System (INIS)

Shekhtman, Louis M.; Danziger, Michael M.; Havlin, Shlomo

2016-01-01

Until recently, network science has focused on the properties of single isolated networks that do not interact or depend on other networks. However it has now been recognized that many real-networks, such as power grids, transportation systems, and communication infrastructures interact and depend on other networks. Here, we will present a review of the framework developed in recent years for studying the vulnerability and recovery of networks composed of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes, like for example certain people, play a role in two networks, i.e. in a multiplex. Dependency relations may act recursively and can lead to cascades of failures concluding in sudden fragmentation of the system. We review the analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. The general theory and behavior of interdependent networks has many novel features that are not present in classical network theory. Interdependent networks embedded in space are significantly more vulnerable compared to non-embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences. Finally, when recovery of components is possible, global spontaneous recovery of the networks and hysteresis phenomena occur. The theory developed for this process points to an optimal repairing strategy for a network of networks. Understanding realistic effects present in networks of networks is required in order to move towards determining system vulnerability.

Processing of seismic signals from a seismometer network

International Nuclear Information System (INIS)

Key, F.A.; Warburton, P.J.

1983-08-01

A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

Deterministic bound for avionics switched networks according to networking features using network calculus