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Sample records for analytic network process

  1. Selecting public relations personnel of hospitals by analytic network process.

    PubMed

    Liao, Sen-Kuei; Chang, Kuei-Lun

    2009-01-01

    This study describes the use of analytic network process (ANP) in the Taiwanese hospital public relations personnel selection process. Starting with interviewing 48 practitioners and executives in north Taiwan, we collected selection criteria. Then, we retained the 12 critical criteria that were mentioned above 40 times by theses respondents, including: interpersonal skill, experience, negotiation, language, ability to follow orders, cognitive ability, adaptation to environment, adaptation to company, emotion, loyalty, attitude, and Response. Finally, we discussed with the 20 executives to take these important criteria into three perspectives to structure the hierarchy for hospital public relations personnel selection. After discussing with practitioners and executives, we find that selecting criteria are interrelated. The ANP, which incorporates interdependence relationships, is a new approach for multi-criteria decision-making. Thus, we apply ANP to select the most optimal public relations personnel of hospitals. An empirical study of public relations personnel selection problems in Taiwan hospitals is conducted to illustrate how the selection procedure works.

  2. Using analytic network process for evaluating mobile text entry methods.

    PubMed

    Ocampo, Lanndon A; Seva, Rosemary R

    2016-01-01

    This paper highlights a preference evaluation methodology for text entry methods in a touch keyboard smartphone using analytic network process (ANP). Evaluation of text entry methods in literature mainly considers speed and accuracy. This study presents an alternative means for selecting text entry method that considers user preference. A case study was carried out with a group of experts who were asked to develop a selection decision model of five text entry methods. The decision problem is flexible enough to reflect interdependencies of decision elements that are necessary in describing real-life conditions. Results showed that QWERTY method is more preferred than other text entry methods while arrangement of keys is the most preferred criterion in characterizing a sound method. Sensitivity analysis using simulation of normally distributed random numbers under fairly large perturbation reported the foregoing results reliable enough to reflect robust judgment. The main contribution of this paper is the introduction of a multi-criteria decision approach in the preference evaluation of text entry methods.

  3. INTEGRATED ENVIRONMENTAL ASSESSMENT OF THE MID-ATLANTIC REGION WITH ANALYTICAL NETWORK PROCESS

    EPA Science Inventory

    A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account interdependency among variables, the method was capable of ran...

  4. An analytic network process model for municipal solid waste disposal options

    SciTech Connect

    Khan, Sheeba Faisal, Mohd Nishat

    2008-07-01

    The aim of this paper is to present an evaluation method that can aid decision makers in a local civic body to prioritize and select appropriate municipal solid waste disposal methods. We introduce a hierarchical network (hiernet) decision structure and apply the analytic network process (ANP) super-matrix approach to measure the relative desirability of disposal alternatives using value judgments as the input of the various stakeholders. ANP is a flexible analytical program that enables decision makers to find the best possible solution to complex problems by breaking down a problem into a systematic network of inter-relationships among the various levels and attributes. This method therefore may not only aid in selecting the best alternative but also helps decision makers to understand why an alternative is preferred over the other options.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Assessment of wastewater treatment alternatives for small communities: An analytic network process approach.

    PubMed

    Molinos-Senante, María; Gómez, Trinidad; Caballero, Rafael; Hernández-Sancho, Francesc; Sala-Garrido, Ramón

    2015-11-01

    The selection of the most appropriate wastewater treatment (WWT) technology is a complex problem since many alternatives are available and many criteria are involved in the decision-making process. To deal with this challenge, the analytic network process (ANP) is applied for the first time to rank a set of seven WWT technology set-ups for secondary treatment in small communities. A major advantage of ANP is that it incorporates interdependent relationships between elements. Results illustrated that extensive technologies, constructed wetlands and pond systems are the most preferred alternatives by WWT experts. The sensitivity analysis performed verified that the ranking of WWT alternatives is very stable since constructed wetlands are almost always placed in the first position. This paper showed that ANP analysis is suitable to deal with complex decision-making problems, such as the selection of the most appropriate WWT system contributing to better understand the multiple interdependences among elements involved in the assessment.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    SciTech Connect

    Gomez-Navarro, Tomas; Diaz-Martin, Diego

    2009-09-15

    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.

  9. Solid waste facilities location using of analytical network process and data envelopment analysis approaches.

    PubMed

    Khadivi, M R; Fatemi Ghomi, S M T

    2012-06-01

    Selection of the appropriate site for solid waste facilities is a complex problem and requires an extensive evaluation process, because it is very difficult to develop a selection criterion that can precisely describe the preference of one location over another. Therefore selection of these sites can be viewed as a multiple criteria decision-making or multiple attributes decision-making problem. For this purpose, we propose a technique that can effectively take managerial preferences and subjective data into consideration, along with quantitative factors. The tool proposed here relies on the use of the analytical network process (ANP) and to help integrate managerial evaluations into a more quantitatively based decision tool, data envelopment analysis (DEA) is applied. In this paper, a location selection procedure is presented to construct an undesirable facility applying ANP and DEA approaches in two stages. In the first stage ANP approach is used, results of this stage are inputs for the second stage. In this stage, DEA is applied to select the best location. Finally, to illustrate the proposed framework, at "Results and discussion" section, a total of four undesirable facility locations are evaluated.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Analytics for Cyber Network Defense

    SciTech Connect

    Plantenga, Todd.; Kolda, Tamara Gibson

    2011-06-01

    This report provides a brief survey of analytics tools considered relevant to cyber network defense (CND). Ideas and tools come from elds such as statistics, data mining, and knowledge discovery. Some analytics are considered standard mathematical or statistical techniques, while others re ect current research directions. In all cases the report attempts to explain the relevance to CND with brief examples.

  12. Analytic Networks in Music Task Definition.

    ERIC Educational Resources Information Center

    Piper, Richard M.

    For a student to acquire the conceptual systems of a discipline, the designer must reflect that structure or analytic network in his curriculum. The four networks identified for music and used in the development of the Southwest Regional Laboratory (SWRL) Music Program are the variable-value, the whole-part, the process-stage, and the class-member…

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

    SciTech Connect

    Bereketli Zafeirakopoulos, Ilke Erol Genevois, Mujde

    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 and

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

    SciTech Connect

    Parwatiningtyas, Diyan E-mail: erlinunindra@gmail.com; Ambarsari, Erlin Windia E-mail: erlinunindra@gmail.com; Marlina, Dwi E-mail: erlinunindra@gmail.com; Wiratomo, Yogi E-mail: erlinunindra@gmail.com

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    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.

  16. An Introduction to Social Network Data Analytics

    NASA Astrophysics Data System (ADS)

    Aggarwal, Charu C.

    The advent of online social networks has been one of the most exciting events in this decade. Many popular online social networks such as Twitter, LinkedIn, and Facebook have become increasingly popular. In addition, a number of multimedia networks such as Flickr have also seen an increasing level of popularity in recent years. Many such social networks are extremely rich in content, and they typically contain a tremendous amount of content and linkage data which can be leveraged for analysis. The linkage data is essentially the graph structure of the social network and the communications between entities; whereas the content data contains the text, images and other multimedia data in the network. The richness of this network provides unprecedented opportunities for data analytics in the context of social networks. This book provides a data-centric view of online social networks; a topic which has been missing from much of the literature. This chapter provides an overview of the key topics in this field, and their coverage in this book.

  17. Optimization of the scheme for natural ecology planning of urban rivers based on ANP (analytic network process) model.

    PubMed

    Zhang, Yichuan; Wang, Jiangping

    2015-07-01

    Rivers serve as a highly valued component in ecosystem and urban infrastructures. River planning should follow basic principles of maintaining or reconstructing the natural landscape and ecological functions of rivers. Optimization of planning scheme is a prerequisite for successful construction of urban rivers. Therefore, relevant studies on optimization of scheme for natural ecology planning of rivers is crucial. In the present study, four planning schemes for Zhaodingpal River in Xinxiang City, Henan Province were included as the objects for optimization. Fourteen factors that influenced the natural ecology planning of urban rivers were selected from five aspects so as to establish the ANP model. The data processing was done using Super Decisions software. The results showed that important degree of scheme 3 was highest. A scientific, reasonable and accurate evaluation of schemes could be made by ANP method on natural ecology planning of urban rivers. This method could be used to provide references for sustainable development and construction of urban rivers. ANP method is also suitable for optimization of schemes for urban green space planning and design.

  18. Managing Complex Network Operation with Predictive Analytics

    SciTech Connect

    Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Chen, Yousu; Ma, Jian; Schneider, Kevin P.; Greitzer, Frank L.

    2008-03-26

    Complex networks play an important role in modern societies. Their failures, such as power grid blackouts, would lead to significant disruption of people’s life, industry and commercial activities, and result in massive economic losses. Operation of these complex networks is an extremely challenging task due to their complex structures, wide geographical coverage, complex data/information technology systems, and highly dynamic and nonlinear behaviors. None of the complex network operation is fully automated; human-in-the-loop operation is critical. Given the complexity involved, there may be thousands of possible topological configurations at any given time. During an emergency, it is not uncommon for human operators to examine thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, network operation is largely based on experience with very limited real-time decision support, resulting in inadequate management of complex predictions and inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, and cyber attacks. A systematic approach is needed to manage the complex operation paradigms and choose the best option in a near-real-time manner. This paper applies predictive analytics techniques to establish a decision support system for complex network operation management and help operators to predict potential network failures and adapt the network to adverse situations. The resultant decision support system enables continuous monitoring of network performance and turns large amounts of data into actionable information. Examples with actual power grid data are presented to demonstrate the capability of this proposed decision support system.

  19. The Computer-Aided Analytic Process Model. Operations Handbook for the Analytic Process Model Demonstration Package

    DTIC Science & Technology

    1986-01-01

    Research Note 86-06 THE COMPUTER-AIDED ANALYTIC PROCESS MODEL : OPERATIONS HANDBOOK FOR THE ANALYTIC PROCESS MODEL DE ONSTRATION PACKAGE Ronald G...ic Process Model ; Operations Handbook; Tutorial; Apple; Systems Taxonomy Mod--l; Training System; Bradl1ey infantry Fighting * Vehicle; BIFV...8217. . . . . . . .. . . . . . . . . . . . . . . . * - ~ . - - * m- .. . . . . . . item 20. Abstract -continued companion volume-- "The Analytic Process Model for

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

    PubMed

    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.

  1. Analytical reasoning task reveals limits of social learning in networks.

    PubMed

    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.

  2. Process analytical applications of Raman spectroscopy.

    PubMed

    Rantanen, Jukka

    2007-02-01

    There is an increasing demand for new approaches to understand the chemical and physical phenomena that occur during pharmaceutical unit operations. Obtaining real-time information from processes opens new perspectives for safer and more efficient manufacture of pharmaceuticals. Raman spectroscopy provides a molecular level insight into processing, and therefore it is a future process analytical tool. In this review, different applications of Raman spectroscopy in the field of process analysis of pharmaceutical solid dosage forms are summarized. In addition, pitfalls associated with interfacing to the process environment and challenges within data management are discussed.

  3. Using Analytic Hierarchy Process in Textbook Evaluation

    ERIC Educational Resources Information Center

    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…

  4. Microsystem process networks

    DOEpatents

    Wegeng, Robert S.; TeGrotenhuis, Ward E.; Whyatt, Greg A.

    2007-09-18

    Various aspects and applications of microsystem process networks are described. The design of many types of Microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  5. Microsystem process networks

    DOEpatents

    Wegeng, Robert S.; TeGrotenhuis, Ward E.; Whyatt, Greg A.

    2006-10-24

    Various aspects and applications of microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having exergetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  6. Microsystem process networks

    DOEpatents

    Wegeng, Robert S [Richland, WA; TeGrotenhuis, Ward E [Kennewick, WA; Whyatt, Greg A [West Richland, WA

    2010-01-26

    Various aspects and applications or microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  7. Visualizing Flow of Uncertainty through Analytical Processes.

    PubMed

    Wu, Yingcai; Yuan, Guo-Xun; Ma, Kwan-Liu

    2012-12-01

    Uncertainty can arise in any stage of a visual analytics process, especially in data-intensive applications with a sequence of data transformations. Additionally, throughout the process of multidimensional, multivariate data analysis, uncertainty due to data transformation and integration may split, merge, increase, or decrease. This dynamic characteristic along with other features of uncertainty pose a great challenge to effective uncertainty-aware visualization. This paper presents a new framework for modeling uncertainty and characterizing the evolution of the uncertainty information through analytical processes. Based on the framework, we have designed a visual metaphor called uncertainty flow to visually and intuitively summarize how uncertainty information propagates over the whole analysis pipeline. Our system allows analysts to interact with and analyze the uncertainty information at different levels of detail. Three experiments were conducted to demonstrate the effectiveness and intuitiveness of our design.

  8. Epidemic processes in complex networks

    NASA Astrophysics Data System (ADS)

    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.

  9. Analytical investigation of self-organized criticality in neural networks.

    PubMed

    Droste, Felix; Do, Anne-Ly; Gross, Thilo

    2013-01-06

    Dynamical criticality has been shown to enhance information processing in dynamical systems, and there is evidence for self-organized criticality in neural networks. A plausible mechanism for such self-organization is activity-dependent synaptic plasticity. Here, we model neurons as discrete-state nodes on an adaptive network following stochastic dynamics. At a threshold connectivity, this system undergoes a dynamical phase transition at which persistent activity sets in. In a low-dimensional representation of the macroscopic dynamics, this corresponds to a transcritical bifurcation. We show analytically that adding activity-dependent rewiring rules, inspired by homeostatic plasticity, leads to the emergence of an attractive steady state at criticality and present numerical evidence for the system's evolution to such a state.

  10. Learning Analytics for Networked Learning Models

    ERIC Educational Resources Information Center

    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…

  11. Statistically Qualified Neuro-Analytic system and Method for Process Monitoring

    SciTech Connect

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

    1998-11-04

    An apparatus and method for monitoring a process involves 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 steps: deterministic model adaption and stochastic 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 emor minimization technique. Stochastic model adaptation 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.

  12. Analytical Modeling of High Rate Processes.

    DTIC Science & Technology

    2007-11-02

    TYPE AND DATES COVERED 1 13 Apr 98 Final (01 Sep 94 - 31 Aug 97) 4. TITLE AND SUBTITLE 5 . FUNDING NUMBERS Analytical Modeling of High Rate Processes...20332- 8050 FROM: S. E. Jones, University Research Professor Department of Aerospace Engineering and Mechanics University of Alabama SUBJECT: Final...Mr. Sandor Augustus and Mr. Jeffrey A. Drinkard. There are no outstanding commitments. The balance in the account, as of July 31 , 1997, was $102,916.42

  13. Analytic information processing style in migraineurs.

    PubMed

    Di Sabato, Francesco; Buonfiglio, Marzia; Mandillo, Silvia

    2013-07-01

    Despite great advances in pathophysiological facets of migraine that have been made during recent years, as of today, migraine etiology is still not completely understood; moreover, to date the relationship between psychological factors and this primary headache must be further elucidated. However, abnormal information processing, as measured by evoked and event-related potentials, has been considered a key feature in migraine pathogenesis. The aim of this work was to study the relationships between analytic/global style of information processing and migraine, hypothesizing an analytic style, as highlighted by our previous study on cluster headache. This study applied three cognitive style tests never previously used in the context of migraine: "Sternberg-Wagner Self-Assessment Inventory", the C. Cornoldi test series called AMOS, and Brain-Dominance Questionnaire. 280 migraneurs with and without aura were tested and matched with two control groups: healthy subjects and tension-type headache patients. Our results demonstrated a strong correlation between analytic information processing style and migraine, indicating a preference toward a visual sensory approach in migraine without aura, in line with known neuroelectrophysiological data. These findings may suggest a role for this specific cognitive behavior in migraine pathogenesis, leading us to further investigate the neuroelectrophysiological, neurobiological, and epigenetic correlates.

  14. Controlling contagion processes in activity driven networks.

    PubMed

    Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro

    2014-03-21

    The vast majority of strategies aimed at controlling contagion processes on networks consider the connectivity pattern of the system either quenched or annealed. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently with the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for a class of time-varying networks, namely activity-driven networks. We develop a block variable mean-field approach that allows the derivation of the equations describing the coevolution of the contagion process and the network dynamic. We derive the critical immunization threshold and assess the effectiveness of three different control strategies. Finally, we validate the theoretical picture by simulating numerically the spreading process and control strategies in both synthetic networks and a large-scale, real-world, mobile telephone call data set.

  15. Improving drug manufacturing with process analytical technology.

    PubMed

    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.

  16. An analytic approach to the design of survivable optical mesh networks

    NASA Astrophysics Data System (ADS)

    Bhardwaj, Manish

    2007-12-01

    One of the key components of the cost of building and operating optical mesh communication networks is the requirement of survivability and many mesh survivability schemes have been suggested and their cost and performance numerically evaluated in the literature. However, little work has been done in developing comprehensive and tractable analytic models of the requirements in terms of capacity deployment and performance of the different mesh restoration schemes. Such analytic models are all the more significant given the large computation time required to numerically evaluate every possible network scenario. The focus of this thesis is to fill this void in our understanding of the costs and performance of mesh restoration schemes. Analytic models of the capacity requirements of mesh restoration schemes are presented and the accuracy of the analytic models evaluated over a wide range of network scenarios. Analytic models of the temporal performance of mesh restoration schemes are also presented thus extending for the first time the network modeling effort into the operational expenditure domain. Consequently, the number and nature of variables incorporated into the analysis is also enhanced from just the network topology and demand profile to include the switch hardware and routing protocols. We show for the first time in a quantifiable fashion the consequences of certain technology choices on the operational expenditure of optical mesh networks. Finally, the analytic models are leveraged to design a novel mesh network restoration architecture with lower restoration capacity requirement and better temporal performance than existing architectures. Such an architecture, although relevant in its own right due to its lower cost and better performance also represents a paradigm shift in the design philosophy of mesh networks wherein the analytic model guides the design process and numerical analysis confirms improvements predicted by the model. Future applications of

  17. Exploring the Analytical Processes of Intelligence Analysts

    SciTech Connect

    Chin, George; Kuchar, Olga A.; Wolf, Katherine E.

    2009-04-04

    We present an observational case study in which we investigate and analyze the analytical processes of intelligence analysts. Participating analysts in the study carry out two scenarios where they organize and triage information, conduct intelligence analysis, report results, and collaborate with one another. Through a combination of artifact analyses, group interviews, and participant observations, we explore the space and boundaries in which intelligence analysts work and operate. We also assess the implications of our findings on the use and application of relevant information technologies.

  18. Analytic solution for heat flow through a general harmonic network.

    PubMed

    Freitas, Nahuel; Paz, Juan Pablo

    2014-10-01

    We present an analytic expression for the heat current through a general harmonic network coupled with Ohmic reservoirs. We use a method that enables us to express the stationary state of the network in terms of the eigenvectors and eigenvalues of a generalized cubic eigenvalue problem. In this way, we obtain exact formulas for the heat current and the local temperature inside the network. Our method does not rely on the usual assumptions of weak coupling to the environments or on the existence of an infinite cutoff in the environmental spectral densities. We use this method to study nonequilibrium processes without the weak coupling and Markovian approximations. As a first application of our method, we revisit the problem of heat conduction in two- and three-dimensional crystals with binary mass disorder. We complement previous results showing that for small systems the scaling of the heat current with the system size greatly depends on the strength of the interaction between system and reservoirs. This somewhat counterintuitive result seems not to have been noticed before.

  19. Analytic solution for heat flow through a general harmonic network

    NASA Astrophysics Data System (ADS)

    Freitas, Nahuel; Paz, Juan Pablo

    2014-10-01

    We present an analytic expression for the heat current through a general harmonic network coupled with Ohmic reservoirs. We use a method that enables us to express the stationary state of the network in terms of the eigenvectors and eigenvalues of a generalized cubic eigenvalue problem. In this way, we obtain exact formulas for the heat current and the local temperature inside the network. Our method does not rely on the usual assumptions of weak coupling to the environments or on the existence of an infinite cutoff in the environmental spectral densities. We use this method to study nonequilibrium processes without the weak coupling and Markovian approximations. As a first application of our method, we revisit the problem of heat conduction in two- and three-dimensional crystals with binary mass disorder. We complement previous results showing that for small systems the scaling of the heat current with the system size greatly depends on the strength of the interaction between system and reservoirs. This somewhat counterintuitive result seems not to have been noticed before.

  20. Risk prioritisation using the analytic hierarchy process

    NASA Astrophysics Data System (ADS)

    Sum, Rabihah Md.

    2015-12-01

    This study demonstrated how to use the Analytic Hierarchy Process (AHP) to prioritise risks of an insurance company. AHP is a technique to structure complex problems by arranging elements of the problems in a hierarchy, assigning numerical values to subjective judgements on the relative importance of the elements and synthesizing the judgements to determine which elements have the highest priority. The study is motivated by wide application of AHP as a prioritisation technique in complex problems. It aims to show AHP is able to minimise some limitations of risk assessment technique using likelihood and impact. The study shows AHP is able to provide consistency check on subjective judgements, organise a large number of risks into a structured framework, assist risk managers to make explicit risk trade-offs, and provide an easy to understand and systematic risk assessment process.

  1. Neural Network Communications Signal Processing

    DTIC Science & Technology

    1994-08-01

    This final technical report describes the research and development- results of the Neural Network Communications Signal Processing (NNCSP) Program...The objectives of the NNCSP program are to: (1) develop and implement a neural network and communications signal processing simulation system for the...purpose of exploring the applicability of neural network technology to communications signal processing; (2) demonstrate several configurations of the

  2. Process-in-Network: A Comprehensive Network Processing Approach

    PubMed Central

    Urzaiz, Gabriel; Villa, David; Villanueva, Felix; Lopez, Juan Carlos

    2012-01-01

    A solid and versatile communications platform is very important in modern Ambient Intelligence (AmI) applications, which usually require the transmission of large amounts of multimedia information over a highly heterogeneous network. This article focuses on the concept of Process-in-Network (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and introduces a more comprehensive approach than current network processing technologies. PIN can take advantage of waiting times in queues of routers, idle processing capacity in intermediate nodes, and the information that passes through the network. PMID:22969390

  3. Process-in-Network: a comprehensive network processing approach.

    PubMed

    Urzaiz, Gabriel; Villa, David; Villanueva, Felix; Lopez, Juan Carlos

    2012-01-01

    A solid and versatile communications platform is very important in modern Ambient Intelligence (AmI) applications, which usually require the transmission of large amounts of multimedia information over a highly heterogeneous network. This article focuses on the concept of Process-in-Network (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and introduces a more comprehensive approach than current network processing technologies. PIN can take advantage of waiting times in queues of routers, idle processing capacity in intermediate nodes, and the information that passes through the network.

  4. Heterogeneous fractionation profiles of meta-analytic coactivation networks.

    PubMed

    Laird, Angela R; Riedel, Michael C; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L; Eickhoff, Simon B; Smith, Stephen M; Fox, Peter T; Sutherland, Matthew T

    2017-04-01

    Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication.

  5. Analytic process and dreaming about analysis.

    PubMed

    Sirois, François

    2016-12-01

    Dreams about the analytic session feature a manifest content in which the analytic setting is subject to distortion while the analyst appears undisguised. Such dreams are a consistent yet infrequent occurrence in most analyses. Their specificity consists in never reproducing the material conditions of the analysis as such. This paper puts forward the following hypothesis: dreams about the session relate to some aspects of the analyst's activity. In this sense, such dreams are indicative of the transference neurosis, prefiguring transference resistances to the analytic elaboration of key conflicts. The parts taken by the patient and by the analyst are discussed in terms of their ability to signal a deepening of the analysis.

  6. Discovery of Information Diffusion Process in Social Networks

    NASA Astrophysics Data System (ADS)

    Kim, Kwanho; Jung, Jae-Yoon; Park, Jonghun

    Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

  7. Generalized epidemic process on modular networks

    NASA Astrophysics Data System (ADS)

    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.

  8. Evaluation of an analytic, approximate formula for the time-varying SIS prevalence in different networks

    NASA Astrophysics Data System (ADS)

    Liu, Qiang; Van Mieghem, Piet

    2017-04-01

    One of the most important quantities of the exact Markovian SIS epidemic process is the time-dependent prevalence, which is the average fraction of infected nodes. Unfortunately, the Markovian SIS epidemic model features an exponentially increasing computational complexity with growing network size N. In this paper, we evaluate a recently proposed analytic approximate prevalence function introduced in Van Mieghem (2016). We compare the approximate function with the N-Intertwined Mean-Field Approximation (NIMFA) and with simulation of the Markovian SIS epidemic process. The results show that the new analytic prevalence function is comparable with other approximate methods.

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

    SciTech Connect

    Ragan, Eric D; Goodall, John R

    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.

  10. The Computer-Aided Analytic Process Model. Operations Handbook for the APM (Analytic Process Model) Demonstration Package. Appendix

    DTIC Science & Technology

    1986-01-01

    The Analytic Process Model for System Design and Measurement: A Computer-Aided Tool for Analyzing Training Systems and Other Human-Machine Systems. A...separate companion volume--The Computer-Aided Analytic Process Model : Operations Handbook for the APM Demonstration Package is also available under

  11. Analytical framework for recurrence network analysis of time series.

    PubMed

    Donges, Jonathan F; Heitzig, Jobst; Donner, Reik V; Kurths, Jürgen

    2012-04-01

    Recurrence networks are a powerful nonlinear tool for time series analysis of complex dynamical systems. While there are already many successful applications ranging from medicine to paleoclimatology, a solid theoretical foundation of the method has still been missing so far. Here, we interpret an ɛ-recurrence network as a discrete subnetwork of a "continuous" graph with uncountably many vertices and edges corresponding to the system's attractor. This step allows us to show that various statistical measures commonly used in complex network analysis can be seen as discrete estimators of newly defined continuous measures of certain complex geometric properties of the attractor on the scale given by ɛ. In particular, we introduce local measures such as the ɛ-clustering coefficient, mesoscopic measures such as ɛ-motif density, path-based measures such as ɛ-betweennesses, and global measures such as ɛ-efficiency. This new analytical basis for the so far heuristically motivated network measures also provides an objective criterion for the choice of ɛ via a percolation threshold, and it shows that estimation can be improved by so-called node splitting invariant versions of the measures. We finally illustrate the framework for a number of archetypical chaotic attractors such as those of the Bernoulli and logistic maps, periodic and two-dimensional quasiperiodic motions, and for hyperballs and hypercubes by deriving analytical expressions for the novel measures and comparing them with data from numerical experiments. More generally, the theoretical framework put forward in this work describes random geometric graphs and other networks with spatial constraints, which appear frequently in disciplines ranging from biology to climate science.

  12. Accelerating Network Traffic Analytics Using Query-DrivenVisualization

    SciTech Connect

    Bethel, E. Wes; Campbell, Scott; Dart, Eli; Stockinger, Kurt; Wu,Kesheng

    2006-07-29

    Realizing operational analytics solutions where large and complex data must be analyzed in a time-critical fashion entails integrating many different types of technology. This paper focuses on an interdisciplinary combination of scientific data management and visualization/analysis technologies targeted at reducing the time required for data filtering, querying, hypothesis testing and knowledge discovery in the domain of network connection data analysis. We show that use of compressed bitmap indexing can quickly answer queries in an interactive visual data analysis application, and compare its performance with two alternatives for serial and parallel filtering/querying on 2.5 billion records worth of network connection data collected over a period of 42 weeks. Our approach to visual network connection data exploration centers on two primary factors: interactive ad-hoc and multiresolution query formulation and execution over n dimensions and visual display of then-dimensional histogram results. This combination is applied in a case study to detect a distributed network scan and to then identify the set of remote hosts participating in the attack. Our approach is sufficiently general to be applied to a diverse set of data understanding problems as well as used in conjunction with a diverse set of analysis and visualization tools.

  13. Laplacian spectra of recursive treelike small-world polymer networks: Analytical solutions and applications

    NASA Astrophysics Data System (ADS)

    Liu, Hongxiao; Zhang, Zhongzhi

    2013-03-01

    A central issue in the study of polymer physics is to understand the relation between the geometrical properties of macromolecules and various dynamics, most of which are encoded in the Laplacian spectra of a related graph describing the macrostructural structure. In this paper, we introduce a family of treelike polymer networks with a parameter, which has the same size as the Vicsek fractals modeling regular hyperbranched polymers. We study some relevant properties of the networks and show that they have an exponentially decaying degree distribution and exhibit the small-world behavior. We then study the Laplacian eigenvalues and their corresponding eigenvectors of the networks under consideration, with both quantities being determined through the recursive relations deduced from the network structure. Using the obtained recursive relations we can find all the eigenvalues and eigenvectors for the networks with any size. Finally, as some applications, we use the eigenvalues to study analytically or semi-analytically three dynamical processes occurring in the networks, including random walks, relaxation dynamics in the framework of generalized Gaussian structure, as well as the fluorescence depolarization under quasiresonant energy transfer. Moreover, we compare the results with those corresponding to Vicsek fractals, and show that the dynamics differ greatly for the two network families, which thus enables us to distinguish between them.

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

    NASA Astrophysics Data System (ADS)

    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.

  15. The influence of retrieval practice on metacognition: The contribution of analytic and non-analytic processes.

    PubMed

    Miller, Tyler M; Geraci, Lisa

    2016-05-01

    People may change their memory predictions after retrieval practice using naïve theories of memory and/or by using subjective experience - analytic and non-analytic processes respectively. The current studies disentangled contributions of each process. In one condition, learners studied paired-associates, made a memory prediction, completed a short-run of retrieval practice and made a second prediction. In another condition, judges read about a yoked learners' retrieval practice performance but did not participate in retrieval practice and therefore, could not use non-analytic processes for the second prediction. In Study 1, learners reduced their predictions following moderately difficult retrieval practice whereas judges increased their predictions. In Study 2, learners made lower adjusted predictions than judges following both easy and difficult retrieval practice. In Study 3, judge-like participants used analytic processes to report adjusted predictions. Overall, the results suggested non-analytic processes play a key role for participants to reduce their predictions after retrieval practice.

  16. Diffusive capture process on complex networks

    NASA Astrophysics Data System (ADS)

    Lee, Sungmin; Yook, Soon-Hyung; Kim, Yup

    2006-10-01

    We study the dynamical properties of a diffusing lamb captured by a diffusing lion on the complex networks with various sizes of N . We find that the lifetime ⟨T⟩ of a lamb scales as ⟨T⟩˜N and the survival probability S(N→∞,t) becomes finite on scale-free networks with degree exponent γ>3 . However, S(N,t) for γ<3 has a long-living tail on tree-structured scale-free networks and decays exponentially on looped scale-free networks. This suggests that the second moment of degree distribution ⟨k2⟩ is the relevant factor for the dynamical properties in the diffusive capture process. We numerically find that the normalized number of capture events at a node with degree k , n(k) , decreases as n(k)˜k-σ . When γ<3 , n(k) still increases anomalously for k≈kmax , where kmax is the maximum value of k of given networks with size N . We analytically show that n(k) satisfies the relation n(k)˜k2P(k) for any degree distribution P(k) and the total number of capture events Ntot is proportional to ⟨k2⟩ , which causes the γ -dependent behavior of S(N,t) and ⟨T⟩ .

  17. Interacting Social Processes on Interconnected Networks

    PubMed Central

    Alvarez-Zuzek, Lucila G.; La Rocca, Cristian E.; Vazquez, Federico; Braunstein, Lidia A.

    2016-01-01

    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 < r*(β). In the r − β phase space, the system displays a transition at a critical threshold βc, from a coexistence of both orientations for β < βc to a dominance of one orientation for β > 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*). PMID:27689698

  18. Interacting Social Processes on Interconnected Networks.

    PubMed

    Alvarez-Zuzek, Lucila G; La Rocca, Cristian E; Vazquez, Federico; Braunstein, Lidia A

    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 < r*(β). In the r - β phase space, the system displays a transition at a critical threshold βc, from a coexistence of both orientations for β < βc to a dominance of one orientation for β > 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*).

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

    PubMed

    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.

  20. Intersubjectivity and the creation of meaning in the analytic process.

    PubMed

    Maier, Christian

    2014-11-01

    By means of a clinical illustration, the author describes how the intersubjective exchanges involved in an analytic process facilitate the representation of affects and memories which have been buried in the unconscious or indeed have never been available to consciousness. As a result of projective identificatory processes in the analytic relationship, in this example the analyst falls into a situation of helplessness which connects with his own traumatic experiences. Then he gets into a formal regression of the ego and responds with a so-to-speak hallucinatory reaction-an internal image which enables him to keep the analytic process on track and, later on, to construct an early traumatic experience of the analysand.

  1. Analytical solution for soil water redistribution during evaporation process.

    PubMed

    Teng, Jidong; Yasufuku, Noriyuki; Liu, Qiang; Liu, Shiyu

    2013-01-01

    Simulating the dynamics of soil water content and modeling soil water evaporation are critical for many environmental and agricultural strategies. The present study aims to develop an analytical solution to simulate soil water redistribution during the evaporation process. This analytical solution was derived utilizing an exponential function to describe the relation of hydraulic conductivity and water content on pressure head. The solution was obtained based on the initial condition of saturation and an exponential function to model the change of surface water content. Also, the evaporation experiments were conducted under a climate control apparatus to validate the theoretical development. Comparisons between the proposed analytical solution and experimental result are presented from the aspects of soil water redistribution, evaporative rate and cumulative evaporation. Their good agreement indicates that this analytical solution provides a reliable way to investigate the interaction of evaporation and soil water profile.

  2. Network command processing system overview

    NASA Technical Reports Server (NTRS)

    Nam, Yon-Woo; Murphy, Lisa D.

    1993-01-01

    The Network Command Processing System (NCPS) developed for the National Aeronautics and Space Administration (NASA) Ground Network (GN) stations is a spacecraft command system utilizing a MULTIBUS I/68030 microprocessor. This system was developed and implemented at ground stations worldwide to provide a Project Operations Control Center (POCC) with command capability for support of spacecraft operations such as the LANDSAT, Shuttle, Tracking and Data Relay Satellite, and Nimbus-7. The NCPS consolidates multiple modulation schemes for supporting various manned/unmanned orbital platforms. The NCPS interacts with the POCC and a local operator to process configuration requests, generate modulated uplink sequences, and inform users of the ground command link status. This paper presents the system functional description, hardware description, and the software design.

  3. Optimizing an Immersion ESL Curriculum Using Analytic Hierarchy Process

    ERIC Educational Resources Information Center

    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…

  4. Assessing Adult Learning Preferences Using the Analytic Hierarchy Process.

    ERIC Educational Resources Information Center

    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.…

  5. Functional Analytic Psychotherapy for Interpersonal Process Groups: A Behavioral Application

    ERIC Educational Resources Information Center

    Hoekstra, Renee

    2008-01-01

    This paper is an adaptation of Kohlenberg and Tsai's work, Functional Analytical Psychotherapy (1991), or FAP, to group psychotherapy. This author applied a behavioral rationale for interpersonal process groups by illustrating key points with a hypothetical client. Suggestions are also provided for starting groups, identifying goals, educating…

  6. Literature Review on Processing and Analytical Methods for ...

    EPA Pesticide Factsheets

    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.

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

    PubMed Central

    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. PMID:18925285

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

    PubMed

    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.

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

    PubMed

    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.

  10. An analytical study of various telecomminication networks using markov models

    NASA Astrophysics Data System (ADS)

    Ramakrishnan, M.; Jayamani, E.; Ezhumalai, P.

    2015-04-01

    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.

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

    SciTech Connect

    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.

  12. Developmental changes in analytic and holistic processes in face perception

    PubMed Central

    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

  13. The analytic hierarchy process in decisionmaking for caprine health programmes.

    PubMed

    Maino, M; Pérez, P; Oviedo, P; Sotomayor, G; Abalos, P

    2012-12-01

    The purpose of this study was to apply the analytic hierarchy process (AHP) to assist decision-making when planning animal health programmes, by assigning priorities to issues of concern to producers in Chile's main goat production region. This process allows a multi-criteria approach to problems, by analysing and ranking them in a hierarchical structure. Industry experts have highlighted the following animal health and disease control criteria: acceptance by breeders of disease control measures; impact of specific diseases on regional animal trade; the cost and efficacy of control measures; a decrease in flock production; and the impact of caprine diseases on human public health. Using these criteria in the AHP, the study found that the most important impacts were on human public health and on the animal trade. The disease priorities were tuberculosis, brucellosis and echinococcosis/hydatidosis, due mainlyto their zoonotic impact. The analytic hierarchy process proved useful when several criteria were involved in public health issues.

  14. On the propagation of diel signals in river networks using analytic solutions of flow equations

    NASA Astrophysics Data System (ADS)

    Fonley, Morgan; Mantilla, Ricardo; Small, Scott J.; Curtu, Rodica

    2016-07-01

    Several authors have reported diel oscillations in streamflow records and have hypothesized that these oscillations are linked to evapotranspiration cycles in the watershed. The timing of oscillations in rivers, however, lags behind those of temperature and evapotranspiration in hillslopes. Two hypotheses have been put forth to explain the magnitude and timing of diel streamflow oscillations during low-flow conditions. The first suggests that delays between the peaks and troughs of streamflow and daily evapotranspiration are due to processes occurring in the soil as water moves toward the channels in the river network. The second posits that they are due to the propagation of the signal through the channels as water makes its way to the outlet of the basin. In this paper, we design and implement a theoretical model to test these hypotheses. We impose a baseflow signal entering the river network and use a linear transport equation to represent flow along the network. We develop analytic streamflow solutions for the case of uniform velocities in space over all river links. We then use our analytic solution to simulate streamflows along a self-similar river network for different flow velocities. Our results show that the amplitude and time delay of the streamflow solution are heavily influenced by transport in the river network. Moreover, our equations show that the geomorphology and topology of the river network play important roles in determining how amplitude and signal delay are reflected in streamflow signals. Finally, we have tested our theoretical formulation in the Dry Creek Experimental Watershed, where oscillations are clearly observed in streamflow records. We find that our solution produces streamflow values and fluctuations that are similar to those observed in the summer of 2011.

  15. Heuristic and analytic processing in online sports betting.

    PubMed

    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.

  16. Signal Processing for Optical Networks

    DTIC Science & Technology

    2007-11-02

    ONLY (Leave Blank) 2. REPORT DATE 5 /1/98 3. REPORT TYPE AND DATES COVERED Final 9/30/95 - 1/1/98 4. TITLE AND SUBTITLE Signal Processing...for Optical Networks: 6. AUTHORS Dennis M. Healy Jr. 5 . FUNDING NUMBERS G (Grant) F1960 93 0567- 7. PERFORMING ORGANIZATION NAME(S) AND...NUMBER 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) AFOSR/PKA 110 Duncan Avenue, Room Bl 15 Boiling, AFB DC 20332- 8050 Monitor

  17. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

  18. Roll levelling semi-analytical model for process optimization

    NASA Astrophysics Data System (ADS)

    Silvestre, E.; Garcia, D.; Galdos, L.; Saenz de Argandoña, E.; Mendiguren, J.

    2016-08-01

    Roll levelling is a primary manufacturing process used to remove residual stresses and imperfections of metal strips in order to make them suitable for subsequent forming operations. In the last years the importance of this process has been evidenced with the apparition of Ultra High Strength Steels with strength > 900 MPa. The optimal setting of the machine as well as a robust machine design has become critical for the correct processing of these materials. Finite Element Method (FEM) analysis is the widely used technique for both aspects. However, in this case, the FEM simulation times are above the admissible ones in both machine development and process optimization. In the present work, a semi-analytical model based on a discrete bending theory is presented. This model is able to calculate the critical levelling parameters i.e. force, plastification rate, residual stresses in a few seconds. First the semi-analytical model is presented. Next, some experimental industrial cases are analyzed by both the semi-analytical model and the conventional FEM model. Finally, results and computation times of both methods are compared.

  19. AtPID: the overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis.

    PubMed

    Li, Peng; Zang, Weidong; Li, Yuhua; Xu, Feng; Wang, Jigang; Shi, Tieliu

    2011-01-01

    Protein interactions are involved in important cellular functions and biological processes that are the fundamentals of all life activities. With improvements in experimental techniques and progress in research, the overall protein interaction network frameworks of several model organisms have been created through data collection and integration. However, most of the networks processed only show simple relationships without boundary, weight or direction, which do not truly reflect the biological reality. In vivo, different types of protein interactions, such as the assembly of protein complexes or phosphorylation, often have their specific functions and qualifications. Ignorance of these features will bring much bias to the network analysis and application. Therefore, we annotate the Arabidopsis proteins in the AtPID database with further information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways. The latest updated AtPID database is available at http://www.megabionet.org/atpid/.

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

    SciTech Connect

    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.

  1. H CANYON PROCESSING IN CORRELATION WITH FH ANALYTICAL LABS

    SciTech Connect

    Weinheimer, E.

    2012-08-06

    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

  2. Inferring network topology via the propagation process

    NASA Astrophysics Data System (ADS)

    Zeng, An

    2013-11-01

    Inferring the network topology from the dynamics is a fundamental problem, with wide applications in geology, biology, and even counter-terrorism. Based on the propagation process, we present a simple method to uncover the network topology. A numerical simulation on artificial networks shows that our method enjoys a high accuracy in inferring the network topology. We find that the infection rate in the propagation process significantly influences the accuracy, and that each network corresponds to an optimal infection rate. Moreover, the method generally works better in large networks. These finding are confirmed in both real social and nonsocial networks. Finally, the method is extended to directed networks, and a similarity measure specific for directed networks is designed.

  3. Process analytical applications in the mid-infrared

    NASA Astrophysics Data System (ADS)

    Lundqvist, S.; Kluczynski, P.

    2011-01-01

    A review of applications for tunable diode laser spectroscopy (TDLS) instrumentation in process analytics is presented. We have investigated applications in olefin production suitable for TDLS instrumentation. The possibility to detect acetylene impurities in different hydrocarbon backgrounds was investigated by TDLS in the 3 micron wavelength region using novel GaInAsSb/AlGaAsSb DFB lasers. The performance of the TDLS instrument for detection of acetylene impurities in pure ethylene and in a gas matrix typical of a hydrogenating reactor was investigated more in detail. Experiments with in-situ measurements of hydrocarbons in an industrial environment using a modified Siemens TDLS instrument are also discussed.

  4. SensePath: Understanding the Sensemaking Process Through Analytic Provenance.

    PubMed

    Nguyen, Phong H; Xu, Kai; Wheat, Ashley; Wong, B L William; Attfield, Simon; Fields, Bob

    2016-01-01

    Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user's sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process.

  5. Analytical and experimental study on complex compressed air pipe network

    NASA Astrophysics Data System (ADS)

    Gai, Yushou; Cai, Maolin; Shi, Yan

    2015-09-01

    To analyze the working characteristics of complex compressed air networks, numerical methods are widely used which are based on finite element technology or intelligent algorithms. However, the effectiveness of the numerical methods is limited. In this paper, to provide a new method to optimize the design and the air supply strategy of the complex compressed air pipe network, firstly, a novel method to analyze the topology structure of the compressed air flow in the pipe network is initially proposed. A matrix is used to describe the topology structure of the compressed air flow. Moreover, based on the analysis of the pressure loss of the pipe network, the relationship between the pressure and the flow of the compressed air is derived, and a prediction method of pressure fluctuation and air flow in a segment in a complex pipe network is proposed. Finally, to inspect the effectiveness of the method, an experiment with a complex network is designed. The pressure and the flow of airflow in the network are measured and studied. The results of the study show that, the predicted results with the proposed method have a good consistency with the experimental results, and that verifies the air flow prediction method of the complex pipe network. This research proposes a new method to analyze the compressed air network and a prediction method of pressure fluctuation and air flow in a segment, which can predicate the fluctuation of the pressure according to the flow of compressed air, and predicate the fluctuation of the flow according to the pressure in a segment of a complex pipe network.

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

    PubMed

    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

  7. Ku-band signal design study. [space shuttle orbiter data processing network

    NASA Technical Reports Server (NTRS)

    Rubin, I.

    1978-01-01

    Analytical tools, methods and techniques for assessing the design and performance of the space shuttle orbiter data processing system (DPS) are provided. The computer data processing network is evaluated in the key areas of queueing behavior synchronization and network reliability. The structure of the data processing network is described as well as the system operation principles and the network configuration. The characteristics of the computer systems are indicated. System reliability measures are defined and studied. System and network invulnerability measures are computed. Communication path and network failure analysis techniques are included.

  8. Analyte species and concentration identification using differentially functionalized microcantilever arrays and artificial neural networks

    SciTech Connect

    Senesac, Larry R; Datskos, Panos G; Sepaniak, Michael J

    2006-01-01

    In the present work, we have performed analyte species and concentration identification using an array of ten differentially functionalized microcantilevers coupled with a back-propagation artificial neural network pattern recognition algorithm. The array consists of ten nanostructured silicon microcantilevers functionalized by polymeric and gas chromatography phases and macrocyclic receptors as spatially dense, differentially responding sensing layers for identification and quantitation of individual analyte(s) and their binary mixtures. The array response (i.e. cantilever bending) to analyte vapor was measured by an optical readout scheme and the responses were recorded for a selection of individual analytes as well as several binary mixtures. An artificial neural network (ANN) was designed and trained to recognize not only the individual analytes and binary mixtures, but also to determine the concentration of individual components in a mixture. To the best of our knowledge, ANNs have not been applied to microcantilever array responses previously to determine concentrations of individual analytes. The trained ANN correctly identified the eleven test analyte(s) as individual components, most with probabilities greater than 97%, whereas it did not misidentify an unknown (untrained) analyte. Demonstrated unique aspects of this work include an ability to measure binary mixtures and provide both qualitative (identification) and quantitative (concentration) information with array-ANN-based sensor methodologies.

  9. The definition and assessment of analytic process: can analysts agree?

    PubMed

    Vaughan, S C; Spitzer, R; Davies, M; Roose, S

    1997-10-01

    Although analytic process (AP) is a core concept in psychoanalytic theory and practice and has emerged as an important variable in outcome studies, there is no consensus regarding its definition and operationalisation. This paper describes the development and validation of the Columbia Analytic Process Scale (CAPS), a rating scale developed to evaluate the presence or absence of AP in a single psychoanalytic session transcript for purposes of an outcome study. Definitions of interrater reliability and construct validity are reviewed and two studies designed to evaluate these important aspects of the CAPS are presented. The results demonstrate that the CAPS has adequate interrater reliability (kappa = .5). To establish construct validity the plan was to compare the CAPS rating of AP to clinical consensus. However, when a group of ten senior training and supervising analysts at Columbia were asked to rate five psychoanalytic session transcripts, no clinical consensus could be established. Statistical analysis of the pattern of the analysts' clinical ratings showed that the largest portion of the variance was accounted for by the error term of a two-way ANOVA. The implication of this finding is that the construct of AP itself is ill-defined. The results of this study suggest that the commonly used term AP has less consensually held meanings than analysts tend to believe; the impact of lack of definition of key terms on clinical and research pursuits within psychoanalysis is discussed.

  10. Model and Analytic Processes for Export License Assessments

    SciTech Connect

    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 approach to

  11. Social network supported process recommender system.

    PubMed

    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.

  12. Analytic solutions for links and triangles distributions in finite Barabási-Albert networks

    NASA Astrophysics Data System (ADS)

    Ferreira, Ricardo M.; de Almeida, Rita M. C.; Brunnet, Leonardo G.

    2017-01-01

    Barabási-Albert model describes many different natural networks, often yielding sensible explanations to the subjacent dynamics. However, finite size effects may prevent from discerning among different underlying physical mechanisms and from determining whether a particular finite system is driven by Barabási-Albert dynamics. Here we propose master equations for the evolution of the degrees, links and triangles distributions, solve them both analytically and by numerical iteration, and compare with numerical simulations. The analytic solutions for all these distributions predict the network evolution for systems as small as 100 nodes. The analytic method we developed is applicable for other classes of networks, representing a powerful tool to investigate the evolution of natural networks.

  13. Neural Networks Applied to Signal Processing

    DTIC Science & Technology

    1989-09-01

    DTIC FILE COpy NAVAL POSTGRADUATE SCHOOL . Monterey, California Lf 0 (0 V’ STATES 4 THESIS NEURAL NETWORKS APPLIED TO SIGNAL PROCESSING by Mark D...FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO NO NO ACCESSION NO. 11. TITLE (Include Security Classification) NEURAL NETWORKS APPLIED TO...for public release; distribution is unlimited Neural Networks Applied to Signal Processing by Mark D. Baehre Captain, United States Army B.S., United

  14. Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions

    PubMed Central

    Laird, Angela R.; Ray, Kimberly L.; Dean, Y. Monica; Glahn, David C.; Carter, Cameron S.

    2013-01-01

    Classic cognitive theory conceptualizes executive functions as involving multiple specific domains, including initiation, inhibition, working memory, flexibility, planning, and vigilance. Lesion and neuroimaging experiments over the past two decades have suggested that both common and unique processes contribute to executive functions during higher cognition. It has been suggested that a superordinate fronto–cingulo–parietal network supporting cognitive control may also underlie a range of distinct executive functions. To test this hypothesis in the largest sample to date, we used quantitative meta-analytic methods to analyze 193 functional neuroimaging studies of 2,832 healthy individuals, ages 18–60, in which performance on executive function measures was contrasted with an active control condition. A common pattern of activation was observed in the prefrontal, dorsal anterior cingulate, and parietal cortices across executive function domains, supporting the idea that executive functions are supported by a superordinate cognitive control network. However, domain-specific analyses showed some variation in the recruitment of anterior prefrontal cortex, anterior and midcingulate regions, and unique subcortical regions such as the basal ganglia and cerebellum. These results are consistent with the existence of a superordinate cognitive control network in the brain, involving dorsolateral prefrontal, anterior cingulate, and parietal cortices, that supports a broad range of executive functions. PMID:22282036

  15. Evaluation of Analytical Modeling Functions for the Phonation Onset Process.

    PubMed

    Petermann, Simon; Kniesburges, Stefan; Ziethe, Anke; Schützenberger, Anne; Döllinger, Michael

    2016-01-01

    The human voice originates from oscillations of the vocal folds in the larynx. The duration of the voice onset (VO), called the voice onset time (VOT), is currently under investigation as a clinical indicator for correct laryngeal functionality. Different analytical approaches for computing the VOT based on endoscopic imaging were compared to determine the most reliable method to quantify automatically the transient vocal fold oscillations during VO. Transnasal endoscopic imaging in combination with a high-speed camera (8000 fps) was applied to visualize the phonation onset process. Two different definitions of VO interval were investigated. Six analytical functions were tested that approximate the envelope of the filtered or unfiltered glottal area waveform (GAW) during phonation onset. A total of 126 recordings from nine healthy males and 210 recordings from 15 healthy females were evaluated. Three criteria were analyzed to determine the most appropriate computation approach: (1) reliability of the fit function for a correct approximation of VO; (2) consistency represented by the standard deviation of VOT; and (3) accuracy of the approximation of VO. The results suggest the computation of VOT by a fourth-order polynomial approximation in the interval between 32.2 and 67.8% of the saturation amplitude of the filtered GAW.

  16. Evaluation of Analytical Modeling Functions for the Phonation Onset Process

    PubMed Central

    Petermann, Simon; Kniesburges, Stefan; Ziethe, Anke; Schützenberger, Anne; Döllinger, Michael

    2016-01-01

    The human voice originates from oscillations of the vocal folds in the larynx. The duration of the voice onset (VO), called the voice onset time (VOT), is currently under investigation as a clinical indicator for correct laryngeal functionality. Different analytical approaches for computing the VOT based on endoscopic imaging were compared to determine the most reliable method to quantify automatically the transient vocal fold oscillations during VO. Transnasal endoscopic imaging in combination with a high-speed camera (8000 fps) was applied to visualize the phonation onset process. Two different definitions of VO interval were investigated. Six analytical functions were tested that approximate the envelope of the filtered or unfiltered glottal area waveform (GAW) during phonation onset. A total of 126 recordings from nine healthy males and 210 recordings from 15 healthy females were evaluated. Three criteria were analyzed to determine the most appropriate computation approach: (1) reliability of the fit function for a correct approximation of VO; (2) consistency represented by the standard deviation of VOT; and (3) accuracy of the approximation of VO. The results suggest the computation of VOT by a fourth-order polynomial approximation in the interval between 32.2 and 67.8% of the saturation amplitude of the filtered GAW. PMID:27066108

  17. Analytical model of reactive transport processes with spatially variable coefficients.

    PubMed

    Simpson, Matthew J; Morrow, Liam C

    2015-05-01

    Analytical solutions of partial differential equation (PDE) models describing reactive transport phenomena in saturated porous media are often used as screening tools to provide insight into contaminant fate and transport processes. While many practical modelling scenarios involve spatially variable coefficients, such as spatially variable flow velocity, v(x), or spatially variable decay rate, k(x), most analytical models deal with constant coefficients. Here we present a framework for constructing exact solutions of PDE models of reactive transport. Our approach is relevant for advection-dominant problems, and is based on a regular perturbation technique. We present a description of the solution technique for a range of one-dimensional scenarios involving constant and variable coefficients, and we show that the solutions compare well with numerical approximations. Our general approach applies to a range of initial conditions and various forms of v(x) and k(x). Instead of simply documenting specific solutions for particular cases, we present a symbolic worksheet, as supplementary material, which enables the solution to be evaluated for different choices of the initial condition, v(x) and k(x). We also discuss how the technique generalizes to apply to models of coupled multispecies reactive transport as well as higher dimensional problems.

  18. Optimal Signal Processing in Small Stochastic Biochemical Networks

    PubMed Central

    Ziv, Etay; Nemenman, Ilya; Wiggins, Chris H.

    2007-01-01

    We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we do this without specifying the function performed by the network. Specifically, we study the maximum mutual information between the input (chemical) signal and the output (genetic) response attainable by the network in the context of an analytic model of particle number fluctuations. We perform this analysis for all biochemical circuits, including various feedback loops, that can be built out of 3 chemical species, each under the control of one regulator. We find that a generic network, constrained to low molecule numbers and reasonable response times, can transduce more information than a simple binary switch and, in fact, manages to achieve close to the optimal information transmission fidelity. These high-information solutions are robust to tenfold changes in most of the networks' biochemical parameters; moreover they are easier to achieve in networks containing cycles with an odd number of negative regulators (overall negative feedback) due to their decreased molecular noise (a result which we derive analytically). Finally, we demonstrate that a single circuit can support multiple high-information solutions. These findings suggest a potential resolution of the “cross-talk” phenomenon as well as the previously unexplained observation that transcription factors that undergo proteolysis are more likely to be auto-repressive. PMID:17957259

  19. How multiple social networks affect user awareness: The information diffusion process in multiplex networks

    NASA Astrophysics Data System (ADS)

    Li, Weihua; Tang, Shaoting; Fang, Wenyi; Guo, Quantong; Zhang, Xiao; Zheng, Zhiming

    2015-10-01

    The information diffusion process in single complex networks has been extensively studied, especially for modeling the spreading activities in online social networks. However, individuals usually use multiple social networks at the same time, and can share the information they have learned from one social network to another. This phenomenon gives rise to a new diffusion process on multiplex networks with more than one network layer. In this paper we account for this multiplex network spreading by proposing a model of information diffusion in two-layer multiplex networks. We develop a theoretical framework using bond percolation and cascading failure to describe the intralayer and interlayer diffusion. This allows us to obtain analytical solutions for the fraction of informed individuals as a function of transmissibility T and the interlayer transmission rate θ . Simulation results show that interaction between layers can greatly enhance the information diffusion process. And explosive diffusion can occur even if the transmissibility of the focal layer is under the critical threshold, due to interlayer transmission.

  20. How multiple social networks affect user awareness: The information diffusion process in multiplex networks.

    PubMed

    Li, Weihua; Tang, Shaoting; Fang, Wenyi; Guo, Quantong; Zhang, Xiao; Zheng, Zhiming

    2015-10-01

    The information diffusion process in single complex networks has been extensively studied, especially for modeling the spreading activities in online social networks. However, individuals usually use multiple social networks at the same time, and can share the information they have learned from one social network to another. This phenomenon gives rise to a new diffusion process on multiplex networks with more than one network layer. In this paper we account for this multiplex network spreading by proposing a model of information diffusion in two-layer multiplex networks. We develop a theoretical framework using bond percolation and cascading failure to describe the intralayer and interlayer diffusion. This allows us to obtain analytical solutions for the fraction of informed individuals as a function of transmissibility T and the interlayer transmission rate θ. Simulation results show that interaction between layers can greatly enhance the information diffusion process. And explosive diffusion can occur even if the transmissibility of the focal layer is under the critical threshold, due to interlayer transmission.

  1. Noise-processing by signaling networks.

    PubMed

    Kontogeorgaki, Styliani; Sánchez-García, Rubén J; Ewing, Rob M; Zygalakis, Konstantinos C; MacArthur, Ben D

    2017-04-03

    Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process environmental noise are not well understood. Here we outline a mathematical framework that relates a network's structure to its capacity to process noise, and use this framework to dissect the noise-processing ability of signaling networks. We find that complex networks that are dense in directed paths are poor noise processors, while those that are sparse and strongly directional process noise well. These results suggest that while cross-talk between signaling pathways may increase the ability of signaling networks to integrate multiple stimuli, too much cross-talk may compromise the ability of the network to distinguish signal from noise. To illustrate these general results we consider the structure of the signalling network that maintains pluripotency in mouse embryonic stem cells, and find an incoherent feedforward loop structure involving Stat3, Tfcp2l1, Esrrb, Klf2 and Klf4 is particularly important for noise-processing. Taken together these results suggest that noise-processing is an important function of signaling networks and they may be structured in part to optimize this task.

  2. Experimental, analytical and computational investigation of bimodal elastomer networks

    NASA Astrophysics Data System (ADS)

    von Lockette, Paris Robert

    Advances in the synthesis of macromolecular materials have led to the creation of special classes of elastomers called bimodal because of their bimodal distributions of linear starting oligomers. Numerous studies on these materials have documented anomalous increases in ultimate strength and toughness at certain mixture combinations of the constituents but have not yet identified a cause for this behavior. In addition, the ability to predict optimal mixtures still eludes polymer chemists. Constitutive models for the behavior of bimodal materials are also unable to predict material behavior, but instead tend to capture results using complicated curve fitting and iterative schemes. This thesis uncovers topological and micromechanical sources of these enhanced properties using periodic, topological simulations of chain-level network formation and develops a constitutive model of the aggregate bimodal network. Using a topological framework, in conjunction with the eight-chain averaging scheme of Arruda and Boyce, this work develops optical and mechanical constitutive models for bimodal elastomers whose results compare favorably with data in the literature. The resulting bimodal network theory is able to predict material response for a range of bimodal compositions using only two sets of data, a direct improvement over previous models. The micromechanics of elastomeric deformation and chain orientation as described by the eight-chain model are further validated by comparing optical and mechanical data generated during large deformation shear tests on unimodal materials with finite element simulations. In addition, a newly developed optical anisotropy model for the Raman tensor of polymeric materials, generated using an eight-chain unit cell model, is shown to compare favorably with tensile data in the literature. Results generated using NETSIM, a computer program developed in this thesis, have revealed naturally occurring, self-reinforcing topological features

  3. Prioritization of multiple CERCLA sites using the analytic hierarchy process

    SciTech Connect

    Brown, G.M.; Olis, A.; Georgariou, P.N.

    1994-12-31

    This paper presents an innovative technique, the Analytic Hierarchy Process (AHP), that was used to prioritize multiple potential hazardous waste sites at a large Department of Defense (DoD) facility identified on the Superfund`s National Priorities List (NPL). Most DoD facilities listed on the NPL are involved in complex investigations and cleanup activities that last for years and cost millions of dollars. Large facilities commonly have dozens of potentially contaminated sites. The AHP was developed to assist people in integrating qualitative and quantitative decision-making. This versatile mathematical technique has since been used for such diverse purposes as making capital investment decisions in third world economies and choosing between alternative wastewater treatment technologies. In this paper, the authors will demonstrate how the AHP can be used in hazardous waste site prioritization where dozens of individuals sites have to be investigated with limited resources, general lack of qualitative and quantitative data, and conflicting priorities.

  4. A Task Analytic Process to Define Future Concepts in Aviation

    NASA Technical Reports Server (NTRS)

    Gore, Brian Francis; Wolter, Cynthia A.

    2014-01-01

    A necessary step when developing next generation systems is to understand the tasks that operators will perform. One NextGen concept under evaluation termed Single Pilot Operations (SPO) is designed to improve the efficiency of airline operations. One SPO concept includes a Pilot on Board (PoB), a Ground Station Operator (GSO), and automation. A number of procedural changes are likely to result when such changes in roles and responsibilities are undertaken. Automation is expected to relieve the PoB and GSO of some tasks (e.g. radio frequency changes, loading expected arrival information). A major difference in the SPO environment is the shift to communication-cued crosschecks (verbal / automated) rather than movement-cued crosschecks that occur in a shared cockpit. The current article highlights a task analytic process of the roles and responsibilities between a PoB, an approach-phase GSO, and automation.

  5. Evaluating supplier quality performance using fuzzy analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Ahmad, Nazihah; Kasim, Maznah Mat; Rajoo, Shanmugam Sundram Kalimuthu

    2014-12-01

    Evaluating supplier quality performance is vital in ensuring continuous supply chain improvement, reducing the operational costs and risks towards meeting customer's expectation. This paper aims to illustrate an application of Fuzzy Analytical Hierarchy Process to prioritize the evaluation criteria in a context of automotive manufacturing in Malaysia. Five main criteria were identified which were quality, cost, delivery, customer serviceand technology support. These criteria had been arranged into hierarchical structure and evaluated by an expert. The relative importance of each criteria was determined by using linguistic variables which were represented as triangular fuzzy numbers. The Center of Gravity defuzzification method was used to convert the fuzzy evaluations into their corresponding crisps values. Such fuzzy evaluation can be used as a systematic tool to overcome the uncertainty evaluation of suppliers' performance which usually associated with human being subjective judgments.

  6. Optimizing an immersion ESL curriculum using analytic hierarchy process.

    PubMed

    Tang, Hui-Wen Vivian

    2011-11-01

    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 importance of course criteria for the purpose of tailoring an optimal one-week immersion English as a second language (ESL) curriculum for elementary school students in a suburban county of Taiwan. The hierarchy model and AHP analysis utilized in the present study will be useful for resolving several important multi-criteria decision-making issues in planning and evaluating ESL programs. This study also offers valuable insights and provides a basis for further research in customizing ESL curriculum models for different student populations with distinct learning needs, goals, and socioeconomic backgrounds.

  7. Analytical chemistry of the citrate process for flue gas desulfurization

    SciTech Connect

    Marchant, W.N.; May, S.L.; Simpson, W.W.; Winter, J.K.; Beard, H.R.

    1980-01-01

    The citrate process for flue gas desulfurization (FGD) is a product of continuing research by the US Bureau of Mines to meet the goal of minimizing the objectionable effects of minerals industry operations upon the environment. The reduction of SO/sub 2/ in solution by H/sub 2/S to produce elemental sulfur by the citrate process is extremely complex and results in solutions that contain at least nine different sulfur species. Process solution analysis is essential to a clear understanding of process chemistry and its safe, efficient operation. The various chemical species, the approximate ranges of their concentrations in citrate process solutions, and the analytical methods evolved to determine them are hydrogen sulfide (approx. 0M to 0.06M) by specific ion electrode, polysulfides (unknown) by ultraviolet (uv) spectrophotometry, elemental sulfur (approx. 0M to approx. 0.001M dissolved, approx. 0M to approx. 0.1M suspended) by uv spectrophotometry, thiosulfate (approx. 0M to approx. 0.25M) by iodometry or high performance liquid chromatography (HPLC), polythionates (approx. 0M to approx. 0.01M) by thin layer chromatography (TLC), dithionite (searched for but not detected in process solutions) by polarography or TLC, bisulfite (approx. 0M to 0.2M) by iodometry, sulfate (approx. 0M to 1M) by a Bureau-developed gravimetric procedure, citric acid (approx. 0M to 0.5M) by titration or visible colorimetry, glycolic acid (approx. 0M to 1M) by HPLC, sodium (approx. 1.5M) by flame photometry, and chloride by argentometric titration.

  8. Analytical controllability of deterministic scale-free networks and Cayley trees

    NASA Astrophysics Data System (ADS)

    Xu, Ming; Xu, Chuan-Yun; Wang, Huan; Deng, Cong-Zheng; Cao, Ke-Fei

    2015-07-01

    According to the exact controllability theory, the controllability is investigated analytically for two typical types of self-similar bipartite networks, i.e., the classic deterministic scale-free networks and Cayley trees. Due to their self-similarity, the analytical results of the exact controllability are obtained, and the minimum sets of driver nodes (drivers) are also identified by elementary transformations on adjacency matrices. For these two types of undirected networks, no matter their links are unweighted or (nonzero) weighted, the controllability of networks and the configuration of drivers remain the same, showing a robustness to the link weights. These results have implications for the control of real networked systems with self-similarity.

  9. Analytical Modeling of Medium Access Control Protocols in Wireless Networks

    DTIC Science & Technology

    2006-03-01

    provide the basic functionalities that are common to any com - puter network. The proposed modeling framework focuses on the interactions between the...colleagues I had the pleasure to meet at the Computer Com - munication Research Group (CCRG). In particular, I would like to thank Marco Spohn, Re- nato...Brazil), the Baskin Chair of Com - puter Engineering at UCSC, the National Science Foundation under Grant CNS-0435522, the UCOP CLC under Grant SC-05

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

    SciTech Connect

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

    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.

  11. CT Image Processing Using Public Digital Networks

    PubMed Central

    Rhodes, Michael L.; Azzawi, Yu-Ming; Quinn, John F.; Glenn, William V.; Rothman, Stephen L.G.

    1984-01-01

    Nationwide commercial computer communication is now commonplace for those applications where digital dialogues are generally short and widely distributed, and where bandwidth does not exceed that of dial-up telephone lines. Image processing using such networks is prohibitive because of the large volume of data inherent to digital pictures. With a blend of increasing bandwidth and distributed processing, network image processing becomes possible. This paper examines characteristics of a digital image processing service for a nationwide network of CT scanner installations. Issues of image transmission, data compression, distributed processing, software maintenance, and interfacility communication are also discussed. Included are results that show the volume and type of processing experienced by a network of over 50 CT scanners for the last 32 months.

  12. Application of a high-throughput process analytical technology metabolomics pipeline to Port wine forced ageing process.

    PubMed

    Castro, Cristiana C; Martins, R C; Teixeira, José A; Silva Ferreira, António C

    2014-01-15

    Metabolomics aims at gathering the maximum amount of metabolic information for a total interpretation of biological systems. A process analytical technology pipeline, combining gas chromatography-mass spectrometry data preprocessing with multivariate analysis, was applied to a Port wine "forced ageing" process under different oxygen saturation regimes at 60°C. It was found that extreme "forced ageing" conditions promote the occurrence of undesirable chemical reactions by production of dioxane and dioxolane isomers, furfural and 5-hydroxymethylfurfural, which affect the quality of the final product through the degradation of the wine aromatic profile, colour and taste. Also, were found high kinetical correlations between these key metabolites with benzaldehyde, sotolon, and many other metabolites that contribute for the final aromatic profile of the Port wine. The use of the kinetical correlations in time-dependent processes as wine ageing can further contribute to biological or chemical systems monitoring, new biomarkers discovery and metabolic network investigations.

  13. Process modeling with the regression network.

    PubMed

    van der Walt, T; Barnard, E; van Deventer, J

    1995-01-01

    A new connectionist network topology called the regression network is proposed. The structural and underlying mathematical features of the regression network are investigated. Emphasis is placed on the intricacies of the optimization process for the regression network and some measures to alleviate these difficulties of optimization are proposed and investigated. The ability of the regression network algorithm to perform either nonparametric or parametric optimization, as well as a combination of both, is also highlighted. It is further shown how the regression network can be used to model systems which are poorly understood on the basis of sparse data. A semi-empirical regression network model is developed for a metallurgical processing operation (a hydrocyclone classifier) by building mechanistic knowledge into the connectionist structure of the regression network model. Poorly understood aspects of the process are provided for by use of nonparametric regions within the structure of the semi-empirical connectionist model. The performance of the regression network model is compared to the corresponding generalization performance results obtained by some other nonparametric regression techniques.

  14. The European Network of Analytical and Experimental Laboratories for Geosciences

    NASA Astrophysics Data System (ADS)

    Freda, Carmela; Funiciello, Francesca; Meredith, Phil; Sagnotti, Leonardo; Scarlato, Piergiorgio; Troll, Valentin R.; Willingshofer, Ernst

    2013-04-01

    Integrating Earth Sciences infrastructures in Europe is the mission of the European Plate Observing System (EPOS).The integration of European analytical, experimental, and analogue laboratories plays a key role in this context and is the task of the EPOS Working Group 6 (WG6). Despite the presence in Europe of high performance infrastructures dedicated to geosciences, there is still limited collaboration in sharing facilities and best practices. The EPOS WG6 aims to overcome this limitation by pushing towards national and trans-national coordination, efficient use of current laboratory infrastructures, and future aggregation of facilities not yet included. This will be attained through the creation of common access and interoperability policies to foster and simplify personnel mobility. The EPOS ambition is to orchestrate European laboratory infrastructures with diverse, complementary tasks and competences into a single, but geographically distributed, infrastructure for rock physics, palaeomagnetism, analytical and experimental petrology and volcanology, and tectonic modeling. The WG6 is presently organizing its thematic core services within the EPOS distributed research infrastructure with the goal of joining the other EPOS communities (geologists, seismologists, volcanologists, etc...) and stakeholders (engineers, risk managers and other geosciences investigators) to: 1) develop tools and services to enhance visitor programs that will mutually benefit visitors and hosts (transnational access); 2) improve support and training activities to make facilities equally accessible to students, young researchers, and experienced users (training and dissemination); 3) collaborate in sharing technological and scientific know-how (transfer of knowledge); 4) optimize interoperability of distributed instrumentation by standardizing data collection, archive, and quality control standards (data preservation and interoperability); 5) implement a unified e-Infrastructure for data

  15. Review of Processing and Analytical Methods for Francisella ...

    EPA Pesticide Factsheets

    Journal Article The etiological agent of tularemia, Francisella tularensis, is a resilient organism within the environment and can be acquired many ways (infectious aerosols and dust, contaminated food and water, infected carcasses, and arthropod bites). However, isolating F. tularensis from environmental samples can be challenging due to its nutritionally fastidious and slow-growing nature. In order to determine the current state of the science regarding available processing and analytical methods for detection and recovery of F. tularensis from water and soil matrices, a review of the literature was conducted. During the review, analysis via culture, immunoassays, and genomic identification were the most commonly found methods for F. tularensis detection within environmental samples. Other methods included combined culture and genomic analysis for rapid quantification of viable microorganisms and use of one assay to identify multiple pathogens from a single sample. Gaps in the literature that were identified during this review suggest that further work to integrate culture and genomic identification would advance our ability to detect and to assess the viability of Francisella spp. The optimization of DNA extraction, whole genome amplification with inhibition-resistant polymerases, and multiagent microarray detection would also advance biothreat detection.

  16. The best motivator priorities parents choose via analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Farah, R. N.; Latha, P.

    2015-05-01

    Motivation is probably the most important factor that educators can target in order to improve learning. Numerous cross-disciplinary theories have been postulated to explain motivation. While each of these theories has some truth, no single theory seems to adequately explain all human motivation. The fact is that human beings in general and pupils in particular are complex creatures with complex needs and desires. In this paper, Analytic Hierarchy Process (AHP) has been proposed as an emerging solution to move towards too large, dynamic and complex real world multi-criteria decision making problems in selecting the most suitable motivator when choosing school for their children. Data were analyzed using SPSS 17.0 ("Statistical Package for Social Science") software. Statistic testing used are descriptive and inferential statistic. Descriptive statistic used to identify respondent pupils and parents demographic factors. The statistical testing used to determine the pupils and parents highest motivator priorities and parents' best priorities using AHP to determine the criteria chosen by parents such as school principals, teachers, pupils and parents. The moderating factors are selected schools based on "Standard Kualiti Pendidikan Malaysia" (SKPM) in Ampang. Inferential statistics such as One-way ANOVA used to get the significant and data used to calculate the weightage of AHP. School principals is found to be the best motivator for parents in choosing school for their pupils followed by teachers, parents and pupils.

  17. Evaluating supplier quality performance using analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Kalimuthu Rajoo, Shanmugam Sundram; Kasim, Maznah Mat; Ahmad, Nazihah

    2013-09-01

    This paper elaborates the importance of evaluating supplier quality performance to an organization. Supplier quality performance evaluation reflects the actual performance of the supplier exhibited at customer's end. It is critical in enabling the organization to determine the area of improvement and thereafter works with supplier to close the gaps. Success of the customer partly depends on supplier's quality performance. Key criteria as quality, cost, delivery, technology support and customer service are categorized as main factors in contributing to supplier's quality performance. 18 suppliers' who were manufacturing automotive application parts evaluated in year 2010 using weight point system. There were few suppliers with common rating which led to common ranking observed by few suppliers'. Analytical Hierarchy Process (AHP), a user friendly decision making tool for complex and multi criteria problems was used to evaluate the supplier's quality performance challenging the weight point system that was used for 18 suppliers'. The consistency ratio was checked for criteria and sub-criteria. Final results of AHP obtained with no overlap ratings, therefore yielded a better decision making methodology as compared to weight point rating system.

  18. Model choice considerations and information integration using analytical hierarchy process

    SciTech Connect

    Langenbrunner, James R; Hemez, Francois M; Booker, Jane M; Ross, Timothy J.

    2010-10-15

    Using the theory of information-gap for decision-making under severe uncertainty, it has been shown that model output compared to experimental data contains irrevocable trade-offs between fidelity-to-data, robustness-to-uncertainty and confidence-in-prediction. We illustrate a strategy for information integration by gathering and aggregating all available data, knowledge, theory, experience, similar applications. Such integration of information becomes important when the physics is difficult to model, when observational data are sparse or difficult to measure, or both. To aggregate the available information, we take an inference perspective. Models are not rejected, nor wasted, but can be integrated into a final result. We show an example of information integration using Saaty's Analytic Hierarchy Process (AHP), integrating theory, simulation output and experimental data. We used expert elicitation to determine weights for two models and two experimental data sets, by forming pair-wise comparisons between model output and experimental data. In this way we transform epistemic and/or statistical strength from one field of study into another branch of physical application. The price to pay for utilizing all available knowledge is that inferences drawn for the integrated information must be accounted for and the costs can be considerable. Focusing on inferences and inference uncertainty (IU) is one way to understand complex information.

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

    PubMed

    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.

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

    ERIC Educational Resources Information Center

    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…

  1. Analytical solution for a class of network dynamics with mechanical and financial applications

    NASA Astrophysics Data System (ADS)

    Krejčí, P.; Lamba, H.; Melnik, S.; Rachinskii, D.

    2014-09-01

    We show that for a certain class of dynamics at the nodes the response of a network of any topology to arbitrary inputs is defined in a simple way by its response to a monotone input. The nodes may have either a discrete or continuous set of states and there is no limit on the complexity of the network. The results provide both an efficient numerical method and the potential for accurate analytic approximation of the dynamics on such networks. As illustrative applications, we introduce a quasistatic mechanical model with objects interacting via frictional forces and a financial market model with avalanches and critical behavior that are generated by momentum trading strategies.

  2. Focused analyte spray emission apparatus and process for mass spectrometric analysis

    DOEpatents

    Roach, Patrick J [Kennewick, WA; Laskin, Julia [Richland, WA; Laskin, Alexander [Richland, WA

    2012-01-17

    An apparatus and process are disclosed that deliver an analyte deposited on a substrate to a mass spectrometer that provides for trace analysis of complex organic analytes. Analytes are probed using a small droplet of solvent that is formed at the junction between two capillaries. A supply capillary maintains the droplet of solvent on the substrate; a collection capillary collects analyte desorbed from the surface and emits analyte ions as a focused spray to the inlet of a mass spectrometer for analysis. The invention enables efficient separation of desorption and ionization events, providing enhanced control over transport and ionization of the analyte.

  3. Impact of bankruptcy through asset portfolios. Network analytic solution unveils 1990s Japanese banking crisis

    NASA Astrophysics Data System (ADS)

    Sakamoto, Y.; Vodenska, I.

    2016-09-01

    We investigate the Japanese banking crisis in the late 1990s with a simple network based mathematical model, which allows us to simulate the crisis as well as to obtain new perspective through analytic solution of our network model. We effectively identify the actual bankrupted banks and the robustness of the banking system using a simulation model based on properties of a bi-partite bank-asset network. We show the mean time property and analytical solution of the model revealing aggregate time dynamics of bank asset prices throughout the banking crisis. The results disclose simple but fundamental property of asset growth, instrumental for understanding the bank crisis. We also estimate the selling pressure for each asset type, derived from a Cascading Failure Model (CFM), offering new perspective for investigating the phenomenon of banking crisis.

  4. Dynamic Graph Analytic Framework (DYGRAF): greater situation awareness through layered multi-modal network analysis

    NASA Astrophysics Data System (ADS)

    Margitus, Michael R.; Tagliaferri, William A., Jr.; Sudit, Moises; LaMonica, Peter M.

    2012-06-01

    Understanding the structure and dynamics of networks are of vital importance to winning the global war on terror. To fully comprehend the network environment, analysts must be able to investigate interconnected relationships of many diverse network types simultaneously as they evolve both spatially and temporally. To remove the burden from the analyst of making mental correlations of observations and conclusions from multiple domains, we introduce the Dynamic Graph Analytic Framework (DYGRAF). DYGRAF provides the infrastructure which facilitates a layered multi-modal network analysis (LMMNA) approach that enables analysts to assemble previously disconnected, yet related, networks in a common battle space picture. In doing so, DYGRAF provides the analyst with timely situation awareness, understanding and anticipation of threats, and support for effective decision-making in diverse environments.

  5. Correlation Between the System Capabilities Analytic Process (SCAP) and the Missions and Means Framework (MMF)

    DTIC Science & Technology

    2013-05-01

    Correlation Between the System Capabilities Analytic Process (SCAP) and the Missions and Means Framework ( MMF ) by Kevin S. Agan ARL-TR...ARL-TR-6455 May 2013 Correlation Between the System Capabilities Analytic Process (SCAP) and the Missions and Means Framework ( MMF ) Kevin...Analytic Process (SCAP) and the Missions and Means Framework ( MMF ) 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

  6. Multipass optical device and process for gas and analyte determination

    DOEpatents

    Bernacki, Bruce E.

    2011-01-25

    A torus multipass optical device and method are described that provide for trace level determination of gases and gas-phase analytes. The torus device includes an optical cavity defined by at least one ring mirror. The mirror delivers optical power in at least a radial and axial direction and propagates light in a multipass optical path of a predefined path length.

  7. Weighted networks as randomly reinforced urn processes

    NASA Astrophysics Data System (ADS)

    Caldarelli, Guido; Chessa, Alessandro; Crimaldi, Irene; Pammolli, Fabio

    2013-02-01

    We analyze weighted networks as randomly reinforced urn processes, in which the edge-total weights are determined by a reinforcement mechanism. We develop a statistical test and a procedure based on it to study the evolution of networks over time, detecting the “dominance” of some edges with respect to the others and then assessing if a given instance of the network is taken at its steady state or not. Distance from the steady state can be considered as a measure of the relevance of the observed properties of the network. Our results are quite general, in the sense that they are not based on a particular probability distribution or functional form of the random weights. Moreover, the proposed tool can be applied also to dense networks, which have received little attention by the network community so far, since they are often problematic. We apply our procedure in the context of the International Trade Network, determining a core of “dominant edges.”

  8. Reconfigurable real-time distributed processing network

    NASA Astrophysics Data System (ADS)

    Page, S. F.; Seely, R. D.; Hickman, D.

    2011-06-01

    This paper describes a novel real-time image and signal processing network, RONINTM, which facilitates the rapid design and deployment of systems providing advanced geospatial surveillance and situational awareness capability. RONINTM is a distributed software architecture consisting of multiple agents or nodes, which can be configured to implement a variety of state-of-the-art computer vision and signal processing algorithms. The nodes operate in an asynchronous fashion and can run on a variety of hardware platforms, thus providing a great deal of scalability and flexibility. Complex algorithmic configuration chains can be assembled using an intuitive graphical interface in a plug-and- play manner. RONINTM has been successfully exploited for a number of applications, ranging from remote event detection to complex multiple-camera real-time 3D object reconstruction. This paper describes the motivation behind the creation of the network, the core design features, and presents details of an example application. Finally, the on-going development of the network is discussed, which is focussed on dynamic network reconfiguration. This allows to the network to automatically adapt itself to node or communications failure by intelligently re-routing network communications and through adaptive resource management.

  9. Resilient networked sensor-processing implementation

    NASA Astrophysics Data System (ADS)

    Wada, Glen; Hansen, J. S.

    1996-05-01

    The spatial infrared imaging telescope (SPIRIT) III sensor data processing requirement for the calibrated conversion of data to engineering units at a rate of 8 gigabytes of input data per day necessitated a distributed processing solution. As the sensor's five-band scanning radiometer and six- channel Fourier-transform spectrometer characteristics became fully understood, the processing requirements were enhanced. Hardware and schedule constraints compounded the need for a simple and resilient distributed implementation. Sensor data processing was implemented as a loosely coupled, fiber distributed data interface network of Silicon Graphics computers under the IRIX Operating Systems. The software was written in ANSI C and incorporated exception processing. Interprocessor communications and control were done both by the native capabilities of the network and Parallel Virtual Machine (PVM) software. The implementation was limited to four software components. The data reformatter component reduced the data coupling among sensor data processing components by providing self-contained data sets. The distributed processing control and graphical user interface components encased the PVM aspect of the implementation and lessened the concern of the sensor data processing component developers for the distributed model. A loosely coupled solution that dissociated the sensor data processing from the distributed processing environment, a simplified error processing scheme using exception processing, and a limited software configuration have proven resilient and compatible with the dynamics of sensor data processing.

  10. Experimental and Analytical Research on Fracture Processes in ROck

    SciTech Connect

    Herbert H.. Einstein; Jay Miller; Bruno Silva

    2009-02-27

    Experimental studies on fracture propagation and coalescence were conducted which together with previous tests by this group on gypsum and marble, provide information on fracturing. Specifically, different fracture geometries wsere tested, which together with the different material properties will provide the basis for analytical/numerical modeling. INitial steps on the models were made as were initial investigations on the effect of pressurized water on fracture coalescence.

  11. Inferring sparse networks for noisy transient processes

    NASA Astrophysics Data System (ADS)

    Tran, Hoang M.; Bukkapatnam, Satish T. S.

    2016-02-01

    Inferring causal structures of real world complex networks from measured time series signals remains an open issue. The current approaches are inadequate to discern between direct versus indirect influences (i.e., the presence or absence of a directed arc connecting two nodes) in the presence of noise, sparse interactions, as well as nonlinear and transient dynamics of real world processes. We report a sparse regression (referred to as the -min) approach with theoretical bounds on the constraints on the allowable perturbation to recover the network structure that guarantees sparsity and robustness to noise. We also introduce averaging and perturbation procedures to further enhance prediction scores (i.e., reduce inference errors), and the numerical stability of -min approach. Extensive investigations have been conducted with multiple benchmark simulated genetic regulatory network and Michaelis-Menten dynamics, as well as real world data sets from DREAM5 challenge. These investigations suggest that our approach can significantly improve, oftentimes by 5 orders of magnitude over the methods reported previously for inferring the structure of dynamic networks, such as Bayesian network, network deconvolution, silencing and modular response analysis methods based on optimizing for sparsity, transients, noise and high dimensionality issues.

  12. Analytical results of asymmetric exclusion processes with ramps

    NASA Astrophysics Data System (ADS)

    Huang, Ding-Wei

    2005-07-01

    We present the analytical results in a simple traffic model describing a single-lane highway with ramps. Both on-ramps and off-ramps are considered. Complete classification of distinct phases is achieved. Exact phase diagrams are derived. In the case of a single ramp (either on-ramp or off-ramp), the bottleneck effect is absent. The traffic conditions of congestion before the ramp and free-flowing after the ramp cannot be realized. In the case of two consecutive ramps, the bottleneck emerges when the on-ramp is placed before the off-ramp and the flow in between the ramps saturates.

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

    SciTech Connect

    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.

  14. Solvent Substitution Methodology Using Multiattribute Utility Theory and the Analytical Hierarchical Process

    DTIC Science & Technology

    1994-09-01

    Wright-Patterson Air Force Base, Ohio AFIT/GEE/ENS/94S-3 SOLVENT SUBSTITUTION METHODOLOGY USING MULTIATTRIBUTE UTILITY THEORY AND THE ANALYTICAL...CLASS: AFIT/GEE/ENS/94S-3 THESIS TITLE: Solvent Substitution Methodology using Multiattribute Utility Theory and the Analytical Hierarchical Process...Process: Depot Level 13 Substitution Process: Field Level 16 Contractor Substitution Process 17 Multiattribute Utility Theory (MAUT) 18 Independence

  15. Calculating of river water quality sampling frequency by the analytic hierarchy process (AHP).

    PubMed

    Do, Huu Tuan; Lo, Shang-Lien; Phan Thi, Lan Anh

    2013-01-01

    River water quality sampling frequency is an important aspect of the river water quality monitoring network. A suitable sampling frequency for each station as well as for the whole network will provide a measure of the real water quality status for the water quality managers as well as the decision makers. The analytic hierarchy process (AHP) is an effective method for decision analysis and calculation of weighting factors based on multiple criteria to solve complicated problems. This study introduces a new procedure to design river water quality sampling frequency by applying the AHP. We introduce and combine weighting factors of variables with the relative weights of stations to select the sampling frequency for each station, monthly and yearly. The new procedure was applied for Jingmei and Xindian rivers, Taipei, Taiwan. The results showed that sampling frequency should be increased at high weighted stations while decreased at low weighted stations. In addition, a detailed monitoring plan for each station and each month could be scheduled from the output results. Finally, the study showed that the AHP is a suitable method to design a system for sampling frequency as it could combine multiple weights and multiple levels for stations and variables to calculate a final weight for stations, variables, and months.

  16. Neural networks in the process industries

    SciTech Connect

    Ben, L.R.; Heavner, L.

    1996-12-01

    Neural networks, or more precisely, artificial neural networks (ANNs), are rapidly gaining in popularity. They first began to appear on the process-control scene in the early 1990s, but have been a research focus for more than 30 years. Neural networks are really empirical models that approximate the way man thinks neurons in the human brain work. Neural-net technology is not trying to produce computerized clones, but to model nature in an effort to mimic some of the brain`s capabilities. Modeling, for the purposes of this article, means developing a mathematical description of physical phenomena. The physics and chemistry of industrial processes are usually quite complex and sometimes poorly understood. Our process understanding, and our imperfect ability to describe complexity in mathematical terms, limit fidelity of first-principle models. Computational requirements for executing these complex models are a further limitation. It is often not possible to execute first-principle model algorithms at the high rate required for online control. Nevertheless, rigorous first principle models are commonplace design tools. Process control is another matter. Important model inputs are often not available as process measurements, making real-time application difficult. In fact, engineers often use models to infer unavailable measurements. 5 figs.

  17. Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks

    PubMed Central

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

    2017-01-01

    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. PMID:28261006

  18. Analytically tractable studies of traveling waves of activity in integrate-and-fire neural networks.

    PubMed

    Zhang, Jie; Osan, Remus

    2016-05-01

    In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration depends quadratically on the instantaneous speed of the activity propagation. We use this property to analytically compute the network spike dynamics and to highlight the emergence of a natural time scale for the evolution of the traveling waves. These results allow us to examine other applications of this model such as the effect that a nonconductive gap of tissue has on further activity propagation. Furthermore we show that activity propagation also depends on local conditions for other more general connectivity functions, by converting the evolution equations for network dynamics into a low-dimensional system of ordinary differential equations. This approach greatly enhances our intuition into the mechanisms of the traveling waves evolution and significantly reduces the simulation time for this class of models.

  19. Analytically tractable studies of traveling waves of activity in integrate-and-fire neural networks

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Osan, Remus

    2016-05-01

    In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration depends quadratically on the instantaneous speed of the activity propagation. We use this property to analytically compute the network spike dynamics and to highlight the emergence of a natural time scale for the evolution of the traveling waves. These results allow us to examine other applications of this model such as the effect that a nonconductive gap of tissue has on further activity propagation. Furthermore we show that activity propagation also depends on local conditions for other more general connectivity functions, by converting the evolution equations for network dynamics into a low-dimensional system of ordinary differential equations. This approach greatly enhances our intuition into the mechanisms of the traveling waves evolution and significantly reduces the simulation time for this class of models.

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

    PubMed

    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.

  1. GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection

    SciTech Connect

    Harshaw, Chris R; Bridges, Robert A; Iannacone, Michael D; Reed, Joel W; Goodall, John R

    2016-01-01

    This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called \\textit{GraphPrints}. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets\\textemdash small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84\\% at the time-interval level, and 0.05\\% at the IP-level with 100\\% true positive rates at both.

  2. Bias and precision of selected analytes reported by the National Atmospheric Deposition Program and National Trends Network, 1984

    USGS Publications Warehouse

    Brooks, M.H.; Schroder, L.J.; Willoughby, T.C.

    1987-01-01

    The U.S. Geological Survey operated a blind audit sample program during 1974 to test the effects of the sample handling and shipping procedures used by the National Atmospheric Deposition Program and National Trends Network on the quality of wet deposition data produced by the combined networks. Blind audit samples, which were dilutions of standard reference water samples, were submitted by network site operators to the central analytical laboratory disguised as actual wet deposition samples. Results from the analyses of blind audit samples were used to calculate estimates of analyte bias associated with all network wet deposition samples analyzed in 1984 and to estimate analyte precision. Concentration differences between double blind samples that were submitted to the central analytical laboratory and separate analyses of aliquots of those blind audit samples that had not undergone network sample handling and shipping were used to calculate analyte masses that apparently were added to each blind audit sample by routine network handling and shipping procedures. These calculated masses indicated statistically significant biases for magnesium, sodium , potassium, chloride, and sulfate. Median calculated masses were 41.4 micrograms (ug) for calcium, 14.9 ug for magnesium, 23.3 ug for sodium, 0.7 ug for potassium, 16.5 ug for chloride and 55.3 ug for sulfate. Analyte precision was estimated using two different sets of replicate measures performed by the central analytical laboratory. Estimated standard deviations were similar to those previously reported. (Author 's abstract)

  3. Speed of synchronization in complex networks of neural oscillators: analytic results based on Random Matrix Theory.

    PubMed

    Timme, Marc; Geisel, Theo; Wolf, Fred

    2006-03-01

    We analyze the dynamics of networks of spiking neural oscillators. First, we present an exact linear stability theory of the synchronous state for networks of arbitrary connectivity. For general neuron rise functions, stability is determined by multiple operators, for which standard analysis is not suitable. We describe a general nonstandard solution to the multioperator problem. Subsequently, we derive a class of neuronal rise functions for which all stability operators become degenerate and standard eigenvalue analysis becomes a suitable tool. Interestingly, this class is found to consist of networks of leaky integrate-and-fire neurons. For random networks of inhibitory integrate-and-fire neurons, we then develop an analytical approach, based on the theory of random matrices, to precisely determine the eigenvalue distributions of the stability operators. This yields the asymptotic relaxation time for perturbations to the synchronous state which provides the characteristic time scale on which neurons can coordinate their activity in such networks. For networks with finite in-degree, i.e., finite number of presynaptic inputs per neuron, we find a speed limit to coordinating spiking activity. Even with arbitrarily strong interaction strengths neurons cannot synchronize faster than at a certain maximal speed determined by the typical in-degree.

  4. Leveraging Big-Data for Business Process Analytics

    ERIC Educational Resources Information Center

    Vera-Baquero, Alejandro; Colomo Palacios, Ricardo; Stantchev, Vladimir; Molloy, Owen

    2015-01-01

    Purpose: This paper aims to present a solution that enables organizations to monitor and analyse the performance of their business processes by means of Big Data technology. Business process improvement can drastically influence in the profit of corporations and helps them to remain viable. However, the use of traditional Business Intelligence…

  5. Classification of user interfaces for graph-based online analytical processing

    NASA Astrophysics Data System (ADS)

    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.

  6. Process models: analytical tools for managing industrial energy systems

    SciTech Connect

    Howe, S O; Pilati, D A; Balzer, C; Sparrow, F T

    1980-01-01

    How the process models developed at BNL are used to analyze industrial energy systems is described and illustrated. Following a brief overview of the industry modeling program, the general methodology of process modeling is discussed. The discussion highlights the important concepts, contents, inputs, and outputs of a typical process model. A model of the US pulp and paper industry is then discussed as a specific application of process modeling methodology. Applications addressed with the case study results include projections of energy demand, conservation technology assessment, energy-related tax policies, and sensitivity analysis. A subsequent discussion of these results supports the conclusion that industry process models are versatile and powerful tools for managing industrial energy systems.

  7. The Challenge of Understanding Process in Clinical Behavior Analysis: The Case of Functional Analytic Psychotherapy

    ERIC Educational Resources Information Center

    Follette, William C.; Bonow, Jordan T.

    2009-01-01

    Whether explicitly acknowledged or not, behavior-analytic principles are at the heart of most, if not all, empirically supported therapies. However, the change process in psychotherapy is only now being rigorously studied. Functional analytic psychotherapy (FAP; Kohlenberg & Tsai, 1991; Tsai et al., 2009) explicitly identifies behavioral-change…

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

    ERIC Educational Resources Information Center

    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…

  9. A European Network of Analytical and Experimental Laboratories for Geosciences: Challenges and Perspectives

    NASA Astrophysics Data System (ADS)

    Freda, C.; Funiciello, F.; Meredith, P.; Sagnotti, L.; Scarlato, P.; Troll, V. R.; Willingshofer, E.; EPOS-WG6

    2012-04-01

    The EU policy for scientific research in the third millennium is that of a coordinated approach to support and develop continent-scale research infrastructures. The vision is to integrate the existing research infrastructures in order to increase the accessibility and usability of multidisciplinary data, enhancing worldwide interoperability by establishing a leading integrated European infrastructure and services. Integrating Earth Sciences infrastructures in Europe is the mission of the European Plate Observing System (EPOS), a research infrastructure and e-science for data and observatories on earthquakes, volcanoes, surface dynamics and tectonics. Within the existing core elements to be integrated in the EPOS cyber-infrastructure are: geographical distributed observational infrastructures (seismic and geodetic networks), observatories for multidisciplinary local data acquisition (e.g., volcanoes, active fault-zone, geothermal and deep drilling experiments), and analytical facilities for data repositories and integration. The integration of European analytical, experimental, and analogue laboratories plays a key role in this context and is the task of EPOS Working Group 6 (WG6). The Analytical and Experimental LaboratoriesGroup thus aims to link experimental, analytical, and analogue laboratories into a single, but geographically distributed, infrastructure for rock physics, including palaeomagnetism, analytical and experimental petrology and volcanology, and tectonic modeling.The WG6 has set a short term goal that has now been achieved, being a review of operational laboratory facilities in the community and the creation of a database from that information. Currently 12 countries (Germany, Greece, Ireland, Italy, Portugal, Romania, Slovenia, Spain, Sweden, Switzerland, The Netherlands, United Kingdom) are included in the database. As long-term goals, the WG6 aims to create mechanisms and procedures for easy access to laboratory facilities, turning small

  10. Rapid process development of chromatographic process using direct analysis in real time mass spectrometry as a process analytical technology tool.

    PubMed

    Yan, Binjun; Chen, Teng; Xu, Zhilin; Qu, Haibin

    2014-06-01

    The concept of quality by design (QbD) is widely applied in the process development of pharmaceuticals. However, the additional cost and time have caused some resistance about QbD implementation. To show a possible solution, this work proposed a rapid process development method, which used direct analysis in real time mass spectrometry (DART-MS) as a process analytical technology (PAT) tool for studying the chromatographic process of Ginkgo biloba L., as an example. The breakthrough curves were fast determined by DART-MS at-line. A high correlation coefficient of 0.9520 was found between the concentrations of ginkgolide A determined by DART-MS and HPLC. Based on the PAT tool, the impacts of process parameters on the adsorption capacity were discovered rapidly, which showed a decreased adsorption capacity with the increase of the flow rate. This work has shown the feasibility and advantages of integrating PAT into QbD implementation for rapid process development.

  11. Formic Acid: Development of an Analytical Method and Use as Process Indicator in Anaerobic Systems

    DTIC Science & Technology

    1992-03-01

    I AD-A250 668 D0 ,I I I 111 Wl’i ill EDT|CS ELECTE MAY 27 1992 I C I FORMIC ACID: DEVELCPMENT OF AN ANALYTICAL METHOD AND USE AS A PROCESS INDICATOR...ANALYTICAL METHOD AND USE AS A PROCESS INDICATOR IN ANAEROBIC SYSTEMS A Special Research Problem Report Presented to the Faculty of the Division of...DEVELOPMENT-OF AN ANALYTICAL-METHOD ANDA USE AS A PROCESS INDICATOR IN ANAEROBIC-SYSTEMS by Sharon L. Perkins APPROVED: rr*W.f-.s, Adviso Dr. JWf . sord

  12. Tensegrity II. How structural networks influence cellular information processing networks

    NASA Technical Reports Server (NTRS)

    Ingber, Donald E.

    2003-01-01

    The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

  13. Exploratory Visual Analytics of a Dynamically Built Network of Nodes in a WebGL-Enabled Browser

    DTIC Science & Technology

    2014-01-01

    Exploratory Visual Analytics of a Dynamically Built Network of Nodes in a WebGL -Enabled Browser by Andrew M. Neiderer ARL-MR-860 January...January 2014 Exploratory Visual Analytics of a Dynamically Built Network of Nodes in a WebGL -Enabled Browser Andrew M. Neiderer...of Nodes in a WebGL -Enabled Browser 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Andrew M. Neiderer 5d

  14. An analytical approach to customer requirement information processing

    NASA Astrophysics Data System (ADS)

    Zhou, Zude; Xiao, Zheng; Liu, Quan; Ai, Qingsong

    2013-11-01

    'Customer requirements' (CRs) management is a key component of customer relationship management (CRM). By processing customer-focused information, CRs management plays an important role in enterprise systems (ESs). Although two main CRs analysis methods, quality function deployment (QFD) and Kano model, have been applied to many fields by many enterprises in the past several decades, the limitations such as complex processes and operations make them unsuitable for online businesses among small- and medium-sized enterprises (SMEs). Currently, most SMEs do not have the resources to implement QFD or Kano model. In this article, we propose a method named customer requirement information (CRI), which provides a simpler and easier way for SMEs to run CRs analysis. The proposed method analyses CRs from the perspective of information and applies mathematical methods to the analysis process. A detailed description of CRI's acquisition, classification and processing is provided.

  15. Analytical calculation of adiabatic processes in real gases

    NASA Astrophysics Data System (ADS)

    Amarskaja, I. B.; Belousov, V. S.; Filippov, P. S.

    2016-10-01

    The impact of gases nonideality in the compression and expansion processes on the specific heat ratio and the heat capacity is analyzed. The specific heat ratio variation leads to temperature variation during compression in the compressor and expansion in the turbine and, consequently, the gas turbine cycle efficiency factor variation. It is also essential to consider the gases nonideality in the compression and expansion processes in the compression processes in compressor. Generally it is assumed during calculations that the heat capacities depend only on temperature, in this case the reference data presented by various authors differs markedly. In the real processes the heat capacity and the specific heat ratio depend on temperature and within the particular temperatures and pressures range depend on pressure. Consequently, the operating fluid nonideality in the gas turbine cycle should be considered.

  16. Analytical model of large data transactions in CoAP networks.

    PubMed

    Ludovici, Alessandro; Di Marco, Piergiuseppe; Calveras, Anna; Johansson, Karl H

    2014-08-22

    We propose a novel analytical model to study fragmentation methods in wireless sensor networks adopting the Constrained Application Protocol (CoAP) and the IEEE 802.15.4 standard for medium access control (MAC). The blockwise transfer technique proposed in CoAP and the 6LoWPAN fragmentation are included in the analysis. The two techniques are compared in terms of reliability and delay, depending on the traffic, the number of nodes and the parameters of the IEEE 802.15.4 MAC. The results are validated trough Monte Carlo simulations. To the best of our knowledge this is the first study that evaluates and compares analytically the performance of CoAP blockwise transfer and 6LoWPAN fragmentation. A major contribution is the possibility to understand the behavior of both techniques with different network conditions. Our results show that 6LoWPAN fragmentation is preferable for delay-constrained applications. For highly congested networks, the blockwise transfer slightly outperforms 6LoWPAN fragmentation in terms of reliability.

  17. Analytical Model of Large Data Transactions in CoAP Networks

    PubMed Central

    Ludovici, Alessandro; Di Marco, Piergiuseppe; Calveras, Anna; Johansson, Karl H.

    2014-01-01

    We propose a novel analytical model to study fragmentation methods in wireless sensor networks adopting the Constrained Application Protocol (CoAP) and the IEEE 802.15.4 standard for medium access control (MAC). The blockwise transfer technique proposed in CoAP and the 6LoWPAN fragmentation are included in the analysis. The two techniques are compared in terms of reliability and delay, depending on the traffic, the number of nodes and the parameters of the IEEE 802.15.4 MAC. The results are validated trough Monte Carlo simulations. To the best of our knowledge this is the first study that evaluates and compares analytically the performance of CoAP blockwise transfer and 6LoWPAN fragmentation. A major contribution is the possibility to understand the behavior of both techniques with different network conditions. Our results show that 6LoWPAN fragmentation is preferable for delay-constrained applications. For highly congested networks, the blockwise transfer slightly outperforms 6LoWPAN fragmentation in terms of reliability. PMID:25153143

  18. Materials, Processes, and Environmental Engineering Network

    NASA Technical Reports Server (NTRS)

    White, Margo M.

    1993-01-01

    Attention is given to the Materials, Processes, and Environmental Engineering Network (MPEEN), which was developed as a central holding facility for materials testing information generated by the Materials and Processes Laboratory of NASA-Marshall. 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. The data base is 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. The data base also contains the usage and performance characteristics of these materials.

  19. Error processing network dynamics in schizophrenia.

    PubMed

    Becerril, Karla E; Repovs, Grega; Barch, Deanna M

    2011-01-15

    Current theories of cognitive dysfunction in schizophrenia emphasize an impairment in the ability of individuals suffering from this disorder to monitor their own performance, and adjust their behavior to changing demands. Detecting an error in performance is a critical component of evaluative functions that allow the flexible adjustment of behavior to optimize outcomes. The dorsal anterior cingulate cortex (dACC) has been repeatedly implicated in error-detection and implementation of error-based behavioral adjustments. However, accurate error-detection and subsequent behavioral adjustments are unlikely to rely on a single brain region. Recent research demonstrates that regions in the anterior insula, inferior parietal lobule, anterior prefrontal cortex, thalamus, and cerebellum also show robust error-related activity, and integrate into a functional network. Despite the relevance of examining brain activity related to the processing of error information and supporting behavioral adjustments in terms of a distributed network, the contribution of regions outside the dACC to error processing remains poorly understood. To address this question, we used functional magnetic resonance imaging to examine error-related responses in 37 individuals with schizophrenia and 32 healthy controls in regions identified in the basic science literature as being involved in error processing, and determined whether their activity was related to behavioral adjustments. Our imaging results support previous findings showing that regions outside the dACC are sensitive to error commission, and demonstrated that abnormalities in brain responses to errors among individuals with schizophrenia extend beyond the dACC to almost all of the regions involved in error-related processing in controls. However, error related responses in the dACC were most predictive of behavioral adjustments in both groups. Moreover, the integration of this network of regions differed between groups, with the

  20. Analytical control of process impurities in Pazopanib hydrochloride by impurity fate mapping.

    PubMed

    Li, Yan; Liu, David Q; Yang, Shawn; Sudini, Ravinder; McGuire, Michael A; Bhanushali, Dharmesh S; Kord, Alireza S

    2010-08-01

    Understanding the origin and fate of organic impurities within the manufacturing process along with a good control strategy is an integral part of the quality control of drug substance. Following the underlying principles of quality by design (QbD), a systematic approach to analytical control of process impurities by impurity fate mapping (IFM) has been developed and applied to the investigation and control of impurities in the manufacturing process of Pazopanib hydrochloride, an anticancer drug approved recently by the U.S. FDA. This approach requires an aggressive chemical and analytical search for potential impurities in the starting materials, intermediates and drug substance, and experimental studies to track their fate through the manufacturing process in order to understand the process capability for rejecting such impurities. Comprehensive IFM can provide elements of control strategies for impurities. This paper highlights the critical roles that analytical sciences play in the IFM process and impurity control. The application of various analytical techniques (HPLC, LC-MS, NMR, etc.) and development of sensitive and selective methods for impurity detection, identification, separation and quantification are highlighted with illustrative examples. As an essential part of the entire control strategy for Pazopanib hydrochloride, analytical control of impurities with 'meaningful' specifications and the 'right' analytical methods is addressed. In particular, IFM provides scientific justification that can allow for control of process impurities up-stream at the starting materials or intermediates whenever possible.

  1. Feedback neural networks for ARTIST ionogram processing

    NASA Astrophysics Data System (ADS)

    Galkin, Ivan A.; Reinisch, Bodo W.; Ososkov, Gennadii A.; Zaznobina, Elena G.; Neshyba, Steven P.

    1996-09-01

    Modern pattern recognition techniques are applied to achieve high quality automatic processing of Digisonde ionograms. An artificial neural network (ANN) was found to be a promising technique for ionospheric echo tracing. A modified rotor model was tested to construct the Hopfield ANN with the mean field theory updating scheme. Tests of the models against various ionospheric data showed that the modified rotor model gives good results where conventional tracing techniques have difficulties. Use of the ANN made it possible to implement a robust scheme of trace interpretation that considers local trace inclination angles available after ANN completes tracing. The interpretation scheme features a new algorithm for ƒ0F1 identification that estimates an α angle for the trace segments in the vicinity of the critical frequency ƒ0F1. First results from off-line tests suggest the potential of implementing new operational autoscaling software in the worldwide Digisonde network.

  2. Application of System Capabilities Analytic Process (SCAP) to Battlefield Obscurants

    DTIC Science & Technology

    2012-08-01

    given of how SCAP’s transient effects can map into Mission and Means Framework ( MMF ) analysis, to allow application in simulations or system evaluation...at higher levels. 15. SUBJECT TERMS SCAP, MMF , MBTE, functional skeleton, smoke, obscurant, modeling 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...Subsystem 15 5.2.3 Blue Obscurant Subsystem 16 5.3 FS Relations for Red and Blue 17 5.4 SCAP Relation to MMF Process Sequence 17 6. Conclusions

  3. Launch Vehicle/Carrier Interaction, Improving the Analytical Integration Process

    NASA Technical Reports Server (NTRS)

    Shariett, Charles A.; McClendon, Randy (Technical Monitor)

    2002-01-01

    A goal of the aerospace industry is to reduce the cost of space transportation by a significant within the next decade. The present cost of launching a space transportation system which includes propulsion system, vehicle, carrier, and payload integrated together to form a system, encompasses much more than the design of the propulsion system and vehicle. The total cost includes the recurring cost of the process of integrating carriers, and payloads into the vehicle for each flight. The recurring cost of the integration of carrier/payloads systems is driven by the interaction of the vehicle. If the interaction can be well characterized and made to be very predictable for a range of payloads, or if it can be minimized then the cost of integrating a payload can be reduced significantly from today's levels. The Space Shuttle is very interactive with the payload. The interaction has been well characterized through finite element modeling and is reasonably predictable for a specific payload. Experience has shown, however, that the interaction is very manifest dependent, and small changes in one portion of a payload complement can change the interaction significantly in another portion. That is the affects of one on the other are such that if one or the other is changed slightly the environment at the interfaces can change significantly. To date the Shuttle has made in excess of one hundred flights. For each of these flights several iterations of dynamic analyses have been required in the development of each vehicle/carrier/payload system. The iterative analyses are needed because of the sensitivity of the interaction of the launch vehicle to the attached carrier/payload. The Multi Purpose Logistics Module (MPLM) is a carrier designed for flight in the Space Shuttle carrying a wide variation of cargo, supplies, and experiments to and from Space Station. Its integration process provides a unique area for improvement in the template in use today for transporting items to

  4. Materials, processes, and environmental engineering network

    NASA Technical Reports Server (NTRS)

    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.

  5. A comprehensive Network Security Risk Model for process control networks.

    PubMed

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  6. Holistic and Analytic Processing Modes in Non-Native Learners' Performance of Narrative Tasks

    ERIC Educational Resources Information Center

    Ben Maad, Mohamed Ridha

    2010-01-01

    Cognitive psychology has gained currency in the study of second language learning with focus on how real-time language use proceeds through two main processing modes: an analytic processing (rule-based) mode and a holistic processing (lexically-based) mode (Skehan, 1998). However, to date there has been little experimental evidence to document the…

  7. Network scaling effects in graph analytic studies of human resting-state FMRI data.

    PubMed

    Fornito, Alex; Zalesky, Andrew; Bullmore, Edward T

    2010-01-01

    Graph analysis has become an increasingly popular tool for characterizing topological properties of brain connectivity networks. Within this approach, the brain is modeled as a graph comprising N nodes connected by M edges. In functional magnetic resonance imaging (fMRI) studies, the nodes typically represent brain regions and the edges some measure of interaction between them. These nodes are commonly defined using a variety of regional parcellation templates, which can vary both in the volume sampled by each region, and the number of regions parcellated. Here, we sought to investigate how such variations in parcellation templates affect key graph analytic measures of functional brain organization using resting-state fMRI in 30 healthy volunteers. Seven different parcellation resolutions (84, 91, 230, 438, 890, 1314, and 4320 regions) were investigated. We found that gross inferences regarding network topology, such as whether the brain is small-world or scale-free, were robust to the template used, but that both absolute values of, and individual differences in, specific parameters such as path length, clustering, small-worldness, and degree distribution descriptors varied considerably across the resolutions studied. These findings underscore the need to consider the effect that a specific parcellation approach has on graph analytic findings in human fMRI studies, and indicate that results obtained using different templates may not be directly comparable.

  8. Testing and Analytical Modeling for Purging Process of a Cryogenic Line

    NASA Technical Reports Server (NTRS)

    Hedayat, A.; Mazurkivich, P. V.; Nelson, M. A.; Majumdar, A. K.

    2013-01-01

    The purging operations for cryogenic main propulsion systems of upper stage are usually carried out for the following cases: 1) Purging of the Fill/Drain line after completion of propellant loading. This operation allows the removal of residual propellant mass; and 2) Purging of the Feed/Drain line if the mission is scrubbed. The lines would be purged by connections to a ground high-pressure gas storage source. The flowrate of purge gas should be regulated such that the pressure in the line will not exceed the required maximum allowable value. Exceeding the maximum allowable pressure may lead to structural damage in the line. To gain confidence in analytical models of the purge process, a test series was conducted. The test article, a 20-cm incline line, was filled with liquid hydrogen and then purged with gaseous helium (GHe). The influences of GHe flowrates and initial temperatures were evaluated. The Generalized Fluid System Simulation Program, an in-house general-purpose computer program for flow network analysis, was utilized to model and simulate the testing. The test procedures, modeling descriptions, and the results will be presented in the final paper.

  9. Testing and Analytical Modeling for Purging Process of a Cryogenic Line

    NASA Technical Reports Server (NTRS)

    Hedayat, A.; Mazurkivich, P. V.; Nelson, M. A.; Majumdar, A. K.

    2015-01-01

    The purging operations for cryogenic main propulsion systems of upper stage are usually carried out for the following cases: 1) Purging of the Fill/Drain line after completion of propellant loading. This operation allows the removal of residual propellant mass; and 2) Purging of the Feed/Drain line if the mission is scrubbed. The lines would be purged by connections to a ground high-pressure gas storage source. The flow-rate of purge gas should be regulated such that the pressure in the line will not exceed the required maximum allowable value. Exceeding the maximum allowable pressure may lead to structural damage in the line. To gain confidence in analytical models of the purge process, a test series was conducted. The test article, a 20-cm incline line, was filled with liquid hydrogen and then purged with gaseous helium (GHe). The influences of GHe flow-rates and initial temperatures were evaluated. The Generalized Fluid System Simulation Program, an in-house general-purpose computer program for flow network analysis, was utilized to model and simulate the testing. The test procedures, modeling descriptions, and the results will be presented in the final paper.

  10. Neural network training as a dissipative process.

    PubMed

    Gori, Marco; Maggini, Marco; Rossi, Alessandro

    2016-09-01

    This paper analyzes the practical issues and reports some results on a theory in which learning is modeled as a continuous temporal process driven by laws describing the interactions of intelligent agents with their own environment. The classic regularization framework is paired with the idea of temporal manifolds by introducing the principle of least cognitive action, which is inspired by the related principle of mechanics. The introduction of the counterparts of the kinetic and potential energy leads to an interpretation of learning as a dissipative process. As an example, we apply the theory to supervised learning in neural networks and show that the corresponding Euler-Lagrange differential equations can be connected to the classic gradient descent algorithm on the supervised pairs. We give preliminary experiments to confirm the soundness of the theory.

  11. CIPP: a versatile analytical model for VBR traffic in ATM networks

    NASA Astrophysics Data System (ADS)

    Manivasakan, R.; Desai, U. B.; Karandikar, Abhay

    1999-08-01

    Correlated Interarrival time Process (CIPP) has been proposed, for modeling both the composite arrival process of packets in broadband networks and the individual source modeling. The CIPP--a generalization of the Poisson process- - is a stationary counting process and is parameterized by a correlation parameter `p' which represents the degree of correlation in adjacent interarrivals in addition to `(lambda) ' the intensity of the process. In this paper, we present the performance modeling of VBR video traffic in ATM networks, using CIPP/M/1 queue. We first give the expressions for stationary distributions for CIPP/M/1 queue. The, we derive the queuing measures of interest. We simulate a queue with smoothed VBR video trace data as input (with exponential services) to compare with the theoretical measures derived above. Experimental results show that the CIPP/M/1 queue, models well with ATM multiplexer performance with the real world VBR video traffic input.

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

    PubMed

    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.

  13. School-based friendship networks and children's physical activity: A spatial analytical approach.

    PubMed

    Macdonald-Wallis, Kyle; Jago, Russell; Page, Angie S; Brockman, Rowan; Thompson, Janice L

    2011-07-01

    Despite the known health benefits, the majority of children do not meet physical activity guidelines, with past interventions to increase physical activity yielding little success. Social and friendship networks have been shown to influence obesity, smoking and academic achievement, and peer-led interventions have successfully reduced the uptake of adolescent smoking. However, the role of social networks on physical activity is not clear. This paper investigates the extent to which friendship networks influence children's physical activity, and attempts to quantify the association using spatial analytical techniques to account for the social influence. Physical activity data were collected for 986 children, aged 10-11 years old, from 40 schools in Bristol, UK. Data from 559 children were used for analysis. Mean accelerometer counts per minute (CPM) and mean minutes of moderate to vigorous physical activity per day (MVPA) were calculated as objective measures of physical activity. Children nominated up to 4 school-friends, and school-based friendship networks were constructed from these nominations. Networks were tested to assess whether physical activity showed spatial dependence (in terms of social proximity in social space) using Moran's I statistic. Spatial autoregressive modelling was then used to assess the extent of spatial dependence, whilst controlling for other known predictors of physical activity. This model was compared with linear regression models for improvement in goodness-of-fit. Results indicated spatial autocorrelation of both mean MVPA (I = .346) and mean CPM (I = .284) in the data, indicating that children clustered in friendship groups with similar activity levels. Spatial autoregressive modelling of mean MVPA concurred that spatial dependence was present (ρ = .26, p < .001), and improved model fit by 31% on the linear regression model. These results demonstrate an association between physical activity levels of children and their

  14. Analytical Model for Chip Formation in Case of Orthogonal Machining Process

    NASA Astrophysics Data System (ADS)

    Salvatore, Ferdinando; Mabrouki, Tarek; Hamdi, Hédi

    2011-01-01

    The present work deals with the presentation of analytical methodology allowing the modelling of chip formation. For that a "decomposition approach", based on assuming that the material removal is the summation of two contributions: ploughing and pure cut was adopted. Moreover, this analytical model was calibrated by a finite element model and experimental data in terms of temperature and forces evolutions. The global aim is to propose to the industrial community, an efficient rapid-execution analytical model concerning the material removal in the case of an orthogonal cutting process.

  15. Downstream processing and chromatography based analytical methods for production of vaccines, gene therapy vectors, and bacteriophages

    PubMed Central

    Kramberger, Petra; Urbas, Lidija; Štrancar, Aleš

    2015-01-01

    Downstream processing of nanoplexes (viruses, virus-like particles, bacteriophages) is characterized by complexity of the starting material, number of purification methods to choose from, regulations that are setting the frame for the final product and analytical methods for upstream and downstream monitoring. This review gives an overview on the nanoplex downstream challenges and chromatography based analytical methods for efficient monitoring of the nanoplex production. PMID:25751122

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

    NASA Astrophysics Data System (ADS)

    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).

  17. AERIAL SHOWING COMPLETED REMOTE ANALYTICAL FACILITY (CPP627) ADJOINING FUEL PROCESSING ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    AERIAL SHOWING COMPLETED REMOTE ANALYTICAL FACILITY (CPP-627) ADJOINING FUEL PROCESSING BUILDING AND EXCAVATION FOR HOT PILOT PLANT TO RIGHT (CPP-640). INL PHOTO NUMBER NRTS-60-1221. J. Anderson, Photographer, 3/22/1960 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

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

    PubMed

    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.

  19. Nonlinear neural networks. II. Information processing

    NASA Astrophysics Data System (ADS)

    van Hemmen, J. L.; Grensing, D.; Huber, A.; Kühn, R.

    1988-01-01

    Information processing in nonlinear neural networks with a finite number q of stored patterns is studied. Each network is characterized completely by its synaptic kernel Q. At low temperatures, the nonlinearity typically results in 2q-2- q metastable, pure states in addition to the q retrieval states that are associated with the q stored patterns. These spurious states start appearing at a temperaturetilde T_q , which depends on q. We give sufficient conditions to guarantee that the retrieval states bifurcate first at a critical temperature T c and thattilde T_q / T c → 0 as q→∞. Hence, there is a large temperature range where only the retrieval states and certain symmetric mixtures thereof exist. The latter are unstable, as they appear at T c . For clipped synapses, the bifurcation and stability structure is analyzed in detail and shown to approach that of the (linear) Hopfield model as q→∞. We also investigate memories that forget and indicate how forgetfulness can be explained in terms of the eigenvalue spectrum of the synaptic kernel Q.

  20. Space-Time Processing for Tactical Mobile Ad Hoc Networks

    DTIC Science & Technology

    2008-08-01

    Maximization in Multi-User, MIMO Channels with Linear Processing...58 2.9 Using Feedback in Ad Hoc Networks....................................................................65 2.10 Feedback MIMO ...in MIMO Ad Hoc Interference Networks.......................................................................................................75 2.12

  1. Technical and analytical support to the ARPA Artificial Neural Network Technology Program

    SciTech Connect

    1995-09-16

    Strategic Analysis (SA) has provided ongoing work for the Advanced Research Projects Agency (ARPA) Artificial Neural Network (ANN) technology program. This effort provides technical and analytical support to the ARPA ANN technology program in support of the following information areas of interest: (1) Alternative approaches for application of ANN technology, hardware approaches that utilize the inherent massive parallelism of ANN technology, and novel ANN theory and modeling analyses. (2) Promising military applications for ANN technology. (3) Measures to use in judging success of ANN technology research and development. (4) Alternative strategies for ARPA involvement in ANN technology R&D. These objectives were accomplished through the development of novel information management tools, strong SA knowledge base, and effective communication with contractors, agents, and other program participants. These goals have been realized. Through enhanced tracking and coordination of research, the ANN program is healthy and recharged for future technological breakthroughs.

  2. Faith (F) and presence moment (O) in analytic processes: an example of a narcissistic disorder.

    PubMed

    Nissen, Bernd

    2015-10-01

    Based on Freud's remark that a neurosis can not be slain in absentia, the thesis is established that presence moments constitute the central points in the analytic process. The interpenetrative dynamics between analyst and analysand creates an analytical field, in which a pre-conception is formed. This pre-conception meets the self-revealing psychic world of the patient. This realization is a moment of presence (O) and the analytic third is determined. In this moment, the presence of psychic reality is irrefutable present and can be called by name. The name, which is seen as a presentational symbol, is a creation of the analytic couple, but has its source in the genetic roots of the patient. The presentational arises from the presence, which can then become the representation. F is central in this process and is part of the analytic couple. Based on detailed case material of a narcissistic disorder it is shown that a dynamic that impresses at first narcissistic, can be understood from a different point of view as a struggle for the analytical attitude and belief (F).

  3. Residential Saudi load forecasting using analytical model and Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Al-Harbi, Ahmad Abdulaziz

    In recent years, load forecasting has become one of the main fields of study and research. Short Term Load Forecasting (STLF) is an important part of electrical power system operation and planning. This work investigates the applicability of different approaches; Artificial Neural Networks (ANNs) and hybrid analytical models to forecast residential load in Kingdom of Saudi Arabia (KSA). These two techniques are based on model human modes behavior formulation. These human modes represent social, religious, official occasions and environmental parameters impact. The analysis is carried out on residential areas for three regions in two countries exposed to distinct people activities and weather conditions. The collected data are for Al-Khubar and Yanbu industrial city in KSA, in addition to Seattle, USA to show the validity of the proposed models applied on residential load. For each region, two models are proposed. First model is next hour load forecasting while second model is next day load forecasting. Both models are analyzed using the two techniques. The obtained results for ANN next hour models yield very accurate results for all areas while relatively reasonable results are achieved when using hybrid analytical model. For next day load forecasting, the two approaches yield satisfactory results. Comparative studies were conducted to prove the effectiveness of the models proposed.

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

    SciTech Connect

    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.

  5. Comparison of the Analytic Hierarchy Process and Incomplete Analytic Hierarchy Process for identifying customer preferences in the Texas retail energy provider market

    NASA Astrophysics Data System (ADS)

    Davis, Christopher

    The competitive market for retail energy providers in Texas has been in existence for 10 years. When the market opened in 2002, 5 energy providers existed, offering, on average, 20 residential product plans in total. As of January 2012, there are now 115 energy providers in Texas offering over 300 residential product plans for customers. With the increase in providers and product plans, customers can be bombarded with information and suffer from the "too much choice" effect. The goal of this praxis is to aid customers in the decision making process of identifying an energy provider and product plan. Using the Analytic Hierarchy Process (AHP), a hierarchical decomposition decision making tool, and the Incomplete Analytic Hierarchy Process (IAHP), a modified version of AHP, customers can prioritize criteria such as price, rate type, customer service, and green energy products to identify the provider and plan that best meets their needs. To gather customer data, a survey tool has been developed for customers to complete the pairwise comparison process. Results are compared for the Incomplete AHP and AHP method to determine if the Incomplete AHP method is just as accurate, but more efficient, than the traditional AHP method.

  6. A comparative analytical assay of gene regulatory networks inferred using microarray and RNA-seq datasets

    PubMed Central

    Izadi, Fereshteh; Zarrini, Hamid Najafi; Kiani, Ghaffar; Jelodar, Nadali Babaeian

    2016-01-01

    A Gene Regulatory Network (GRN) is a collection of interactions between molecular regulators and their targets in cells governing gene expression level. Omics data explosion generated from high-throughput genomic assays such as microarray and RNA-Seq technologies and the emergence of a number of pre-processing methods demands suitable guidelines to determine the impact of transcript data platforms and normalization procedures on describing associations in GRNs. In this study exploiting publically available microarray and RNA-Seq datasets and a gold standard of transcriptional interactions in Arabidopsis, we performed a comparison between six GRNs derived by RNA-Seq and microarray data and different normalization procedures. As a result we observed that compared algorithms were highly data-specific and Networks reconstructed by RNA-Seq data revealed a considerable accuracy against corresponding networks captured by microarrays. Topological analysis showed that GRNs inferred from two platforms were similar in several of topological features although we observed more connectivity in RNA-Seq derived genes network. Taken together transcriptional regulatory networks obtained by Robust Multiarray Averaging (RMA) and Variance-Stabilizing Transformed (VST) normalized data demonstrated predicting higher rate of true edges over the rest of methods used in this comparison. PMID:28293077

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

    PubMed

    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.

  8. Knowledge spillover processes as complex networks

    NASA Astrophysics Data System (ADS)

    Konno, Tomohiko

    2016-11-01

    We introduce the model of knowledge spillover on networks. Knowledge spillover is a major source of economic growth; and is a representative externality in economic phenomena. We show that the model has the following four characteristics: (1) the long-run growth rate is not relevant to the mean degree, but is determined by the mean degree of the nearest neighbors; (2) the productivity level of a firm is proportional to the degree of the firm; (3) the long-run growth rate increases with the increasing heterogeneity of the network; and (4) of three representative networks, the largest growth rate is in scale-free networks and the least in regular networks.

  9. A uniform method for analytically modeling mulit-target acquisition with independent networked imaging sensors

    NASA Astrophysics Data System (ADS)

    Friedman, Melvin

    2014-05-01

    The problem solved in this paper is easily stated: for a scenario with 𝑛 networked and moving imaging sensors, 𝑚 moving targets and 𝑘 independent observers searching imagery produced by the 𝑛 moving sensors, analytically model system target acquisition probability for each target as a function of time. Information input into the model is the time dependence of 𝘗∞ and 𝜏, two parameters that describe observer-sensor-atmosphere-range-target properties of the target acquisition system for the case where neither the sensor nor target is moving. The parameter 𝘗∞ can be calculated by the NV-IPM model and 𝜏 is estimated empirically from 𝘗∞. In this model 𝑛, 𝑚 and 𝑘 are integers and 𝑘 can be less than, equal to or greater than 𝑛. Increasing 𝑛 and 𝑘 results in a substantial increase in target acquisition probabilities. Because the sensors are networked, a target is said to be detected the moment the first of the 𝑘 observers declares the target. The model applies to time-limited or time-unlimited search, and applies to any imaging sensors operating in any wavelength band provided each sensor can be described by 𝘗∞ and 𝜏 parameters.

  10. Neural network classifier with analytic translation and scaling capabilities for optimal signal viewing

    SciTech Connect

    Vilim, R.B.; Wegerich, S.W.

    1995-12-31

    A neural network originally proposed by Szu for performing pattern recognition has been modified for use in a noisy manufacturing environment. Signals from the factory floor are frequently affine transformed and, as a consequence, a signal may not be properly aligned with respect to the input node that corresponds to the signal leading edge or with respect to the number of nodes representing the time varying part. Rater than translate and scale the presented signal, an operation which because of noise can be prone to numerical error since the signal is not smoothly varying, the network in this paper has the capability to analytically translate and scale its internal representation of the signal so that it overlays the presented signal. A response surface in the neighborhood of the stored reference signal is built during, training, and covers the range of translate and scale parameter values expected. A genetic algorithm is used to search over this hilly terrain to find the optimal values of these parameters so that the reference signal overlays the presented signal. The procedure is repeated over all hypothesized pattern classes with the best fit identifying the class.

  11. Lack of habituation of evoked visual potentials in analytic information processing style: evidence in healthy subjects.

    PubMed

    Buonfiglio, Marzia; Toscano, M; Puledda, F; Avanzini, G; Di Clemente, L; Di Sabato, F; Di Piero, V

    2015-03-01

    Habituation is considered one of the most basic mechanisms of learning. Habituation deficit to several sensory stimulations has been defined as a trait of migraine brain and also observed in other disorders. On the other hand, analytic information processing style is characterized by the habit of continually evaluating stimuli and it has been associated with migraine. We investigated a possible correlation between lack of habituation of evoked visual potentials and analytic cognitive style in healthy subjects. According to Sternberg-Wagner self-assessment inventory, 15 healthy volunteers (HV) with high analytic score and 15 HV with high global score were recruited. Both groups underwent visual evoked potentials recordings after psychological evaluation. We observed significant lack of habituation in analytical individuals compared to global group. In conclusion, a reduced habituation of visual evoked potentials has been observed in analytic subjects. Our results suggest that further research should be undertaken regarding the relationship between analytic cognitive style and lack of habituation in both physiological and pathophysiological conditions.

  12. Survey on Neural Networks Used for Medical Image Processing.

    PubMed

    Shi, Zhenghao; He, Lifeng; Suzuki, Kenji; Nakamura, Tsuyoshi; Itoh, Hidenori

    2009-02-01

    This paper aims to present a review of neural networks used in medical image processing. We classify neural networks by its processing goals and the nature of medical images. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of neural network application for medical image processing and an outlook for the future research are also discussed. By this survey, we try to answer the following two important questions: (1) What are the major applications of neural networks in medical image processing now and in the nearby future? (2) What are the major strengths and weakness of applying neural networks for solving medical image processing tasks? We believe that this would be very helpful researchers who are involved in medical image processing with neural network techniques.

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

    PubMed Central

    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. PMID:26973503

  14. A theoretical framework for understanding river networks: Connecting process, geometry and topology across many scales

    NASA Astrophysics Data System (ADS)

    Veitzer, Seth Andrew

    A new class of models with statistically self-similar network topology is proposed for the modeling of river networks. The network construction process exhibits both topological variability and scale invariance in a statistical sense. The network construction model allows for a derivation of generalized Horton laws in terms of simple scaling of probability distributions in the limit of large Strahler order, representing a reformulation of traditional Horton laws which are defined only in terms of averages. Properties of networks constructed by the random self-similar model are evaluated. An analytic algorithm is introduced which generates width functions, an important network property that connects network structure to hydrologic basin response, based on a new procedure called braided convolution in the deterministic limit. The braided convolution algorithm is a powerful tool, in that it can recursively generate both smooth and multifractal width functions, and may have wider applications in the fields of data analysis, turbulence, and signal processing. Tests are made to determine the possible multifractal nature of both simulated and real width functions. Increasing and decreasing trends inherent to width functions mask any underlying singularity structure, producing inconclusive results using the standard tools of multifractal analysis. Scaling properties of the maximum of the width function are calculated in terms of the braided convolution algorithm for deterministically generated networks, and by ensemble simulation for random networks. The scaling properties of the maximum of the width function compare favorably to real networks for a large variety of parameterizations, both for topological and psuedo-geometric width functions. In addition distributions of the maximum of the width function as indexed by Strahler order are shown to exhibit generalized Horton laws both in simulation and in data. This represents a fundamentally new way to think about the

  15. Analytical estimation of laser phase noise induced BER floor in coherent receiver with digital signal processing.

    PubMed

    Vanin, Evgeny; Jacobsen, Gunnar

    2010-03-01

    The Bit-Error-Ratio (BER) floor caused by the laser phase noise in the optical fiber communication system with differential quadrature phase shift keying (DQPSK) and coherent detection followed by digital signal processing (DSP) is analytically evaluated. An in-phase and quadrature (I&Q) receiver with a carrier phase recovery using DSP is considered. The carrier phase recovery is based on a phase estimation of a finite sum (block) of the signal samples raised to the power of four and the phase unwrapping at transitions between blocks. It is demonstrated that errors generated at block transitions cause the dominating contribution to the system BER floor when the impact of the additive noise is negligibly small in comparison with the effect of the laser phase noise. Even the BER floor in the case when the phase unwrapping is omitted is analytically derived and applied to emphasize the crucial importance of this signal processing operation. The analytical results are verified by full Monte Carlo simulations. The BER for another type of DQPSK receiver operation, which is based on differential phase detection, is also obtained in the analytical form using the principle of conditional probability. The principle of conditional probability is justified in the case of differential phase detection due to statistical independency of the laser phase noise induced signal phase error and the additive noise contributions. Based on the achieved analytical results the laser linewidth tolerance is calculated for different system cases.

  16. 75 FR 13766 - Food and Drug Administration and Process Analytical Technology for Pharma Manufacturing: Food and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-23

    ... HUMAN SERVICES Food and Drug Administration Food and Drug Administration and Process Analytical Technology for Pharma Manufacturing: Food and Drug Administration--Partnering With Industry; Public Conference AGENCY: Food and Drug Administration, HHS. ACTION: Notice of public conference. The Food and...

  17. Evaluating the Effectiveness of the Chemistry Education by Using the Analytic Hierarchy Process

    ERIC Educational Resources Information Center

    Yüksel, Mehmet

    2012-01-01

    In this study, an attempt was made to develop a method of measurement and evaluation aimed at overcoming the difficulties encountered in the determination of the effectiveness of chemistry education based on the goals of chemistry education. An Analytic Hierarchy Process (AHP), which is a multi-criteria decision technique, is used in the present…

  18. Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

    ERIC Educational Resources Information Center

    Zhang, Zhidong

    2016-01-01

    This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

  19. Analytical investigation of machining chatter by considering the nonlinearity of process damping

    NASA Astrophysics Data System (ADS)

    Ahmadi, Keivan

    2017-04-01

    In this paper, the well-established problem of self-excited vibrations in machining is revisited to include the nonlinearity of process damping at the tool and workpiece interface. Machining dynamics is modeled using a time-delayed system with nonlinear damping, and the method of averaging is used to obtain the amplitude of the resulting limit cycles. As a result, an analytical relationship is presented to establish the stability charts corresponding with arbitrary limit cycles in machining systems. The presented analytical solutions are verified using experiments and numerical solutions.

  20. Development of an Analytical Hierarchy Process (AHP) Model for Siting of Municipal Solid Waste Facilities

    DTIC Science & Technology

    1994-09-01

    of the model in Chapter 3. The Analytical Hierarchy Process (AHP), sometimes referred as a subset of the Multi-Attribute Utility Theory , will be...stated goods or objectives." (26:2-5) At the forefront of this concept 18 is Multi-attribute utility theory (MAUT). Ralph L. Keeney, sometimes regarded as...Process and Utility Theory . The two schools of thought have gone to great extent to prove and disprove each other.. .so much that the literature appear

  1. Fast radiative transfer of dust reprocessing in semi-analytic models with artificial neural networks

    NASA Astrophysics Data System (ADS)

    Silva, Laura; Fontanot, Fabio; Granato, Gian Luigi

    2012-06-01

    A serious concern for semi-analytical galaxy formation models, aiming to simulate multiwavelength surveys and to thoroughly explore the model parameter space, is the extremely time-consuming numerical solution of the radiative transfer of stellar radiation through dusty media. To overcome this problem, we have implemented an artificial neural network (ANN) algorithm in the radiative transfer code GRASIL, in order to significantly speed up the computation of the infrared (IR) spectral energy distribution (SED). The ANN we have implemented is of general use, in that its input neurons are defined as those quantities effectively determining the shape of the IR SED. Therefore, the training of the ANN can be performed with any model and then applied to other models. We made a blind test to check the algorithm, by applying a net trained with a standard chemical evolution model (i.e. CHE_EVO) to a mock catalogue extracted from the semi-analytic model MORGANA, and compared galaxy counts and evolution of the luminosity functions in several near-IR to sub-millimetre (sub-mm) bands, and also the spectral differences for a large subset of randomly extracted models. The ANN is able to excellently approximate the full computation, but with a gain in CPU time by ˜2 orders of magnitude. It is only advisable that the training covers reasonably well the range of values of the input neurons in the application. Indeed in the sub-mm at high redshift, a tiny fraction of models with some sensible input neurons out of the range of the trained net cause wrong answer by the ANN. These are extreme starbursting models with high optical depths, favourably selected by sub-mm observations, and are difficult to predict a priori.

  2. Information Processing in Social Insect Networks

    PubMed Central

    Waters, James S.; Fewell, Jennifer H.

    2012-01-01

    Investigating local-scale interactions within a network makes it possible to test hypotheses about the mechanisms of global network connectivity and to ask whether there are general rules underlying network function across systems. Here we use motif analysis to determine whether the interactions within social insect colonies resemble the patterns exhibited by other animal associations or if they exhibit characteristics of biological regulatory systems. Colonies exhibit a predominance of feed-forward interaction motifs, in contrast to the densely interconnected clique patterns that characterize human interaction and animal social networks. The regulatory motif signature supports the hypothesis that social insect colonies are shaped by selection for network patterns that integrate colony functionality at the group rather than individual level, and demonstrates the utility of this approach for analysis of selection effects on complex systems across biological levels of organization. PMID:22815740

  3. Reasoning about anomalies: a study of the analytical process of detecting and identifying anomalous behavior in maritime traffic data

    NASA Astrophysics Data System (ADS)

    Riveiro, Maria; Falkman, Göran; Ziemke, Tom; Kronhamn, Thomas

    2009-05-01

    The goal of visual analytical tools is to support the analytical reasoning process, maximizing human perceptual, understanding and reasoning capabilities in complex and dynamic situations. Visual analytics software must be built upon an understanding of the reasoning process, since it must provide appropriate interactions that allow a true discourse with the information. In order to deepen our understanding of the human analytical process and guide developers in the creation of more efficient anomaly detection systems, this paper investigates how is the human analytical process of detecting and identifying anomalous behavior in maritime traffic data. The main focus of this work is to capture the entire analysis process that an analyst goes through, from the raw data to the detection and identification of anomalous behavior. Three different sources are used in this study: a literature survey of the science of analytical reasoning, requirements specified by experts from organizations with interest in port security and user field studies conducted in different marine surveillance control centers. Furthermore, this study elaborates on how to support the human analytical process using data mining, visualization and interaction methods. The contribution of this paper is twofold: (1) within visual analytics, contribute to the science of analytical reasoning with practical understanding of users tasks in order to develop a taxonomy of interactions that support the analytical reasoning process and (2) within anomaly detection, facilitate the design of future anomaly detector systems when fully automatic approaches are not viable and human participation is needed.

  4. A semi-analytical model for the flow behavior of naturally fractured formations with multi-scale fracture networks

    NASA Astrophysics Data System (ADS)

    Jia, Pin; Cheng, Linsong; Huang, Shijun; Wu, Yonghui

    2016-06-01

    This paper presents a semi-analytical model for the flow behavior of naturally fractured formations with multi-scale fracture networks. The model dynamically couples an analytical dual-porosity model with a numerical discrete fracture model. The small-scale fractures with the matrix are idealized as a dual-porosity continuum and an analytical flow solution is derived based on source functions in Laplace domain. The large-scale fractures are represented explicitly as the major fluid conduits and the flow is numerically modeled, also in Laplace domain. This approach allows us to include finer details of the fracture network characteristics while keeping the computational work manageable. For example, the large-scale fracture network may have complex geometry and varying conductivity, and the computations can be done at predetermined, discrete times, without any grids in the dual-porosity continuum. The validation of the semi-analytical model is demonstrated in comparison to the solution of ECLIPSE reservoir simulator. The simulation is fast, gridless and enables rapid model setup. On the basis of the model, we provide detailed analysis of the flow behavior of a horizontal production well in fractured reservoir with multi-scale fracture networks. The study has shown that the system may exhibit six flow regimes: large-scale fracture network linear flow, bilinear flow, small-scale fracture network linear flow, pseudosteady-state flow, interporosity flow and pseudoradial flow. During the first four flow periods, the large-scale fracture network behaves as if it only drains in the small-scale fracture network; that is, the effect of the matrix is negligibly small. The characteristics of the bilinear flow and the small-scale fracture network linear flow are predominantly determined by the dimensionless large-scale fracture conductivity. And low dimensionless fracture conductivity will generate large pressure drops in the large-scale fractures surrounding the wellbore. With

  5. Network Traffic Analysis With Query Driven VisualizationSC 2005HPC Analytics Results

    SciTech Connect

    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.

  6. Analytical Solutions for Rumor Spreading Dynamical Model in a Social Network

    NASA Astrophysics Data System (ADS)

    Fallahpour, R.; Chakouvari, S.; Askari, H.

    2015-03-01

    In this paper, Laplace Adomian decomposition method is utilized for evaluating of spreading model of rumor. Firstly, a succinct review is constructed on the subject of using analytical methods such as Adomian decomposion method, Variational iteration method and Homotopy Analysis method for epidemic models and biomathematics. In continue a spreading model of rumor with consideration of forgetting mechanism is assumed and subsequently LADM is exerted for solving of it. By means of the aforementioned method, a general solution is achieved for this problem which can be readily employed for assessing of rumor model without exerting any computer program. In addition, obtained consequences for this problem are discussed for different cases and parameters. Furthermore, it is shown the method is so straightforward and fruitful for analyzing equations which have complicated terms same as rumor model. By employing numerical methods, it is revealed LADM is so powerful and accurate for eliciting solutions of this model. Eventually, it is concluded that this method is so appropriate for this problem and it can provide researchers a very powerful vehicle for scrutinizing rumor models in diverse kinds of social networks such as Facebook, YouTube, Flickr, LinkedIn and Tuitor.

  7. Data Processing and Analytic Support in the PLCO Cancer Screening Trial.

    PubMed

    Mabie, Jerome; Riley, Tom; Marcus, Pamela M; Black, Amanda; Rozjabek, Heather; Yu, Kelly; Young, Michael; Austin, Joe; Rathmell, Josh; Williams, Craig; Prorok, Philip C

    2015-01-01

    The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial was a large, randomized controlled trial of cancer screening that also evolved over time into a unique epidemiologic cohort. Vast quantities of data have been collected since the beginning of the trial in 1993. Screening data was obtained through 2006. Questionnaire-based risk factor data (collected at baseline and at other points in the trial), vital status, cancer diagnoses and treatment, biospecimen data and additional ancillary efforts continue to be collected. Accurate data collection and efficient management methods are required to ensure high-quality data and valid and consistent analyses of trial outcomes. Information Management Services (IMS) was and continues to be responsible for processing and converting the collected raw PLCO data into comprehensive and accessible datasets. IMS also continues to provide a wide spectrum of analytic support including support for trial monitoring, data sharing, and epidemiologic research. In this paper, we describe the data processing and management requirements from the analytic team perspective, highlighting the various data sources and their complexity. We also illustrate the construction of usable analytic data files and discuss the wide range of analytic support provided. Instructions for accessing PLCO data also are provided.

  8. Optical processing for future computer networks

    NASA Technical Reports Server (NTRS)

    Husain, A.; Haugen, P. R.; Hutcheson, L. D.; Warrior, J.; Murray, N.; Beatty, M.

    1986-01-01

    In the development of future data management systems, such as the NASA Space Station, a major problem represents the design and implementation of a high performance communication network which is self-correcting and repairing, flexible, and evolvable. To obtain the goal of designing such a network, it will be essential to incorporate distributed adaptive network control techniques. The present paper provides an outline of the functional and communication network requirements for the Space Station data management system. Attention is given to the mathematical representation of the operations being carried out to provide the required functionality at each layer of communication protocol on the model. The possible implementation of specific communication functions in optics is also considered.

  9. Further results in multiset processing with neural networks.

    PubMed

    McGregor, Simon

    2008-08-01

    This paper presents new experimental results on the variadic neural network (VNN) [McGregor, S. (2007). Neural network processing for multiset data. In Proceedings: Vol. 4668. Artificial neural networks - ICANN 2007, 17th international conference (pp. 460-470). Springer]. The inputs to a variadic network are an arbitrary-length list of n-tuples of real numbers, where n is fixed, and the function computed by the network is unaffected by permutation of the inputs. This paper describes improvements in the training algorithm for the variadic perceptron, based on a constructive cascade topology, and performance of the improved networks on geometric problems inspired by vector graphics. Further development may allow practical application of these or similar networks to vector graphics processing and statistical analysis.

  10. Gaussian process regression for sensor networks under localization uncertainty

    USGS Publications Warehouse

    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.

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

    PubMed

    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.

  12. Prioritizing factors influencing nurses' satisfaction with hospital information systems: a fuzzy analytic hierarchy process approach.

    PubMed

    Kimiafar, Khalil; Sadoughi, Farahnaz; Sheikhtaheri, Abbas; Sarbaz, Masoumeh

    2014-04-01

    Our aim was to use the fuzzy analytic hierarchy process approach to prioritize the factors that influence nurses' satisfaction with a hospital information system. First, we reviewed the related literature to identify and select possible factors. Second, we developed an analytic hierarchy process framework with three main factors (quality of services, of systems, and of information) and 22 subfactors. Third, we developed a questionnaire based on pairwise comparisons and invited 10 experienced nurses who were identified through snowball sampling to rate these factors. Finally, we used Chang's fuzzy extent analysis method to compute the weights of these factors and prioritize them. We found that information quality was the most important factor (58%), followed by service quality (22%) and then system quality (19%). In conclusion, although their weights were not similar, all factors were important and should be considered in evaluating nurses' satisfaction.

  13. A micro-process analysis of Functional Analytic Psychotherapy's mechanism of change.

    PubMed

    Busch, Andrew M; Kanter, Jonathan W; Callaghan, Glenn M; Baruch, David E; Weeks, Cristal E; Berlin, Kristoffer S

    2009-09-01

    This study sought to clarify the micro-process of Functional Analytic Psychotherapy (FAP) by using the Functional Analytic Psychotherapy Rating Scale (FAPRS) to code every client and therapist turn of speech over the course of successful treatment of an individual meeting diagnostic criteria for depression and histrionic personality disorder. Treatment consisted of cognitive behavioral therapy alone followed by the addition of FAP techniques in a unique A / A+B design. In-session client behavior improved following the shift to FAP techniques, and micro-process data suggested that client behavior was effectively shaped by in-vivo FAP procedures. These results support FAP's purported mechanisms of change and highlight the advantages of utilizing molecular coding systems to explore these mechanisms.

  14. Load Shedding Scheme in Large Pulp Mill by Using Analytic Hierarchy Process

    NASA Astrophysics Data System (ADS)

    Goh, H. H.; Kok, B. C.; Lee, S. W.; Zin, A. A. Mohd.

    2011-06-01

    Pulp mill is one of the heavy industries that consumes large amount of electricity in its production. In particular, the breakdown of the generator would cause other generators to be overloaded. Thus, load shedding scheme is the best way in handling such condition. Selected load will be shed under this scheme in order to protect the generators from being damaged. In the meantime, the subsequence loads will be shed until the generators are sufficient to provide the power to other loads. In order to determine the sequences of load shedding scheme, analytic hierarchy process (AHP) is introduced. Analytic Hierarchy Process is one of the multi-criteria decision making methods. By using this method, the priority of the load can be determined. This paper presents the theory of the alternative methods to choose the load priority in load shedding scheme for a large pulp mill.

  15. Neural networks in windprofiler data processing

    NASA Astrophysics Data System (ADS)

    Weber, H.; Richner, H.; Kretzschmar, R.; Ruffieux, D.

    2003-04-01

    Wind profilers are basically Doppler radars yielding 3-dimensional wind profiles that are deduced from the Doppler shift caused by turbulent elements in the atmosphere. These signals can be contaminated by other airborne elements such as birds or hydrometeors. Using a feed-forward neural network with one hidden layer and one output unit, birds and hydrometeors can be successfully identified in non-averaged single spectra; theses are subsequently removed in the wind computation. An infrared camera was used to identify birds in one of the beams of the wind profiler. After training the network with about 6000 contaminated data sets, it was able to identify contaminated data in a test data set with a reliability of 96 percent. The assumption was made that the neural network parameters obtained in the beam for which bird data was collected can be transferred to the other beams (at least three beams are needed for computing wind vectors). Comparing the evolution of a wind field with and without the neural network shows a significant improvement of wind data quality. Current work concentrates on training the network also for hydrometeors. It is hoped that the instrument's capability can thus be expanded to measure not only correct winds, but also observe bird migration, estimate precipitation and -- by combining precipitation information with vertical velocity measurement -- the monitoring of the height of the melting layer.

  16. Importance of regression processes in evaluating analytical errors in argon isotope measurements

    NASA Astrophysics Data System (ADS)

    Min, K.; Powell, L.

    2003-04-01

    For 40Ar/39Ar dating, it is required to measure five argon isotopes of 36Ar ~ 40Ar with high precision. The process involves isolating the purified gas in an analytical volume and cyclically measuring the abundance of each Ar isotope using an electron multiplier to minimize detector calibration and sensitivity errors. Each cycle is composed of maximum several tens of fundamental digital voltmeter (DVM) readings per isotope. Since the abundance of each isotope varies over analytical time, it is necessary to statistically treat the data to obtain most probable estimates. The readings on one mass from one cycle are commonly averaged to be treated as a single data point for regression. The y-intercept derived from the regression is assumed to represent an initial isotopic abundance at the time (t0) when the gas was introduced to the analytical volume. This procedure is repeated for each Ar isotope. About 0.2 % precision is often claimed for 40Ar and 39Ar measurements for properly irradiated, K-rich samples. The uncertainty of the calculated y-intercept varies depending on the distribution of the averaged DVM readings as well as the model equation used in regression. The “internal error” associated with the distribution of individual DVM readings in the group average are, however, commonly ignored in the regression procedure probably due to complex weighting processes. Including the internal error may significantly increase the uncertainties of 40Ar/39Ar ages especially for young samples because the analytical errors (from isotopic ratio measurements) are more dominant than the systematic errors (from decay constant, age of neutron flux monitor, etc). Alternative way to include the internal error is to regress all of the DVM readings with a single equation, then propagate the regression error into y-intercept calculation. In any case, it is necessary to propagate uncertainties derived from fundamental readings to properly estimate analytical errors in 40Ar/39Ar age

  17. A formalism for evaluating analytically the cross-correlation structure of a firing-rate network model.

    PubMed

    Fasoli, Diego; Faugeras, Olivier; Panzeri, Stefano

    2015-01-01

    We introduce a new formalism for evaluating analytically the cross-correlation structure of a finite-size firing-rate network with recurrent connections. The analysis performs a first-order perturbative expansion of neural activity equations that include three different sources of randomness: the background noise of the membrane potentials, their initial conditions, and the distribution of the recurrent synaptic weights. This allows the analytical quantification of the relationship between anatomical and functional connectivity, i.e. of how the synaptic connections determine the statistical dependencies at any order among different neurons. The technique we develop is general, but for simplicity and clarity we demonstrate its efficacy by applying it to the case of synaptic connections described by regular graphs. The analytical equations so obtained reveal previously unknown behaviors of recurrent firing-rate networks, especially on how correlations are modified by the external input, by the finite size of the network, by the density of the anatomical connections and by correlation in sources of randomness. In particular, we show that a strong input can make the neurons almost independent, suggesting that functional connectivity does not depend only on the static anatomical connectivity, but also on the external inputs. Moreover we prove that in general it is not possible to find a mean-field description à la Sznitman of the network, if the anatomical connections are too sparse or our three sources of variability are correlated. To conclude, we show a very counterintuitive phenomenon, which we call stochastic synchronization, through which neurons become almost perfectly correlated even if the sources of randomness are independent. Due to its ability to quantify how activity of individual neurons and the correlation among them depends upon external inputs, the formalism introduced here can serve as a basis for exploring analytically the computational capability of

  18. Regulatory gene networks and the properties of the developmental process

    NASA Technical Reports Server (NTRS)

    Davidson, Eric H.; McClay, David R.; Hood, Leroy

    2003-01-01

    Genomic instructions for development are encoded in arrays of regulatory DNA. These specify large networks of interactions among genes producing transcription factors and signaling components. The architecture of such networks both explains and predicts developmental phenomenology. Although network analysis is yet in its early stages, some fundamental commonalities are already emerging. Two such are the use of multigenic feedback loops to ensure the progressivity of developmental regulatory states and the prevalence of repressive regulatory interactions in spatial control processes. Gene regulatory networks make it possible to explain the process of development in causal terms and eventually will enable the redesign of developmental regulatory circuitry to achieve different outcomes.

  19. Using neural networks for dynamic light scattering time series processing

    NASA Astrophysics Data System (ADS)

    Chicea, Dan

    2017-04-01

    A basic experiment to record dynamic light scattering (DLS) time series was assembled using basic components. The DLS time series processing using the Lorentzian function fit was considered as reference. A Neural Network was designed and trained using simulated frequency spectra for spherical particles in the range 0–350 nm, assumed to be scattering centers, and the neural network design and training procedure are described in detail. The neural network output accuracy was tested both on simulated and on experimental time series. The match with the DLS results, considered as reference, was good serving as a proof of concept for using neural networks in fast DLS time series processing.

  20. [Preliminary Study on Error Control of Medical Devices Test Reports Based on the Analytic Hierarchy Process].

    PubMed

    Huang, Yanhong; Xu, Honglei; Tu, Rong; Zhang, Xu; Huang, Min

    2016-01-01

    In this paper, the common errors in medical devices test reports are classified and analyzed. And then the main 11 influence factors for these inspection report errors are summarized. The hierarchy model was also developed and verified by presentation data using MATLAB. The feasibility of comprehensive weights quantitative comparison has been analyzed by using the analytic hierarchy process. In the end, this paper porspects the further research direction.

  1. Large-scale analytical Fourier transform of photomask layouts using graphics processing units

    NASA Astrophysics Data System (ADS)

    Sakamoto, Julia A.

    2015-10-01

    Compensation of lens-heating effects during the exposure scan in an optical lithographic system requires knowledge of the heating profile in the pupil of the projection lens. A necessary component in the accurate estimation of this profile is the total integrated distribution of light, relying on the squared modulus of the Fourier transform (FT) of the photomask layout for individual process layers. Requiring a layout representation in pixelated image format, the most common approach is to compute the FT numerically via the fast Fourier transform (FFT). However, the file size for a standard 26- mm×33-mm mask with 5-nm pixels is an overwhelming 137 TB in single precision; the data importing process alone, prior to FFT computation, can render this method highly impractical. A more feasible solution is to handle layout data in a highly compact format with vertex locations of mask features (polygons), which correspond to elements in an integrated circuit, as well as pattern symmetries and repetitions (e.g., GDSII format). Provided the polygons can decompose into shapes for which analytical FT expressions are possible, the analytical approach dramatically reduces computation time and alleviates the burden of importing extensive mask data. Algorithms have been developed for importing and interpreting hierarchical layout data and computing the analytical FT on a graphics processing unit (GPU) for rapid parallel processing, not assuming incoherent imaging. Testing was performed on the active layer of a 392- μm×297-μm virtual chip test structure with 43 substructures distributed over six hierarchical levels. The factor of improvement in the analytical versus numerical approach for importing layout data, performing CPU-GPU memory transfers, and executing the FT on a single NVIDIA Tesla K20X GPU was 1.6×104, 4.9×103, and 3.8×103, respectively. Various ideas for algorithm enhancements will be discussed.

  2. Self-processing networks and their biomedical implications

    SciTech Connect

    Reggia, J.A.; Sutton, G.G. III )

    1988-06-01

    Self-processing networks (connectionist models, neural networks, marker-passing systems, etc.) represent information as a network of interconnected nodes and process that information through the controlled spread of activation throughout the network. This paper characterizes the nature of self-processing networks developed as models of intelligent systems in neuroscience, cognitive science, and artificial intelligence, and contrasts them with more traditional information processing models. In spite of the different perspectives and goals of individuals in these three fields, it is seen that important common principles are being revealed by this multidisciplinary work. In addition to the emphasis on intelligence as an emergent ''system property,'' these common themes include the importance of parallelism to intelligent systems and the notion of an active rather than passive memory. The historical evolution of these principles is emphasized and their potential biomedical significance is explored.

  3. Relative frequencies of constrained events in stochastic processes: An analytical approach

    NASA Astrophysics Data System (ADS)

    Rusconi, S.; Akhmatskaya, E.; Sokolovski, D.; Ballard, N.; de la Cal, J. C.

    2015-10-01

    The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They relies on knowledge of interevent probability density functions (PDFs) and on information about dependencies between all possible events. Analytical representations of a PDF are difficult to specify in advance, in many real life applications. Knowing the shapes of PDFs, and using experimental data, different optimization schemes can be applied in order to evaluate probability density functions and, therefore, the properties of the studied system. Such methods, however, are computationally demanding, and often not feasible. We show that, in the case where experimentally accessed properties are directly related to the frequencies of events involved, it may be possible to replace the heavy Monte Carlo core of optimization schemes with an analytical solution. Such a replacement not only provides a more accurate estimation of the properties of the process, but also reduces the simulation time by a factor of order of the sample size (at least ≈104 ). The proposed analytical approach is valid for any choice of PDF. The accuracy, computational efficiency, and advantages of the method over MC procedures are demonstrated in the exactly solvable case and in the evaluation of branching fractions in controlled radical polymerization (CRP) of acrylic monomers. This polymerization can be modeled by a constrained stochastic process. Constrained systems are quite common, and this makes the method useful for various applications.

  4. Relative frequencies of constrained events in stochastic processes: An analytical approach.

    PubMed

    Rusconi, S; Akhmatskaya, E; Sokolovski, D; Ballard, N; de la Cal, J C

    2015-10-01

    The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They relies on knowledge of interevent probability density functions (PDFs) and on information about dependencies between all possible events. Analytical representations of a PDF are difficult to specify in advance, in many real life applications. Knowing the shapes of PDFs, and using experimental data, different optimization schemes can be applied in order to evaluate probability density functions and, therefore, the properties of the studied system. Such methods, however, are computationally demanding, and often not feasible. We show that, in the case where experimentally accessed properties are directly related to the frequencies of events involved, it may be possible to replace the heavy Monte Carlo core of optimization schemes with an analytical solution. Such a replacement not only provides a more accurate estimation of the properties of the process, but also reduces the simulation time by a factor of order of the sample size (at least ≈10(4)). The proposed analytical approach is valid for any choice of PDF. The accuracy, computational efficiency, and advantages of the method over MC procedures are demonstrated in the exactly solvable case and in the evaluation of branching fractions in controlled radical polymerization (CRP) of acrylic monomers. This polymerization can be modeled by a constrained stochastic process. Constrained systems are quite common, and this makes the method useful for various applications.

  5. Contagion processes on the static and activity-driven coupling networks.

    PubMed

    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.

  6. Contagion processes on the static and activity-driven coupling networks

    NASA Astrophysics Data System (ADS)

    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.

  7. Curvature-processing network in macaque visual cortex

    PubMed Central

    Yue, Xiaomin; Pourladian, Irene S.; Tootell, Roger B. H.; Ungerleider, Leslie G.

    2014-01-01

    Our visual environment abounds with curved features. Thus, the goal of understanding visual processing should include the processing of curved features. Using functional magnetic resonance imaging in behaving monkeys, we demonstrated a network of cortical areas selective for the processing of curved features. This network includes three distinct hierarchically organized regions within the ventral visual pathway: a posterior curvature-biased patch (PCP) located in the near-foveal representation of dorsal V4, a middle curvature-biased patch (MCP) located on the ventral lip of the posterior superior temporal sulcus (STS) in area TEO, and an anterior curvature-biased patch (ACP) located just below the STS in anterior area TE. Our results further indicate that the processing of curvature becomes increasingly complex from PCP to ACP. The proximity of the curvature-processing network to the well-known face-processing network suggests a possible functional link between them. PMID:25092328

  8. Network cloning unfolds the effect of clustering on dynamical processes

    NASA Astrophysics Data System (ADS)

    Faqeeh, Ali; Melnik, Sergey; Gleeson, James P.

    2015-05-01

    We introduce network L -cloning, a technique for creating ensembles of random networks from any given real-world or artificial network. Each member of the ensemble is an L -cloned network constructed from L copies of the original network. The degree distribution of an L -cloned network and, more importantly, the degree-degree correlation between and beyond nearest neighbors are identical to those of the original network. The density of triangles in an L -cloned network, and hence its clustering coefficient, is reduced by a factor of L compared to those of the original network. Furthermore, the density of loops of any fixed length approaches zero for sufficiently large values of L . Other variants of L -cloning allow us to keep intact the short loops of certain lengths. As an application, we employ these network cloning methods to investigate the effect of short loops on dynamical processes running on networks and to inspect the accuracy of corresponding tree-based theories. We demonstrate that dynamics on L -cloned networks (with sufficiently large L ) are accurately described by the so-called adjacency tree-based theories, examples of which include the message passing technique, some pair approximation methods, and the belief propagation algorithm used respectively to study bond percolation, SI epidemics, and the Ising model.

  9. Reducing neural network training time with parallel processing

    NASA Technical Reports Server (NTRS)

    Rogers, James L., Jr.; Lamarsh, William J., II

    1995-01-01

    Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.

  10. Reliability theory for diffusion processes on interconnected networks

    NASA Astrophysics Data System (ADS)

    Khorramzadeh, Yasamin; Youssef, Mina; Eubank, Stephen

    2014-03-01

    We present the concept of network reliability as a framework to study diffusion dynamics in interdependent networks. We illustrate how different outcomes of diffusion processes, such as cascading failure, can be studied by estimating the reliability polynomial under different reliability rules. As an example, we investigate the effect of structural properties on diffusion dynamics for a few different topologies of two coupled networks. We evaluate the effect of varying the probability of failure propagating along the edges, both within a single network as well as between the networks. We exhibit the sensitivity of interdependent network reliability and connectivity to edge failures in each topology. Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia 24061, USA.

  11. Detecting link failures in complex network processes using remote monitoring

    NASA Astrophysics Data System (ADS)

    Dhal, R.; Abad Torres, J.; Roy, S.

    2015-11-01

    We study whether local structural changes in a complex network can be distinguished from passive remote time-course measurements of the network's dynamics. Specifically the detection of link failures in a network synchronization process from noisy measurements at a single network component is considered. By phrasing the detection task as a Maximum A Posteriori Probability hypothesis testing problem, we are able to obtain conditions under which the detection is (1) improved over the a priori and (2) asymptotically perfect, in terms of the network spectrum and graph. We find that, in the case where the detector has knowledge of the network's state, perfect detection is possible under general connectivity conditions regardless of the measurement location. When the detector does not have state knowledge, a remote signature permits improved but not perfect detection, under the same connectivity conditions. At its essence, detectability is achieved because of the close connection between a network's topology, its eigenvalues and local response characteristics.

  12. Analytical Methodologies for Semiconductor Process Characterization—Novel Mass Spectrometric Methods

    NASA Astrophysics Data System (ADS)

    Vartanian, Victor H.; Goolsby, Brian

    2003-09-01

    New analytical techniques and applications are needed to address the challenges facing the semiconductor industry as transistor feature sizes continue to decrease beyond the 100 nm technology node. Several new applications of quadrupole ion trap (QIT) and Fourier transform ion cyclotron resonance (FTICR) mass spectrometry are presented, specifically applied to process tool effluent characterization. A QIT with atmospheric pressure transfer line and pneumatically driven valves is used to characterize a dielectric etch process, with response times comparable to extractive Fourier transform infrared (FTIR) spectroscopy. The QIT allows application of collision-induced dissociation (CID) for structure elucidation, and is useful when high-molecular weight metal organic precursors are used in processes that evolve byproducts that are ambiguous by gas-phase infrared analysis. Similarly, a transportable FTICR with a fixed magnet and pulsed-valve sample introduction allows matrix ion ejection to improve the sensitivity to analyte ions. The FTICR has also been evaluated for a low-pressure chemical vapor deposition (LPCVD) process using a high-molecular weight precursor. Byproducts are ambiguous in FTIR spectra, but the FTICR provided structural confirmation of the effluent species, and is a useful complement to FTIR. The FTICR was also used with FTIR to characterize process tool effluent emissions in a study using SF6 and Ar to plasma etch a candidate metal oxide gate electrode material, RuO2. The results confirmed that no significant amount of RuO4, a toxic byproduct, were produced in this process.

  13. A Sensemaking Approach to Visual Analytics of Attribute-Rich Social Networks

    ERIC Educational Resources Information Center

    Gou, Liang

    2012-01-01

    Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

  14. Advanced information processing system: Input/output network management software

    NASA Technical Reports Server (NTRS)

    Nagle, Gail; Alger, Linda; Kemp, Alexander

    1988-01-01

    The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

  15. Integrating the dynamics of personality and close relationship processes: methodological and data analytic implications.

    PubMed

    Graber, Elana C; Laurenceau, Jean-Philippe; Carver, Charles S

    2011-12-01

    A common theme that has emerged from classic and contemporary theoretical work in both the fields of personality and relationship science is a focus on process. Current process-focused theories bearing on personality invoke a view of the individual in ongoing action and interaction with the environment, reflecting a flow of experience rather than a static depiction. To understand the processes by which personality interacts with the social environment (particularly dyads), investigations must capture individuals interacting in multiple interpersonal situations, which likely necessitates complex study designs and corresponding data analytic strategies. Using an illustrative simulated data set, we focus on diary methods and corresponding individual and dyadic multilevel models to capture person-situation interaction within the context of processes in daily close relationship life. Finally, we consider future directions that conceptualize personality and close relationship processes from a dynamical systems theoretical and methodological perspective.

  16. Coal liquefaction process streams characterization and evaluation. Novel analytical techniques for coal liquefaction: Fluorescence microscopy

    SciTech Connect

    Rathbone, R.F.; Hower, J.C.; Derbyshire, F.J.

    1991-10-01

    This study demonstrated the feasibility of using fluorescence and reflectance microscopy techniques for the examination of distillation resid materials derived from direct coal liquefaction. Resid, as defined here, is the 850{degrees}F{sup +} portion of the process stream, and includes soluble organics, insoluble organics and ash. The technique can be used to determine the degree of hydrogenation and the presence of multiple phases occurring within a resid sample. It can also be used to infer resid reactivity. The technique is rapid, requiring less than one hour for sample preparation and examination, and thus has apparent usefulness for process monitoring. Additionally, the technique can distinguish differences in samples produced under various process conditions. It can, therefore, be considered a potentially useful technique for the process developer. Further development and application of this analytical method as a process development tool is justified based on these results.

  17. Toward an Analytic Framework of Interdisciplinary Reasoning and Communication (IRC) Processes in Science

    NASA Astrophysics Data System (ADS)

    Shen, Ji; Sung, Shannon; Zhang, Dongmei

    2015-11-01

    Students need to think and work across disciplinary boundaries in the twenty-first century. However, it is unclear what interdisciplinary thinking means and how to analyze interdisciplinary interactions in teamwork. In this paper, drawing on multiple theoretical perspectives and empirical analysis of discourse contents, we formulate a theoretical framework that helps analyze interdisciplinary reasoning and communication (IRC) processes in interdisciplinary collaboration. Specifically, we propose four interrelated IRC processes-integration, translation, transfer, and transformation, and develop a corresponding analytic framework. We apply the framework to analyze two meetings of a project that aims to develop interdisciplinary science assessment items. The results illustrate that the framework can help interpret the interdisciplinary meeting dynamics and patterns. Our coding process and results also suggest that these IRC processes can be further examined in terms of interconnected sub-processes. We also discuss the implications of using the framework in conceptualizing, practicing, and researching interdisciplinary learning and teaching in science education.

  18. An analytical hierarchy process for decision making of high-level-waste management

    SciTech Connect

    Wang, J.H.C.; Jang, W.

    1995-12-01

    To prove the existence value of nuclear technology for the world of post cold war, demonstration of safe rad-waste disposal is essential. High-level-waste (HLW) certainly is the key issue to be resolved. To assist a rational and persuasive process on various disposal options, an Analytical Hierarchy Process (AHP) for the decision making of HLW management is presented. The basic theory and rationale are discussed, and applications are shown to illustrate the usefulness of the AHP. The authors wish that the AHP can provide a better direction for the current doomed situations of Taiwan nuclear industry, and to exchange with other countries for sharing experiences on the HLW management.

  19. An Overview of the Canadian Forces’ Second Generation Capability-Based Planning Analytical Process

    DTIC Science & Technology

    2010-09-01

    cadre de la transformation des FC, dont celui de la prise de décisions stratégiques où la communauté de la recherche opéra- tionnelle joue un rôle de...processus de réaction. Dans l’optique de rendre le processus d’approvisionnement de la Défense plus proactif, on a créé un processus rationnel de décision...development process. At the core of CBP is the CBP analytical process, which is comprised of a set of soft and hard op - erational research methods that

  20. Understanding wax screen-printing: a novel patterning process for microfluidic cloth-based analytical devices.

    PubMed

    Liu, Min; Zhang, Chunsun; Liu, Feifei

    2015-09-03

    In this work, we first introduce the fabrication of microfluidic cloth-based analytical devices (μCADs) using a wax screen-printing approach that is suitable for simple, inexpensive, rapid, low-energy-consumption and high-throughput preparation of cloth-based analytical devices. We have carried out a detailed study on the wax screen-printing of μCADs and have obtained some interesting results. Firstly, an analytical model is established for the spreading of molten wax in cloth. Secondly, a new wax screen-printing process has been proposed for fabricating μCADs, where the melting of wax into the cloth is much faster (∼5 s) and the heating temperature is much lower (75 °C). Thirdly, the experimental results show that the patterning effects of the proposed wax screen-printing method depend to a certain extent on types of screens, wax melting temperatures and melting time. Under optimized conditions, the minimum printing width of hydrophobic wax barrier and hydrophilic channel is 100 μm and 1.9 mm, respectively. Importantly, the developed analytical model is also well validated by these experiments. Fourthly, the μCADs fabricated by the presented wax screen-printing method are used to perform a proof-of-concept assay of glucose or protein in artificial urine with rapid high-throughput detection taking place on a 48-chamber cloth-based device and being performed by a visual readout. Overall, the developed cloth-based wax screen-printing and arrayed μCADs should provide a new research direction in the development of advanced sensor arrays for detection of a series of analytes relevant to many diverse applications.

  1. Identifying and tracking dynamic processes in social networks

    NASA Astrophysics Data System (ADS)

    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.

  2. Process analytical techniques for hot-melt extrusion and their application to amorphous solid dispersions.

    PubMed

    Hitzer, Patrick; Bäuerle, Tim; Drieschner, Tobias; Ostertag, Edwin; Paulsen, Katharina; van Lishaut, Holger; Lorenz, Günter; Rebner, Karsten

    2017-03-25

    Newly developed active pharmaceutical ingredients (APIs) are often poorly soluble in water. As a result the bioavailability of the API in the human body is reduced. One approach to overcome this restriction is the formulation of amorphous solid dispersions (ASDs), e.g., by hot-melt extrusion (HME). Thus, the poorly soluble crystalline form of the API is transferred into a more soluble amorphous form. To reach this aim in HME, the APIs are embedded in a polymer matrix. The resulting amorphous solid dispersions may contain small amounts of residual crystallinity and have the tendency to recrystallize. For the controlled release of the API in the final drug product the amount of crystallinity has to be known. This review assesses the available analytical methods that have been recently used for the characterization of ASDs and the quantification of crystalline API content. Well-established techniques like near- and mid-infrared spectroscopy (NIR and MIR, respectively), Raman spectroscopy, and emerging ones like UV/VIS, terahertz, and ultrasonic spectroscopy are considered in detail. Furthermore, their advantages and limitations are discussed with regard to general practical applicability as process analytical technology (PAT) tools in industrial manufacturing. The review focuses on spectroscopic methods which have been proven as most suitable for in-line and on-line process analytics. Further aspects are spectroscopic techniques that have been or could be integrated into an extruder.

  3. Analytical treatment of ultrafast laser-induced spin-flipping Λ processes on magnetic nanostructures

    NASA Astrophysics Data System (ADS)

    Lefkidis, Georgios; Hübner, Wolfgang

    2013-01-01

    In this paper, we analytically treat ultrafast, laser-induced, spin-flipping processes based on Λ model systems with triplet ground state. After obtaining the wave functions, we give analytical solutions for the induced material polarization in the time domain. Compact summation formulas for the time-dependent (windowed) induced polarization of the material in the frequency domain, as well as its helicity (fourth Stokes parameter), are given. These solutions compare excellently with numerical results obtained for realistic systems (i.e., systems that can or have been synthesized and were treated with high-level quantum chemical methods including electron correlations and relativistic effects). We thus analytically show that laser-induced spin flip is possible and can be detected from the helicity of the emitted light during the process. Additionally, we analyze the effects of a finite temperature and the time window of a measuring apparatus on the signal detected. These are very crucial steps not only for verifying the validity of previous numerical results, but also for the deeper understanding of the physical mechanisms involved.

  4. Laser processes and analytics for high power 3D battery materials

    NASA Astrophysics Data System (ADS)

    Pfleging, W.; Zheng, Y.; Mangang, M.; Bruns, M.; Smyrek, P.

    2016-03-01

    Laser processes for cutting, modification and structuring of energy storage materials such as electrodes, separator materials and current collectors have a great potential in order to minimize the fabrication costs and to increase the performance and operational lifetime of high power lithium-ion-batteries applicable for stand-alone electric energy storage devices and electric vehicles. Laser direct patterning of battery materials enable a rather new technical approach in order to adjust 3D surface architectures and porosity of composite electrode materials such as LiCoO2, LiMn2O4, LiFePO4, Li(NiMnCo)O2, and Silicon. The architecture design, the increase of active surface area, and the porosity of electrodes or separator layers can be controlled by laser processes and it was shown that a huge impact on electrolyte wetting, lithium-ion diffusion kinetics, cell life-time and cycling stability can be achieved. In general, the ultrafast laser processing can be used for precise surface texturing of battery materials. Nevertheless, regarding cost-efficient production also nanosecond laser material processing can be successfully applied for selected types of energy storage materials. A new concept for an advanced battery manufacturing including laser materials processing is presented. For developing an optimized 3D architecture for high power composite thick film electrodes electrochemical analytics and post mortem analytics using laser-induced breakdown spectroscopy were performed. Based on mapping of lithium in composite electrodes, an analytical approach for studying chemical degradation in structured and unstructured lithium-ion batteries will be presented.

  5. Point Process Modeling for Directed Interaction Networks

    DTIC Science & Technology

    2011-10-01

    maximized via Newton’s method or a gradient- based optimization approach (Nocedal and Wright, 2006). These methods require one or both of the first two...Hand (2010). Bayesian anomaly detection methods for social networks. Ann. Appl. Statist. 4, 645–662. Jackson, M. O. (2008). Social and Economic...Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA, 22202-4302

  6. Analytical characterization of spontaneous firing in networks of developing rat cultured cortical neurons

    NASA Astrophysics Data System (ADS)

    Tateno, Takashi; Kawana, Akio; Jimbo, Yasuhiko

    2002-05-01

    We have used a multiunit electrode array in extracellular recording to investigate changes in the firing patterns in networks of developing rat cortical neurons. The spontaneous activity of continual asynchronous firing or the alternation of asynchronous spikes and synchronous bursts changed over time so that activity in the later stages consisted exclusively of synchronized bursts. The spontaneous coordinated activity in bursts produced a variability in interburst interval (IBI) sequences that is referred to as ``form.'' The stochastic and nonlinear dynamical analysis of IBI sequences revealed that these sequences reflected a largely random process and that the form for relatively immature neurons was largely oscillatory while the form for the more mature neurons was Poisson-like. The observed IBI sequences thus showed changes in form associated with both the intrinsic properties of the developing cells and the neural response to correlated synaptic inputs due to interaction between the developing neural circuits.

  7. Process analytical technology in the pharmaceutical industry: a toolkit for continuous improvement.

    PubMed

    Scott, Bradley; Wilcock, Anne

    2006-01-01

    Process analytical technology (PAT) refers to a series of tools used to ensure that quality is built into products while at the same time improving the understanding of processes, increasing efficiency, and decreasing costs. It has not been widely adopted by the pharmaceutical industry. As the setting for this paper, the current pharmaceutical manufacturing paradigm and PAT guidance to date are discussed prior to the review of PAT principles and tools, benefits, and challenges. The PAT toolkit contains process analyzers, multivariate analysis tools, process control tools, and continuous improvement/knowledge management/information technology systems. The integration and implementation of these tools is complex, and has resulted in uncertainty with respect to both regulation and validation. The paucity of staff knowledgeable in this area may complicate adoption. Studies to quantitate the benefits resulting from the adoption of PAT within the pharmaceutical industry would be a valuable addition to the qualitative studies that are currently available.

  8. Analytical and knowledge-based redundancy for fault diagnosis in process plants

    SciTech Connect

    Fathi, Z.; Ramirez, W.F. ); Korbicz, J. )

    1993-01-01

    The increasing complexity of process plants and their reliability have necessitated the development of more powerful methods for detecting and diagnosing process abnormalities. Among the underlying strategies, analytical redundancy and knowledge-based system techniques offer viable solutions. In this work, the authors consider the adaptive inclusion of analytical redundancy models (state and parameter estimation modules) in the diagnostic reasoning loop of a knowledge-based system. This helps overcome the difficulties associated with each category. The design method is a new layered knowledge base that houses compiled/qualitative knowledge in the high levels and process-general estimation knowledge in the low levels of a hierarchical knowledge structure. The compiled knowledge is used to narrow the diagnostic search space and provide an effective way of employing estimation modules. The estimation-based methods that resort to fundamental analysis provide the rationale for a qualitatively-guided reasoning process. The overall structure of the fault detection and isolation system based on the combined strategy is discussed focusing on the model-based redundancy methods which create the low levels of the hierarchical knowledge base. The system has been implemented using the condensate-feedwater subsystem of a coal-fired power plant. Due to the highly nonlinear and mixed-mode nature of the power plant dynamics, the modified extended Kalman filter is used in designing local detection filters.

  9. Optical Multiple Access Network (OMAN) for advanced processing satellite applications

    NASA Technical Reports Server (NTRS)

    Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

    1991-01-01

    An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

  10. Bipartite memory network architectures for parallel processing

    SciTech Connect

    Smith, W.; Kale, L.V. . Dept. of Computer Science)

    1990-01-01

    Parallel architectures are boradly classified as either shared memory or distributed memory architectures. In this paper, the authors propose a third family of architectures, called bipartite memory network architectures. In this architecture, processors and memory modules constitute a bipartite graph, where each processor is allowed to access a small subset of the memory modules, and each memory module allows access from a small set of processors. The architecture is particularly suitable for computations requiring dynamic load balancing. The authors explore the properties of this architecture by examining the Perfect Difference set based topology for the graph. Extensions of this topology are also suggested.

  11. Component criticality in failure cascade processes of network systems.

    PubMed

    Zio, Enrico; Sansavini, Giovanni

    2011-08-01

    In this work, specific indicators are used to characterize the criticality of components in a network system with respect to their contribution to failure cascade processes. A realistic-size network is considered as reference case study. Three different models of cascading failures are analyzed, differing both on the failure load distribution logic and on the cascade triggering event. The criticality indicators are compared to classical measures of topological centrality to identify the one most characteristic of the cascade processes considered.

  12. Experimental and analytical investigation of the seizure process in aluminum-silicon alloy/steel tribocontacts

    NASA Astrophysics Data System (ADS)

    He, Xiaozhou

    1998-12-01

    This research is an experimental and analytical investigation of the scuffing/seizure mechanism in Al-Si alloy/steel tribocontacts. An analytical model is developed based on analyses and experiments to predict scuffing/seizure failure in Al-Si alloy/steel tribocontacts, which can be applied to tribo-components in engines, refrigerators and air conditioners. The wear and scuffing/seizure experiments have been conducted through a block-on-ring tester for 339 and ESE-M2A137 Al-Si alloys under the dry and boundary lubrication conditions. The experimental research consists of: (a) wear debris generation and EDX analysis, (b) wear surface morphological analysis, (c) scuffing/seizure mechanism and process analysis, (d) scuffing/seizure PV curves under the dry contact and boundary lubrication, and (e) effects of several main factors on scuffing/seizure. The analytical research includes the following: (a) the investigation of the scuffing/seizure mechanisms in the Al-Si alloy/steel tribocontacts, (b) 3-D asperity contact pressures for longitudinal, transverse and isotropic surface roughness profiles, (c) 3-D surface asperity contact temperature rise due to the friction, (d) failure analyses of the various lubricating films, (e) analyses of the temperature dependence of surface tangential traction and shear strength in a surface layer of Al-Si alloy, (f) the scuffing/seizure failure analytical model under dry contact and boundary lubrication. The analytical model is based on the new hypothesis of three defense lines against scuffing/seizure failure: the adsorbed oil film, oxide film and the ratio of surface tangential traction with the shear strength in a surface layer. These two films together with a surface layer itself form three defense lines against scuffing/seizure. The surface tangential traction exceeds the bulk shear strength in a surface layer of Al-Si alloy is the necessary and sufficient condition for the scuffing/seizure occurrence. The analytical model has a

  13. On-board processing satellite network architectures for broadband ISDN

    NASA Technical Reports Server (NTRS)

    Inukai, Thomas; Faris, Faris; Shyy, Dong-Jye

    1992-01-01

    Onboard baseband processing architectures for future satellite broadband integrated services digital networks (B-ISDN's) are addressed. To assess the feasibility of implementing satellite B-ISDN services, critical design issues, such as B-ISDN traffic characteristics, transmission link design, and a trade-off between onboard circuit and fast packet switching, are analyzed. Examples of the two types of switching mechanisms and potential onboard network control functions are presented. A sample network architecture is also included to illustrate a potential onboard processing system.

  14. Demonstration of FBRM as process analytical technology tool for dewatering processes via CST correlation.

    PubMed

    Cobbledick, Jeffrey; Nguyen, Alexander; Latulippe, David R

    2014-07-01

    The current challenges associated with the design and operation of net-energy positive wastewater treatment plants demand sophisticated approaches for the monitoring of polymer-induced flocculation. In anaerobic digestion (AD) processes, the dewaterability of the sludge is typically assessed from off-line lab-bench tests - the capillary suction time (CST) test is one of the most common. Focused beam reflectance measurement (FBRM) is a promising technique for real-time monitoring of critical performance attributes in large scale processes and is ideally suited for dewatering applications. The flocculation performance of twenty-four cationic polymers, that spanned a range of polymer size and charge properties, was measured using both the FBRM and CST tests. Analysis of the data revealed a decreasing monotonic trend; the samples that had the highest percent removal of particles less than 50 microns in size as determined by FBRM had the lowest CST values. A subset of the best performing polymers was used to evaluate the effects of dosage amount and digestate sources on dewatering performance. The results from this work show that FBRM is a powerful tool that can be used for optimization and on-line monitoring of dewatering processes.

  15. A results-based process for evaluation of diverse visual analytics tools

    NASA Astrophysics Data System (ADS)

    Rubin, Gary; Berger, David H.

    2013-05-01

    With the pervasiveness of still and full-motion imagery in commercial and military applications, the need to ingest and analyze these media has grown rapidly in recent years. Additionally, video hosting and live camera websites provide a near real-time view of our changing world with unprecedented spatial coverage. To take advantage of these controlled and crowd-sourced opportunities, sophisticated visual analytics (VA) tools are required to accurately and efficiently convert raw imagery into usable information. Whether investing in VA products or evaluating algorithms for potential development, it is important for stakeholders to understand the capabilities and limitations of visual analytics tools. Visual analytics algorithms are being applied to problems related to Intelligence, Surveillance, and Reconnaissance (ISR), facility security, and public safety monitoring, to name a few. The diversity of requirements means that a onesize- fits-all approach to performance assessment will not work. We present a process for evaluating the efficacy of algorithms in real-world conditions, thereby allowing users and developers of video analytics software to understand software capabilities and identify potential shortcomings. The results-based approach described in this paper uses an analysis of end-user requirements and Concept of Operations (CONOPS) to define Measures of Effectiveness (MOEs), test data requirements, and evaluation strategies. We define metrics that individually do not fully characterize a system, but when used together, are a powerful way to reveal both strengths and weaknesses. We provide examples of data products, such as heatmaps, performance maps, detection timelines, and rank-based probability-of-detection curves.

  16. Lateralized goal framing: How health messages are influenced by valence and contextual/analytic processing.

    PubMed

    McCormick, Michael; Seta, John J

    2016-05-01

    The effectiveness of health messages has been shown to vary due to the positive or negative framing of information, often known as goal framing. In two experiments we altered, the strength of the goal framing manipulation by selectively activating the processing style of the left or right hemisphere (RH). In Experiment 1, we found support for the contextual/analytic perspective; a significant goal framing effect was observed when the contextual processing style of the RH - but not the analytic processing style of the left hemisphere (LH) - was initially activated. In Experiment 2, support for the valence hypothesis was found when a message that had a higher level of personal involvement was used than that in Experiment 1. When the LH was initially activated, there was an advantage for the gain- vs. loss-framed message; however, an opposite pattern - an advantage for the loss-framed message - was obtained when the RH was activated. These are the first framing results that support the valence hypothesis. We discuss the theoretical and applied implications of these experiments.

  17. Impact of Recent Hardware and Software Trends on High Performance Transaction Processing and Analytics

    NASA Astrophysics Data System (ADS)

    Mohan, C.

    In this paper, I survey briefly some of the recent and emerging trends in hardware and software features which impact high performance transaction processing and data analytics applications. These features include multicore processor chips, ultra large main memories, flash storage, storage class memories, database appliances, field programmable gate arrays, transactional memory, key-value stores, and cloud computing. While some applications, e.g., Web 2.0 ones, were initially built without traditional transaction processing functionality in mind, slowly system architects and designers are beginning to address such previously ignored issues. The availability, analytics and response time requirements of these applications were initially given more importance than ACID transaction semantics and resource consumption characteristics. A project at IBM Almaden is studying the implications of phase change memory on transaction processing, in the context of a key-value store. Bitemporal data management has also become an important requirement, especially for financial applications. Power consumption and heat dissipation properties are also major considerations in the emergence of modern software and hardware architectural features. Considerations relating to ease of configuration, installation, maintenance and monitoring, and improvement of total cost of ownership have resulted in database appliances becoming very popular. The MapReduce paradigm is now quite popular for large scale data analysis, in spite of the major inefficiencies associated with it.

  18. Development of balanced key performance indicators for emergency departments strategic dashboards following analytic hierarchical process.

    PubMed

    Safdari, Reza; Ghazisaeedi, Marjan; Mirzaee, Mahboobeh; Farzi, Jebrail; Goodini, Azadeh

    2014-01-01

    Dynamic reporting tools, such as dashboards, should be developed to measure emergency department (ED) performance. However, choosing an effective balanced set of performance measures and key performance indicators (KPIs) is a main challenge to accomplish this. The aim of this study was to develop a balanced set of KPIs for use in ED strategic dashboards following an analytic hierarchical process. The study was carried out in 2 phases: constructing ED performance measures based on balanced scorecard perspectives and incorporating them into analytic hierarchical process framework to select the final KPIs. The respondents placed most importance on ED internal processes perspective especially on measures related to timeliness and accessibility of care in ED. Some measures from financial, customer, and learning and growth perspectives were also selected as other top KPIs. Measures of care effectiveness and care safety were placed as the next priorities too. The respondents placed least importance on disease-/condition-specific "time to" measures. The methodology can be presented as a reference model for development of KPIs in various performance related areas based on a consistent and fair approach. Dashboards that are designed based on such a balanced set of KPIs will help to establish comprehensive performance measurements and fair benchmarks and comparisons.

  19. Development of Multi-slice Analytical Tool to Support BIM-based Design Process

    NASA Astrophysics Data System (ADS)

    Atmodiwirjo, P.; Johanes, M.; Yatmo, Y. A.

    2017-03-01

    This paper describes the on-going development of computational tool to analyse architecture and interior space based on multi-slice representation approach that is integrated with Building Information Modelling (BIM). Architecture and interior space is experienced as a dynamic entity, which have the spatial properties that might be variable from one part of space to another, therefore the representation of space through standard architectural drawings is sometimes not sufficient. The representation of space as a series of slices with certain properties in each slice becomes important, so that the different characteristics in each part of space could inform the design process. The analytical tool is developed for use as a stand-alone application that utilises the data exported from generic BIM modelling tool. The tool would be useful to assist design development process that applies BIM, particularly for the design of architecture and interior spaces that are experienced as continuous spaces. The tool allows the identification of how the spatial properties change dynamically throughout the space and allows the prediction of the potential design problems. Integrating the multi-slice analytical tool in BIM-based design process thereby could assist the architects to generate better design and to avoid unnecessary costs that are often caused by failure to identify problems during design development stages.

  20. Evaluation Methodology for Advance Heat Exchanger Concepts Using Analytical Hierarchy Process

    SciTech Connect

    Piyush Sabharwall; Eung Soo Kim

    2012-07-01

    The primary purpose of this study is to aid in the development and selection of the secondary/process heat exchanger (SHX) for power production and process heat application for a Next Generation Nuclear Reactors (NGNR). The potential options for use as an SHX are explored such as shell and tube, printed circuit heat exchanger. A shell and tube (helical coiled) heat exchanger is a recommended for a demonstration reactor because of its reliability while the reactor design is being further developed. The basic setup for the selection of the SHX has been established with evaluation goals, alternatives, and criteria. This study describes how these criteria and the alternatives are evaluated using the analytical hierarchy process (AHP).

  1. A Big Data and Learning Analytics Approach to Process-Level Feedback in Cognitive Simulations.

    PubMed

    Pecaric, Martin; Boutis, Kathy; Beckstead, Jason; Pusic, Martin

    2017-02-01

    Collecting and analyzing large amounts of process data for the purposes of education can be considered a big data/learning analytics (BD/LA) approach to improving learning. However, in the education of health care professionals, the application of BD/LA is limited to date. The authors discuss the potential advantages of the BD/LA approach for the process of learning via cognitive simulations. Using the lens of a cognitive model of radiograph interpretation with four phases (orientation, searching/scanning, feature detection, and decision making), they reanalyzed process data from a cognitive simulation of pediatric ankle radiography where 46 practitioners from three expertise levels classified 234 cases online. To illustrate the big data component, they highlight the data available in a digital environment (time-stamped, click-level process data). Learning analytics were illustrated using algorithmic computer-enabled approaches to process-level feedback.For each phase, the authors were able to identify examples of potentially useful BD/LA measures. For orientation, the trackable behavior of re-reviewing the clinical history was associated with increased diagnostic accuracy. For searching/scanning, evidence of skipping views was associated with an increased false-negative rate. For feature detection, heat maps overlaid on the radiograph can provide a metacognitive visualization of common novice errors. For decision making, the measured influence of sequence effects can reflect susceptibility to bias, whereas computer-generated path maps can provide insights into learners' diagnostic strategies.In conclusion, the augmented collection and dynamic analysis of learning process data within a cognitive simulation can improve feedback and prompt more precise reflection on a novice clinician's skill development.

  2. Global tree network for computing structures enabling global processing operations

    DOEpatents

    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.

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

    DOEpatents

    Crosetto, D.B.

    1996-12-31

    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 to a plurality of slave processors 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, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

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

    DOEpatents

    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.

  5. IJA: an efficient algorithm for query processing in sensor networks.

    PubMed

    Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa

    2011-01-01

    One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm.

  6. A performance data network for solar process heat systems

    SciTech Connect

    Barker, G.; Hale, M.J.

    1996-03-01

    A solar process heat (SPH) data network has been developed to access remote-site performance data from operational solar heat systems. Each SPH system in the data network is outfitted with monitoring equipment and a datalogger. The datalogger is accessed via modem from the data network computer at the National Renewable Energy Laboratory (NREL). The dataloggers collect both ten-minute and hourly data and download it to the data network every 24-hours for archiving, processing, and plotting. The system data collected includes energy delivered (fluid temperatures and flow rates) and site meteorological conditions, such as solar insolation and ambient temperature. The SPH performance data network was created for collecting performance data from SPH systems that are serving in industrial applications or from systems using technologies that show promise for industrial applications. The network will be used to identify areas of SPH technology needing further development, to correlate computer models with actual performance, and to improve the credibility of SPH technology. The SPH data network also provides a centralized bank of user-friendly performance data that will give prospective SPH users an indication of how actual systems perform. There are currently three systems being monitored and archived under the SPH data network: two are parabolic trough systems and the third is a flat-plate system. The two trough systems both heat water for prisons; the hot water is used for personal hygiene, kitchen operations, and laundry. The flat plate system heats water for meat processing at a slaughter house. We plan to connect another parabolic trough system to the network during the first months of 1996. We continue to look for good examples of systems using other types of collector technologies and systems serving new applications (such as absorption chilling) to include in the SPH performance data network.

  7. Stimulus Dependent Dynamic Reorganization of the Human Face Processing Network.

    PubMed

    Rosenthal, Gideon; Sporns, Olaf; Avidan, Galia

    2016-09-12

    Using the "face inversion effect", a hallmark of face perception, we examined network mechanisms supporting face representation by tracking functional magnetic resonance imaging (fMRI) stimulus-dependent dynamic functional connectivity within and between brain networks associated with the processing of upright and inverted faces. We developed a novel approach adapting the general linear model (GLM) framework classically used for univariate fMRI analysis to capture stimulus-dependent fMRI dynamic connectivity of the face network. We show that under the face inversion manipulation, the face and non-face networks have complementary roles that are evident in their stimulus-dependent dynamic connectivity patterns as assessed by network decomposition into components or communities. Moreover, we show that connectivity patterns are associated with the behavioral face inversion effect. Thus, we establish "a network-level signature" of the face inversion effect and demonstrate how a simple physical transformation of the face stimulus induces a dramatic functional reorganization across related brain networks. Finally, we suggest that the dynamic GLM network analysis approach, developed here for the face network, provides a general framework for modeling the dynamics of blocked stimulus-dependent connectivity experimental designs and hence can be applied to a host of neuroimaging studies.

  8. Recovery processes and dynamics in single and interdependent networks

    NASA Astrophysics Data System (ADS)

    Majdandzic, Antonio

    Systems composed of dynamical networks --- such as the human body with its biological networks or the global economic network consisting of regional clusters --- often exhibit complicated collective dynamics. Three fundamental processes that are typically present are failure, damage spread, and recovery. Here we develop a model for such systems and find phase diagrams for single and interacting networks. By investigating networks with a small number of nodes, where finite-size effects are pronounced, we describe the spontaneous recovery phenomenon present in these systems. In the case of interacting networks the phase diagram is very rich and becomes increasingly more complex as the number of interacting networks increases. In the simplest example of two interacting networks we find two critical points, four triple points, ten allowed transitions, and two forbidden transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To test our model, we analyze an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model.

  9. Scalable Networked Information Processing Environment (SNIPE)

    SciTech Connect

    Fagg, G.E.; Moore, K.; Dongarra, J.J. |; Geist, A.

    1997-11-01

    SNIPE is a metacomputing system that aims to provide a reliable, secure, fault tolerant environment for long term distributed computing applications and data stores across the global Internet. This system combines global naming and replication of both processing and data to support large scale information processing applications leading to better availability and reliability than currently available with typical cluster computing and/or distributed computer environments.

  10. Process and analytical studies of enhanced low severity co-processing using selective coal pretreatment

    SciTech Connect

    Baldwin, R.M.; Miller, R.L.

    1991-12-01

    The findings in the first phase were as follows: 1. Both reductive (non-selective) alkylation and selective oxygen alkylation brought about an increase in liquefaction reactivity for both coals. 2. Selective oxygen alkylation is more effective in enhancing the reactivity of low rank coals. In the second phase of studies, the major findings were as follows: 1. Liquefaction reactivity increases with increasing level of alkylation for both hydroliquefaction and co-processing reaction conditions. 2. the increase in reactivity found for O-alkylated Wyodak subbituminous coal is caused by chemical changes at phenolic and carboxylic functional sites. 3. O-methylation of Wyodak subbituminous coal reduced the apparent activation energy for liquefaction of this coal.

  11. Study of SSIN (Single Stage Interconnection Networks) Parallel Processing Interconnection Networks

    DTIC Science & Technology

    1988-10-31

    Processing Networks,----_ 𔄃 ABSTRACT (Continue on reverse if necessary and identify by bloc;umr.ber) The increase in dynamic average path length ( DAPL ...increase in dynamic average path length ( DAPL ) with network size is moderate while it is significantly less than log 2N , the number of stages needed in

  12. Competing Contact Processes on Homogeneous Networks with Tunable Clusterization

    NASA Astrophysics Data System (ADS)

    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.

  13. A Process Analytical Technology (PAT) approach to control a new API manufacturing process: development, validation and implementation.

    PubMed

    Schaefer, Cédric; Clicq, David; Lecomte, Clémence; Merschaert, Alain; Norrant, Edith; Fotiadu, Frédéric

    2014-03-01

    Pharmaceutical companies are progressively adopting and introducing Process Analytical Technology (PAT) and Quality-by-Design (QbD) concepts promoted by the regulatory agencies, aiming the building of the quality directly into the product by combining thorough scientific understanding and quality risk management. An analytical method based on near infrared (NIR) spectroscopy was developed as a PAT tool to control on-line an API (active pharmaceutical ingredient) manufacturing crystallization step during which the API and residual solvent contents need to be precisely determined to reach the predefined seeding point. An original methodology based on the QbD principles was designed to conduct the development and validation of the NIR method and to ensure that it is fitted for its intended use. On this basis, Partial least squares (PLS) models were developed and optimized using chemometrics methods. The method was fully validated according to the ICH Q2(R1) guideline and using the accuracy profile approach. The dosing ranges were evaluated to 9.0-12.0% w/w for the API and 0.18-1.50% w/w for the residual methanol. As by nature the variability of the sampling method and the reference method are included in the variability obtained for the NIR method during the validation phase, a real-time process monitoring exercise was performed to prove its fit for purpose. The implementation of this in-process control (IPC) method on the industrial plant from the launch of the new API synthesis process will enable automatic control of the final crystallization step in order to ensure a predefined quality level of the API. In addition, several valuable benefits are expected including reduction of the process time, suppression of a rather difficult sampling and tedious off-line analyses.

  14. Analytical Study on Multi-Tier 5G Heterogeneous Small Cell Networks: Coverage Performance and Energy Efficiency

    PubMed Central

    Xiao, Zhu; Liu, Hongjing; Havyarimana, Vincent; Li, Tong; Wang, Dong

    2016-01-01

    In this paper, we investigate the coverage performance and energy efficiency of multi-tier heterogeneous cellular networks (HetNets) which are composed of macrocells and different types of small cells, i.e., picocells and femtocells. By virtue of stochastic geometry tools, we model the multi-tier HetNets based on a Poisson point process (PPP) and analyze the Signal to Interference Ratio (SIR) via studying the cumulative interference from pico-tier and femto-tier. We then derive the analytical expressions of coverage probabilities in order to evaluate coverage performance in different tiers and investigate how it varies with the small cells’ deployment density. By taking the fairness and user experience into consideration, we propose a disjoint channel allocation scheme and derive the system channel throughput for various tiers. Further, we formulate the energy efficiency optimization problem for multi-tier HetNets in terms of throughput performance and resource allocation fairness. To solve this problem, we devise a linear programming based approach to obtain the available area of the feasible solutions. System-level simulations demonstrate that the small cells’ deployment density has a significant effect on the coverage performance and energy efficiency. Simulation results also reveal that there exits an optimal small cell base station (SBS) density ratio between pico-tier and femto-tier which can be applied to maximize the energy efficiency and at the same time enhance the system performance. Our findings provide guidance for the design of multi-tier HetNets for improving the coverage performance as well as the energy efficiency. PMID:27827917

  15. Analytical Study on Multi-Tier 5G Heterogeneous Small Cell Networks: Coverage Performance and Energy Efficiency.

    PubMed

    Xiao, Zhu; Liu, Hongjing; Havyarimana, Vincent; Li, Tong; Wang, Dong

    2016-11-04

    In this paper, we investigate the coverage performance and energy efficiency of multi-tier heterogeneous cellular networks (HetNets) which are composed of macrocells and different types of small cells, i.e., picocells and femtocells. By virtue of stochastic geometry tools, we model the multi-tier HetNets based on a Poisson point process (PPP) and analyze the Signal to Interference Ratio (SIR) via studying the cumulative interference from pico-tier and femto-tier. We then derive the analytical expressions of coverage probabilities in order to evaluate coverage performance in different tiers and investigate how it varies with the small cells' deployment density. By taking the fairness and user experience into consideration, we propose a disjoint channel allocation scheme and derive the system channel throughput for various tiers. Further, we formulate the energy efficiency optimization problem for multi-tier HetNets in terms of throughput performance and resource allocation fairness. To solve this problem, we devise a linear programming based approach to obtain the available area of the feasible solutions. System-level simulations demonstrate that the small cells' deployment density has a significant effect on the coverage performance and energy efficiency. Simulation results also reveal that there exits an optimal small cell base station (SBS) density ratio between pico-tier and femto-tier which can be applied to maximize the energy efficiency and at the same time enhance the system performance. Our findings provide guidance for the design of multi-tier HetNets for improving the coverage performance as well as the energy efficiency.

  16. Oneiric activity and the analytical process. A semiotic perspective on Willy Baranger's theory of dreams.

    PubMed

    Vinocur-Fischbein, Susana

    2005-10-01

    This author reconsiders, from a semiotic perspective, the theoretical and technical ideas developed by Willy and Madeleine Baranger, especially W. Baranger's views on the function of dreams, the status of oneiric symbols and the further clinical-technical use of dreams in the context of the inter-subjective dynamic field, together with the basic unconscious fantasy that emerges in the analytic situation. She attempts to relate the Barangers' ideas to others arising from Peirce's analytic semiotics that would support a triadic conceptualization of dreams. The need to incorporate a pragmatic view of communication and of the processes of production of sense as contributions to dream metapsychology and interpretation in the case of non-neurotic patients is particularly emphasized. On the basis of the hypothesis of a described series of triads underlying the production and retelling of dreams, the acknowledgment of these produced/told dreams as intentional signs allows the presence of a continuous process of semiosis to be proposed. The author introduces clinical material to illustrate the communicative value of dreams through the textual analysis of the report and accompanying associations of three dreams. Such analysis takes a linguistic pragmatics approach that examines those aspects of meaning not accounted for by a restricted semantic theory.

  17. Quantum Information Processing with Modular Networks

    NASA Astrophysics Data System (ADS)

    Crocker, Clayton; Inlek, Ismail V.; Hucul, David; Sosnova, Ksenia; Vittorini, Grahame; Monroe, Chris

    2015-05-01

    Trapped atomic ions are qubit standards for the production of entangled states in quantum information science and metrology applications. Trapped ions can exhibit very long coherence times, external fields can drive strong local interactions via phonons, and remote qubits can be entangled via photons. Transferring quantum information across spatially separated ion trap modules for a scalable quantum network architecture relies on the juxtaposition of both phononic and photonic buses. We report the successful combination of these protocols within and between two ion trap modules on a unit structure of this architecture where the remote entanglement generation rate exceeds the experimentally measured decoherence rate. Additionally, we report an experimental implementation of a technique to maintain phase coherence between spatially and temporally distributed quantum gate operations, a crucial prerequisite for scalability. Finally, we discuss our progress towards addressing the issue of uncontrolled cross-talk between photonic qubits and memory qubits by implementing a second ion species, Barium, to generate the photonic link. This work is supported by the ARO with funding from the IARPA MQCO program, the DARPA Quiness Program, the ARO MURI on Hybrid Quantum Circuits, the AFOSR MURI on Quantum Transduction, and the NSF Physics Frontier Center at JQI.

  18. The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing/Archival Methodology, and First Results

    NASA Technical Reports Server (NTRS)

    Blakelee, Richard

    1999-01-01

    A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measurement Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/MSFC are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.

  19. The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing/Archival Methodology, and First Results

    NASA Technical Reports Server (NTRS)

    Blakeslee, Rich; Bailey, Jeff; Koshak, Bill

    1999-01-01

    A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/ Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/Marshall Space Flight Center (MSFC) are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.

  20. IT vendor selection model by using structural equation model & analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Maitra, Sarit; Dominic, P. D. D.

    2012-11-01

    Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

  1. Analytical solution of steady-state equations for chemical reaction networks with bilinear rate laws.

    PubMed

    Halász, Adám M; Lai, Hong-Jian; McCabe Pryor, Meghan; Radhakrishnan, Krishnan; Edwards, Jeremy S

    2013-01-01

    True steady states are a rare occurrence in living organisms, yet their knowledge is essential for quasi-steady-state approximations, multistability analysis, and other important tools in the investigation of chemical reaction networks (CRN) used to describe molecular processes on the cellular level. Here, we present an approach that can provide closed form steady-state solutions to complex systems, resulting from CRN with binary reactions and mass-action rate laws. We map the nonlinear algebraic problem of finding steady states onto a linear problem in a higher-dimensional space. We show that the linearized version of the steady-state equations obeys the linear conservation laws of the original CRN. We identify two classes of problems for which complete, minimally parameterized solutions may be obtained using only the machinery of linear systems and a judicious choice of the variables used as free parameters. We exemplify our method, providing explicit formulae, on CRN describing signal initiation of two important types of RTK receptor-ligand systems, VEGF and EGF-ErbB1.

  2. Analytical Solution of Steady State Equations for Chemical Reaction Networks with Bilinear Rate Laws

    PubMed Central

    Halász, Ádám M.; Lai, Hong-Jian; McCabe, Meghan M.; Radhakrishnan, Krishnan; Edwards, Jeremy S.

    2014-01-01

    True steady states are a rare occurrence in living organisms, yet their knowledge is essential for quasi-steady state approximations, multistability analysis, and other important tools in the investigation of chemical reaction networks (CRN) used to describe molecular processes on the cellular level. Here we present an approach that can provide closed form steady-state solutions to complex systems, resulting from CRN with binary reactions and mass-action rate laws. We map the nonlinear algebraic problem of finding steady states onto a linear problem in a higher dimensional space. We show that the linearized version of the steady state equations obeys the linear conservation laws of the original CRN. We identify two classes of problems for which complete, minimally parameterized solutions may be obtained using only the machinery of linear systems and a judicious choice of the variables used as free parameters. We exemplify our method, providing explicit formulae, on CRN describing signal initiation of two important types of RTK receptor-ligand systems, VEGF and EGF-ErbB1. PMID:24334389

  3. Characteristic Functions and Process Identification by Neural Networks.

    PubMed

    Vilela Mendes, Rui; Dente, Joaquim A.

    1997-11-01

    Principal component analysis (PCA) algorithms use neural networks to extract the eigenvectors of the correlation matrix from the data. However, if the process is non-Gaussian, PCA algorithms or their higher order generalisations provide only incomplete or misleading information on the statistical properties of the data. To handle such situations we propose neural network algorithms, with an hybrid (supervised and unsupervised) learning scheme, which constructs the characteristic function of the probability distribution and the transition functions of the stochastic process. Illustrative examples are presented, which include Cauchy and Lévy-type processes.

  4. Review of neural network modelling of cracking process

    NASA Astrophysics Data System (ADS)

    Rosli, M. N.; Aziz, N.

    2016-11-01

    Cracking process is a very important process that converts low value products into high value products such as conversion of naphtha into ethylene and propylene. The process is nonlinear with extensive reaction network. Thus, nonlinear technique such as artificial neural network is explored to develop the model of the system. The paper will review and discuss the research works done on the technique in modelling cracking process using artificial neural network starting from early 1990s until recent development in 2015. Timeline is provided to show progression of work done throughout the years, the main issues addressed, and the proposed techniques for each. In the next section, the main objective of each work and each techniques explored by previous researchers is discussed in more detail. A table that summarizes previous works is provided to show common works done throughout the years. Lastly, potential gap for future works in the area is highlighted.

  5. Cortical network architecture for context processing in primate brain

    PubMed Central

    Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

    2015-01-01

    Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

  6. A multisensory network for olfactory processing

    PubMed Central

    Maier, Joost X.; Blankenship, Meredith L.; Li, Jennifer X.; Katz, Donald B.

    2015-01-01

    Summary Primary gustatory cortex (GC) is connected (both mono- and poly-synaptically) to primary olfactory (piriform) cortex (PC)—connections that might be hypothesized to underlie the construction of a “flavor” percept when both gustatory and olfactory stimuli are present. Here, we use multi-site electrophysiology and optical inhibition of GC neurons (GCx, produced via infection with ArchT) to demonstrate that, indeed, during gustatory stimulation, taste-selective information is transmitted from GC to PC. We go on to show that these connections impact olfactory processing even in the absence of gustatory stimulation: GCx alters PC responses to olfactory stimuli presented alone, enhancing some and eliminating others, despite leaving the path from nasal epithelium to PC intact. Finally, we show the functional importance of this latter phenomenon, demonstrating that GCx renders rats unable to properly recognize odor stimuli. This sequence of findings suggests that sensory processing may be more intrinsically integrative than previously thought. PMID:26441351

  7. Prediction and control of chaotic processes using nonlinear adaptive networks

    SciTech Connect

    Jones, R.D.; Barnes, C.W.; Flake, G.W.; Lee, K.; Lewis, P.S.; O'Rouke, M.K.; Qian, S.

    1990-01-01

    We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

  8. Scenes for Social Information Processing in Adolescence: Item and factor analytic procedures for psychometric appraisal.

    PubMed

    Vagos, Paula; Rijo, Daniel; Santos, Isabel M

    2016-04-01

    Relatively little is known about measures used to investigate the validity and applications of social information processing theory. The Scenes for Social Information Processing in Adolescence includes items built using a participatory approach to evaluate the attribution of intent, emotion intensity, response evaluation, and response decision steps of social information processing. We evaluated a sample of 802 Portuguese adolescents (61.5% female; mean age = 16.44 years old) using this instrument. Item analysis and exploratory and confirmatory factor analytic procedures were used for psychometric examination. Two measures for attribution of intent were produced, including hostile and neutral; along with 3 emotion measures, focused on negative emotional states; 8 response evaluation measures; and 4 response decision measures, including prosocial and impaired social behavior. All of these measures achieved good internal consistency values and fit indicators. Boys seemed to favor and choose overt and relational aggression behaviors more often; girls conveyed higher levels of neutral attribution, sadness, and assertiveness and passiveness. The Scenes for Social Information Processing in Adolescence achieved adequate psychometric results and seems a valuable alternative for evaluating social information processing, even if it is essential to continue investigation into its internal and external validity.

  9. The physics of spreading processes in multilayer networks

    NASA Astrophysics Data System (ADS)

    de Domenico, Manlio; Granell, Clara; Porter, Mason A.; Arenas, Alex

    2016-10-01

    Despite the success of traditional network analysis, standard networks provide a limited representation of complex systems, which often include different types of relationships (or `multiplexity’) between their components. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and be a major obstacle towards attempts to understand complex systems. The recent multilayer approach for modelling networked systems explicitly allows the incorporation of multiplexity and other features of realistic systems. It allows one to couple different structural relationships by encoding them in a convenient mathematical object. It also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping to achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remain hidden when using ordinary graphs, the traditional network representation. Here we survey progress towards attaining a deeper understanding of spreading processes on multilayer networks, and we highlight some of the physical phenomena related to spreading processes that emerge from multilayer structure.

  10. Parallel plan execution with self-processing networks

    NASA Technical Reports Server (NTRS)

    Dautrechy, C. Lynne; Reggia, James A.

    1989-01-01

    A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities is being explored. Goals are to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, a model of the execution of a Spaceworld plan was implemented. This is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. It is shown that plan execution, a task usually solved using traditional artificial intelligence (AI) techniques, can be accomplished using a self-processing network. The fact that self-processing networks were applied to other space-related tasks, in addition to the one discussed here, demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. It is also demonstrated that MIRRORS/II is a powerful environment for the development and evaluation of self-processing systems.

  11. Stupidity in the analytic field: Vicissitudes of the detachment process in adolescence.

    PubMed

    Cassorla, Roosevelt M S

    2017-04-01

    This paper has the objective of broadening the understanding of technical aspects in working with adolescents who defend themselves against detachment from infantile aspects through defensive organizations. These organizations numb the adolescent toward both triangular reality and narcissistic defenses. The families of such young people may be part of the organization and the analyst can also be recruited to participate in it. But the analyst's perception can become blurry and this fact makes him appear stupid. Aspects of the myths of Narcissus and Oedipus are used here as models for studying stupidity. The analysis of a psychotic teenage girl who is symbiotic in relation to her family shows how the analytical field can be invaded by defensive configurations. Collusions of idealization and domination/submission involve the young person, her family and the analyst but the defensive organizations are only identified after their traumatic breakdown. The expansion of the symbolic network allows symbiotic transgenerational organizations to be identified, while models related to enactments prove helpful for understanding technical ups and downs. The paper ends with imaginative conjectures where Oedipus, as 'patient', is compared to the patient discussed here. These conjectures lead to reinterpretations of aspects of the Oedipus myth. The reinterpretations, together with the theoretical and clinical study, may serve as models for understanding the technical ups and downs in working with troubled teens.

  12. The Challenge of Understanding Process in Clinical Behavior Analysis: The Case of Functional Analytic Psychotherapy

    PubMed Central

    Follette, William C; Bonow, Jordan T

    2009-01-01

    Whether explicitly acknowledged or not, behavior-analytic principles are at the heart of most, if not all, empirically supported therapies. However, the change process in psychotherapy is only now being rigorously studied. Functional analytic psychotherapy (FAP; Kohlenberg & Tsai, 1991; Tsai et al., 2009) explicitly identifies behavioral-change principles used to bring about therapeutic improvements in adult outpatients whose clinical problems stem from ineffective interpersonal repertoires. These principles include contingent responding to behavioral excesses and deficits by a therapist who has established him- or herself as a salient source of social reinforcement. Empirical support for FAP is emerging, but a variety of pragmatic and theoretical questions warrant investigation. Among the issues described in this paper are the training and dissemination of procedures for how to conduct a functional analysis, how to train therapists to identify functional stimulus classes, how to best address decreasing problem behavior without creating an aversive environment, how to enhance generalization, and how to account for the principle of equifinality when trying to specify therapeutic procedures. These and other issues stem largely from trying to disseminate a behavioral principle-based intervention rather than a topographically specified intervention. These issues present challenges and research opportunities for applied clinical behavior analysts if they wish to extend their science to address clinical issues important to the treatment of adult outpatients with normal intellectual functioning. PMID:22478517

  13. Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex

    PubMed Central

    Wang, Quanxin; Sporns, Olaf; Burkhalter, Andreas

    2012-01-01

    Much of the information used for visual perception and visually guided actions is processed in complex networks of connections within the cortex. To understand how this works in the normal brain and to determine the impact of disease, mice are promising models. In primate visual cortex, information is processed in a dorsal stream specialized for visuospatial processing and guided action and a ventral stream for object recognition. Here, we traced the outputs of 10 visual areas and used quantitative graph analytic tools of modern network science to determine, from the projection strengths in 39 cortical targets, the community structure of the network. We found a high density of the cortical graph that exceeded that previously shown in monkey. Each source area showed a unique distribution of projection weights across its targets (i.e. connectivity profile) that was well-fit by a lognormal function. Importantly, the community structure was strongly dependent on the location of the source area: outputs from medial/anterior extrastriate areas were more strongly linked to parietal, motor and limbic cortex, whereas lateral extrastriate areas were preferentially connected to temporal and parahippocampal cortex. These two subnetworks resemble dorsal and ventral cortical streams in primates, demonstrating that the basic layout of cortical networks is conserved across species. PMID:22457489

  14. Development of analytic intermodal freight networks for use within a GIS

    SciTech Connect

    Southworth, F.; Xiong, D.; Middendorf, D.

    1997-05-01

    The paper discusses the practical issues involved in constructing intermodal freight networks that can be used within GIS platforms to support inter-regional freight routing and subsequent (for example, commodity flow) analysis. The procedures described can be used to create freight-routable and traffic flowable interstate and intermodal networks using some combination of highway, rail, water and air freight transportation. Keys to realistic freight routing are the identification of intermodal transfer locations and associated terminal functions, a proper handling of carrier-owned and operated sub-networks within each of the primary modes of transport, and the ability to model the types of carrier services being offered.

  15. Modeling socio-cultural processes in network-centric environments

    NASA Astrophysics Data System (ADS)

    Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

    2012-05-01

    The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

  16. Strategy for design NIR calibration sets based on process spectrum and model space: An innovative approach for process analytical technology.

    PubMed

    Cárdenas, V; Cordobés, M; Blanco, M; Alcalà, M

    2015-10-10

    The pharmaceutical industry is under stringent regulations on quality control of their products because is critical for both, productive process and consumer safety. According to the framework of "process analytical technology" (PAT), a complete understanding of the process and a stepwise monitoring of manufacturing are required. Near infrared spectroscopy (NIRS) combined with chemometrics have lately performed efficient, useful and robust for pharmaceutical analysis. One crucial step in developing effective NIRS-based methodologies is selecting an appropriate calibration set to construct models affording accurate predictions. In this work, we developed calibration models for a pharmaceutical formulation during its three manufacturing stages: blending, compaction and coating. A novel methodology is proposed for selecting the calibration set -"process spectrum"-, into which physical changes in the samples at each stage are algebraically incorporated. Also, we established a "model space" defined by Hotelling's T(2) and Q-residuals statistics for outlier identification - inside/outside the defined space - in order to select objectively the factors to be used in calibration set construction. The results obtained confirm the efficacy of the proposed methodology for stepwise pharmaceutical quality control, and the relevance of the study as a guideline for the implementation of this easy and fast methodology in the pharma industry.

  17. Introducing diffusing wave spectroscopy as a process analytical tool for pharmaceutical emulsion manufacturing.

    PubMed

    Reufer, Mathias; Machado, Alexandra H E; Niederquell, Andreas; Bohnenblust, Katharina; Müller, Beat; Völker, Andreas Charles; Kuentz, Martin

    2014-12-01

    Emulsions are widely used for pharmaceutical, food, and cosmetic applications. To guarantee that their critical quality attributes meet specifications, it is desirable to monitor the emulsion manufacturing process. However, finding of a suitable process analyzer has so far remained challenging. This article introduces diffusing wave spectroscopy (DWS) as an at-line technique to follow the manufacturing process of a model oil-in-water pharmaceutical emulsion containing xanthan gum. The DWS results were complemented with mechanical rheology, microscopy analysis, and stability tests. DWS is an advanced light scattering technique that assesses the microrheology and in general provides information on the dynamics and statics of dispersions. The obtained microrheology results showed good agreement with those obtained with bulk rheology. Although no notable changes in the rheological behavior of the model emulsions were observed during homogenization, the intensity correlation function provided qualitative information on the evolution of the emulsion dynamics. These data together with static measurements of the transport mean free path (l*) correlated very well with the changes in droplet size distribution occurring during the emulsion homogenization. This study shows that DWS is a promising process analytical technology tool for development and manufacturing of pharmaceutical emulsions.

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

    PubMed

    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.

  19. Group decision making with the analytic hierarchy process in benefit-risk assessment: a tutorial.

    PubMed

    Hummel, J Marjan; Bridges, John F P; IJzerman, Maarten J

    2014-01-01

    The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee.

  20. Analytic hierarchy process as module for productivity evaluation and decision-making of the operation theater.

    PubMed

    Ezzat, Abdelrahman E M; Hamoud, Hesham S

    2016-01-01

    The analytic hierarchy process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgments of experts to derive priority scales, these scales that measure intangibles in relative terms. The aim of the article was to develop a model for productivity measurement of the operation theater (OT), which could be applied as a model for quality improvement and decision-making. AHP is used in this article to evolve such a model. The steps consist of identifying the critical success factors for measuring the productivity of OT, identifying subfactors that inflauence the critical factors, comparing the pairwise, deriving their relative importance and ratings, and calculating the cumulative effect according to the attributes in OT. The cumulative productivitycan be calculated by the end and can be compared Ideal productivity to measure the productive of OT in percentage fraction. Hence, the productivity could be calculated. Hence, AHP is a very useful model to measure the productivity in OT.

  1. Stakeholder prioritization of zoonoses in Japan with analytic hierarchy process method.

    PubMed

    Kadohira, M; Hill, G; Yoshizaki, R; Ota, S; Yoshikawa, Y

    2015-05-01

    There exists an urgent need to develop iterative risk assessment strategies of zoonotic diseases. The aim of this study is to develop a method of prioritizing 98 zoonoses derived from animal pathogens in Japan and to involve four major groups of stakeholders: researchers, physicians, public health officials, and citizens. We used a combination of risk profiling and analytic hierarchy process (AHP). Profiling risk was accomplished with semi-quantitative analysis of existing public health data. AHP data collection was performed by administering questionnaires to the four stakeholder groups. Results showed that researchers and public health officials focused on case fatality as the chief important factor, while physicians and citizens placed more weight on diagnosis and prevention, respectively. Most of the six top-ranked diseases were similar among all stakeholders. Transmissible spongiform encephalopathy, severe acute respiratory syndrome, and Ebola fever were ranked first, second, and third, respectively.

  2. Paper-based analytical devices for electrochemical study of the breathing process of red blood cells.

    PubMed

    Lin, Xiang-Yun; Wu, Ling-Ling; Pan, Zhong-Qin; Shi, Chuan-Guo; Bao, Ning; Gu, Hai-Ying

    2015-04-01

    Herein we utilized the filter paper to physically trap red blood cells (RBC) to observe the breathing process of red blood cells based on the permeability of the filter paper. By integrating double-sided conductive carbon tape as the working electrodes, the device could be applied to monitor electrochemical responses of RBC for up to hundreds of minutes. The differential pulse voltammetry (DPV) peak currents increased under oxygen while decreased under nitrogen, indicating that RBC could take in and release oxygen. Further studies demonstrated that the RBC suspension could more effectively take in oxygen than the solution of hemoglobin and the supernatant of RBC, suggesting the natural advantage of RBC on oxygen transportation. This study implied that simple paper-based analytical devices might be effectively applied in the study of gas-participating reactions and biochemical detections.

  3. Using the analytical hierarchy process to assess the environmental vulnerabilities of basins in Taiwan.

    PubMed

    Chang, Chia-Ling; Chao, Yu-Chi

    2012-05-01

    Every year, Taiwan endures typhoons and earthquakes; these natural hazards often induce landslides and debris flows. Therefore, watershed management strategies must consider the environmental vulnerabilities of local basins. Because many factors affect basin ecosystems, this study applied multiple criteria analysis and the analytical hierarchy process (AHP) to evaluate seven criteria in three phases (geographic phase, hydrologic phase, and societal phase). This study focused on five major basins in Taiwan: the Tan-Shui River Basin, the Ta-Chia River Basin, the Cho-Shui River Basin, the Tseng-Wen River Basin, and the Kao-Ping River Basin. The objectives were a comprehensive examination of the environmental characteristics of these basins and a comprehensive assessment of their environmental vulnerabilities. The results of a survey and AHP analysis showed that landslide area is the most important factor for basin environmental vulnerability. Of all these basins, the Cho-Shui River Basin in central Taiwan has the greatest environmental vulnerability.

  4. [Applying analytical hierarchy process to assess eco-environment quality of Heilongjiang province].

    PubMed

    Li, Song; Qiu, Wei; Zhao, Qing-liang; Liu, Zheng-mao

    2006-05-01

    The analytical hierarchy process (AHP) was adopted to study the index system of eco-province and the index system was set up for eco-province construction. The comparison matrix was constructed on the basis of experts' investigation questionnaires. MATLAB 6.5 was used to confirm the weights of the indices. The general environment quality index model was used to grade the environment quality and assessed the progress of constructing eco-province in Heilongjiang province. The results indicate that it is feasible to apply the AHP to assess quantitatively the ecological environmental quality province-wide. The ecological environment quality of Heilongjiang province has been improved obviously from the beginning of eco-province construction.

  5. Priority survey between indicators and analytic hierarchy process analysis for green chemistry technology assessment

    PubMed Central

    Kim, Sungjune; Hong, Seokpyo; Ahn, Kilsoo; Gong, Sungyong

    2015-01-01

    Objectives This study presents the indicators and proxy variables for the quantitative assessment of green chemistry technologies and evaluates the relative importance of each assessment element by consulting experts from the fields of ecology, chemistry, safety, and public health. Methods The results collected were subjected to an analytic hierarchy process to obtain the weights of the indicators and the proxy variables. Results These weights may prove useful in avoiding having to resort to qualitative means in absence of weights between indicators when integrating the results of quantitative assessment by indicator. Conclusions This study points to the limitations of current quantitative assessment techniques for green chemistry technologies and seeks to present the future direction for quantitative assessment of green chemistry technologies. PMID:26206364

  6. Testing and analytical modelling for the purging process of a cryogenic line

    NASA Astrophysics Data System (ADS)

    Hedayat, A.; Mazurkivich, P. V.; Nelson, M. A.; Majumdar, A. K.

    2015-12-01

    To gain confidence in developing analytical models of the purging process for the cryogenic main propulsion systems of the upper stage, two test series were conducted. The test article, 3.35 m long with a 20-cm-diameter incline line, was filled with liquid or gaseous hydrogen and then purged with gaseous helium (GHe). A total of 10 tests were conducted. The influences of GHe flow rates and initial temperatures were evaluated. The Generalized Fluid System Simulation Program (GFSSP), an in-house general purpose fluid system analyzer computer program, was utilized to model and simulate selective tests. The test procedures, modelling descriptions, and the results are presented in the accompanying text.

  7. [Advance of studies on metabolic fingerprinting analytical techniques and data processing methods].

    PubMed

    Gao, Jian; Yang, Geng-liang; Yang, Hong-jun; Xu, Hai-yu; Li, Shao-jing

    2012-09-01

    Metabolomics is an emerging discipline subsequent to genomics, transcriptomics and proteomics, aiming for systematically studying the regularity of changes in metabolite to revealing organism's nature of movement and metabolism. It is especially important in modern pharmacological studies. Metabolic fingerprinting analysis is a method for metabolic analysis on high throughput of all metabolites, studying changes in drugs, organisms and endogenic metabolites caused by drugs and finding out related biomarkers to reflect dynamic changes inside organisms more directly and explain the mechanism of drugs and their effects on diseases. This essay summarizes some new metabolic fingerprint analytical methods and data processing methods used for metabolic fingerprint, elaborates their advantages and disadvantages and looks ahead to their combination with studies on traditional Chinese medicines, providing room for the development of new methods and new approaches for studies on complexity theory system of traditional Chinese medicines.

  8. Flavor pleasantness processing in the ventral emotion network

    PubMed Central

    Weitkamp, Liselore; Renken, Remco J.; Nanetti, Luca; ter Horst, Gert J.

    2017-01-01

    The ventral emotion network–encompassing the amygdala, insula, ventral striatum, and ventral regions of the prefrontal cortex–has been associated with the identification of emotional significance of perceived external stimuli and the production of affective states. Functional magnetic resonance imaging (fMRI) studies investigating chemosensory stimuli have associated parts of this network with pleasantness coding. In the current study, we independently analyzed two datasets in which we measured brain responses to flavor stimuli in young adult men. In the first dataset, participants evaluated eight regular off the shelf drinking products while participants evaluated six less familiar oral nutritional supplements (ONS) in the second dataset. Participants provided pleasantness ratings 20 seconds after tasting. Using independent component analysis (ICA) and mixed effect models, we identified one brain network in the regular products dataset that was associated with flavor pleasantness. This network was very similar to the ventral emotion network. Although we identified an identical network in the ONS dataset using ICA, we found no linear relation between activation of any network and pleasantness scores within this dataset. Our results indicate that flavor pleasantness is processed in a network encompassing amygdala, ventral prefrontal, insular, striatal and parahippocampal regions for familiar drinking products. For more unfamiliar ONS products the association is not obvious, which could be related to the unfamiliarity of these products. PMID:28207751

  9. Beyond business process redesign: redefining Baxter's business network.

    PubMed

    Short, J E; Venkatraman, N

    1992-01-01

    Business process redesign has focused almost exclusively on improving the firm's internal operations. Although internal efficiency and effectiveness are important objectives, the authors argue that business network redesign--reconceptualizing the role of the firm and its key business processes in the larger business network--is of greater strategic importance. To support their argument, they analyze the evolution of Baxter's ASAP system, one of the most publicized but inadequately understood strategic information systems of the 1980s. They conclude by examining whether ASAP's early successes have positioned the firm well for the changing hospital supplies marketplace of the 1990s.

  10. Natural Language Processing Neural Network Considering Deep Cases

    NASA Astrophysics Data System (ADS)

    Sagara, Tsukasa; Hagiwara, Masafumi

    In this paper, we propose a novel neural network considering deep cases. It can learn knowledge from natural language documents and can perform recall and inference. Various techniques of natural language processing using Neural Network have been proposed. However, natural language sentences used in these techniques consist of about a few words, and they cannot handle complicated sentences. In order to solve these problems, the proposed network divides natural language sentences into a sentence layer, a knowledge layer, ten kinds of deep case layers and a dictionary layer. It can learn the relations among sentences and among words by dividing sentences. The advantages of the method are as follows: (1) ability to handle complicated sentences; (2) ability to restructure sentences; (3) usage of the conceptual dictionary, Goi-Taikei, as the long term memory in a brain. Two kinds of experiments were carried out by using goo dictionary and Wikipedia as knowledge sources. Superior performance of the proposed neural network has been confirmed.

  11. Applications of neural networks to process control and modeling

    SciTech Connect

    Barnes, C.W.; Brown, S.K.; Flake, G.W.; Jones, R.D.; O'Rourke, M.K.; Lee, Y.C.

    1991-01-01

    Modeling and control of physical processes are universal parts of modern life, from control of chemical plants to riding a bicycle. Often, an effective model of the process is not known so that traditional control theory is of little use. If a process can be represented by a set of a data which captures it behavior over a range of parameter settings, a neural net can inductively model the process and form the basis of an optimization procedure. We present a neural network architecture which is particularly effective in process modeling and control. We discuss its effectiveness in several application areas as well as some of the non-ideal characteristics present in real control problems which effect the form and style of the network architecture and learning algorithm. 8 refs., 6 figs.

  12. Recurrent networks with recursive processing elements: paradigm for dynamical computing

    NASA Astrophysics Data System (ADS)

    Farhat, Nabil H.; del Moral Hernandez, Emilio

    1996-11-01

    It was shown earlier that models of cortical neurons can, under certain conditions of coherence in their input, behave as recursive processing elements (PEs) that are characterized by an iterative map on the phase interval and by bifurcation diagrams that demonstrate the complex encoding cortical neurons might be able to perform on their input. Here we present results of numerical experiments carried on a recurrent network of such recursive PEs modeled by the logistic map. Network behavior is studied under a novel scheme for generating complex spatio-temporal input patterns that could range from being coherent to partially coherent to being completely incoherent. A nontraditional nonlinear coupling scheme between neurons is employed to incorporate recent findings in brain science, namely that neurons use more than one kind of neurotransmitter in their chemical signaling. It is shown that such network shave the capacity to 'self-anneal' or collapse into period-m attractors that are uniquely related to the stimulus pattern following a transient 'chaotic' period during which the network searches it state-space for the associated dynamic attractor. The network accepts naturally both dynamical or stationary input patterns. Moreover we find that the use of quantized coupling strengths, introduced to reflect recent molecular biology and neurophysiological reports on synapse dynamics, endows the network with clustering ability wherein, depending ont eh stimulus pattern, PEs in the network with clustering ability wherein, depending on the stimulus pattern, PEs in the network divide into phase- locked groups with the PEs in each group being synchronized in period-m orbits. The value of m is found to be the same for all clusters and the number of clusters gives the dimension of the periodic attractor. The implications of these findings for higher-level processing such as feature- binding and for the development of novel learning algorithms are briefly discussed.

  13. Dynamics of sensory thalamocortical synaptic networks during information processing states.

    PubMed

    Castro-Alamancos, Manuel A

    2004-11-01

    The thalamocortical network consists of the pathways that interconnect the thalamus and neocortex, including thalamic sensory afferents, corticothalamic and thalamocortical pathways. These pathways are essential to acquire, analyze, store and retrieve sensory information. However, sensory information processing mostly occurs during behavioral arousal, when activity in thalamus and neocortex consists of an electrographic sign of low amplitude fast activity, known as activation, which is caused by several neuromodulator systems that project to the thalamocortical network. Logically, in order to understand how the thalamocortical network processes sensory information it is essential to study its response properties during states of activation. This paper reviews the temporal and spatial response properties of synaptic pathways in the whisker thalamocortical network of rodents during activated states as compared to quiescent (non-activated) states. The evidence shows that these pathways are differentially regulated via the effects of neuromodulators as behavioral contingencies demand. Thus, during activated states, the temporal and spatial response properties of pathways in the thalamocortical network are transformed to allow the processing of sensory information.

  14. Two Distinct Scene-Processing Networks Connecting Vision and Memory

    PubMed Central

    Esteva, Andre; Fei-Fei, Li

    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. PMID:27822493

  15. The network formation assay: a spatially standardized neurite outgrowth analytical display for neurotoxicity screening.

    PubMed

    Frimat, Jean-Philippe; Sisnaiske, Julia; Subbiah, Subanatarajan; Menne, Heike; Godoy, Patricio; Lampen, Peter; Leist, Marcel; Franzke, Joachim; Hengstler, Jan G; van Thriel, Christoph; West, Jonathan

    2010-03-21

    We present a rapid, reproducible and sensitive neurotoxicity testing platform that combines the benefits of neurite outgrowth analysis with cell patterning. This approach involves patterning neuronal cells within a hexagonal array to standardize the distance between neighbouring cellular nodes, and thereby standardize the length of the neurite interconnections. This feature coupled with defined assay coordinates provides a streamlined display for rapid and sensitive analysis. We have termed this the network formation assay (NFA). To demonstrate the assay we have used a novel cell patterning technique involving thin film poly(dimethylsiloxane) (PDMS) microcontact printing. Differentiated human SH-SY5Y neuroblastoma cells colonized the array with high efficiency, reliably producing pattern occupancies above 70%. The neuronal array surface supported neurite outgrowth, resulting in the formation of an interconnected neuronal network. Exposure to acrylamide, a neurotoxic reference compound, inhibited network formation. A dose-response curve from the NFA was used to determine a 20% network inhibition (NI(20)) value of 260 microM. This concentration was approximately 10-fold lower than the value produced by a routine cell viability assay, and demonstrates that the NFA can distinguish network formation inhibitory effects from gross cytotoxic effects. Inhibition of the mitogen-activated protein kinase (MAPK) ERK1/2 and phosphoinositide-3-kinase (PI-3K) signaling pathways also produced a dose-dependent reduction in network formation at non-cytotoxic concentrations. To further refine the assay a simulation was developed to manage the impact of pattern occupancy variations on network formation probability. Together these developments and demonstrations highlight the potential of the NFA to meet the demands of high-throughput applications in neurotoxicology and neurodevelopmental biology.

  16. Analytical methods to characterize heterogeneous raw material for thermal spray process: cored wire Inconel 625

    NASA Astrophysics Data System (ADS)

    Lindner, T.; Bonebeau, S.; Drehmann, R.; Grund, T.; Pawlowski, L.; Lampke, T.

    2016-03-01

    In wire arc spraying, the raw material needs to exhibit sufficient formability and ductility in order to be processed. By using an electrically conductive, metallic sheath, it is also possible to handle non-conductive and/or brittle materials such as ceramics. In comparison to massive wire, a cored wire has a heterogeneous material distribution. Due to this fact and the complex thermodynamic processes during wire arc spraying, it is very difficult to predict the resulting chemical composition in the coating with sufficient accuracy. An Inconel 625 cored wire was used to investigate this issue. In a comparative study, the analytical results of the raw material were compared to arc sprayed coatings and droplets, which were remelted in an arc furnace under argon atmosphere. Energy-dispersive X-ray spectroscopy (EDX) and X-ray fluorescence (XRF) analysis were used to determine the chemical composition. The phase determination was performed by X-ray diffraction (XRD). The results were related to the manufacturer specifications and evaluated in respect to differences in the chemical composition. The comparison between the feedstock powder, the remelted droplets and the thermally sprayed coatings allows to evaluate the influence of the processing methods on the resulting chemical and phase composition.

  17. High temperature and dynamic testing of AHSS for an analytical description of the adiabatic cutting process

    NASA Astrophysics Data System (ADS)

    Winter, S.; Schmitz, F.; Clausmeyer, T.; Tekkaya, A. E.; F-X Wagner, M.

    2017-03-01

    In the automotive industry, advanced high strength steels (AHSS) are widely used as sheet part components to reduce weight, even though this leads to several challenges. The demand for high-quality shear cutting surfaces that do not require reworking can be fulfilled by adiabatic shear cutting: High strain rates and local temperatures lead to the formation of adiabatic shear bands (ASB). While this process is well suited to produce AHSS parts with excellent cutting surface quality, a fundamental understanding of the process is still missing today. In this study, compression tests in a Split-Hopkinson Pressure Bar with an initial strain rate of 1000 s-1 were performed in a temperature range between 200 °C and 1000 °C. The experimental results show that high strength steels with nearly the same mechanical properties at RT may possess a considerably different behavior at higher temperatures. The resulting microstructures after testing at different temperatures were analyzed by optical microscopy. The thermo-mechanical material behavior was then considered in an analytical model. To predict the local temperature increase that occurs during the adiabatic blanking process, experimentally determined flow curves were used. Furthermore, the influence of temperature evolution with respect to phase transformation is discussed. This study contributes to a more complete understanding of the relevant microstructural and thermo-mechanical mechanisms leading to the evolution of ASB during cutting of AHSS.

  18. Analytical tools employed to determine pharmaceutical compounds in wastewaters after application of advanced oxidation processes.

    PubMed

    Afonso-Olivares, Cristina; Montesdeoca-Esponda, Sarah; Sosa-Ferrera, Zoraida; Santana-Rodríguez, José Juan

    2016-12-01

    Today, the presence of contaminants in the environment is a topic of interest for society in general and for the scientific community in particular. A very large amount of different chemical substances reaches the environment after passing through wastewater treatment plants without being eliminated. This is due to the inefficiency of conventional removal processes and the lack of government regulations. The list of compounds entering treatment plants is gradually becoming longer and more varied because most of these compounds come from pharmaceuticals, hormones or personal care products, which are increasingly used by modern society. As a result of this increase in compound variety, to address these emerging pollutants, the development of new and more efficient removal technologies is needed. Different advanced oxidation processes (AOPs), especially photochemical AOPs, have been proposed as supplements to traditional treatments for the elimination of pollutants, showing significant advantages over the use of conventional methods alone. This work aims to review the analytical methodologies employed for the analysis of pharmaceutical compounds from wastewater in studies in which advanced oxidation processes are applied. Due to the low concentrations of these substances in wastewater, mass spectrometry detectors are usually chosen to meet the low detection limits and identification power required. Specifically, time-of-flight detectors are required to analyse the by-products.

  19. Process mapping as a tool for home health network analysis.

    PubMed

    Pluto, Delores M; Hirshorn, Barbara A

    2003-01-01

    Process mapping is a qualitative tool that allows service providers, policy makers, researchers, and other concerned stakeholders to get a "bird's eye view" of a home health care organizational network or a very focused, in-depth view of a component of such a network. It can be used to share knowledge about community resources directed at the older population, identify gaps in resource availability and access, and promote on-going collaborative interactions that encourage systemic policy reassessment and programmatic refinement. This article is a methodological description of process mapping, which explores its utility as a practice and research tool, illustrates its use in describing service-providing networks, and discusses some of the issues that are key to successfully using this methodology.

  20. Multiple-predators-based capture process on complex networks

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

    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 $\\alpha$. We derive the distribution of the lamb's lifetime and the expected lifetime $\\left\\langle T\\right\\rangle $. Through simulation, we find that the expected lifetime drops substantially with the increasing number of lions. We also study how the underlying topological structure affects the capture process, and obtain that locating on small-degree nodes is better than large-degree nodes to prolong the lifetime of the lamb. Moreover, dense or homogeneous network structures are against the survival of the lamb.

  1. Diffusion processes of fragmentary information on scale-free networks

    NASA Astrophysics Data System (ADS)

    Li, Xun; Cao, Lang

    2016-05-01

    Compartmental models of diffusion over contact networks have proven representative of real-life propagation phenomena among interacting individuals. However, there is a broad class of collective spreading mechanisms departing from compartmental representations, including those for diffusive objects capable of fragmentation and transmission unnecessarily as a whole. Here, we consider a continuous-state susceptible-infected-susceptible (SIS) model as an ideal limit-case of diffusion processes of fragmentary information on networks, where individuals possess fractions of the information content and update them by selectively exchanging messages with partners in the vicinity. Specifically, we incorporate local information, such as neighbors' node degrees and carried contents, into the individual partner choice, and examine the roles of a variety of such strategies in the information diffusion process, both qualitatively and quantitatively. Our method provides an effective and flexible route of modulating continuous-state diffusion dynamics on networks and has potential in a wide array of practical applications.

  2. The longitudinal use of SaNDVis: visual social network analytics in the enterprise.

    PubMed

    Perer, Adam; Guy, Ido; Uziel, Erel; Ronen, Inbal; Jacovi, Michal

    2013-07-01

    As people continue to author and share increasing amounts of information in social media, the opportunity to leverage such information for relationship discovery tasks increases. In this paper, we describe a set of systems that mine, aggregate, and infer a social graph from social media inside an enterprise, resulting in over 73 million relationships between 450,000 people. We then describe SaNDVis, a novel visual analytics tool that supports people-centric tasks like expertise location, team building, and team coordination in the enterprise. We provide details of a 22-month-long, large-scale deployment to over 2,300 users from which we analyze longitudinal usage patterns, classify types of visual analytics queries and users, and extract dominant use cases from log and interview data. By integrating social position, evidence, and facets into SaNDVis, we demonstrate how users can use a visual analytics tool to reflect on existing relationships as well as build new relationships in an enterprise setting.

  3. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Jaehan; Wu, Yik-Chung; Chaudhari, Qasim; Qaraqe, Khalid; Serpedin, Erchin

    2010-11-01

    Clock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated.

  4. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing.

  5. Guerrilla Warfare: A Word Processing Network Progress Report.

    ERIC Educational Resources Information Center

    Cepek, John R.; Vandercook, Elizabeth

    1984-01-01

    Without clear administrative support, a consultant's wisdom, or political harmony, but with much equipment already in place, two middle managers at the University of Illinois at Chicago worked to build a word processing network. Issues such as forging alliances, sharing resources, and creating administrative support are discussed. (Author/MLW)

  6. Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

    ERIC Educational Resources Information Center

    Moisl, Hermann

    It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

  7. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

  8. Brain Network Interactions in Auditory, Visual and Linguistic Processing

    ERIC Educational Resources Information Center

    Horwitz, Barry; Braun, Allen R.

    2004-01-01

    In the paper, we discuss the importance of network interactions between brain regions in mediating performance of sensorimotor and cognitive tasks, including those associated with language processing. Functional neuroimaging, especially PET and fMRI, provide data that are obtained essentially simultaneously from much of the brain, and thus are…

  9. An analytical method for 14C in environmental water based on a wet-oxidation process.

    PubMed

    Huang, Yan-Jun; Guo, Gui-Yin; Wu, Lian-Sheng; Zhang, Bing; Chen, Chao-Feng; Zhang, Hai-Ying; Qin, Hong-Juan; Shang-Guan, Zhi-Hong

    2015-04-01

    An analytical method for (14)C in environmental water based on a wet-oxidation process was developed. The method can be used to determine the activity concentrations of organic and inorganic (14)C in environmental water, or total (14)C, including in drinking water, surface water, rainwater and seawater. The wet-oxidation of the organic component allows the conversion of organic carbon to an inorganic form, and the extraction of the inorganic (14)C can be achieved by acidification and nitrogen purging. Environmental water with a volume of 20 L can be used for the wet-oxidation and extraction, and a detection limit of about 0.02 Bq/g(C) can be achieved for water with carbon content above 15 mg(C)/L, obviously lower than the natural level of (14)C in the environment. The collected carbon is sufficient for measurement with a low level liquid scintillation counter (LSC) for typical samples. Extraction or recovery experiments for inorganic carbon and organic carbon from typical materials, including analytical reagents of organic benzoquinone, sucrose, glutamic acid, nicotinic acid, humic acid, ethane diol, et cetera., were conducted with excellent results based on measurement on a total organic carbon analyzer and LSC. The recovery rate for inorganic carbon ranged tween 98.7%-99.0% with a mean of 98.9(± 0.1)%, for organic carbon recovery ranged between 93.8% and 100.0% with a mean of 97.1(± 2.6)%. Verification and an uncertainty budget of the method are also presented for a representative environmental water. The method is appropriate for (14)C analysis in environmental water, and can be applied also to the analysis of liquid effluent from nuclear facilities.

  10. A fuzzy neural network for intelligent data processing

    NASA Astrophysics Data System (ADS)

    Xie, Wei; Chu, Feng; Wang, Lipo; Lim, Eng Thiam

    2005-03-01

    In this paper, we describe an incrementally generated fuzzy neural network (FNN) for intelligent data processing. This FNN combines the features of initial fuzzy model self-generation, fast input selection, partition validation, parameter optimization and rule-base simplification. A small FNN is created from scratch -- there is no need to specify the initial network architecture, initial membership functions, or initial weights. Fuzzy IF-THEN rules are constantly combined and pruned to minimize the size of the network while maintaining accuracy; irrelevant inputs are detected and deleted, and membership functions and network weights are trained with a gradient descent algorithm, i.e., error backpropagation. Experimental studies on synthesized data sets demonstrate that the proposed Fuzzy Neural Network is able to achieve accuracy comparable to or higher than both a feedforward crisp neural network, i.e., NeuroRule, and a decision tree, i.e., C4.5, with more compact rule bases for most of the data sets used in our experiments. The FNN has achieved outstanding results for cancer classification based on microarray data. The excellent classification result for Small Round Blue Cell Tumors (SRBCTs) data set is shown. Compared with other published methods, we have used a much fewer number of genes for perfect classification, which will help researchers directly focus their attention on some specific genes and may lead to discovery of deep reasons of the development of cancers and discovery of drugs.

  11. Wireless integrated sensing, processing, and display networks for site security

    NASA Astrophysics Data System (ADS)

    Morrison, Rick L.; Brady, David J.; Rittgers, Andrew; Stack, Ronald A.

    2001-02-01

    We consider data management on ad hoc networks of sensing and processing nodes. We describe the construction of simple nodes from off the shelf components (PC 104 single board computers with flash memory, video capture cards and 802.1 lb wireless interfaces). We describe a Java interface to controlling these nodes and accessing images and image processing algorithms. We demonstrate target tracking across nodes and the potential for heterogeneous sensor types.

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

    SciTech Connect

    2011-02-24

    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 the scope of the data processing needs of CERN. Pulse is available as open-­-source and can be licensed both for non-­-commercial and commercial applications. FeedZai is interested in exploring possible synergies with CERN in high-­-volume low-­-latency data processing applications. The seminar will be structured in two sessions, the first one being aimed to expose the general scope of FeedZai's activities, and the second focused on Pulse itself: 10:00-11:00 FeedZai and Large Scale Data Processing Introduction to FeedZai FeedZai Pulse and Complex Event Processing Demonstration Use-Cases and Applications Conclusion and Q&A 11:00-11:15 Coffee break 11:15-12:30 FeedZai Pulse Under the Hood A First FeedZai Pulse Application PulseQL overview Defining KPIs and Baselines Conclusion and Q&A About the speakers Nuno Sebastião is the CEO of FeedZai. Having worked for many years for the European Space Agency (ESA), he was responsible the overall design and development of Satellite Simulation Infrastructure of the agency. Having left ESA to found FeedZai, Nuno is

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

    ScienceCinema

    None

    2016-07-12

    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 the scope of the data processing needs of CERN. Pulse is available as open-­-source and can be licensed both for non-­-commercial and commercial applications. FeedZai is interested in exploring possible synergies with CERN in high-­-volume low-­-latency data processing applications. The seminar will be structured in two sessions, the first one being aimed to expose the general scope of FeedZai's activities, and the second focused on Pulse itself: 10:00-11:00 FeedZai and Large Scale Data Processing Introduction to FeedZai FeedZai Pulse and Complex Event Processing Demonstration Use-Cases and Applications Conclusion and Q&A 11:00-11:15 Coffee break 11:15-12:30 FeedZai Pulse Under the Hood A First FeedZai Pulse Application PulseQL overview Defining KPIs and Baselines Conclusion and Q&A About the speakers Nuno Sebastião is the CEO of FeedZai. Having worked for many years for the European Space Agency (ESA), he was responsible the overall design and development of Satellite Simulation Infrastructure of the agency. Having left ESA to found FeedZai, Nuno is

  14. Reaction-diffusion processes and metapopulation models on duplex networks

    NASA Astrophysics Data System (ADS)

    Xuan, Qi; Du, Fang; Yu, Li; Chen, Guanrong

    2013-03-01

    Reaction-diffusion processes, used to model various spatially distributed dynamics such as epidemics, have been studied mostly on regular lattices or complex networks with simplex links that are identical and invariant in transferring different kinds of particles. However, in many self-organized systems, different particles may have their own private channels to keep their purities. Such division of links often significantly influences the underlying reaction-diffusion dynamics and thus needs to be carefully investigated. This article studies a special reaction-diffusion process, named susceptible-infected-susceptible (SIS) dynamics, given by the reaction steps β→α and α+β→2β, on duplex networks where links are classified into two groups: α and β links used to transfer α and β particles, which, along with the corresponding nodes, consist of an α subnetwork and a β subnetwork, respectively. It is found that the critical point of particle density to sustain reaction activity is independent of the network topology if there is no correlation between the degree sequences of the two subnetworks, and this critical value is suppressed or extended if the two degree sequences are positively or negatively correlated, respectively. Based on the obtained results, it is predicted that epidemic spreading may be promoted on positive correlated traffic networks but may be suppressed on networks with modules composed of different types of diffusion links.

  15. Competing spreading processes and immunization in multiplex networks

    NASA Astrophysics Data System (ADS)

    Gao, Bo; Deng, Zhenghong; Zhao, Dawei

    2016-12-01

    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.

  16. U.S. EPA's National Dioxin Air Monitoring Network: Analytical Issues

    EPA Science Inventory

    The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locatio...

  17. Analytical Study of different types Of network failure detection and possible remedies

    NASA Astrophysics Data System (ADS)

    Saxena, Shikha; Chandra, Somnath

    2012-07-01

    Faults in a network have various causes,such as the failure of one or more routers, fiber-cuts, failure of physical elements at the optical layer, or extraneous causes like power outages. These faults are usually detected as failures of a set of dependent logical entities and the links affected by the failed components. A reliable control plane plays a crucial role in creating high-level services in the next-generation transport network based on the Generalized Multiprotocol Label Switching (GMPLS) or Automatically Switched Optical Networks (ASON) model. In this paper, approaches to control-plane survivability, based on protection and restoration mechanisms, are examined. Procedures for the control plane state recovery are also discussed, including link and node failure recovery and the concepts of monitoring paths (MPs) and monitoring cycles (MCs) for unique localization of shared risk linked group (SRLG) failures in all-optical networks. An SRLG failure is a failure of multiple links due to a failure of a common resource. MCs (MPs) start and end at same (distinct) monitoring location(s). They are constructed such that any SRLG failure results in the failure of a unique combination of paths and cycles. We derive necessary and sufficient conditions on the set of MCs and MPs needed for localizing an SRLG failure in an arbitrary graph. Procedure of Protection and Restoration of the SRLG failure by backup re-provisioning algorithm have also been discussed.

  18. Tools for Large-Scale Data Analytic Examination of Relational and Epistemic Networks in Engineering Education

    ERIC Educational Resources Information Center

    Madhavan, Krishna; Johri, Aditya; Xian, Hanjun; Wang, G. Alan; Liu, Xiaomo

    2014-01-01

    The proliferation of digital information technologies and related infrastructure has given rise to novel ways of capturing, storing and analyzing data. In this paper, we describe the research and development of an information system called Interactive Knowledge Networks for Engineering Education Research (iKNEER). This system utilizes a framework…

  19. On-line near infrared monitoring of glycerol-boosted anaerobic digestion processes: evaluation of process analytical technologies.

    PubMed

    Holm-Nielsen, Jens Bo; Lomborg, Carina Juel; Oleskowicz-Popiel, Piotr; Esbensen, Kim H

    2008-02-01

    A study of NIR as a tool for process monitoring of thermophilic anaerobic digestion boosted by glycerol has been carried out, aiming at developing simple and robust Process Analytical Technology modalities for on-line surveillance in full scale biogas plants. Three 5 L laboratory fermenters equipped with on-line NIR sensor and special sampling stations were used as a basis for chemometric multivariate calibration. NIR characterisation using Transflexive Embedded Near Infra-Red Sensor (TENIRS) equipment integrated into an external recurrent loop on the fermentation reactors, allows for representative sampling, of the highly heterogeneous fermentation bio slurries. Glycerol is an important by-product from the increasing European bio-diesel production. Glycerol addition can boost biogas yields, if not exceeding a limiting 5-7 g L(-1) concentration inside the fermenter-further increase can cause strong imbalance in the anaerobic digestion process. A secondary objective was to evaluate the effect of addition of glycerol, in a spiking experiment which introduced increasing organic overloading as monitored by volatile fatty acids (VFA) levels. High correlation between on-line NIR determinations of glycerol and VFA contents has been documented. Chemometric regression models (PLS) between glycerol and NIR spectra needed no outlier removals and only one PLS-component was required. Test set validation resulted in excellent measures of prediction performance, precision: r(2) = 0.96 and accuracy = 1.04, slope of predicted versus reference fitting. Similar prediction statistics for acetic acid, iso-butanoic acid and total VFA proves that process NIR spectroscopy is able to quantify all pertinent levels of both volatile fatty acids and glycerol.

  20. Process analytical technology (PAT) in insect and mammalian cell culture processes: dielectric spectroscopy and focused beam reflectance measurement (FBRM).

    PubMed

    Druzinec, Damir; Weiss, Katja; Elseberg, Christiane; Salzig, Denise; Kraume, Matthias; Pörtner, Ralf; Czermak, Peter

    2014-01-01

    Modern bioprocesses demand for a careful definition of the critical process parameters (CPPs) already during the early stages of process development in order to ensure high-quality products and satisfactory yields. In this context, online monitoring tools can be applied to recognize unfavorable changes of CPPs during the production processes and to allow for early interventions in order to prevent losses of production batches due to quality issues. Process analytical technologies such as the dielectric spectroscopy or focused beam reflectance measurement (FBRM) are possible online monitoring tools, which can be applied to monitor cell growth as well as morphological changes. Since the dielectric spectroscopy only captures cells with intact cell membranes, even information about dead cells with ruptured or leaking cell membranes can be derived. The following chapter describes the application of dielectric spectroscopy on various virus-infected and non-infected cell lines with respect to adherent as well as suspension cultures in common stirred tank reactors. The adherent mammalian cell lines Vero (African green monkey kidney cells) and hMSC-TERT (telomerase-immortalized human mesenchymal stem cells) are thereby cultured on microcarrier, which provide the required growth surface and allow the cultivation of these cells even in dynamic culture systems. In turn, the insect-derived cell lines S2 and Sf21 are used as examples for cells typically cultured in suspension. Moreover, the FBRM technology as a further monitoring tool for cell culture applications has been included in this chapter using the example of Drosophila S2 insect cells.

  1. Introducing process analytical technology (PAT) in filamentous cultivation process development: comparison of advanced online sensors for biomass measurement.

    PubMed

    Rønnest, Nanna Petersen; Stocks, Stuart M; Eliasson Lantz, Anna; Gernaey, Krist V

    2011-10-01

    The recent process analytical technology (PAT) initiative has put an increased focus on online sensors to generate process-relevant information in real time. Specifically for fermentation, however, introduction of online sensors is often far from straightforward, and online measurement of biomass is one of the best examples. The purpose of this study was therefore to compare the performance of various online biomass sensors, and secondly to demonstrate their use in early development of a filamentous cultivation process. Eight Streptomyces coelicolor fed-batch cultivations were run as part of process development in which the pH, the feeding strategy, and the medium composition were varied. The cultivations were monitored in situ using multi-wavelength fluorescence (MWF) spectroscopy, scanning dielectric (DE) spectroscopy, and turbidity measurements. In addition, we logged all of the classical cultivation data, such as the carbon dioxide evolution rate (CER) and the concentration of dissolved oxygen. Prediction models for the biomass concentrations were estimated on the basis of the individual sensors and on combinations of the sensors. The results showed that the more advanced sensors based on MWF and scanning DE spectroscopy did not offer any advantages over the simpler sensors based on dual frequency DE spectroscopy, turbidity, and CER measurements for prediction of biomass concentration. By combining CER, DE spectroscopy, and turbidity measurements, the prediction error was reduced to 1.5 g/l, corresponding to 6% of the covered biomass range. Moreover, by using multiple sensors it was possible to check the quality of the individual predictions and switch between the sensors in real time.

  2. An experimental comparison of fuzzy logic and analytic hierarchy process for medical decision support systems.

    PubMed

    Uzoka, Faith-Michael Emeka; Obot, Okure; Barker, Ken; Osuji, J

    2011-07-01

    The task of medical diagnosis is a complex one, considering the level vagueness and uncertainty management, especially when the disease has multiple symptoms. A number of researchers have utilized the fuzzy-analytic hierarchy process (fuzzy-AHP) methodology in handling imprecise data in medical diagnosis and therapy. The fuzzy logic is able to handle vagueness and unstructuredness in decision making, while the AHP has the ability to carry out pairwise comparison of decision elements in order to determine their importance in the decision process. This study attempts to do a case comparison of the fuzzy and AHP methods in the development of medical diagnosis system, which involves basic symptoms elicitation and analysis. The results of the study indicate a non-statistically significant relative superiority of the fuzzy technology over the AHP technology. Data collected from 30 malaria patients were used to diagnose using AHP and fuzzy logic independent of one another. The results were compared and found to covary strongly. It was also discovered from the results of fuzzy logic diagnosis covary a little bit more strongly to the conventional diagnosis results than that of AHP.

  3. A note on the use of the analytic hierarchy process for environmental impact assessment.

    PubMed

    Ramanathan, R

    2001-09-01

    Environmental impact assessment (EIA) is an intrinsically complex multi-dimensional process, involving multiple criteria and multiple actors. Multi-criteria methods can serve as useful decision aids for carrying out the EIA. This paper proposes the use of a multi-criteria technique, namely the analytic hierarchy process (AHP), for the purpose. AHP has the flexibility to combine quantitative and qualitative factors, to handle different groups of actors, to combine the opinions expressed by many experts, and can help in stakeholder analysis. The main shortcomings of AHP and some modifications to it to overcome the shortcomings are briefly described. Finally, the use of AHP is illustrated for a case study involving socio-economic impact assessment. In this case study, AHP has been used for capturing the perceptions of stakeholders on the relative severity of different socio-economic impacts, which will help the authorities in prioritizing their environmental management plan, and can also help in allocating the budget available for mitigating adverse socio-economic impacts.

  4. On the location selection problem using analytic hierarchy process and multi-choice goal programming

    NASA Astrophysics Data System (ADS)

    Ho, Hui-Ping; Chang, Ching-Ter; Ku, Cheng-Yuan

    2013-01-01

    Location selection is a crucial decision in cost/benefit analysis of restaurants, coffee shops and others. However, it is difficult to be solved because there are many conflicting multiple goals in the problem of location selection. In order to solve the problem, this study integrates analytic hierarchy process (AHP) and multi-choice goal programming (MCGP) as a decision aid to obtain an appropriate house from many alternative locations that better suit the preferences of renters under their needs. This study obtains weights from AHP and implements it upon each goal using MCGP for the location selection problem. According to the function of multi-aspiration provided by MCGP, decision makers can set multi-aspiration for each location goal to rank the candidate locations. Compared to the unaided selection processes, the integrated approach of AHP and MCGP is a better scientific and efficient method than traditional methods in finding a suitable location for buying or renting a house for business, especially under multiple qualitative and quantitative criteria within a shorter evaluation time. In addition, a real case is provided to demonstrate the usefulness of the proposed method. The results show that the proposed method is able to provide better quality decision than normal manual methods.

  5. Structural damage localization by outlier analysis of signal-processed mode shapes - Analytical and experimental validation

    NASA Astrophysics Data System (ADS)

    Ulriksen, M. D.; Damkilde, L.

    2016-02-01

    Contrary to global modal parameters such as eigenfrequencies, mode shapes inherently provide structural information on a local level. Therefore, this particular modal parameter and its derivatives are utilized extensively for damage identification. Typically, more or less advanced mathematical methods are employed to identify damage-induced discontinuities in the spatial mode shape signals, hereby, potentially, facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement noise. In the present paper, a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement noise is proposed. The method is based on signal processing of a spatial mode shape by means of continuous wavelet transformation (CWT) and subsequent application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact damage-induced, outlier analysis is conducted by applying the Mahalanobis metric to major principal scores of the sensor-located bands of the signal-processed mode shape. The method is tested analytically and benchmarked with other mode shape-based damage localization approaches on the basis of a free-vibrating beam and validated experimentally in the context of a residential-sized wind turbine blade subjected to an impulse load.

  6. Epidemic process on activity-driven modular networks

    NASA Astrophysics Data System (ADS)

    Han, Dun; Sun, Mei; Li, Dandan

    2015-08-01

    In this paper, we propose two novel models of epidemic spreading by considering the activity-driven and the network modular. Firstly, we consider the susceptible-infected-susceptible (SIS) contagion model and derive analytically the epidemic threshold. The results indicate that the epidemic threshold only involves with the value of the spread rate and the recovery rate. In addition, the asymptotic refractory density of infected nodes in the different communities exhibits different trends with the change of the modularity-factor. Then, the infected-driven vaccination model is presented. Simulation results illustrate that the final density of vaccination will increase with the increase of the response strength of vaccination. Moreover, the final infected density in the original-infected-community shows different trends with the change of the response strength of vaccination and the spreading rate. The infected-driven vaccination is a good way to control the epidemic spreading.

  7. Living ordered neural networks as model systems for signal processing

    NASA Astrophysics Data System (ADS)

    Villard, C.; Amblard, P. O.; Becq, G.; Gory-Fauré, S.; Brocard, J.; Roth, S.

    2007-06-01

    Neural circuit architecture is a fundamental characteristic of the brain, and how architecture is bound to biological functions is still an open question. Some neuronal geometries seen in the retina or the cochlea are intriguing: information is processed in parallel by several entities like in "pooling" networks which have recently drawn the attention of signal processing scientists. These systems indeed exhibit the noise-enhanced processing effect, which is also actively discussed in the neuroscience community at the neuron scale. The aim of our project is to use in-vitro ordered neuron networks as living paradigms to test ideas coming from the computational science. The different technological bolts that have to be solved are enumerated and the first results are presented. A neuron is a polarised cell, with an excitatory axon and a receiving dendritic tree. We present how soma confinement and axon differentiation can be induced by surface functionalization techniques. The recording of large neuron networks, ordered or not, is also detailed and biological signals shown. The main difficulty to access neural noise in the case of weakly connected networks grown on micro electrode arrays is explained. This open the door to a new detection technology suitable for sub-cellular analysis and stimulation, whose development will constitute the next step of this project.

  8. The transmission process: A combinatorial stochastic process for the evolution of transmission trees over networks.

    PubMed

    Sainudiin, Raazesh; Welch, David

    2016-12-07

    We derive a combinatorial stochastic process for the evolution of the transmission tree over the infected vertices of a host contact network in a susceptible-infected (SI) model of an epidemic. Models of transmission trees are crucial to understanding the evolution of pathogen populations. We provide an explicit description of the transmission process on the product state space of (rooted planar ranked labelled) binary transmission trees and labelled host contact networks with SI-tags as a discrete-state continuous-time Markov chain. We give the exact probability of any transmission tree when the host contact network is a complete, star or path network - three illustrative examples. We then develop a biparametric Beta-splitting model that directly generates transmission trees with exact probabilities as a function of the model parameters, but without explicitly modelling the underlying contact network, and show that for specific values of the parameters we can recover the exact probabilities for our three example networks through the Markov chain construction that explicitly models the underlying contact network. We use the maximum likelihood estimator (MLE) to consistently infer the two parameters driving the transmission process based on observations of the transmission trees and use the exact MLE to characterize equivalence classes over the space of contact networks with a single initial infection. An exploratory simulation study of the MLEs from transmission trees sampled from three other deterministic and four random families of classical contact networks is conducted to shed light on the relation between the MLEs of these families with some implications for statistical inference along with pointers to further extensions of our models. The insights developed here are also applicable to the simplest models of "meme" evolution in online social media networks through transmission events that can be distilled from observable actions such as "likes", "mentions

  9. A neural network refinement of seismic data processing

    NASA Astrophysics Data System (ADS)

    Fernandez, Francisco Brito

    Seismic reflection data processing that is widely applied to oil exploration uses data acquired with low frequency ranges that are in the order of tens to hundreds hertz. This range of frequencies allow very deep penetration and low resolution data acquisition. Engineering and environmental applications require high resolution shallow subsurface seismic reflection data acquired using frequencies that range on the order of thousands hertz. Processing of high resolution shallow subsurface seismic reflection data has not been addressed in detail in the seismic exploration literature. This research presents a technique including Artificial Neural Networks to process high resolution shallow subsurface seismic reflection data. This technique is applied to locate oyster reefs and paleochannels in a seismic reflection survey performed by The Mississippi Mineral Resources Institute near Cat Island, Mississippi. Artificial Neural Networks that allow the selection of positive picks and the enhancement of reflectors in seismic reflection data are developed and applied to seismic reflection data processing. Seismic sections of the subsurface of the studied area are developed and maps depicting the location of oyster reefs and paleochannels near Cat Island, Mississippi are produced. A stepwise procedure to apply Artificial Neural Networks to the seismic data processing is also presented.

  10. Multistability of the Brain Network for Self-other Processing

    PubMed Central

    Chen, Yi-An; Huang, Tsung-Ren

    2017-01-01

    Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520

  11. Multistability of the Brain Network for Self-other Processing.

    PubMed

    Chen, Yi-An; Huang, Tsung-Ren

    2017-03-03

    Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate "self-specific" and "other-specific" regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed "multistability," could serve as an alternative model in theorising the mechanism of processing self-other information.

  12. Automatic data processing and crustal modeling on Brazilian Seismograph Network

    NASA Astrophysics Data System (ADS)

    Moreira, L. P.; Chimpliganond, C.; Peres Rocha, M.; Franca, G.; Marotta, G. S.; Von Huelsen, M. G.

    2014-12-01

    The Brazilian Seismograph Network (RSBR) is a joint project of four Brazilian research institutions with the support of Petrobras and its main goal is to monitor the seismic activities, generate alerts of seismic hazard and provide data for Brazilian tectonic and structure research. Each institution operates and maintain their seismic network, sharing their data in an virtual private network. These networks have seismic stations transmitting in real time (or near real time) raw data to their respective data centers, where the seismogram files are then shared with other institutions. Currently RSBR has 57 broadband stations, some of them operating since 1994, transmitting data through mobile phone data networks or satellite links. Station management, data acquisition and storage and earthquake data processing at the Seismological Observatory of the University of Brasilia is automatically performed by SeisComP3 (SC3). However, the SC3 data processing is limited to event detection, location and magnitude. An automatic crustal modeling system was designed process raw seismograms and generate 1D S-velocity profiles. This system automatically calculates receiver function (RF) traces, Vp/Vs ratio (h-k stack) and surface waves dispersion (SWD) curves. These traces and curves are then used to calibrate the lithosphere seismic velocity models using a joint inversion scheme The results can be reviewed by an analyst, change processing parameters and selecting/neglecting RF traces and SWD curves used in lithosphere model calibration. The results to be obtained from this system will be used to generate and update a quasi-3D crustal model of Brazil's territory.

  13. Performance analysis for wireless networks: an analytical approach by multifarious Sym Teredo.

    PubMed

    Punithavathani, D Shalini; Radley, Sheryl

    2014-01-01

    IPv4-IPv6 transition rolls out numerous challenges to the world of Internet as the Internet is drifting from IPv4 to IPv6. IETF recommends few transition techniques which includes dual stack and translation and tunneling. By means of tunneling the IPv6 packets over IPv4 UDP, Teredo maintains IPv4/IPv6 dual stack node in isolated IPv4 networks behindhand network address translation (NAT). However, the proposed tunneling protocol works with the symmetric and asymmetric NATs. In order to make a Teredo support several symmetric NATs along with several asymmetric NATs, we propose multifarious Sym Teredo (MTS), which is an extension of Teredo with a capability of navigating through several symmetric NATs. The work preserves the Teredo architecture and also offers a backward compatibility with the original Teredo protocol.

  14. Performance Analysis for Wireless Networks: An Analytical Approach by Multifarious Sym Teredo

    PubMed Central

    Punithavathani, D. Shalini; Radley, Sheryl

    2014-01-01

    IPv4-IPv6 transition rolls out numerous challenges to the world of Internet as the Internet is drifting from IPv4 to IPv6. IETF recommends few transition techniques which includes dual stack and translation and tunneling. By means of tunneling the IPv6 packets over IPv4 UDP, Teredo maintains IPv4/IPv6 dual stack node in isolated IPv4 networks behindhand network address translation (NAT). However, the proposed tunneling protocol works with the symmetric and asymmetric NATs. In order to make a Teredo support several symmetric NATs along with several asymmetric NATs, we propose multifarious Sym Teredo (MTS), which is an extension of Teredo with a capability of navigating through several symmetric NATs. The work preserves the Teredo architecture and also offers a backward compatibility with the original Teredo protocol. PMID:25506611

  15. Using Google Analytics as a process evaluation method for Internet-delivered interventions: an example on sexual health.

    PubMed

    Crutzen, Rik; Roosjen, Johanna L; Poelman, Jos

    2013-03-01

    The study aimed to demonstrate the potential of Google Analytics as a process evaluation method for Internet-delivered interventions, using a website about sexual health as an example. This study reports visitors' behavior until 21 months after the release of the website (March 2009-December 2010). In total, there were 850 895 visitors with an average total visiting time (i.e. dose) of 5:07 min. Google Analytics provided data to answer three key questions in terms of process evaluation of an Internet-delivered intervention: (i) How do visitors behave?; (ii) Where do visitors come from? and (iii) What content are visitors exposed to? This real-life example demonstrated the potential of Google Analytics as a method to be used in a process evaluation of Internet-delivered interventions. This is highly relevant given the current expansion of these interventions within the field of health promotion.

  16. Transdisciplinarity among tobacco harm-reduction researchers: a network analytic approach.

    PubMed

    Provan, Keith G; Clark, Pamela I; Huerta, Timothy

    2008-08-01

    Progress in tobacco control and other areas of health research is thought to be heavily influenced by the extent to which researchers are able to work with each other not only within, but also across disciplines. This study provides an examination of the extent to which researchers in the area of tobacco harm reduction work together. Specifically, data were collected in 2005 from a national group of 67 top tobacco-control researchers from eight broadly defined disciplines representing 17 areas of expertise. Network analysis was utilized to examine the extent to which these researchers were engaged in research that was interdisciplinary or transdisciplinary, based on the outcome or product attained. Findings revealed that interdisciplinary network ties were much denser than transdisciplinary ties, but researchers in some disciplines were more likely to work across disciplines than others, especially when synergistic outcomes resulted. The study demonstrates for the first time how tobacco-control researchers work together, providing direction for policy officials seeking to encourage greater transdisciplinarity. The study also demonstrates the value of network-analysis methods for understanding research relationships in one important area of health care.

  17. Collectivism culture, HIV stigma and social network support in Anhui, China: a path analytic model.

    PubMed

    Zang, Chunpeng; Guida, Jennifer; Sun, Yehuan; Liu, Hongjie

    2014-08-01

    HIV stigma is rooted in culture and, therefore, it is essential to investigate it within the context of culture. The objective of this study was to examine the interrelationships among individualism-collectivism, HIV stigma, and social network support. A social network study was conducted among 118 people living with HIVAIDS in China, who were infected by commercial plasma donation, a nonstigmatized behavior. The Individualism-Collectivism Interpersonal Assessment Inventory (ICIAI) was used to measure cultural norms and values in the context of three social groups, family members, friends, and neighbors. Path analyses revealed (1) a higher level of family ICIAI was significantly associated with a higher level of HIV self-stigma (β=0.32); (2) a higher level of friend ICIAI was associated with a lower level of self-stigma (β=-035); (3) neighbor ICIAI was associated with public stigma (β=-0.61); (4) self-stigman was associated with social support from neighbors (β=-0.27); and (5) public stigma was associated with social support from neighbors (β=-0.24). This study documents that HIV stigma may mediate the relationship between collectivist culture and social network support, providing an empirical basis for interventions to include aspects of culture into HIV intervention strategies.

  18. Critical behavior of the contact process in a multiscale network

    NASA Astrophysics Data System (ADS)

    Ferreira, Silvio C.; Martins, Marcelo L.

    2007-09-01

    Inspired by dengue and yellow fever epidemics, we investigated the contact process (CP) in a multiscale network constituted by one-dimensional chains connected through a Barabási-Albert scale-free network. In addition to the CP dynamics inside the chains, the exchange of individuals between connected chains (travels) occurs at a constant rate. A finite epidemic threshold and an epidemic mean lifetime diverging exponentially in the subcritical phase, concomitantly with a power law divergence of the outbreak’s duration, were found. A generalized scaling function involving both regular and SF components was proposed for the quasistationary analysis and the associated critical exponents determined, demonstrating that the CP on this hybrid network and nonvanishing travel rates establishes a new universality class.

  19. Heuristic and Analytic Processing: Age Trends and Associations with Cognitive Ability and Cognitive Styles.

    ERIC Educational Resources Information Center

    Kokis, Judite V.; Macpherson, Robyn; Toplak, Maggie E.; West, Richard F.; Stanovich, Keith E.

    2002-01-01

    Examined developmental and individual differences in tendencies to favor analytic over heuristic responses in three tasks (inductive reasoning, deduction under belief bias conditions, probabilistic reasoning) in children varying in age and cognitive ability. Found significant increases in analytic responding with development on first two tasks.…

  20. CONDENSED MATTER: STRUCTURE, MECHANICAL AND THERMAL PROPERTIES: Self-Organization of Weighted Networks in Connection with the Misanthrope Process

    NASA Astrophysics Data System (ADS)

    Meng, Qing-Kuan; Zhu, Jian-Yang

    2009-08-01

    From an undirected random graph, by the weight redistribution of the edges, we obtain a weighted network. The weight redistribution of the edges can be connected to the well-known Misanthrope process, in which distinguishable particles hop among different urns. Under specific conditions, the condensation phenomena can be observed, i.e., nearly all the edges connect to one vertex in the network. When there is no condensation, by adjusting the parameters, the strength distribution can be scale-free or exponentially decreasing. The numerical results fit well with the analytical ones.

  1. Internal quality control system for non-stationary, non-ergodic analytical processes based upon exponentially weighted estimation of process means and process standard deviation.

    PubMed

    Jansen, Rob T P; Laeven, Mark; Kardol, Wim

    2002-06-01

    The analytical processes in clinical laboratories should be considered to be non-stationary, non-ergodic and probably non-stochastic processes. Both the process mean and the process standard deviation vary. The variation can be different at different levels of concentration. This behavior is shown in five examples of different analytical systems: alkaline phosphatase on the Hitachi 911 analyzer (Roche), vitamin B12 on the Access analyzer (Beckman), prothrombin time and activated partial thromboplastin time on the STA Compact analyzer (Roche) and PO2 on the ABL 520 analyzer (Radiometer). A model is proposed to assess the status of a process. An exponentially weighted moving average and standard deviation was used to estimate process mean and standard deviation. Process means were estimated overall and for each control level. The process standard deviation was estimated in terms of within-run standard deviation. Limits were defined in accordance with state of the art- or biological variance-derived cut-offs. The examples given are real, not simulated, data. Individual control sample results were normalized to a target value and target standard deviation. The normalized values were used in the exponentially weighted algorithm. The weighting factor was based on a process time constant, which was estimated from the period between two calibration or maintenance procedures. The proposed system was compared with Westgard rules. The Westgard rules perform well, despite the underlying presumption of ergodicity. This is mainly caused by the introduction of the starting rule of 12s, which proves essential to prevent a large number of rule violations. The probability of reporting a test result with an analytical error that exceeds the total allowable error was calculated for the proposed system as well as for the Westgard rules. The proposed method performed better. The proposed algorithm was implemented in a computer program running on computers to which the analyzers were

  2. Towards Semantic Modelling of Business Processes for Networked Enterprises

    NASA Astrophysics Data System (ADS)

    Furdík, Karol; Mach, Marián; Sabol, Tomáš

    The paper presents an approach to the semantic modelling and annotation of business processes and information resources, as it was designed within the FP7 ICT EU project SPIKE to support creation and maintenance of short-term business alliances and networked enterprises. A methodology for the development of the resource ontology, as a shareable knowledge model for semantic description of business processes, is proposed. Systematically collected user requirements, conceptual models implied by the selected implementation platform as well as available ontology resources and standards are employed in the ontology creation. The process of semantic annotation is described and illustrated using an example taken from a real application case.

  3. Network Detection in Raster Data Using Marked Point Processes

    NASA Astrophysics Data System (ADS)

    Schmidt, A.; Kruse, C.; Rottensteiner, F.; Soergel, U.; Heipke, C.

    2016-06-01

    We propose a new approach for the automatic detection of network structures in raster data. The model for the network structure is represented by a graph whose nodes and edges correspond to junction-points and to connecting line segments, respectively; nodes and edges are further described by certain parameters. We embed this model in the probabilistic framework of marked point processes and determine the most probable configuration of objects by stochastic sampling. That is, different graph configurations are constructed randomly by modifying the graph entity parameters, by adding and removing nodes and edges to/ from the current graph configuration. Each configuration is then evaluated based on the probabilities of the changes and an energy function describing the conformity with a predefined model. By using the Reversible Jump Markov Chain Monte Carlo sampler, a global optimum of the energy function is determined. We apply our method to the detection of river and tidal channel networks in digital terrain models. In comparison to our previous work, we introduce constraints concerning the flow direction of water into the energy function. Our goal is to analyse the influence of different parameter settings on the results of network detection in both, synthetic and real data. Our results show the general potential of our method for the detection of river networks in different types of terrain.

  4. Braess paradox in a network of totally asymmetric exclusion processes

    NASA Astrophysics Data System (ADS)

    Bittihn, Stefan; Schadschneider, Andreas

    2016-12-01

    We study the Braess paradox in the transport network as originally proposed by Braess with totally asymmetric exclusion processes (TASEPs) on the edges. The Braess paradox describes the counterintuitive situation in which adding an edge to a road network leads to a user optimum with higher travel times for all network users. Travel times on the TASEPs are nonlinear in the density, and jammed states can occur due to the microscopic exclusion principle, leading to a more realistic description of trafficlike transport on the network than in previously studied linear macroscopic mathematical models. Furthermore, the stochastic dynamics allows us to explore the effects of fluctuations on network performance. We observe that for low densities, the added edge leads to lower travel times. For slightly higher densities, the Braess paradox occurs in its classical sense. At intermediate densities, strong fluctuations in the travel times dominate the system's behavior due to links that are in a domain-wall state. At high densities, the added link leads to lower travel times. We present a phase diagram that predicts the system's state depending on the global density and crucial path-length ratios.

  5. Multi criteria decision making to select the suitable method for the preparation of nanoparticles using an analytical hierarchy process.

    PubMed

    Velmurugan, R; Selvamuthukumar, S; Manavalan, R

    2011-11-01

    Selecting the right method for the preparation of nanoparticles is a crucial decision. A wrong decision can result in the product having to be formulated and developed again. One tool that can be useful in determining the most appropriate method is the Analytical Hierarchy Process (AHP). AHP has been employed in almost all areas related to decision-making problems. In this paper, the results of a case study illustrate that the AHP concept can assist designers in the effective evaluation of various methods available for the preparation of nanoparticles. This paper presents the methodology of selecting the most suitable method for preparing nanoparticles using the analytical hierarchy process.

  6. Selection of reference standard during method development using the analytical hierarchy process.

    PubMed

    Sun, Wan-yang; Tong, Ling; Li, Dong-xiang; Huang, Jing-yi; Zhou, Shui-ping; Sun, Henry; Bi, Kai-shun

    2015-03-25

    Reference standard is critical for ensuring reliable and accurate method performance. One important issue is how to select the ideal one from the alternatives. Unlike the optimization of parameters, the criteria of the reference standard are always immeasurable. The aim of this paper is to recommend a quantitative approach for the selection of reference standard during method development based on the analytical hierarchy process (AHP) as a decision-making tool. Six alternative single reference standards were assessed in quantitative analysis of six phenolic acids from Salvia Miltiorrhiza and its preparations by using ultra-performance liquid chromatography. The AHP model simultaneously considered six criteria related to reference standard characteristics and method performance, containing feasibility to obtain, abundance in samples, chemical stability, accuracy, precision and robustness. The priority of each alternative was calculated using standard AHP analysis method. The results showed that protocatechuic aldehyde is the ideal reference standard, and rosmarinic acid is about 79.8% ability as the second choice. The determination results successfully verified the evaluation ability of this model. The AHP allowed us comprehensive considering the benefits and risks of the alternatives. It was an effective and practical tool for optimization of reference standards during method development.

  7. Approach of decision making based on the analytic hierarchy process for urban landscape management.

    PubMed

    Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan

    2013-03-01

    This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.

  8. Application of analytic hierarchy process in a waste treatment technology assessment in Mexico.

    PubMed

    Taboada-González, Paul; Aguilar-Virgen, Quetzalli; Ojeda-Benítez, Sara; Cruz-Sotelo, Samantha

    2014-09-01

    The high per capita generation of solid waste and the environmental problems in major rural communities of Ensenada, Baja California, have prompted authorities to seek alternatives for waste treatment. In the absence of a selection methodology, three technologies of waste treatment with energy recovery (an anaerobic digester, a downdraft gasifier, and a plasma gasifier) were evaluated, taking the broader social, political, economic, and environmental issues into considerations. Using the scientific literature as a baseline, interviews with experts, decision makers and the community, and waste stream studies were used to construct a hierarchy that was evaluated by the analytic hierarchy process. In terms of the criteria, judgments, and assumptions made in the model, the anaerobic digester was found to have the highest rating and should consequently be selected as the waste treatment technology for this area. The study results showed low sensitivity, so alternative scenarios were not considered. The methodology developed in this study may be useful for other governments who wish to assess technologies to select waste treatment.

  9. Fuzzy Analytic Hierarchy Process-based Chinese Resident Best Fitness Behavior Method Research.

    PubMed

    Wang, Dapeng; Zhang, Lan

    2015-01-01

    With explosive development in Chinese economy and science and technology, people's pursuit of health becomes more and more intense, therefore Chinese resident sports fitness activities have been rapidly developed. However, different fitness events popularity degrees and effects on body energy consumption are different, so bases on this, the paper researches on fitness behaviors and gets Chinese residents sports fitness behaviors exercise guide, which provides guidance for propelling to national fitness plan's implementation and improving Chinese resident fitness scientization. The paper starts from the perspective of energy consumption, it mainly adopts experience method, determines Chinese resident favorite sports fitness event energy consumption through observing all kinds of fitness behaviors energy consumption, and applies fuzzy analytic hierarchy process to make evaluation on bicycle riding, shadowboxing practicing, swimming, rope skipping, jogging, running, aerobics these seven fitness events. By calculating fuzzy rate model's membership and comparing their sizes, it gets fitness behaviors that are more helpful for resident health, more effective and popular. Finally, it gets conclusions that swimming is a best exercise mode and its membership is the highest. Besides, the memberships of running, rope skipping and shadowboxing practicing are also relative higher. It should go in for bodybuilding by synthesizing above several kinds of fitness events according to different physical conditions; different living conditions so that can better achieve the purpose of fitness exercises.

  10. Empirical investigation of radiologists' priorities for PACS selection: an analytical hierarchy process approach.

    PubMed

    Joshi, Vivek; Lee, Kyootai; Melson, David; Narra, Vamsi R

    2011-08-01

    Picture archiving and communication systems (PACS) are being widely adopted in radiology practice. The objective of this study was to find radiologists' perspective on the relative importance of the required features when selecting or developing a PACS. Important features for PACS were identified based on the literature and consultation/interviews with radiologists. These features were categorized and organized into a logical hierarchy consisting of the main dimensions and sub-dimensions. An online survey was conducted to obtain data from 58 radiologists about their relative preferences. Analytical hierarchy process methodology was used to determine the relative priority weights for different dimensions along with the consistency of responses. System continuity and functionality was found to be the most important dimension, followed by system performance and architecture, user interface for workflow management, user interface for image manipulation, and display quality. Among the sub-dimensions, the top two features were: security, backup, and downtime prevention; and voice recognition, transcription, and reporting. Structured reporting was also given very high priority. The results point to the dimensions that can be critical discriminators between different PACS and highlight the importance of faster integration of the emerging developments in radiology into PACS.

  11. The Prioritization of Clinical Risk Factors of Obstructive Sleep Apnea Severity Using Fuzzy Analytic Hierarchy Process.

    PubMed

    Maranate, Thaya; Pongpullponsak, Adisak; Ruttanaumpawan, Pimon

    2015-01-01

    Recently, there has been a problem of shortage of sleep laboratories that can accommodate the patients in a timely manner. Delayed diagnosis and treatment may lead to worse outcomes particularly in patients with severe obstructive sleep apnea (OSA). For this reason, the prioritization in polysomnography (PSG) queueing should be endorsed based on disease severity. To date, there have been conflicting data whether clinical information can predict OSA severity. The 1,042 suspected OSA patients underwent diagnostic PSG study at Siriraj Sleep Center during 2010-2011. A total of 113 variables were obtained from sleep questionnaires and anthropometric measurements. The 19 groups of clinical risk factors consisting of 42 variables were categorized into each OSA severity. This study aimed to array these factors by employing Fuzzy Analytic Hierarchy Process approach based on normalized weight vector. The results revealed that the first rank of clinical risk factors in Severe, Moderate, Mild, and No OSA was nighttime symptoms. The overall sensitivity/specificity of the approach to these groups was 92.32%/91.76%, 89.52%/88.18%, 91.08%/84.58%, and 96.49%/81.23%, respectively. We propose that the urgent PSG appointment should include clinical risk factors of Severe OSA group. In addition, the screening for Mild from No OSA patients in sleep center setting using symptoms during sleep is also recommended (sensitivity = 87.12% and specificity = 72.22%).

  12. Markov-CA model using analytical hierarchy process and multiregression technique

    NASA Astrophysics Data System (ADS)

    Omar, N. Q.; Sanusi, S. A. M.; Hussin, W. M. W.; Samat, N.; Mohammed, K. S.

    2014-06-01

    The unprecedented increase in population and rapid rate of urbanisation has led to extensive land use changes. Cellular automata (CA) are increasingly used to simulate a variety of urban dynamics. This paper introduces a new CA based on an integration model built-in multi regression and multi-criteria evaluation to improve the representation of CA transition rule. This multi-criteria evaluation is implemented by utilising data relating to the environmental and socioeconomic factors in the study area in order to produce suitability maps (SMs) using an analytical hierarchical process, which is a well-known method. Before being integrated to generate suitability maps for the periods from 1984 to 2010 based on the different decision makings, which have become conditioned for the next step of CA generation. The suitability maps are compared in order to find the best maps based on the values of the root equation (R2). This comparison can help the stakeholders make better decisions. Thus, the resultant suitability map derives a predefined transition rule for the last step for CA model. The approach used in this study highlights a mechanism for monitoring and evaluating land-use and land-cover changes in Kirkuk city, Iraq owing changes in the structures of governments, wars, and an economic blockade over the past decades. The present study asserts the high applicability and flexibility of Markov-CA model. The results have shown that the model and its interrelated concepts are performing rather well.

  13. Characterization of a nonribosomal peptide antibiotic solid dispersion formulation by process analytical technologies sensors.

    PubMed

    Rahman, Ziyaur; Siddiqui, Akhtar; Khan, Mansoor A

    2013-12-01

    The focus of present investigation was to characterize and evaluate the variability of solid dispersion (SD) of amorphous vancomycin (VCM), utilizing crystalline polyethylene glycol (PEG-6000) as a carrier and subsequently, determining their percentage composition by nondestructive method of process analytical technology (PAT) sensors. The SD were prepared by heat fusion method and characterized for physicochemical and spectral properties. Enhanced dissolution was shown by the SD formulations. Decreased crystallinity of PEG-6000 was observed indicating that the drug was present as solution and dispersed form within the polymer. The SD formulations were homogenous as shown by near infrared (NIR) chemical imaging data. Principal component analysis (PCA) and partial least square (PLS) method were applied to NIR and PXRD (powder X-ray diffraction) data to develop model for quantification of drug and carrier. PLS of both data showed correlation coefficient >0.9934 with good prediction capability as revealed by smaller value of root mean square and standard error. The model based on NIR and PXRD were two folds more accurate in estimating PEG-6000 than VCM. In conclusion, the drug dissolution from the SD increased by decreasing crystallinity of PEG-6000, and the chemometric models showed usefulness of PAT sensor in estimating percentage of both VCM and PEG-600 simultaneously.

  14. Selection of infectious medical waste disposal firms by using the analytic hierarchy process and sensitivity analysis

    SciTech Connect

    Hsu, P.-F. Wu, C.-R. Li, Y.-T.

    2008-07-01

    While Taiwanese hospitals dispose of large amounts of medical waste to ensure sanitation and personal hygiene, doing so inefficiently creates potential environmental hazards and increases operational expenses. However, hospitals lack objective criteria to select the most appropriate waste disposal firm and evaluate its performance, instead relying on their own subjective judgment and previous experiences. Therefore, this work presents an analytic hierarchy process (AHP) method to objectively select medical waste disposal firms based on the results of interviews with experts in the field, thus reducing overhead costs and enhancing medical waste management. An appropriate weight criterion based on AHP is derived to assess the effectiveness of medical waste disposal firms. The proposed AHP-based method offers a more efficient and precise means of selecting medical waste firms than subjective assessment methods do, thus reducing the potential risks for hospitals. Analysis results indicate that the medical sector selects the most appropriate infectious medical waste disposal firm based on the following rank: matching degree, contractor's qualifications, contractor's service capability, contractor's equipment and economic factors. By providing hospitals with an effective means of evaluating medical waste disposal firms, the proposed AHP method can reduce overhead costs and enable medical waste management to understand the market demand in the health sector. Moreover, performed through use of Expert Choice software, sensitivity analysis can survey the criterion weight of the degree of influence with an alternative hierarchy.

  15. Process analytical technology to understand the disintegration behavior of alendronate sodium tablets.

    PubMed

    Xu, Xiaoming; Gupta, Abhay; Sayeed, Vilayat A; Khan, Mansoor A

    2013-05-01

    Various adverse events including esophagus irritations have been reported with the use of alendronate tablets, likely attributed to the rapid tablet disintegration in the mouth or esophagus. Accordingly, the disintegration of six alendronate tablet drug products was studied using a newly developed testing device equipped with in-line sensors, in addition to the official compendial procedure for measuring the disintegration time. The in-line sensors were used to monitor the particle count and solution pH change to assess the onset and duration of disintegration. A relatively large variation was observed in the disintegration time of the tested drug products using the compendial method. The data collected using the in-line sensors suggested that all tested drug products exhibited almost instantaneous onset of disintegration, under 2 s, and a sharp drop in solution pH. The drop in pH was slower for tablets with slower disintegration. The in-house prepared alendronate test tablets also showed similar trends suggesting rapid solubilization of the drug contributed to the fast tablet disintegration. This research highlights the usefulness of the newly developed in-line analytical method in combination with the compendial method in providing a better understanding of the disintegration and the accompanying drug solubilization processes for fast disintegrating tablet drug products.

  16. Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process

    SciTech Connect

    Ho, Chao Chung

    2011-07-15

    Ever since Taiwan's National Health Insurance implemented the diagnosis-related groups payment system in January 2010, hospital income has declined. Therefore, to meet their medical waste disposal needs, hospitals seek suppliers that provide high-quality services at a low cost. The enactment of the Waste Disposal Act in 1974 had facilitated some improvement in the management of waste disposal. However, since the implementation of the National Health Insurance program, the amount of medical waste from disposable medical products has been increasing. Further, of all the hazardous waste types, the amount of infectious medical waste has increased at the fastest rate. This is because of the increase in the number of items considered as infectious waste by the Environmental Protection Administration. The present study used two important findings from previous studies to determine the critical evaluation criteria for selecting infectious medical waste disposal firms. It employed the fuzzy analytic hierarchy process to set the objective weights of the evaluation criteria and select the optimal infectious medical waste disposal firm through calculation and sorting. The aim was to propose a method of evaluation with which medical and health care institutions could objectively and systematically choose appropriate infectious medical waste disposal firms.

  17. Evaluation of generic types of drilling fluid using a risk-based analytic hierarchy process.

    PubMed

    Sadiq, Rehan; Husain, Tahir; Veitch, Brian; Bose, Neil

    2003-12-01

    The composition of drilling muds is based on a mixture of clays and additives in a base fluid. There are three generic categories of base fluid--water, oil, and synthetic. Water-based fluids (WBFs) are relatively environmentally benign, but drilling performance is better with oil-based fluids (OBFs). The oil and gas industry developed synthetic-based fluids (SBFs), such as vegetable esters, olefins, ethers, and others, which provide drilling performance comparable to OBFs, but with lower environmental and occupational health effects. The primary objective of this paper is to present a methodology to guide decision-making in the selection and evaluation of three generic types of drilling fluids using a risk-based analytic hierarchy process (AHP). In this paper a comparison of drilling fluids is made considering various activities involved in the life cycle of drilling fluids. This paper evaluates OBFs, WBFs, and SBFs based on four major impacts--operations, resources, economics, and liabilities. Four major activities--drilling, discharging offshore, loading and transporting, and disposing onshore--cause the operational impacts. Each activity involves risks related to occupational injuries (safety), general public health, environmental impact, and energy use. A multicriteria analysis strategy was used for the selection and evaluation of drilling fluids using a risk-based AHP. A four-level hierarchical structure is developed to determine the final relative scores, and the SBFs are found to be the best option.

  18. The Prioritization of Clinical Risk Factors of Obstructive Sleep Apnea Severity Using Fuzzy Analytic Hierarchy Process

    PubMed Central

    Maranate, Thaya; Pongpullponsak, Adisak; Ruttanaumpawan, Pimon

    2015-01-01

    Recently, there has been a problem of shortage of sleep laboratories that can accommodate the patients in a timely manner. Delayed diagnosis and treatment may lead to worse outcomes particularly in patients with severe obstructive sleep apnea (OSA). For this reason, the prioritization in polysomnography (PSG) queueing should be endorsed based on disease severity. To date, there have been conflicting data whether clinical information can predict OSA severity. The 1,042 suspected OSA patients underwent diagnostic PSG study at Siriraj Sleep Center during 2010-2011. A total of 113 variables were obtained from sleep questionnaires and anthropometric measurements. The 19 groups of clinical risk factors consisting of 42 variables were categorized into each OSA severity. This study aimed to array these factors by employing Fuzzy Analytic Hierarchy Process approach based on normalized weight vector. The results revealed that the first rank of clinical risk factors in Severe, Moderate, Mild, and No OSA was nighttime symptoms. The overall sensitivity/specificity of the approach to these groups was 92.32%/91.76%, 89.52%/88.18%, 91.08%/84.58%, and 96.49%/81.23%, respectively. We propose that the urgent PSG appointment should include clinical risk factors of Severe OSA group. In addition, the screening for Mild from No OSA patients in sleep center setting using symptoms during sleep is also recommended (sensitivity = 87.12% and specificity = 72.22%). PMID:26221183

  19. Academic staff promotion in higher education by using Analytic Hierarchy Process (AHP)

    NASA Astrophysics Data System (ADS)

    Saaludin, Nurashikin; Harun, Suriyati; Wahab, Siti Zahariah Abdul; Yahya, Yasmin

    2016-10-01

    The academic staff promotional system varies according to the nature of the work and designation within an organization. It is vital to enhance the system in local higher education standard to an international education standard. In Universiti Kuala Lumpur (UniKL); teaching and supervision, research and publication, administration and management, professional contribution to the society and scholarly recognition are the main criteria being used in appraising its staff. The purpose of this study is to improve the method of academic staff promotional system by using the Analytic Hierarchy Process (AHP). In AHP, pair wise comparison is used to obtain the weightage score for every candidate. The results show that by implementing the new system, UniKL will be able to better produce academic staff who are responsive to the university's mission and vision. The qualified candidates will be based on the highest overall score. The reliability level of the results obtained in this study is less than 0.1 of the inconsistency ratio (CR).

  20. Using analytic hierarchy process approach in ontological multicriterial decision making - Preliminary considerations

    NASA Astrophysics Data System (ADS)

    Wasielewska, K.; Ganzha, M.

    2012-10-01

    In this paper we consider combining ontologically demarcated information with Saaty's Analytic Hierarchy Process (AHP) [1] for the multicriterial assessment of offers during contract negotiations. The context for the proposal is provided by the Agents in Grid project (AiG; [2]), which aims at development of an agent-based infrastructure for efficient resource management in the Grid. In the AiG project, software agents representing users can either (1) join a team and earn money, or (2) find a team to execute a job. Moreover, agents form teams, managers of which negotiate with clients and workers terms of potential collaboration. Here, ontologically described contracts (Service Level Agreements) are the results of autonomous multiround negotiations. Therefore, taking into account relatively complex nature of the negotiated contracts, multicriterial assessment of proposals plays a crucial role. The AHP method is based on pairwise comparisons of criteria and relies on the judgement of a panel of experts. It measures how well does an offer serve the objective of a decision maker. In this paper, we propose how the AHP method can be used to assess ontologically described contract proposals.

  1. Practical use of analytically derived runoff models based on rainfall point processes

    NASA Astrophysics Data System (ADS)

    Puente, C. E.; Bierkens, M. F. P.; Diaz-Granados, M. A.; Dik, P. E.; López, M. M.

    1993-10-01

    This work reports on the practical usage of the four stochastic rainfall-runoff models introduced by Bierkens and Puente (1990). These models, which are lumped in space, were analytically derived combining two rainfall point process models with two simple runoff parameterizations. The rainfall models employ rectangular pulses with Poisson (PRP) and Neyman-Scott (NSRP) arrivals, respectively. The runoff models route individual rainfall pulses via linear reservoirs. One runoff parameterization accounts for surface runoff by using a single linear reservoir (SLR). The other model considers both surface and groundwater runoff employing two linear reservoirs in parallel (PLR). All four representations were tested on two catchments located in the Netherlands and Colombia. Emphasis was placed on the models' ability to (1) give stable parameter values for data sets at alternative averaging (aggregation) lengths (consistency) and (2) preserve historical statistics at alternative averaging lengths when using parameters found from data at other averaging scales (robustness). Results show that the use of alternative rainfall models may have little effect on runoff performance. Specifically, the NSRP model resulted in more robust runoff behavior than the PRP model only when combined to the SLR parameterization. The type of model used to route individual rainfall pulses was found to be important. Runoff representations containing the PLR component were found more robust than those having the SLR model.

  2. Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems.

    PubMed

    Liao, Wen-Hwa; Qiu, Wan-Li

    2016-01-01

    Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture.

  3. Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process.

    PubMed

    Ho, Chao Chung

    2011-07-01

    Ever since Taiwan's National Health Insurance implemented the diagnosis-related groups payment system in January 2010, hospital income has declined. Therefore, to meet their medical waste disposal needs, hospitals seek suppliers that provide high-quality services at a low cost. The enactment of the Waste Disposal Act in 1974 had facilitated some improvement in the management of waste disposal. However, since the implementation of the National Health Insurance program, the amount of medical waste from disposable medical products has been increasing. Further, of all the hazardous waste types, the amount of infectious medical waste has increased at the fastest rate. This is because of the increase in the number of items considered as infectious waste by the Environmental Protection Administration. The present study used two important findings from previous studies to determine the critical evaluation criteria for selecting infectious medical waste disposal firms. It employed the fuzzy analytic hierarchy process to set the objective weights of the evaluation criteria and select the optimal infectious medical waste disposal firm through calculation and sorting. The aim was to propose a method of evaluation with which medical and health care institutions could objectively and systematically choose appropriate infectious medical waste disposal firms.

  4. Modeling cognitive and emotional processes: a novel neural network architecture.

    PubMed

    Khashman, Adnan

    2010-12-01

    In our continuous attempts to model natural intelligence and emotions in machine learning, many research works emerge with different methods that are often driven by engineering concerns and have the common goal of modeling human perception in machines. This paper aims to go further in that direction by investigating the integration of emotion at the structural level of cognitive systems using the novel emotional DuoNeural Network (DuoNN). This network has hidden layer DuoNeurons, where each has two embedded neurons: a dorsal neuron and a ventral neuron for cognitive and emotional data processing, respectively. When input visual stimuli are presented to the DuoNN, the dorsal cognitive neurons process local features while the ventral emotional neurons process the entire pattern. We present the computational model and the learning algorithm of the DuoNN, the input information-cognitive and emotional-parallel streaming method, and a comparison between the DuoNN and a recently developed emotional neural network. Experimental results show that the DuoNN architecture, configuration, and the additional emotional information processing, yield higher recognition rates and faster learning and decision making.

  5. Fair fund distribution for a municipal incinerator using GIS-based fuzzy analytic hierarchy process.

    PubMed

    Chang, Ni-Bin; Chang, Ying-Hsi; Chen, Ho-Wen

    2009-01-01

    Burning municipal solid waste (MSW) can generate energy and reduce the waste volume, which delivers benefits to society through resources conservation. But current practices by society are not sustainable because the associated environmental impacts of waste incineration on urbanized regions have been a long-standing concern in local communities. Public reluctance with regard to accepting the incinerators as typical utilities often results in an intensive debate concerning how much welfare is lost for those residents living in the vicinity of those incinerators. As the measure of welfare change with respect to environmental quality constraints nearby these incinerators remains critical, new arguments related to how to allocate the fair fund among affected communities became a focal point in environmental management. Given the fact that most County fair fund rules allow a great deal of flexibility for redistribution, little is known about what type of methodology may be a good fit to determine the distribution of such a fair fund under uncertainty. This paper purports to demonstrate a system-based approach that helps any fair fund distribution, which is made with respect to residents' possible claim for fair damages due to the installation of a new incinerator. Holding a case study using integrated geographic information system (GIS) and fuzzy analytic hierarchy process (FAHP) for finding out the most appropriate distribution strategy between two neighboring towns in Taipei County, Taiwan demonstrates the application potential. Participants in determining the use of a fair fund also follow a highly democratic procedure where all stakeholders involved eventually express a high level of satisfaction with the results facilitating the final decision making process. It ensures that plans for the distribution of such a fair fund were carefully thought out and justified with a multi-faceted nature that covers political, socio-economic, technical, environmental, public

  6. Analytical solution and scaling of fluctuations in complex networks traversed by damped, interacting random walkers

    NASA Astrophysics Data System (ADS)

    Hamaneh, Mehdi Bagheri; Haber, Jonah; Yu, Yi-Kuo

    2015-11-01

    A general model for random walks (RWs) on networks is proposed. It incorporates damping and time-dependent links, and it includes standard (undamped, noninteracting) RWs (SRWs), coalescing RWs, and coalescing-branching RWs as special cases. The exact, time-dependent solutions for the average numbers of visits (w ) to nodes and their fluctuations (σ2) are given, and the long-term σ -w relation is studied. Although σ ∝w1 /2 for SRWs, this power law can be fragile when coalescing-branching interaction is present. Damping, however, often strengthens it but with an exponent generally different from 1 /2 .

  7. Temporal Sequence of Hemispheric Network Activation during Semantic Processing: A Functional Network Connectivity Analysis

    ERIC Educational Resources Information Center

    Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince; Kraut, Michael; Hart, John, Jr.; Pearlson, Godfrey

    2009-01-01

    To explore the temporal sequence of, and the relationship between, the left and right hemispheres (LH and RH) during semantic memory (SM) processing we identified the neural networks involved in the performance of functional MRI semantic object retrieval task (SORT) using group independent component analysis (ICA) in 47 healthy individuals. SORT…

  8. Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

    NASA Astrophysics Data System (ADS)

    Kirst, Christoph

    It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

  9. Contextuality Scenarios Arising from Networks of Stochastic Processes

    NASA Astrophysics Data System (ADS)

    Iglesias, Rodrigo; Tohmé, Fernando; Auday, Marcelo

    2016-10-01

    An empirical model is a generalization of a probability space. It consists of a simplicial complex of subsets of a class 𝒳 of random variables such that each simplex has an associated probability distribution. The ensuing marginalizations are coherent, in the sense that the distribution on a face of a simplex coincides with the marginal of the distribution over the entire simplex. An empirical model is called contextual if its distributions cannot be obtained by marginalizing a joint distribution over 𝒳. Contextual empirical models arise naturally in quantum theory, giving rise to some of its counter -intuitive statistical consequences. In this paper, we present a different and classical source of contextual empirical models: the interaction among many stochastic processes. We attach an empirical model to the ensuing network in which each node represents an open stochastic process with input and output random variables. The statistical behaviour of the network in the long run makes the empirical model generically contextual and even strongly contextual.

  10. Neural networks for process control and optimization: two industrial applications.

    PubMed

    Bloch, Gérard; Denoeux, Thierry

    2003-01-01

    The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony. Two applications are described in steel industry and water treatment, respectively, the control of alloying process in a hot dipped galvanizing line and the control of a coagulation process in a drinking water treatment plant. These examples highlight the interest of neural techniques, when complex nonlinear phenomena are involved, but the empirical knowledge of control operators can be learned.

  11. Individual Differences in Information Processing in Networked Decision Making

    DTIC Science & Technology

    2015-03-31

    frequently face the problem of information overload . The amount of information available for a decision is often much larger than a person can process to make...team performance and can lead to information overload if it is coupled with high information push activity. Similarly, heuristic decisions as a...today’s networks, individuals frequently face the problem of information overload : the amount of information available for a decision far ex- ceeds the

  12. Process for forming synapses in neural networks and resistor therefor

    DOEpatents

    Fu, C.Y.

    1996-07-23

    Customizable neural network in which one or more resistors form each synapse is disclosed. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength. 5 figs.

  13. Process for forming synapses in neural networks and resistor therefor

    DOEpatents

    Fu, Chi Y.

    1996-01-01

    Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

  14. Energy efficient on-sensor processing in Body Sensor Networks.

    PubMed

    Marnane, W; Faul, S; Bleakley, C; Conway, R; Jones, E; Popovici, E; de la Guia Solaz, M; Morgan, F; Patel, K

    2010-01-01

    Body Sensor Networks (BSNs) have tremendous potential in facilitating the real-time monitoring of the health of an individual in their own environment. However to truly exploit this potential, the powerful signal processing and analysis techniques available in the hospital environment must also be deployed in BSNs. In this paper, techniques in algorithm development, communications, hardware architecture and circuit design are described that will achieve the necessary power savings to make intelligent BSNs a reality.

  15. Understanding disease processes by partitioned dynamic Bayesian networks.

    PubMed

    Bueno, Marcos L P; Hommersom, Arjen; Lucas, Peter J F; Lappenschaar, Martijn; Janzing, Joost G E

    2016-06-01

    For many clinical problems in patients the underlying pathophysiological process changes in the course of time as a result of medical interventions. In model building for such problems, the typical scarcity of data in a clinical setting has been often compensated by utilizing time homogeneous models, such as dynamic Bayesian networks. As a consequence, the specificities of the underlying process are lost in the obtained models. In the current work, we propose the new concept of partitioned dynamic Bayesian networks to capture distribution regime changes, i.e. time non-homogeneity, benefiting from an intuitive and compact representation with the solid theoretical foundation of Bayesian network models. In order to balance specificity and simplicity in real-world scenarios, we propose a heuristic algorithm to search and learn these non-homogeneous models taking into account a preference for less complex models. An extensive set of experiments were ran, in which simulating experiments show that the heuristic algorithm was capable of constructing well-suited solutions, in terms of goodness of fit and statistical distance to the original distributions, in consonance with the underlying processes that generated data, whether it was homogeneous or non-homogeneous. Finally, a study case on psychotic depression was conducted using non-homogeneous models learned by the heuristic, leading to insightful answers for clinically relevant questions concerning the dynamics of this mental disorder.

  16. Processes involved in sweeping as sample enrichment method in cyclodextrin-modified micellar electrokinetic chromatography of hydrophobic basic analytes.

    PubMed

    El-Awady, Mohamed; Pyell, Ute

    2014-03-01

    Sweeping is an enrichment method in MEKC, which includes following steps: stacking/destacking of the micelles, sweeping of analyte by the stacked/destacked micelles, destacking/stacking of the swept analyte zone and additional focusing/defocusing due to the retention factor gradient effect (RFGE). In this study, we investigate additional processes, regarding online focusing in cyclodextrin-modified MEKC (CD-MEKC) of hydrophobic basic analytes: dynamic pH junction (sample with pH different from that of BGE) and adsorption of analyte onto the capillary wall within the sample zone. It is demonstrated that the developed method for the assessment of the sweeping efficiency is also applicable to CD-MEKC taking ethylparaben as an example of acidic analytes and desloratadine as an example of basic analytes using different types of β-cyclodextrin. Our previous results regarding RFGE as an additional focusing/defocusing effect in sweeping-MEKC are confirmed for the case that the apparent distribution coefficient differs for the sample and the BGE due to a different content of the complex-forming agent cyclodextrin and due to a pH difference between the sample and the BGE. Despite being significantly more hydrophobic than ethylparaben, desloratadine shows an unexpectedly low enrichment factor. This enrichment factor is nearly unaffected by the addition of CD to the BGE. This unexpected behavior is attributed to wall adsorption of the protonated hydrophobic basic analyte within the sample zone, which significantly counteracts the sweeping process. This assumption is corroborated by an improvement in the enrichment factor achieved via addition of a dynamic coating agent (triethylamine) to the sample solution.

  17. Concept mapping and network analysis: an analytic approach to measure ties among constructs.

    PubMed

    Goldman, Alyssa W; Kane, Mary

    2014-12-01

    Group concept mapping is a mixed-methods approach that helps a group visually represent its ideas on a topic of interest through a series of related maps. The maps and additional graphics are useful for planning, evaluation and theory development. Group concept maps are typically described, interpreted and utilized through points, clusters and distances, and the implications of these features in understanding how constructs relate to one another. This paper focuses on the application of network analysis to group concept mapping to quantify the strength and directionality of relationships among clusters. The authors outline the steps of this analysis, and illustrate its practical use through an organizational strategic planning example. Additional benefits of this analysis to evaluation projects are also discussed, supporting the overall utility of this supplemental technique to the standard concept mapping methodology.

  18. Are Social Networking Sites Making Health Behavior Change Interventions More Effective? A Meta-Analytic Review.

    PubMed

    Yang, Qinghua

    2017-03-01

    The increasing popularity of social networking sites (SNSs) has drawn scholarly attention in recent years, and a large amount of efforts have been made in applying SNSs to health behavior change interventions. However, these interventions showed mixed results, with a large variance of effect sizes in Cohen's d ranging from -1.17 to 1.28. To provide a better understanding of SNS-based interventions' effectiveness, a meta-analysis of 21 studies examining the effects of health interventions using SNS was conducted. Results indicated that health behavior change interventions using SNS are effective in general, but the effects were moderated by health topic, methodological features, and participant features. Theoretical and practical implications of findings are discussed.

  19. Estimating complicated baselines in analytical signals using the iterative training of Bayesian regularized artificial neural networks.

    PubMed

    Mani-Varnosfaderani, Ahmad; Kanginejad, Atefeh; Gilany, Kambiz; Valadkhani, Abolfazl

    2016-10-12

    The present work deals with the development of a new baseline correction method based on the comparative learning capabilities of artificial neural networks. The developed method uses the Bayes probability theorem for prevention of the occurrence of the over-fitting and finding a generalized baseline. The developed method has been applied on simulated and real metabolomic gas-chromatography (GC) and Raman data sets. The results revealed that the proposed method can be used to handle different types of baselines with cave, convex, curvelinear, triangular and sinusoidal patterns. For further evaluation of the performances of this method, it has been compared with benchmarking baseline correction methods such as corner-cutting (CC), morphological weighted penalized least squares (MPLS), adaptive iteratively-reweighted penalized least squares (airPLS) and iterative polynomial fitting (iPF). In order to compare the methods, the projected difference resolution (PDR) criterion has been calculated for the data before and after the baseline correction procedure. The calculated values of PDR after the baseline correction using iBRANN, airPLS, MPLS, iPF and CC algorithms for the GC metabolomic data were 4.18, 3.64, 3.88, 1.88 and 3.08, respectively. The obtained results in this work demonstrated that the developed iterative Bayesian regularized neural network (iBRANN) method in this work thoroughly detects the baselines and is superior over the CC, MPLS, airPLS and iPF techniques. A graphical user interface has been developed for the suggested algorithm and can be used for easy implementation of the iBRANN algorithm for the correction of different chromatography, NMR and Raman data sets.

  20. Extreme Values of Queues, Point Processes and Stochastic Networks.

    DTIC Science & Technology

    2014-09-26

    AD-A158 619 EXTREMIE YALUES OF QUEUES POINT PROCESSES AND STOCHASTIC i/i NETUORKS(U) GEORGIA INST OF TECH ATLANTA R F SERFOZO 25 JUN 85 SFOSR-TR-85...O If "Extreme Values of Queues, Point Processes VW- and Stochastic Networks" 1 Grant No. AFOSR 84-0367 by Professor Richard F. Serfozo Industrial and...NOS. Bldg. 410 PROGRAM PROJECT TASK WORK UNIT Boiling AFB, D.C. 20332-6448 ELEMENT NO. NO. NO. NO. 61102F 2304 A5 11. TITLE (Include Security

  1. Using a Practical Instructional Development Process to Show That Integrating Lab and Active Learning Benefits Undergraduate Analytical Chemistry

    ERIC Educational Resources Information Center

    Goacher, Robyn E.; Kline, Cynthia M.; Targus, Alexis; Vermette, Paul J.

    2017-01-01

    We describe how a practical instructional development process helped a first-year assistant professor rapidly develop, implement, and assess the impact on her Analytical Chemistry course caused by three changes: (a) moving the lab into the same semester as the lecture, (b) developing a more collaborative classroom environment, and (c) increasing…

  2. A Pilot Study in the Application of the Analytic Hierarchy Process to Predict Student Performance in Mathematics

    ERIC Educational Resources Information Center

    Warwick, Jon

    2007-01-01

    The decline in the development of mathematical skills in students prior to university entrance has been a matter of concern to UK higher education staff for a number of years. This article describes a pilot study that uses the Analytic Hierarchy Process to quantify the mathematical experiences of computing students prior to the start of a first…

  3. APPLICATION OF THE ANALYTIC HIERARCHY PROCESS TO COMPARE ALTERNATIVES FOR THE LONG-TERM MANAGEMENT OF SURPLUS MERCURY

    EPA Science Inventory

    This paper describes a systematic method for comparing options for the long-term management of surplus elemental mercury in the U.S., using the Analytic Hierarchy Process (AHP) as embodied in commercially available Expert Choice software. A limited scope multi-criteria decision-a...

  4. Marketing Mix Formulation for Higher Education: An Integrated Analysis Employing Analytic Hierarchy Process, Cluster Analysis and Correspondence Analysis

    ERIC Educational Resources Information Center

    Ho, Hsuan-Fu; Hung, Chia-Chi

    2008-01-01

    Purpose: The purpose of this paper is to examine how a graduate institute at National Chiayi University (NCYU), by using a model that integrates analytic hierarchy process, cluster analysis and correspondence analysis, can develop effective marketing strategies. Design/methodology/approach: This is primarily a quantitative study aimed at…

  5. Application of analytical hierarchy process for effective selection of agricultural best management practices.

    PubMed

    Giri, Subhasis; Nejadhashemi, A Pouyan

    2014-01-01

    In this study an analytical hierarchy process (AHP) was used for ranking best management practices (BMPs) in the Saginaw River Watershed based on environmental, economic and social factors. Three spatial targeting methods were used for placement of BMPs on critical source areas (CSAs). The environment factors include sediment, total nitrogen, and total phosphorus reductions at the subbasin level and the watershed outlet. Economic factors were based on total BMP cost, including installation, maintenance, and opportunity costs. Social factors were divided into three favorability rankings (most favorable, moderately favorable, and least favorable) based on area allocated to each BMP. Equal weights (1/3) were considered for the three main factors while calculating the BMP rank by AHP. In this study three scenarios were compared. A comprehensive approach in which environmental, economic, and social aspects are simultaneously considered (Scenario 1) versus more traditional approaches in which both environmental and economic aspects were considered (Scenario 2) or only environmental aspects (sediment, TN, and TP) were considered (Scenario 3). In Scenario 1, only stripcropping (moderately favorable) was selected on all CSAs at the subbasin level, whereas stripcropping (49-69% of CSAs) and residue management (most favorable, 31-51% of CSAs) were selected by AHP based on the watershed outlet and three spatial targeting methods. In Scenario 2, native grass was eliminated by moderately preferable BMPs (stripcropping) both at the subbasin and watershed outlet levels due the lower BMP implementations cost compared to native grass. Finally, in Scenario 3, at subbasin level, the least socially preferable BMP (native grass) was selected in 100% of CSAs due to greater pollution reduction capacity compared to other BMPs. At watershed level, nearly 50% the CSAs selected stripcropping, and the remaining 50% of CSAs selected native grass and residue management equally.

  6. Land suitability assessment on a watershed of Loess Plateau using the analytic hierarchy process.

    PubMed

    Yi, Xiaobo; Wang, Li

    2013-01-01

    In order to reduce soil erosion and desertification, the Sloping Land Conversion Program has been conducted in China for more than 15 years, and large areas of farmland have been converted to forest and grassland. However, this large-scale vegetation-restoration project has faced some key problems (e.g. soil drying) that have limited the successful development of the current ecological-recovery policy. Therefore, it is necessary to know about the land use, vegetation, and soil, and their inter-relationships in order to identify the suitability of vegetation restoration. This study was conducted at the watershed level in the ecologically vulnerable region of the Loess Plateau, to evaluate the land suitability using the analytic hierarchy process (AHP). The results showed that (1) the area unsuitable for crops accounted for 73.3% of the watershed, and the main factors restricting cropland development were soil physical properties and soil nutrients; (2) the area suitable for grassland was about 86.7% of the watershed, with the remaining 13.3% being unsuitable; (3) an area of 3.95 km(2), accounting for 66.7% of the watershed, was unsuitable for forest. Overall, the grassland was found to be the most suitable land-use to support the aims of the Sloping Land Conversion Program in the Liudaogou watershed. Under the constraints of soil water shortage and nutrient deficits, crops and forests were considered to be inappropriate land uses in the study area, especially on sloping land. When selecting species for re-vegetation, non-native grass species with high water requirements should be avoided so as to guarantee the sustainable development of grassland and effective ecological functioning. Our study provides local land managers and farmers with valuable information about the inappropriateness of growing trees in the study area along with some information on species selection for planting in the semi-arid area of the Loess Plateau.

  7. [Patients' Priorities in the Treatment of Neuroendocrine Tumours: An Analytical Hierarchy Process].

    PubMed

    Mühlbacher, A C; Juhnke, C; Kaczynski, A

    2016-10-01

    Background: Neuroendocrine tumours (NET) are relatively rare, usually slow-growing malignant tumours. So far there are no data on the patient preferences/priorities regarding the therapy for NET. This empirical study aimed at the elicitation of patient priorities in the drug treatment of NET. Method: Qualitative patient interviews (N=9) were conducted. To elicit the patient's perspective regarding various treatment aspects of NET a self-administered questionnaire using the Analytical Hierarchy Process (AHP) was developed. The data collection was carried out using paper questionnaires supported by an item response system in a group discussion. To evaluate the patient-relevant outcomes, the eigenvector method was applied. Results: N=24 patients, experts and relatives participated in the AHP survey. In the AHP all respondents had clear priorities for all considered attributes. The attribute "overall survival" was the most significant feature of a drug therapy for all respondents. As in the qualitative interviews, "efficacy attributes" dominated the side effects in the AHP as well. The evaluation of all participants thus showed the attributes "overall survival" (Wglobal:0.418), "progression-free survival" (Wglobal:0.172) and "response to treatment" (Wglobal:0.161) to be most relevant. "Occurrence of abdominal pain" (Wglobal:0.051) was ranked sixth, with "tiredness/fatigue" and "risk of a hypoglycaemia" (Wglobal:0.034) in a shared seventh place. Conclusion: The results thus provide evidence about how much influence a treatment capacity has on therapeutic decisions. Using the AHP major aspects of drug therapy from the perspective of those affected were captured, and positive and negative therapeutic properties could be related against each other. Based on the assessment of the patient's perspective further investigation must elicit patient preferences for NET drug therapy. In the context of a discrete choice experiment or another choice-based method of preference

  8. Applying the Analytic Hierarchy Process to Oil Sands Environmental Compliance Risk Management

    NASA Astrophysics Data System (ADS)

    Roux, Izak Johannes, III

    Oil companies in Alberta, Canada, invested $32 billion on new oil sands projects in 2013. Despite the size of this investment, there is a demonstrable deficiency in the uniformity and understanding of environmental legislation requirements that manifest into increased project compliance risks. This descriptive study developed 2 prioritized lists of environmental regulatory compliance risks and mitigation strategies and used multi-criteria decision theory for its theoretical framework. Information from compiled lists of environmental compliance risks and mitigation strategies was used to generate a specialized pairwise survey, which was piloted by 5 subject matter experts (SMEs). The survey was validated by a sample of 16 SMEs, after which the Analytic Hierarchy Process (AHP) was used to rank a total of 33 compliance risks and 12 mitigation strategy criteria. A key finding was that the AHP is a suitable tool for ranking of compliance risks and mitigation strategies. Several working hypotheses were also tested regarding how SMEs prioritized 1 compliance risk or mitigation strategy compared to another. The AHP showed that regulatory compliance, company reputation, environmental compliance, and economics ranked the highest and that a multi criteria mitigation strategy for environmental compliance ranked the highest. The study results will inform Alberta oil sands industry leaders about the ranking and utility of specific compliance risks and mitigations strategies, enabling them to focus on actions that will generate legislative and public trust. Oil sands leaders implementing a risk management program using the risks and mitigation strategies identified in this study will contribute to environmental conservation, economic growth, and positive social change.

  9. Acoustic-resonance spectrometry as a process analytical technology for rapid and accurate tablet identification.

    PubMed

    Medendorp, Joseph; Lodder, Robert A

    2006-03-01

    This research was performed to test the hypothesis that acoustic-resonance spectrometry (ARS) is able to rapidly and accurately differentiate tablets of similar size and shape. The US Food and Drug Administration frequently orders recalls of tablets because of labeling problems (eg, the wrong tablet appears in a bottle). A high-throughput, nondestructive method of online analysis and label comparison before shipping could obviate the need for recall or disposal of a batch of mislabeled drugs, thus saving a company considerable expense and preventing a major safety risk. ARS is accurate and precise as well as inexpensive and nondestructive, and the sensor, is constructed from readily available parts, suggesting utility as a process analytical technology (PAT). To test the classification ability of ARS, 5 common household tablets of similar size and shape were chosen for analysis (aspirin, ibuprofen, acetaminophen, vitamin C, and vitamin B12). The measures of successful tablet identification were intertablet distances in nonparametric multidimensional standard deviations (MSDs) greater than, 3 and intratablet MSDs less than 3, as calculated from an extended bootstrap erroradjusted single sample technique. The average intertablet MSD was 65.64, while the average intratablet MSD from cross-validation was 1.91. Tablet mass (r(2)=0.977), thickness (r(2)=0.977), and density (r(2)=0.900) were measured very accurately from the AR spectra, each with less than 10% error. Tablets were identified correctly with only 250 ms data collection time. These results demonstrate that ARS effectively identified and characterized the 5 types of tablets and could potentially serve as a rapid high-throughput online pharmaceutical sensor.

  10. Analytical Hierarchy Process modeling for malaria risk zones in Vadodara district, Gujarat

    NASA Astrophysics Data System (ADS)

    Bhatt, B.; Joshi, J. P.

    2014-11-01

    Malaria epidemic is one of the complex spatial problems around the world. According to WHO, an estimated 6, 27, 000 deaths occurred due to malaria in 2012. In many developing nations with diverse ecological regions, it is still a large cause of human mortality. Owing to the incompleteness of epidemiological data and their spatial origin, the quantification of disease incidence burdening basic public health planning is a major constrain especially in developing countries. The present study focuses on the integrated Geospatial and Multi-Criteria Evaluation (AHP) technique to determine malaria risk zones. The study is conducted in Vadodara district, including 12 Taluka among which 4 Taluka are predominantly tribal. The influence of climatic and physical environmental factors viz., rainfall, hydro geomorphology; drainage, elevation, and land cover are used to score their share in the evaluation of malariogenic condition. This was synthesized on the basis of preference over each factor and the total weights of each data and data layer were computed and visualized. The district was divided into three viz., high, moderate and low risk zones .It was observed that a geographical area of 1885.2sq.km comprising 30.3% fall in high risk zone. The risk zones identified on the basis of these parameters and assigned weights shows a close resemblance with ground condition. As the API distribution for 2011overlaid corresponds to the risk zones identified. The study demonstrates the significance and prospect of integrating Geospatial tools and Analytical Hierarchy Process for malaria risk zones and dynamics of malaria transmission.

  11. Tattoo and taboo: on the meaning of tattoos in the analytic process.

    PubMed

    Karacaoglan, Uta

    2012-02-01

    Tattooing projects a visual image in transference to form a backdrop for the most salient unconscious inner conflicts arising during an ongoing analytic process. Like a snapshot, the tattoo is a dialectic record of the mother-father relationship, of desires for closeness and distance, commonality and difference, identification and individuation. As Walter Benjamin famously stated about the nature of visual images in his Arcades Project, the tattoo represents "dialectics at a standstill." What seems paramount to the patient who participates in the act of tattooing is the need for stasis and immutability, as if bringing unconscious conflicts to "standstill" were to deliver a sense of stability. Unconsciously, the need is triggered by a threat to the inner stability resulting from fear of violating a taboo escalating to the point that fears of abandonment and fusion become unbearable. On the one hand, the tattoo is a visual symbolization of a taboo transgression; on the other hand, it activates the same through an act of self-injury that resembles the magical ritual acts of indigenous peoples' use of tattoos. The taboo thus serves as an ersatz for the actual violation of the taboo in real life, so that the tattoo may be ascribed a magical significance or totemic function. And yet the tattoo's success as a vehicle for constructing a transitional object is always contingent on the tangible manipulation of the skin conjoined with the creation of a symbolizing visual image. The image then acts like a "patch" to repair holes blown into Winnicott's "potential space" and to reconstruct it.

  12. Graphics processing unit-based alignment of protein interaction networks.

    PubMed

    Xie, Jiang; Zhou, Zhonghua; Ma, Jin; Xiang, Chaojuan; Nie, Qing; Zhang, Wu

    2015-08-01

    Network alignment is an important bridge to understanding human protein-protein interactions (PPIs) and functions through model organisms. However, the underlying subgraph isomorphism problem complicates and increases the time required to align protein interaction networks (PINs). Parallel computing technology is an effective solution to the challenge of aligning large-scale networks via sequential computing. In this study, the typical Hungarian-Greedy Algorithm (HGA) is used as an example for PIN alignment. The authors propose a HGA with 2-nearest neighbours (HGA-2N) and implement its graphics processing unit (GPU) acceleration. Numerical experiments demonstrate that HGA-2N can find alignments that are close to those found by HGA while dramatically reducing computing time. The GPU implementation of HGA-2N optimises the parallel pattern, computing mode and storage mode and it improves the computing time ratio between the CPU and GPU compared with HGA when large-scale networks are considered. By using HGA-2N in GPUs, conserved PPIs can be observed, and potential PPIs can be predicted. Among the predictions based on 25 common Gene Ontology terms, 42.8% can be found in the Human Protein Reference Database. Furthermore, a new method of reconstructing phylogenetic trees is introduced, which shows the same relationships among five herpes viruses that are obtained using other methods.

  13. Test of the Use of Regional Networks for OPUS Processing

    NASA Astrophysics Data System (ADS)

    Weston, Neil D.; Ray, Jim R.

    2010-05-01

    We investigate the performance of two processing methodologies for the Online Positioning User Service (OPUS), a web-based tool to process GPS data offered by the National Geodetic Survey, NOAA. The current operational implementation of OPUS (OPUS-S) uses reference station data from the U.S. National CORS Network and fixed IGS ephemerides to compute independent, double-differenced baseline solutions between the unknown and three neighboring CORS reference stations. All computations use relative antenna patterns, phase ambiguity integer fixing, relative troposphere modeling (GPT and GMF a priori models), and are performed in the ITRF2000 (IGb00) reference frame. The most accurate IGS orbits available at the time of processing are used. Although the three baselines are not strictly independent because of local biases, such as multipath at the rover, the solutions are analyzed to identify problems with any of the baselines before they are averaged to obtain a final set of coordinates and uncertainties. A new OPUS processing methodology has been tested using a network approach (OPUS-Net). Otherwise the analysis models and weighted least squares adjustment method are unchanged, except that models for absolute antenna patterns and ocean tide loading are also implemented. The network consists of a rover, three nearby CORS reference stations, and up to 10 reference stations from the global IGS network (IGS05). The multipliers for the a priori weights for the CORS and IGS reference station monument sigmas (meters) in the adjustment are 0.1 and 1000.0 respectively, mainly because the coordinates and velocities for the IGS05 stations are much more precisely known and monitored. To evaluate the positioning performance of the two OPUS approaches, GPS reference station data from three CORS stations (azco, brew, p036) were used as rovers. Approximately 360 daily datasets from each of the three stations collected in 2008 were submitted to each OPUS version for processing. The

  14. Exit probability of the one-dimensional q-voter model: Analytical results and simulations for large networks

    NASA Astrophysics Data System (ADS)

    Timpanaro, André M.; Prado, Carmen P. C.

    2014-05-01

    We discuss the exit probability of the one-dimensional q-voter model and present tools to obtain estimates about this probability, both through simulations in large networks (around 107 sites) and analytically in the limit where the network is infinitely large. We argue that the result E(ρ )=ρq/ρq+(1-ρ)q, that was found in three previous works [F. Slanina, K. Sznajd-Weron, and P. Przybyła, Europhys. Lett. 82, 18006 (2008), 10.1209/0295-5075/82/18006; R. Lambiotte and S. Redner, Europhys. Lett. 82, 18007 (2008), 10.1209/0295-5075/82/18007, for the case q =2; and P. Przybyła, K. Sznajd-Weron, and M. Tabiszewski, Phys. Rev. E 84, 031117 (2011), 10.1103/PhysRevE.84.031117, for q >2] using small networks (around 103 sites), is a good approximation, but there are noticeable deviations that appear even for small systems and that do not disappear when the system size is increased (with the notable exception of the case q =2). We also show that, under some simple and intuitive hypotheses, the exit probability must obey the inequality ρq/ρq+(1-ρ)≤E(ρ)≤ρ/ρ +(1-ρ)q in the infinite size limit. We believe this settles in the negative the suggestion made [S. Galam and A. C. R. Martins, Europhys. Lett. 95, 48005 (2001), 10.1209/0295-5075/95/48005] that this result would be a finite size effect, with the exit probability actually being a step function. We also show how the result that the exit probability cannot be a step function can be reconciled with the Galam unified frame, which was also a source of controversy.

  15. Cellular Neural Network for Real Time Image Processing

    SciTech Connect

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-03-12

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  16. Cellular Neural Network for Real Time Image Processing

    NASA Astrophysics Data System (ADS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-03-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET).

  17. Tough, processable semi-interpenetrating polymer networks from monomer reactants

    NASA Technical Reports Server (NTRS)

    Pater, Ruth H. (Inventor)

    1994-01-01

    A high temperature semi-interpenetrating polymer network (semi-IPN) was developed which had significantly improved processability, damage tolerance, and mechanical performance, when compared to the commercial Thermid materials. This simultaneous semi-IPN was prepared by mixing the monomer precursors of Thermid AL-600 (a thermoset) and NR-150B2 (a thermoplastic) and allowing the monomers to react randomly upon heating. This reaction occurs at a rate which decreases the flow and broadens the processing window. Upon heating at a higher temperature, there is an increase in flow. Because of the improved flow properties, broadened processing window and enhanced toughness, high strength polymer matrix composites, adhesives and molded articles can now be prepared from the acetylene end-capped polyimides which were previously inherently brittle and difficult to process.

  18. Assessment of economic instruments for countries with low municipal waste management performance: An approach based on the analytic hierarchy process.

    PubMed

    Kling, Maximilian; Seyring, Nicole; Tzanova, Polia

    2016-09-01

    Economic instruments provide significant potential for countries with low municipal waste management performance in decreasing landfill rates and increasing recycling rates for municipal waste. In this research, strengths and weaknesses of landfill tax, pay-as-you-throw charging systems, deposit-refund systems and extended producer responsibility schemes are compared, focusing on conditions in countries with low waste management performance. In order to prioritise instruments for implementation in these countries, the analytic hierarchy process is applied using results of a literature review as input for the comparison. The assessment reveals that pay-as-you-throw is the most preferable instrument when utility-related criteria are regarded (wb = 0.35; analytic hierarchy process distributive mode; absolute comparison) mainly owing to its waste prevention effect, closely followed by landfill tax (wb = 0.32). Deposit-refund systems (wb = 0.17) and extended producer responsibility (wb = 0.16) rank third and fourth, with marginal differences owing to their similar nature. When cost-related criteria are additionally included in the comparison, landfill tax seems to provide the highest utility-cost ratio. Data from literature concerning cost (contrary to utility-related criteria) is currently not sufficiently available for a robust ranking according to the utility-cost ratio. In general, the analytic hierarchy process is seen as a suitable method for assessing economic instruments in waste management. Independent from the chosen analytic hierarchy process mode, results provide valuable indications for policy-makers on the application of economic instruments, as well as on their specific strengths and weaknesses. Nevertheless, the instruments need to be put in the country-specific context along with the results of this analytic hierarchy process application before practical decisions are made.

  19. Risk assessment in the upstream crude oil supply chain: Leveraging analytic hierarchy process

    NASA Astrophysics Data System (ADS)

    Briggs, Charles Awoala

    For an organization to be successful, an effective strategy is required, and if implemented appropriately the strategy will result in a sustainable competitive advantage. The importance of decision making in the oil industry is reflected in the magnitude and nature of the industry. Specific features of the oil industry supply chain, such as its longer chain, the complexity of its transportation system, its complex production and storage processes, etc., pose challenges to its effective management. Hence, understanding the risks, the risk sources, and their potential impacts on the oil industry's operations will be helpful in proposing a risk management model for the upstream oil supply chain. The risk-based model in this research uses a three-level analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to underline the importance of risk analysis and risk management in the upstream crude oil supply chain. Level 1 represents the overall goal of risk management; Level 2 is comprised of the various risk factors; and Level 3 represents the alternative criteria of the decision maker as indicated on the hierarchical structure of the crude oil supply chain. Several risk management experts from different oil companies around the world were surveyed, and six major types of supply chain risks were identified: (1) exploration and production, (2) environmental and regulatory compliance, (3) transportation, (4) availability of oil, (5) geopolitical, and (6) reputational. Also identified are the preferred methods of managing risks which include; (1) accept and control the risks, (2) avoid the risk by stopping the activity, or (3) transfer or share the risks to other companies or insurers. The results from the survey indicate that the most important risk to manage is transportation risk with a priority of .263, followed by exploration/production with priority of .198, with an overall inconsistency of .03. With respect to major objectives the most

  20. [Allocating resources for cancer control--resolving multicriteria decision-making using the analytic hierarchy process].

    PubMed

    Gróf, Agnes

    2007-01-01

    When competing programs ought to be financed simultaneously for the same purpose, an allocation problem occurs due to scarce resources, and different perspectives and preferences. Facing the problem needs determining criteria which the decision might be based on. Those criteria form the objectives (the scope) of the different participants, and are relevant for the achievement of the goal, providing a comprehensive resource allocation that bridges and integrates the different perspectives. In case of cancer control primary prevention, secondary prevention, therapy and tertiary prevention, education, basic sciences, and clinical trials form the alternatives. An analytic hierarchy process (AHP) is used for supporting decision-making in the resource allocation problem. AHP is a method for setting priorities, but can only work out the implications of what was declared through the pairwise-ranking process, namely the relative preferences, weighing the criteria and rating the alternatives two by two. In the first analysis the relative weights to criteria were 0.099 for 'distributive justice'; 0.120 for constitutional and human rights; 0.251 for lay opinion; 0.393 for EBM; 0.137 for cost-effectiveness. Ranking the alternatives using 'judgements' resulted in relative preference of 0.238 for therapy, 0.204 for primary prevention, 0.201 for secondary prevention, 0.135 for clinical trials, 0.111 for tertiary prevention, 0.066 for basic sciences and 0.045 for education. In the second analysis the relative importance of "cost-effectiveness" was doubled, thus resulting in 0.234 for therapy, 0.216 for secondary prevention, 0.183 for primary prevention, 0.145 for clinical trials, 0.113 for tertiary prevention, 0.063 for basic sciences and 0.046 for education. Sensitivity analysis has shown that increasing the relative weight of cost-effectiveness up to approximately 0.4 changes the rank of alternatives, and above 0.4 this criterion gives secondary prevention preferences. According

  1. Neural networks in front-end processing and control

    SciTech Connect

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M. )

    1992-04-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper the authors illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. The authors also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. The authors outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. The authors also present some of the difficulties encountered in applying these networks.

  2. The neuron net method for processing the clear pixels and method of the analytical formulas for processing the cloudy pixels of POLDER instrument images

    NASA Astrophysics Data System (ADS)

    Melnikova, I.; Mukai, S.; Vasilyev, A.

    Data of remote measurements of reflected radiance with the POLDER instrument on board of ADEOS satellite are used for retrieval of the optical thickness, single scattering albedo and phase function parameter of cloudy and clear atmosphere. The method of perceptron neural network that from input values of multiangle radiance and Solar incident angle allows to obtain surface albedo, the optical thickness, single scattering albedo and phase function parameter in case of clear sky. Two last parameters are determined as optical average for atmospheric column. The calculation of solar radiance with using the MODTRAN-3 code with taking into account multiple scattering is accomplished for neural network learning. All mentioned parameters were randomly varied on the base of statistical models of possible measured parameters variation. Results of processing one frame of remote observation that consists from 150,000 pixels are presented. The methodology elaborated allows operative determining optical characteristics as cloudy as clear atmosphere. Further interpretation of these results gives the possibility to extract the information about total contents of atmospheric aerosols and absorbing gases in the atmosphere and create models of the real cloudiness An analytical method of interpretation that based on asymptotic formulas of multiple scattering theory is applied to remote observations of reflected radiance in case of cloudy pixel. Details of the methodology and error analysis were published and discussed earlier. Here we present results of data processing of pixel size 6x6 km In many studies the optical thickness is evaluated earlier in the assumption of the conservative scattering. But in case of true absorption in clouds the large errors in parameter obtained are possible. The simultaneous retrieval of two parameters at every wavelength independently is the advantage comparing with earlier studies. The analytical methodology is based on the transfer theory asymptotic

  3. The Martian valley networks: Origin by niveo-fluvial processes

    NASA Technical Reports Server (NTRS)

    Rice, J. W., Jr.

    1993-01-01

    The valley networks may hold the key to unlocking the paleoclimatic history of Mars. These enigmatic landforms may be regarded as the Martian equivalent of the Rosetta Stone. Therefore, a more thorough understanding of their origin and evolution is required. However, there is still no consensus among investigators regarding the formation (runoff vs. sapping) of these features. Recent climatic modeling precludes warm (0 degrees C) globally averaged surface temperatures prior to 2 b.y. when solar luminosity was 25-30 percent less than present levels. This paper advocates snowmelt as the dominant process responsible for the formation of the dendritic valley networks. Evidence for Martian snowfall and subsequent melt has been discussed in previous studies.

  4. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  5. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  6. Elementary processes governing the evolution of road networks

    PubMed Central

    Strano, Emanuele; Nicosia, Vincenzo; Latora, Vito; Porta, Sergio; Barthélemy, Marc

    2012-01-01

    Urbanisation is a fundamental phenomenon whose quantitative characterisation is still inadequate. We report here the empirical analysis of a unique data set regarding almost 200 years of evolution of the road network in a large area located north of Milan (Italy). We find that urbanisation is characterised by the homogenisation of cell shapes, and by the stability throughout time of high–centrality roads which constitute the backbone of the urban structure, confirming the importance of historical paths. We show quantitatively that the growth of the network is governed by two elementary processes: (i) ‘densification’, corresponding to an increase in the local density of roads around existing urban centres and (ii) ‘exploration’, whereby new roads trigger the spatial evolution of the urbanisation front. The empirical identification of such simple elementary mechanisms suggests the existence of general, simple properties of urbanisation and opens new directions for its modelling and quantitative description. PMID:22389765

  7. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  8. Competing spreading processes on multiplex networks: Awareness and epidemics

    NASA Astrophysics Data System (ADS)

    Granell, Clara; Gómez, Sergio; Arenas, Alex

    2014-07-01

    Epidemiclike spreading processes on top of multilayered interconnected complex networks reveal a rich phase diagram of intertwined competition effects. A recent study by the authors [C. Granell et al., Phys. Rev. Lett. 111, 128701 (2013)., 10.1103/PhysRevLett.111.128701] presented an analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the spreading of information awareness to prevent infection, on top of multiplex networks. The results in the case in which awareness implies total immunization to the disease revealed the existence of a metacritical point at which the critical onset of the epidemics starts, depending on completion of the awareness process. Here we present a full analysis of these critical properties in the more general scenario where the awareness spreading does not imply total immunization, and where infection does not imply immediate awareness of it. We find the critical relation between the two competing processes for a wide spectrum of parameters representing the interaction between them. We also analyze the consequences of a massive broadcast of awareness (mass media) on the final outcome of the epidemic incidence. Importantly enough, the mass media make the metacritical point disappear. The results reveal that the main finding, i.e., existence of a metacritical point, is rooted in the competition principle and holds for a large set of scenarios.

  9. Forecasting financial asset processes: stochastic dynamics via learning neural networks.

    PubMed

    Giebel, S; Rainer, M

    2010-01-01

    Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

  10. Using Hybrid Simulation/Analytical Queueing Networks to Capacitate USAF Air Mobility Command Passenger Terminals

    DTIC Science & Technology

    2012-03-01

    researchers have taken many approaches to quantify the impact of increasing demand and changing policies in the aviation industry . Aviation professionals...higher quality service, and more robust processes. The US Air Force has analogous interests to those in the civilian air industry , and can equally benefit...terminals throughout AMC. 5 II. Review of Related Literature Air transportation industry planners have heavily invested in studies focused on how best

  11. Precision and bias of selected analytes reported by the National Atmospheric Deposition Program and National Trends Network, 1983; and January 1980 through September 1984

    USGS Publications Warehouse

    Schroder, L.J.; Bricker, A.W.; Willoughby, T.C.

    1985-01-01

    Blind-audit samples with known analyte concentrations have been prepared by the U.S. Geological Survey and distributed to the National Atmospheric Deposition Program 's Central Analytical Laboratory. The difference between the National Atmospheric Deposition Program and National Trends Network reported analyte concentrations and known analyte concentrations have been calculated, and the bias has been determined. Calcium, magnesium , sodium, and chloride were biased at the 99-percent confidence limit; potassium and sulfate were unbiased at the 99-percent confidence limit, for 1983 results. Relative-percent differences between the measured and known analyte concentration for calcium , magnesium, sodium, potassium, chloride, and sulfate have been calculated for 1983. The median relative percent difference for calcium was 17.0; magnesium was 6.4; sodium was 10.8; potassium was 6.4; chloride was 17.2; and sulfate was -5.3. These relative percent differences should be used to correct the 1983 data before user-analysis of the data. Variances have been calculated for calcium, magnesium, sodium, potassium, chloride, and sulfate determinations. These variances should be applicable to natural-sample analyte concentrations reported by the National Atmospheric Deposition Program and National Trends Network for calendar year 1983. (USGS)

  12. Defining desired genetic gains for rainbow trout breeding objective using analytic hierarchy process.

    PubMed

    Sae-Lim, P; Komen, H; Kause, A; van Arendonk, J A M; Barfoot, A J; Martin, K E; Parsons, J E

    2012-06-01

    Distributing animals from a single breeding program to a global market may not satisfy all producers, as they may differ in market objectives and farming environments. Analytic hierarchy process (AHP) is used to estimate preferences, which can be aggregated to consensus preference values using weighted goal programming (WGP). The aim of this study was to use an AHP-WGP based approach to derive desired genetic gains for rainbow trout breeding and to study whether breeding trait preferences vary depending on commercial products and farming environments. Two questionnaires were sent out. Questionnaire-A (Q-A) was distributed to 178 farmers from 5 continents and used to collect information on commercial products and farming environments. In this questionnaire, farmers were asked to rank the 6 most important traits for genetic improvement from a list of 13 traits. Questionnaire B (Q-B) was sent to all farmers who responded to Q-A (53 in total). For Q-B, preferences of the 6 traits were obtained using pairwise comparison. Preference intensity was given to quantify (in % of a trait mean; G%) the degree to which 1 trait is preferred over the other. Individual preferences, social preferences, and consensus preferences (Con-P) were estimated using AHP and WGP. Desired gains were constructed by multiplying Con-P by G%. The analysis revealed that the 6 most important traits were thermal growth coefficient (TGC), survival (Surv), feed conversion ratio (FCR), condition factor (CF), fillet percentage (FIL%), and late maturation (LMat). Ranking of traits based on average Con-P values were Surv (0.271), FCR (0.246), TGC (0.246), LMat (0.090), FIL% (0.081), and CF (0.067). Corresponding desired genetic gains (in % of trait mean) were 1.63, 1.87, 1.67, 1.29, 0.06, and 0.33%, respectively. The results from Con-P values show that trait preferences may vary for different types of commercial production or farming environments. This study demonstrated that combination of AHP and WGP can

  13. Coastal vulnerability assessment of Puducherry coast, India using analytical hierarchical process

    NASA Astrophysics Data System (ADS)

    Mani Murali, R.; Ankita, M.; Amrita, S.; Vethamony, P.

    2013-03-01

    Increased frequency of natural hazards such as storm surge, tsunami and cyclone, as a consequence of change in global climate, is predicted to have dramatic effects on the coastal communities and ecosystems by virtue of the devastation they cause during and after their occurrence. The tsunami of December 2004 and the Thane cyclone of 2011 caused extensive human and economic losses along the coastline of Puducherry and Tamil Nadu. The devastation caused by these events highlighted the need for vulnerability assessment to ensure better understanding of the elements causing different hazards and to consequently minimize the after-effects of the future events. This paper advocates an Analytical Hierarchical Process (AHP) based approach to coastal vulnerability studies as an improvement to the existing methodologies for vulnerability assessment. The paper also encourages the inclusion of socio-economic parameters along with the physical parameters to calculate the coastal vulnerability index using AHP derived weights. Seven physical-geological parameters (slope, geomorphology, elevation, shoreline change, sea level rise, significant wave height and tidal range) and four socio-economic factors (population, Land-use/Land-cover (LU/LC), roads and location of tourist places) are considered to measure the Physical Vulnerability Index (PVI) as well as the Socio-economic Vulnerability Index (SVI) of the Puducherry coast. Based on the weights and scores derived using AHP, vulnerability maps are prepared to demarcate areas with very low, medium and high vulnerability. A combination of PVI and SVI values are further utilized to compute the Coastal Vulnerability Index (CVI). Finally, the various coastal segments are grouped into the 3 vulnerability classes to obtain the final coastal vulnerability map. The entire coastal extent between Muthiapet and Kirumampakkam as well as the northern part of Kalapet is designated as the high vulnerability zone which constitutes 50% of the

  14. Coastal vulnerability assessment of Puducherry coast, India, using the analytical hierarchical process

    NASA Astrophysics Data System (ADS)

    Mani Murali, R.; Ankita, M.; Amrita, S.; Vethamony, P.

    2013-12-01

    As a consequence of change in global climate, an increased frequency of natural hazards such as storm surges, tsunamis and cyclones, is predicted to have dramatic affects on the coastal communities and ecosystems by virtue of the devastation they cause during and after their occurrence. The tsunami of December 2004 and the Thane cyclone of 2011 caused extensive human and economic losses along the coastline of Puducherry and Tamil Nadu. The devastation caused by these events highlighted the need for vulnerability assessment to ensure better understanding of the elements causing different hazards and to consequently minimize the after- effects of the future events. This paper demonstrates an analytical hierarchical process (AHP)-based approach to coastal vulnerability studies as an improvement to the existing methodologies for vulnerability assessment. The paper also encourages the inclusion of socio-economic parameters along with the physical parameters to calculate the coastal vulnerability index using AHP-derived weights. Seven physical-geological parameters (slope, geomorphology, elevation, shoreline change, sea level rise, significant wave height and tidal range) and four socio-economic factors (population, land use/land cover (LU/LC), roads and location of tourist areas) are considered to measure the physical vulnerability index (PVI) as well as the socio-economic vulnerability index (SVI) of the Puducherry coast. Based on the weights and scores derived using AHP, vulnerability maps are prepared to demarcate areas with very low, medium and high vulnerability. A combination of PVI and SVI values are further utilized to compute the coastal vulnerability index (CVI). Finally, the various coastal segments are grouped into the 3 vulnerability classes to obtain the coastal vulnerability map. The entire coastal extent between Muthiapet and Kirumampakkam as well as the northern part of Kalapet is designated as the high vulnerability zone, which constitutes 50% of the

  15. A Brain Network Processing the Age of Faces

    PubMed Central

    Homola, György A.; Jbabdi, Saad; Beckmann, Christian F.; Bartsch, Andreas J.

    2012-01-01

    Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships. PMID:23185334

  16. Learning Analytics: A Case Study of the Process of Design of Visualizations

    ERIC Educational Resources Information Center

    Olmos, Martin; Corrin, Linda

    2012-01-01

    The ability to visualize student engagement and experience data provides valuable opportunities for learning support and curriculum design. With the rise of the use of learning analytics to provide "actionable intelligence" on students' learning, the challenge is to create visualizations of the data, which are clear and useful to the…

  17. Enterprise Systems Value-Based R&D Portfolio Analytics: Methods, Processes, and Tools

    DTIC Science & Technology

    2014-01-14

    in database and data warehousing, data mining and machine learning, risk analysis and optimization, as well as applied analytics. Practitioners...analyzing historical time series data to provide insights regarding future decisions. • Data mining – which involves mining transactional data bases...reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of

  18. Acoustic-resonance spectrometry as a process analytical technology for the quantification of active pharmaceutical ingredient in semi-solids.

    PubMed

    Medendorp, Joseph; Buice, Robert G; Lodder, Robert A

    2006-09-01

    The purpose of this study was to demonstrate acoustic resonance spectrometry (ARS) as an alternative process analytical technology to near infrared (NIR) spectroscopy for the quantification of active pharmaceutical ingradient (API) in semi-solids such as creams, gels, ointments, and lotions. The ARS used for this research was an inexpensive instrument constructed from readily available parts. Acoustic-resonance spectra were collected with a frequency spectrum from 0 to 22.05 KHz. NIR data were collected from 1100 to 2500 nm. Using 1-point net analyte signal (NAS) calibration, NIR for the API (colloidal oatmeal [CO]) gave anr (2) prediction accuracy of 0.971, and a standard error of performance (SEP) of 0.517%CO. ARS for the API resulted in anr (2) of 0.983 and SEP of 0.317%CO. NAS calibration is compared with principal component regression. This research demonstrates that ARS can sometimes outperform NIR spectrometry and can be an effective analytical method for the quantification of API in semi-solids. ARS requires no sample preparation, provides larger penetration depths into lotions than optical techniques, and measures API concentrations faster and more accurately. These results suggest that ARS is a useful process analytical technology (PAT).

  19. Universality classes of the generalized epidemic process on random networks

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    We present a self-contained discussion of the universality classes of the generalized epidemic process (GEP) on Poisson random networks, which is a simple model of social contagions with cooperative effects. These effects lead to rich phase transitional behaviors that include continuous and discontinuous transitions with tricriticality in between. With the help of a comprehensive finite-size scaling theory, we numerically confirm static and dynamic scaling behaviors of the GEP near continuous phase transitions and at tricriticality, which verifies the field-theoretical results of previous studies. We also propose a proper criterion for the discontinuous transition line, which is shown to coincide with the bond percolation threshold.

  20. Aberrant network connectivity during error processing in patients with schizophrenia

    PubMed Central

    Voegler, Rolf; Becker, Michael P.I.; Nitsch, Alexander; Miltner, Wolfgang H.R.; Straube, Thomas

    2016-01-01

    Background Neuroimaging methods have pointed to deficits in the interaction of large-scale brain networks in patients with schizophrenia. Abnormal connectivity of the right anterior insula (AI), a central hub of the salience network, is frequently reported and may underlie patients’ deficits in adaptive salience processing and cognitive control. While most previous studies used resting state approaches, we examined right AI interactions in a task-based fMRI study. Methods Patients with schizophrenia and healthy controls performed an adaptive version of the Eriksen Flanker task that was specifically designed to ensure a comparable number of errors between groups. Results We included 27 patients with schizophrenia and 27 healthy controls in our study. The between-groups comparison replicated the classic finding of reduced activation in the midcingulate cortex (MCC) in patients with schizophrenia during the commission of errors while controlling for confounding factors, such as task performance and error frequency, which have been neglected in many previous studies. Subsequent psychophysiological interaction analysis revealed aberrant functional connectivity (FC) between the right AI and regions in the inferior frontal gyrus and temporoparietal junction. Additionally, FC between the MCC and the dorsolateral prefrontal cortex was reduced. Limitations As we examined a sample of medicated patients, effects of antipsychotic medication may have influenced our results. Conclusion Overall, it appears that schizophrenia is associated with impairment of networks associated with detection of errors, refocusing of attention, superordinate guiding of cognitive control and their respective coordination. PMID:26836622

  1. Near Real Time Analytics of Human Sensor Networks in the Realm of Big Data

    NASA Astrophysics Data System (ADS)

    Aulov, O.; Halem, M.

    2012-12-01

    With the prolific development of social media, emergency responders have an increasing interest in harvesting social media from outlets such as Flickr, Twitter, and Facebook, in order to assess the scale and specifics of extreme events including wild fires, earthquakes, terrorist attacks, oil spills, etc. A number of experimental platforms have successfully been implemented to demonstrate the utilization of social media data in extreme events, including Twitter Earthquake Detector, which relied on tweets for earthquake monitoring; AirTwitter, which used tweets for air quality reporting; and our previous work, using Flickr data as boundary value forcings to improve the forecast of oil beaching in the aftermath of the Deepwater Horizon oil spill. The majority of these platforms addressed a narrow, specific type of emergency and harvested data from a particular outlet. We demonstrate an interactive framework for monitoring, mining and analyzing a plethora of heterogeneous social media sources for a diverse range of extreme events. Our framework consists of three major parts: a real time social media aggregator, a data processing and analysis engine, and a web-based visualization and reporting tool. The aggregator gathers tweets, Facebook comments from fan pages, Google+ posts, forum discussions, blog posts (such as LiveJournal and Blogger.com), images from photo-sharing platforms (such as Flickr, Picasa), videos from video-sharing platforms (youtube, Vimeo), and so forth. The data processing and analysis engine pre-processes the aggregated information and annotates it with geolocation and sentiment information. In many cases, the metadata of the social media posts does not contain geolocation information—-however, a human reader can easily guess from the body of the text what location is discussed. We are automating this task by use of Named Entity Recognition (NER) algorithms and a gazetteer service. The visualization and reporting tool provides a web-based, user

  2. Analytical Approach to the One-Dimensional Disordered Exclusion Process with Open Boundaries and Random Sequential Dynamics

    NASA Astrophysics Data System (ADS)

    Loulidi, M.

    2008-07-01

    A one-dimensional disordered particle hopping rate asymmetric exclusion process (ASEP) with open boundaries and a random sequential dynamics is studied analytically. Combining the exact results of the steady states in the pure case with a perturbative mean field-like approach the broken particle-hole symmetry is highlighted and the phase diagram is studied in the parameter space ( α, β), where α and β represent respectively the injection rate and the extraction rate of particles. The model displays, as in the pure case, high-density, low-density and maximum-current phases. All critical lines are determined analytically showing that the high-density low-density first order phase transition occurs at α≠ β. We show that the maximum-current phase extends its stability region as the disorder is increased and the usual 1/sqrt{ell} -decay of the density profile in this phase is universal. Assuming that some exact results for the disordered model on a ring hold for a system with open boundaries, we derive some analytical results for platoon phase transition within the low-density phase and we give an analytical expression of its corresponding critical injection rate α *. As it was observed numerically (Bengrine et al. J. Phys. A: Math. Gen. 32:2527, [1999]), we show that the quenched disorder induces a cusp in the current-density relation at maximum flow in a certain region of parameter space and determine the analytical expression of its slope. The results of numerical simulations we develop agree with the analytical ones.

  3. Incomplete fuzzy data processing systems using artificial neural network

    NASA Technical Reports Server (NTRS)

    Patyra, Marek J.

    1992-01-01

    In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

  4. Enhanced surface sampler and process for collection and release of analytes

    DOEpatents

    Addleman, Raymond S; Atkinson, David A; Bays, John T; Chouyyok, Wilaiwan; Cinson, Anthony D; Ewing, Robert G; Gerasimenko, Aleksandr A

    2015-02-03

    An enhanced swipe sampler and method of making are described. The swipe sampler is made of a fabric containing selected glass, metal oxide, and/or oxide-coated glass or metal fibers. Fibers are modified with silane ligands that are directly attached to the surface of the fibers to functionalize the sampling surface of the fabric. The swipe sampler collects various target analytes including explosives and other threat agents on the surface of the sampler.

  5. Managing the Pre- and Post-analytical Phases of the Total Testing Process

    PubMed Central

    2012-01-01

    For many years, the clinical laboratory's focus on analytical quality has resulted in an error rate of 4-5 sigma, which surpasses most other areas in healthcare. However, greater appreciation of the prevalence of errors in the pre- and post-analytical phases and their potential for patient harm has led to increasing requirements for laboratories to take greater responsibility for activities outside their immediate control. Accreditation bodies such as the Joint Commission International (JCI) and the College of American Pathologists (CAP) now require clear and effective procedures for patient/sample identification and communication of critical results. There are a variety of free on-line resources available to aid in managing the extra-analytical phase and the recent publication of quality indicators and proposed performance levels by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) working group on laboratory errors and patient safety provides particularly useful benchmarking data. Managing the extra-laboratory phase of the total testing cycle is the next challenge for laboratory medicine. By building on its existing quality management expertise, quantitative scientific background and familiarity with information technology, the clinical laboratory is well suited to play a greater role in reducing errors and improving patient safety outside the confines of the laboratory. PMID:22259773

  6. Using Fuzzy Analytic Hierarchy Process multicriteria and Geographical information system for coastal vulnerability analysis in Morocco: The case of Mohammedia

    NASA Astrophysics Data System (ADS)

    Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha

    2016-04-01

    This paper shows a method to assess the vulnerability of coastal risks such as coastal erosion or submarine applying Fuzzy Analytic Hierarchy Process (FAHP) and spatial analysis techniques with Geographic Information System (GIS). The coast of the Mohammedia located in Morocco was chosen as the study site to implement and validate the proposed framework by applying a GIS-FAHP based methodology. The coastal risk vulnerability mapping follows multi-parametric causative factors as sea level rise, significant wave height, tidal range, coastal erosion, elevation, geomorphology and distance to an urban area. The Fuzzy Analytic Hierarchy Process methodology enables the calculation of corresponding criteria weights. The result shows that the coastline of the Mohammedia is characterized by a moderate, high and very high level of vulnerability to coastal risk. The high vulnerability areas are situated in the east at Monika and Sablette beaches. This technical approach is based on the efficiency of the Geographic Information System tool based on Fuzzy Analytical Hierarchy Process to help decision maker to find optimal strategies to minimize coastal risks.

  7. Analytical algorithm for modeling polarized solar radiation transfer through the atmosphere for application in processing complex lidar and radiometer measurements

    NASA Astrophysics Data System (ADS)

    Chaikovskaya, L.; Dubovik, O.; Litvinov, P.; Grudo, J.; Lopatsin, A.; Chaikovsky, A.; Denisov, S.

    2015-01-01

    Inversion algorithms and program packages recently created for processing data of the ground-based radiometer spectral measurements along with lidar multi-wavelength measurements are extremely multiparametric. Therefore, it is very important to develop an efficient program module for computations of functions modeling measurements by a sun-radiometer in the inversion procedure. In this paper, we present the analytical version of such efficient algorithm and analytical code on C++ designed for performance of algorithm testing. The code computes multiple scattering of the Sun light in the atmosphere. Data output are the radiance and linear polarization parameters angular patterns at a preselected altitude. The atmosphere model with mixed aerosol and molecular scattering is given approximately as the homogeneous atmosphere model. The algorithm testing has been carried out by comparison of computed data with accurate data obtained on the base of the discrete-ordinate code. Errors of estimates of downward radiance above the Earth surface turned out to be within 10%-15%.. The analytical solution construction concept has taken from the scalar task of solar radiation transfer in the atmosphere where an approximate analytical solution was developed. Taking into account the fact that aerosol phase functions are highly forward elongated, the multi-component method of solving vector transfer equations and small-angle approximation have been used. Generalization of the scalar approach to the polarization parameters is described.

  8. Dynamic Processes in Network Goods: Modeling, Analysis and Applications

    ERIC Educational Resources Information Center

    Paothong, Arnut

    2013-01-01

    The network externality function plays a very important role in the study of economic network industries. Moreover, the consumer group dynamic interactions coupled with network externality concept is going to play a dominant role in the network goods in the 21st century. The existing literature is stemmed on a choice of externality function with…

  9. Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

    PubMed

    Bujkiewicz, Sylwia; Thompson, John R; Riley, Richard D; Abrams, Keith R

    2016-03-30

    A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression.

  10. Receptive amusia: evidence for cross-hemispheric neural networks underlying music processing strategies.

    PubMed

    Schuppert, M; Münte, T F; Wieringa, B M; Altenmüller, E

    2000-03-01

    Perceptual musical functions were investigated in patients suffering from unilateral cerebrovascular cortical lesions. Using MIDI (Musical Instrument Digital Interface) technique, a standardized short test battery was established that covers local (analytical) as well as global perceptual mechanisms. These represent the principal cognitive strategies in melodic and temporal musical information processing (local, interval and rhythm; global, contour and metre). Of the participating brain-damaged patients, a total of 69% presented with post-lesional impairments in music perception. Left-hemisphere-damaged patients showed significant deficits in the discrimination of local as well as global structures in both melodic and temporal information processing. Right-hemisphere-damaged patients also revealed an overall impairment of music perception, reaching significance in the temporal conditions. Detailed analysis outlined a hierarchical organization, with an initial right-hemisphere recognition of contour and metre followed by identification of interval and rhythm via left-hemisphere subsystems. Patterns of dissociated and associated melodic and temporal deficits indicate autonomous, yet partially integrated neural subsystems underlying the processing of melodic and temporal stimuli. In conclusion, these data contradict a strong hemispheric specificity for music perception, but indicate cross-hemisphere, fragmented neural substrates underlying local and global musical information processing in the melodic and temporal dimensions. Due to the diverse profiles of neuropsychological deficits revealed in earlier investigations as well as in this study, individual aspects of musicality and musical behaviour very likely contribute to the definite formation of these widely distributed neural networks.

  11. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    PubMed

    Orbán, Levente L; Chartier, Sylvain

    2015-01-01

    Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

  12. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    PubMed

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high.

  13. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    PubMed

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  14. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

    PubMed Central

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  15. Retinal vessel extraction using Lattice Neural Networks with Dendritic Processing.

    PubMed

    Vega, Roberto; Sanchez-Ante, Gildardo; Falcon-Morales, Luis E; Sossa, Humberto; Guevara, Elizabeth

    2015-03-01

    Retinal images can be used to detect and follow up several important chronic diseases. The classification of retinal images requires an experienced ophthalmologist. This has been a bottleneck to implement routine screenings performed by general physicians. It has been proposed to create automated systems that can perform such task with little intervention from humans, with partial success. In this work, we report advances in such endeavor, by using a Lattice Neural Network with Dendritic Processing (LNNDP). We report results using several metrics, and compare against well known methods such as Support Vector Machines (SVM) and Multilayer Perceptrons (MLP). Our proposal shows better performance than other approaches reported in the literature. An additional advantage is that unlike those other tools, LNNDP requires no parameters, and it automatically constructs its structure to solve a particular problem. The proposed methodology requires four steps: (1) Pre-processing, (2) Feature computation, (3) Classification and (4) Post-processing. The Hotelling T(2) control chart was used to reduce the dimensionality of the feature vector, from 7 that were used before to 5 in this work. The experiments were run on images of DRIVE and STARE databases. The results show that on average, F1-Score is better in LNNDP, compared with SVM and MLP implementations. Same improvement is observed for MCC and the accuracy.

  16. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

  17. Neural Networks for Signal Processing VII Proceeding of the 1997 IEEE Workshop

    DTIC Science & Technology

    2007-11-02

    Fu, Hsin-Chia and Xu, Y. Y. 626 Neural Networks for Engine Fault Diagnostics Dong, Dawei W., Hopfield , John J., and Unnikrishnan, K. P. 636...June 98 REPORT TYPE AND DATES COVERED Final \\^Q\\ Cf\\ - M DteC ^ TITLE AND SUBTITLE Neural Networks for Signal Processing VII Proceeding...sponsored by the Neural Networks Technical Committee of the IEEE Signal Processing Society, in cooperation with the IEEE Neural Networks Council and

  18. Process analytical technology case study, part III: calibration monitoring and transfer.

    PubMed

    Cogdill, Robert P; Anderson, Carl A; Drennen, James K

    2005-10-06

    This is the third of a series of articles detailing the development of near-infrared spectroscopy methods for solid dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to develop a system for continuous calibration monitoring and formulate an appropriate strategy for calibration transfer. Indicators of high-flux noise (noise factor level) and wavelength uncertainty were developed. These measurements, in combination with Hotelling's T(2) and Q residual, are used to continuously monitor instrument performance and model relevance. Four calibration transfer techniques were compared. Three established techniques, finite impulse response filtering, generalized least squares weighting, and piecewise direct standardization were evaluated. A fourth technique, baseline subtraction, was the most effective for calibration transfer. Using as few as 15 transfer samples, predictive capability of the analytical method was maintained across multiple instruments and major instrument maintenance.

  19. Reducing congestion on complex networks by dynamic relaxation processes

    NASA Astrophysics Data System (ADS)

    Macri, Pablo A.; Pastore y Piontti, Ana L.; Braunstein, Lidia A.

    2007-12-01

    We study the effects of relaxational dynamics on the congestion pressure in general transport networks. We show that the congestion pressure is reduced in scale-free networks if a relaxation mechanism is utilized, while this is in general not the case for non-scale-free graphs such as random graphs. We also present evidence supporting the idea that the emergence of scale-free networks arise from optimization mechanisms to balance the load of the networks nodes.

  20. The Scaling of Human Contacts and Epidemic Processes in Metapopulation Networks

    NASA Astrophysics Data System (ADS)

    Tizzoni, Michele; Sun, Kaiyuan; Benusiglio, Diego; Karsai, Márton; Perra, Nicola

    2015-10-01

    We study the dynamics of reaction-diffusion processes on heterogeneous metapopulation networks where interaction rates scale with subpopulation sizes. We first present new empirical evidence, based on the analysis of the interactions of 13 million users on Twitter, that supports the scaling of human interactions with population size with an exponent γ ranging between 1.11 and 1.21, as observed in recent studies based on mobile phone data. We then integrate such observations into a reaction- diffusion metapopulation framework. We provide an explicit analytical expression for the global invasion threshold which sets a critical value of the diffusion rate below which a contagion process is not able to spread to a macroscopic fraction of the system. In particular, we consider the Susceptible-Infectious-Recovered epidemic model. Interestingly, the scaling of human contacts is found to facilitate the spreading dynamics. This behavior is enhanced by increasing heterogeneities in the mobility flows coupling the subpopulations. Our results show that the scaling properties of human interactions can significantly affect dynamical processes mediated by human contacts such as the spread of diseases, ideas and behaviors.

  1. Aggregation Processes on Networks: Deterministic Equations, Stochastic Model and Numerical Simulation

    SciTech Connect

    Guias, Flavius

    2008-09-01

    We introduce an infinite system of equations modeling the time evolution of the growth process of a network. The nodes are characterized by their degree k(set-membership sign)N and a fitness parameter f(set-membership sign)[0,h]. Every new node which emerges becomes a fitness f' according to a given distribution P and attaches to an existing node with fitness f and degree k at rate fA{sub k}, where A{sub k} are positive coefficients, growing sub-linearly in k. If the parameter f takes only one value, the dynamics of this process can be described by a variant of the Becker-Doering equations, where the l growth of the size of clusters of size k occurs only with increment 1. In contrast l to the established Becker-Doering equations, the system considered here is nonconservative, since mass (i.e. links) is continuously added. Nevertheless, it has the property of linearity, which is a natural consequence of the process which is being modeled. The purpose of this paper is to construct a solution of the system based on a stochastic approximation algorithm, which allows also a numerical simulation in order to get insight into its qualitative behaviour. In particular we show analytically and numerically the property of Bose-Einstein condensation, which was observed in the literature on random graphs and which can be described as an emergence of a huge cluster which captures a macroscopic fraction of the total link density.

  2. Pre-PCR processing in bioterrorism preparedness: improved diagnostic capabilities for laboratory response networks.

    PubMed

    Hedman, Johannes; Knutsson, Rickard; Ansell, Ricky; Rådström, Peter; Rasmusson, Birgitta

    2013-09-01

    Diagnostic DNA analysis using polymerase chain reaction (PCR) has become a valuable tool for rapid detection of biothreat agents. However, analysis is often challenging because of the limited size, quality, and purity of the biological target. Pre-PCR processing is an integrated concept in which the issues of analytical limit of detection and simplicity for automation are addressed in all steps leading up to PCR amplification--that is, sampling, sample treatment, and the chemical composition of PCR. The sampling method should maximize target uptake and minimize uptake of extraneous substances that could impair the analysis--so-called PCR inhibitors. In sample treatment, there is a trade-off between yield and purity, as extensive purification leads to DNA loss. A cornerstone of pre-PCR processing is to apply DNA polymerase-buffer systems that are tolerant to specific sample impurities, thereby lowering the need for expensive purification steps and maximizing DNA recovery. Improved awareness among Laboratory Response Networks (LRNs) regarding pre-PCR processing is important, as ineffective sample processing leads to increased cost and possibly false-negative or ambiguous results, hindering the decision-making process in a bioterrorism crisis. This article covers the nature and mechanisms of PCR-inhibitory substances relevant for agroterrorism and bioterrorism preparedness, methods for quality control of PCR reactions, and applications of pre-PCR processing to optimize and simplify the analysis of various biothreat agents. Knowledge about pre-PCR processing will improve diagnostic capabilities of LRNs involved in the response to bioterrorism incidents.

  3. Non-transcriptional regulatory processes shape transcriptional network dynamics.

    PubMed

    Ray, J Christian J; Tabor, Jeffrey J; Igoshin, Oleg A

    2011-10-11

    Information about the extra- or intracellular environment is often captured as biochemical signals that propagate through regulatory networks. These signals eventually drive phenotypic changes, typically by altering gene expression programmes in the cell. Reconstruction of transcriptional regulatory networks has given a compelling picture of bacterial physiology, but transcriptional network maps alone often fail to describe phenotypes. Cellular response dynamics are ultimately determined by interactions between transcriptional and non-transcriptional networks, with dramatic implications for physiology and evolution. Here, we provide an overview of non-transcriptional interactions that can affect the performance of natural and synthetic bacterial regulatory networks.

  4. Biospeckle image stack process based on artificial neural networks.

    PubMed

    Meschino, Gustavo; Murialdo, Silvia; Passoni, Lucia; Rabal, Hector; Trivi, Marcelo

    2010-01-01

    This paper proposes the identification of regions of interest in biospeckle patterns using unsupervised neural networks of the type Self-Organizing Maps. Segmented images are obtained from the acquisition and processing of laser speckle sequences. The dynamic speckle is a phenomenon that occurs when a beam of coherent light illuminates a sample in which there is some type of activity, not visible, which results in a variable pattern over time. In this particular case the method is applied to the evaluation of bacterial chemotaxis. Image stacks provided by a set of experiments are processed to extract features of the intensity dynamics. A Self-Organizing Map is trained and its cells are colored according to a criterion of similarity. During the recall stage the features of patterns belonging to a new biospeckle sample impact on the map, generating a new image using the color of the map cells impacted by the sample patterns. It is considered that this method has shown better performance to identify regions of interest than those that use a single descriptor. To test the method a chemotaxis assay experiment was performed, where regions were differentiated according to the bacterial motility within the sample.

  5. High level cognitive information processing in neural networks

    NASA Technical Reports Server (NTRS)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

  6. A cognitive information processing framework for distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Wang, Feiyi; Qi, Hairong

    2004-09-01

    In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

  7. Connectivity of the subthalamic nucleus and globus pallidus pars interna to regions within the speech network: a meta-analytic connectivity study.

    PubMed

    Manes, Jordan L; Parkinson, Amy L; Larson, Charles R; Greenlee, Jeremy D; Eickhoff, Simon B; Corcos, Daniel M; Robin, Donald A

    2014-07-01

    Cortico-basal ganglia connections are involved in a range of behaviors within motor, cognitive, and emotional domains; however, the whole-brain functional connections of individual nuclei are poorly understood in humans. The first aim of this study was to characterize and compare the connectivity of the subthalamic nucleus (STN) and globus pallidus pars interna (GPi) using meta-analytic connectivity modeling. Structure-based activation likelihood estimation meta-analyses were performed for STN and GPi seeds using archived functional imaging coordinates from the BrainMap database. Both regions coactivated with caudate, putamen, thalamus, STN, GPi, and GPe, SMA, IFG, and insula. Contrast analyses also revealed coactivation differences within SMA, IFG, insula, and premotor cortex. The second aim of this study was to examine the degree of overlap between the connectivity maps derived for STN and GPi and a functional activation map representing the speech network. To do this, we examined the intersection of coactivation maps and their respective contrasts (STN > GPi and GPi > STN) with a coordinate-based meta-analysis of speech function. In conjunction with the speech map, both STN and GPi coactivation maps revealed overlap in the anterior insula with GPi map additionally showing overlap in the supplementary motor area (SMA). Among cortical regions activated by speech tasks, STN was found to have stronger connectivity than GPi with regions involved in cognitive linguistic processes (pre-SMA, dorsal anterior insula, and inferior frontal gyrus), while GPi demonstrated stronger connectivity to regions involved in motor speech processes (middle insula, SMA, and premotor cortex).

  8. Anxious personality and functional efficiency of the insular-opercular network: A graph-analytic approach to resting-state fMRI.

    PubMed

    Markett, Sebastian; Montag, Christian; Melchers, Martin; Weber, Bernd; Reuter, Martin

    2016-12-01

    The brain is an intricate network, not only structurally but also functionally. On the functional level, connectivity in the brain is organized in separable yet interacting networks that support information processing by maintaining a ready state, even in the absence of external stimulation. It has been hypothesized that an insular-opercular network underlies the processing of emotionally salient information and that individual differences in functional connectivity within this network correspond to individual differences in trait anxiety. Here, we tested this relationship by applying graph analysis to multiple regions of interests delineating the insular-opercular network to estimate the characteristic path length that quantifies the overall information exchange efficiency within a given network. We found that people scoring high on the anxiety-related temperament-dimension harm avoidance had decreased insular-opercular network efficiency in the resting state, as indicated by a higher characteristic path length. Furthermore, people scoring high on harm avoidance showed generally reduced functional connectivity between brain regions; the relationship between harm avoidance and insular-opercular network efficiency remained significant when controlling for mean connectivity within this network. No such results were found for other resting-state networks. The results provide insights into how personality is organized in the human brain and point toward clinically relevant endophenotypes for affective and mood disorders.

  9. Application of analytic hierarchy process-grey target theory systematic model in comprehensive evaluation of water environmental quality.

    PubMed

    Wu, Jun; Tian, Xiaogang; Tang, Ya; Zhao, Yujie; Hu, Yandi; Fang, Zili

    2010-07-01

    Comprehensive evaluation of the water environment for effective water quality management is complicated by a considerable number of factors and uncertainties. It is difficult to combine micro-evaluation with the macro-evaluation process. To effectively eliminate the subjective errors of the traditional analytic hierarchy process (AHP), a new modeling approach--the analytic hierarchy process and grey target theory (AHP-GTT) systematic model--is presented in this study to evaluate water quality in a certain watershed. A case study of applying the AHP-GTT systematic model to the evaluation and analysis of the water environment was conducted in the Yibin section of the Yangtze River, China. The micro-evaluation is based on defining the weights of indices of the water quality (IWQ) of each water cross-section, while the macro-evaluation is based on calculating the comprehensive indices of water environmental quality and analyzing the tendency of the water environment of each cross-section. The results indicated that the Baixi and Shuidongmen sections are seriously polluted areas, with the tendencies of becoming worse. Also, the key IWQs of these two cross-sections are 5-day biochemical oxygen demand and chemical oxygen demand of permanganate, respectively.

  10. Analytic Root Locus and Lambert W Function in Control of a Process with Time Delay

    NASA Astrophysics Data System (ADS)

    Cogan, Brian; de Paor, Annraoi M.

    2011-11-01

    Recently, the Lambert W function has arisen in the analysis of many systems including a restricted class of time-delay systems. An alternative approach to this analysis, based on the well-established root locus method, is shown here to contain the Lambert W function as a special case. As a purely illustrative example of the equivalence between the Lambert W function and analytic root locus a system comprising a Proportional controller with a time-delay process is analysed. Controller designs based on rightmost eigenvalue location and the dominant eigenvalue method are described.

  11. Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

    PubMed

    da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

    2005-01-01

    This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment.

  12. [Discussion on Quality Evaluation Method of Medical Device During Life-Cycle in Operation Based on the Analytic Hierarchy Process].

    PubMed

    Zheng, Caixian; Zheng, Kun; Shen, Yunming; Wu, Yunyun

    2016-01-01

    The content related to the quality during life-cycle in operation of medical device includes daily use, repair volume, preventive maintenance, quality control and adverse event monitoring. In view of this, the article aims at discussion on the quality evaluation method of medical devices during their life cycle in operation based on the Analytic Hierarchy Process (AHP). The presented method is proved to be effective by evaluating patient monitors as example. The method presented in can promote and guide the device quality control work, and it can provide valuable inputs to decisions about purchase of new device.

  13. An analytical method for PID controller tuning with specified gain and phase margins for integral plus time delay processes.

    PubMed

    Hu, Wuhua; Xiao, Gaoxi; Li, Xiumin

    2011-04-01

    In this paper, an analytical method is proposed for proportional-integral/proportional-derivative/proportional-integral-derivative (PI/PD/PID) controller tuning with specified gain and phase margins (GPMs) for integral plus time delay (IPTD) processes. Explicit formulas are also obtained for estimating the GPMs resulting from given PI/PD/PID controllers. The proposed method indicates a general form of the PID parameters and unifies a large number of existing rules as PI/PD/PID controller tuning with various GPM specifications. The GPMs realized by existing PID tuning rules are computed and documented as a reference for control engineers to tune the PID controllers.

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

    NASA Astrophysics Data System (ADS)

    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

  15. A Semi-Analytic Study of Feedback Processes and Metallicity Profiles in Disc Galaxies

    NASA Astrophysics Data System (ADS)

    Sandford, Nathan Ross; Lu, Yu

    2016-01-01

    The metallicity gradients of disc galaxies contain valuable information about the physics governing their formation and evolution. The observed metallicity profiles have negative gradients that are steeper at high redshifts, indicating an inside-out formation of disc galaxies. We improve on our semi-analytic galaxy formation model (Lu, Mo & Wechsler 2015) by incorporating the radial distribution of metals into the model. With the improved model, we explore how feedback scenarios affect metallicity gradients. The model features 3 feedback scenarios: An Ejective (EJ) model, which includes ejective supernova (SN) feedback, a PRe-Heating (PR) model, which assumes that the intergalactic medium is preheated, preventing it from collapsing onto galaxies, and a Re-Incorporation (RI) model, which also includes strong outflows but allows ejected gas to re-accrete onto the galaxies. We compare the models with observations from Ho et al. (2015) and find that while all models struggle to match the observed metallicity gradient-stellar mass relationship, the PR model predicts metallicity gradients that best match observations. We also find that the RI model predicts a flat gradient because its outflow and re-accretion replenish the disc uniformly with newly accreted enriched gas, erasing the mark of inside-out formation. Our findings suggest feedback plays a key role in shaping the metallicity gradients of disc galaxies and require more detailed theoretical modeling to understand them.

  16. Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing.

    PubMed

    Ernst, Madeleine; Silva, Denise Brentan; Silva, Ricardo Roberto; Vêncio, Ricardo Z N; Lopes, Norberto Peporine

    2014-06-01

    Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

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

    PubMed

    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.

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

    PubMed Central

    Kermajani, Hamidreza; Gomez, Carles

    2014-01-01

    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. PMID:25004154

  19. Process analytical technology (PAT) for biopharmaceutical products: Part II. Concepts and applications.

    PubMed

    Read, E K; Shah, R B; Riley, B S; Park, J T; Brorson, K A; Rathore, A S

    2010-02-01

    Implementing real-time product quality control meets one or both of the key goals outlined in FDA's PAT guidance: "variability is managed by the process" and "product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions." The first part of the paper presented an overview of PAT concepts and applications in the areas of upstream and downstream processing. In this second part, we present principles and case studies to illustrate implementation of PAT for drug product manufacturing, rapid microbiology, and chemometrics. We further present our thoughts on how PAT will be applied to biotech processes going forward. The role of PAT as an enabling component of the Quality by Design framework is highlighted. Integration of PAT with the principles stated in the ICH Q8, Q9, and Q10 guidance documents is also discussed.

  20. Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

    NASA Astrophysics Data System (ADS)

    Brennan, Sean R.; Torgersen, Christian E.; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K.; Schindler, Daniel E.

    2016-05-01

    A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called "isoscapes," form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

  1. Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

    USGS Publications Warehouse

    Brennan, Sean R.; Torgersen, Christian; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K; Schindler, Daniel E.

    2016-01-01

    A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

  2. Study of an ultrasound-based process analytical tool for homogenization of nanoparticulate pharmaceutical vehicles.

    PubMed

    Cavegn, Martin; Douglas, Ryan; Akkermans, Guy; Kuentz, Martin

    2011-08-01

    There are currently no adequate process analyzers for nanoparticulate viscosity enhancers. This article aims to evaluate ultrasonic resonator technology as a monitoring tool for homogenization of nanoparticulate gels. Aqueous dispersions of colloidal microcrystalline cellulose (MCC) and a mixture of clay particles with xanthan gum were compared with colloidal silicon dioxide in oil. The processing was conducted using a laboratory-scale homogenizing vessel. The study investigated first the homogenization kinetics of the different systems to focus then on process factors in the case of colloidal MCC. Moreover, rheological properties were analyzed offline to assess the structure of the resulting gels. Results showed the suitability of ultrasound velocimetry to monitor the homogenization process. The obtained data were fitted using a novel heuristic model. It was possible to identify characteristic homogenization times for each formulation. The subsequent study of the process factors demonstrated that ultrasonic process analysis was equally sensitive as offline rheological measurements in detecting subtle manufacturing changes. It can be concluded that the ultrasonic method was able to successfully assess homogenization of nanoparticulate viscosity enhancers. This novel technique can become a vital tool for development and production of pharmaceutical suspensions in the future.

  3. Analytical considerations and dimensionless analysis for a description of particle interactions in high pressure processes

    NASA Astrophysics Data System (ADS)

    Rauh, Cornelia; Delgado, Antonio

    2010-12-01

    High pressures of up to several hundreds of MPa are utilized in a wide range of applications in chemical, bio-, and food engineering, aiming at selective control of (bio-)chemical reactions. Non-uniformity of process conditions may threaten the safety and quality of the resulting products because processing conditions such as pressure, temperature, and treatment history are crucial for the course of (bio-)chemical reactions. Therefore, thermofluid-dynamical phenomena during the high pressure process have to be examined, and numerical tools to predict process uniformity and to optimize the processes have to be developed. Recently applied mathematical models and numerical simulations of laboratory and industrial scale high pressure processes investigating the mentioned crucial phenomena are based on continuum balancing models of thermofluid dynamics. Nevertheless, biological systems are complex fluids containing the relevant (bio-)chemical compounds (enzymes and microorganisms). These compounds are particles that interact with the surrounding medium and between each other. This contribution deals with thermofluid-dynamical interactions of the relevant particulate (bio-)chemical compounds (enzymes and microorganisms) with the surrounding fluid. By consideration of characteristic time and length scales and particle forces, the motion of the (bio-)chemical compounds is characterized.

  4. An Analytical and Experimental Study of Super-Seeding in BitTorrent-Like P2P Networks

    NASA Astrophysics Data System (ADS)

    Chen, Zhijia; Lin, Chuang; Chen, Yang; Nivargi, Vaibhav; Cao, Pei

    With the popularity of BitTorrent-like P2P applications, improving its performance has been an active research area. Super-seeding, a special upload policy for the initial seeder, improves the efficiency in producing multiple seeds and reduces the uploading bytes of content initiators, thus being highly expected as a promising solution for improving downloading performance while decreasing uploading cost. However, the overall impacts of super seeding upon BitTorrent performance remain a question and have not been analyzed so far in literature. In this paper, we present an analytical and experimental study over the performance of super-seeding scheme. We attempt to answer the following questions: whether and how much super-seeding saves uploading cost, whether the overall downloading time is decreased by super-seeding, and in which circumstances super-seeding performs worse. Based on the seeding process, our analytical study gives formulas on the new piece distribution time, average downloading time and minimum distribution time for heterogeneous P2P file distribution system with super-seeding. Robust evidence supporting the use (or not) of super-seeding is given based on our worldwide Internet experiments over wide distribution of 250 PlanetLab nodes. With a well-designed experimental scenario, we study the overall download time and upload cost of super seeding scheme under varying seed bandwidth and peer behavior. Results show that super-seeding can save an upload ratio of 20% and does help speeding up swarms in certain modes. Tentative conclusions about the effectiveness of super-seeding and its optimal working circumstances are given with inside mechanism analyzed and negative factor identified. Our work not only provides reference for the potential adoption of super-seeding in BitTorrent and other P2P applications, but also much insights for the tussle of enhancing of Quality of Experience (QoE) and saving cost for a large-scale BitTorrent-like P2P commercial

  5. Technosocial Predictive Analytics for Illicit Nuclear Trafficking

    SciTech Connect

    Sanfilippo, Antonio P.; Butner, R. Scott; Cowell, Andrew J.; Dalton, Angela C.; Haack, Jereme N.; Kreyling, Sean J.; Riensche, Roderick M.; White, Amanda M.; Whitney, Paul D.

    2011-03-29

    Illicit nuclear trafficking networks are a national security threat. These networks can directly lead to nuclear proliferation, as state or non-state actors attempt to identify and acquire nuclear weapons-related expertise, technologies, components, and materials. The ability to characterize and anticipate the key nodes, transit routes, and exchange mechanisms associated with these networks is essential to influence, disrupt, interdict or destroy the function of the networks and their processes. The complexities inherent to the characterization and anticipation of illicit nuclear trafficking networks requires that a variety of modeling and knowledge technologies be jointly harnessed to construct an effective analytical and decision making workflow in which specific case studies can be built in reasonable time and with realistic effort. In this paper, we explore a solution to this challenge that integrates evidentiary and dynamic modeling with knowledge management and analytical gaming, and demonstrate its application to a geopolitical region at risk.

  6. Morphological Processing as We Know It: An Analytical Review of Morphological Effects in Visual Word Identification

    PubMed Central

    Amenta, Simona; Crepaldi, Davide

    2012-01-01

    The last 40 years have witnessed a growing interest in the mechanisms underlying the visual identification of complex words. A large amount of experimental data has been amassed, but although a growing number of studies are proposing explicit theoretical models for their data, no comprehensive theory has gained substantial agreement among scholars in the field. We believe that this is due, at least in part, to the presence of several controversial pieces of evidence in the literature and, consequently, to the lack of a well-defined set of experimental facts that any theory should be able to explain. With this review, we aim to delineate the state of the art in the research on the visual identification of complex words. By reviewing major empirical evidences in a number of different paradigms such as lexical decision, word naming, and masked and unmasked priming, we were able to identify a series of effects that we judge as reliable or that were consistently replicated in different experiments, along with some more controversial data, which we have tried to resolve and explain. We concentrated on behavioral and electrophysiological studies on inflected, derived, and compound words, so as to span over all types of complex words. The outcome of this work is an analytical summary of well-established facts on the most relevant morphological issues, such as regularity, morpheme position coding, family size, semantic transparency, morpheme frequency, suffix allomorphy, and productivity, morphological entropy, and morpho-orthographic parsing. In discussing this set of benchmark effects, we have drawn some methodological considerations on why contrasting evidence might have emerged, and have tried to delineate a target list for the construction of a new all-inclusive model of the visual identification of morphologically complex words. PMID:22807919

  7. Biomorphic Networks for ATR and Higher-Level Processing.

    DTIC Science & Technology

    1998-01-10

    Publications during this period: 1. N.H. Farhat, "Biomorphic Dynamical Networks for Cognition and Control", Journal of Intelligent and Rototic Systems...34 Neurodynamic networks for recognition of radar targets", Ph.D. dissertation, University of Pennsyl- vania, 1992. 2. J. Wood, "Invariant pattern...167-177,1998. 167 © 1998 Kluwer Academic Publishers. Printed in the Netherlands. Biomorphic Dynamical Networks for Cognition and Control N. H

  8. Complex Network Structure Influences Processing in Long-Term and Short-Term Memory

    ERIC Educational Resources Information Center

    Vitevitch, Michael S.; Chan, Kit Ying; Roodenrys, Steven

    2012-01-01

    Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological…

  9. Real-time determination of critical quality attributes using near-infrared spectroscopy: a contribution for Process Analytical Technology (PAT).

    PubMed

    Rosas, Juan G; Blanco, Marcel; González, Josep M; Alcalà, Manel

    2012-08-15

    Process Analytical Technology (PAT) is playing a central role in current regulations on pharmaceutical production processes. Proper understanding of all operations and variables connecting the raw materials to end products is one of the keys to ensuring quality of the products and continuous improvement in their production. Near infrared spectroscopy (NIRS) has been successfully used to develop faster and non-invasive quantitative methods for real-time predicting critical quality attributes (CQA) of pharmaceutical granulates (API content, pH, moisture, flowability, angle of repose and particle size). NIR spectra have been acquired from the bin blender after granulation process in a non-classified area without the need of sample withdrawal. The methodology used for data acquisition, calibration modelling and method application in this context is relatively inexpensive and can be easily implemented by most pharmaceutical laboratories. For this purpose, Partial Least-Squares (PLS) algorithm was used to calculate multivariate calibration models, that provided acceptable Root Mean Square Error of Predictions (RMSEP) values (RMSEP(API)=1.0 mg/g; RMSEP(pH)=0.1; RMSEP(Moisture)=0.1%; RMSEP(Flowability)=0.6 g/s; RMSEP(Angle of repose)=1.7° and RMSEP(Particle size)=2.5%) that allowed the application for routine analyses of production batches. The proposed method affords quality assessment of end products and the determination of important parameters with a view to understanding production processes used by the pharmaceutical industry. As shown here, the NIRS technique is a highly suitable tool for Process Analytical Technologies.

  10. Applying decision-making tools to national e-waste recycling policy: an example of Analytic Hierarchy Process.

    PubMed

    Lin, Chun-Hsu; Wen, Lihchyi; Tsai, Yue-Mi

    2010-05-01

    As policy making is in essence a process of discussion, decision-making tools have in many cases been proposed to resolve the differences of opinion among the different parties. In our project that sought to promote a country's performance in recycling, we used the Analytic Hierarchy Process (AHP) to evaluate the possibilities and determine the priority of the addition of new mandatory recycled waste, also referred to as Due Recycled Wastes, from candidate waste appliances. The evaluation process started with the collection of data based on telephone interviews and field investigations to understand the behavior of consumers as well as their overall opinions regarding the disposal of certain waste appliances. With the data serving as background information, the research team then implemented the Analytic Hierarchy Process using the information that formed an incomplete hierarchy structure in order to determine the priority for recycling. Since the number of objects to be evaluated exceeded the number that the AHP researchers had suggested, we reclassified the objects into four groups and added one more level of pair-wise comparisons, which substantially reduced the inconsistency in the judgment of the AHP participants. The project was found to serve as a flexible and achievable application of AHP to the environmental policy-making process. In addition, based on the project's outcomes derived from the project as a whole, the research team drew conclusions regarding the government's need to take back 15 of the items evaluated, and suggested instruments that could be used or recycling regulations that could be changed in the future. Further analysis on the top three items recommended by the results of the evaluation for recycling, namely, Compact Disks, Cellular Phones and Computer Keyboards, was then conducted to clarify their concrete feasibility. After the trial period for recycling ordered by the Taiwan Environmental Protection Administration, only Computer

  11. Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks

    PubMed Central

    Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

    2014-01-01

    A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic–phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits. PMID:24723897

  12. Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks.

    PubMed

    Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

    2014-01-01

    A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits.

  13. Site selection of sanitary landfills on the small island of Mauritius using the analytical hierarchy process multi-criteria method.

    PubMed

    Ramjeawon, T; Beerachee, B

    2008-10-01

    This paper focuses on the application of a multi-criteria analysis methodology - the analytical hierarchy process - for the locating of a sanitary landfill on the small island of Mauritius. Four candidate sites were assessed using three main criteria (environmental, technical and socio-economic) and twenty-one sub-criteria. Scores were assigned to each criterion and sub-criterion by stakeholders in the solid waste sector, based on the impact assessment of each site so as to obtain their relative importance. The analytical hierarchy process was then applied, which involved the combination of the weights obtained at the different stages of pair-wise comparisons. The candidate sites were finally ranked to obtain the optimum site. Because of political factors, the second best ranked site was chosen by the authorities for the location of a new landfill on the island. This technique provides a realistic approach for use by small island developing states such as Mauritius for choosing and justifying to all stakeholders the best location for a sanitary landfill site or any other waste management site.

  14. MALDI based identification of soybean protein markers--possible analytical targets for allergen detection in processed foods.

    PubMed

    Cucu, Tatiana; De Meulenaer, Bruno; Devreese, Bart

    2012-02-01

    Soybean (Glycine max) is extensively used all over the world due to its nutritional qualities. However, soybean is included in the "big eight" list of food allergens. According to the EU directive 2007/68/EC, food products containing soybeans have to be labeled in order to protect the allergic consumers. Nevertheless, soybeans can still inadvertently be present in food products. The development of analytical methods for the detection of traces of allergens is important for the protection of allergic consumers. Mass spectrometry of marker proteolytical fragments of protein allergens is growingly recognized as a detection method in food control. However, quantification of soybean at the peptide level is hindered due to limited information regarding specific stable markers derived after proteolytic digestion. The aim of this study was to use MALDI-TOF/MS and MS/MS as a fast screening tool for the identification of stable soybean derived tryptic markers which were still identifiable even if the proteins were subjected to various changes at the molecular level through a number of reactions typically occurring during food processing (denaturation, the Maillard reaction and oxidation). The peptides (401)Val-Arg(410) from the G1 glycinin (Gly m 6) and the (518)Gln-Arg(528) from the α' chain of the β-conglycinin (Gly m 5) proved to be the most stable. These peptides hold potential to be used as targets for the development of new analytical methods for the detection of soybean protein traces in processed foods.

  15. Evaluation of the effect of a health education campaign of HIV by using an analytical hierarchy process method.

    PubMed

    Tan, Xiaodong; Lin, Jianyan; Wang, Fengjie; Luo, Hong; Luo, Lan; Wu, Lei

    2007-09-01

    This study was designed to understand the status of HIV/AIDS knowledge, attitude and practice (KAP) among different populations and to provide scientific evidences for further health education. Three rounds of questionnaires were administered among service industry workers who were selected through stratified cluster sampling. Study subjects included hotel attendants, employees of beauty parlors and service workers of transportation industry. Data were analyzed using the analytical hierarchy process. All demonstrated high KAP overall. Synthetic scoring indexes of the three surveys were above 75%. However, the correct response rate on questions whether mosquito bite can transmit HIV/AIDS and what is the relationship between STD with HIV was unsatisfactory (lower than expected); and their attitudes towards people living with HIV and AIDS need to be improved. Moreover, the effect of health education on these groups was unclear. In conclusion, analytical hierarchy process is a valid method in estimating overall effect of HIV/AIDS health education. Although the present status of HIV/AIDS KAP among the service industry workers was relatively good, greater efforts should be made to improve their HIV transmission knowledge, attitude and understanding of the relationship between STDs and HIV.

  16. On-board processing satellite network architecture and control study

    NASA Technical Reports Server (NTRS)

    Campanella, S. Joseph; Pontano, B.; Chalmers, H.

    1987-01-01

    For satellites to remain a vital part of future national and international communications, system concepts that use their inherent advantages to the fullest must be created. Network architectures that take maximum advantage of satellites equipped with onboard processing are explored. Satellite generations must accommodate various services for which satellites constitute the preferred vehicle of delivery. Such services tend to be those that are widely dispersed and present thin to medium loads to the system. Typical systems considered are thin and medium route telephony, maritime, land and aeronautical radio, VSAT data, low bit rate video teleconferencing, and high bit rate broadcast of high definition video. Delivery of services by TDMA and FDMA multiplexing techniques and combinations of the two for individual and mixed service types are studied. The possibilities offered by onboard circuit switched and packet switched architectures are examined and the results strongly support a preference for the latter. A detailed design architecture encompassing the onboard packet switch and its control, the related demand assigned TDMA burst structures, and destination packet protocols for routing traffic are presented. Fundamental onboard hardware requirements comprising speed, memory size, chip count, and power are estimated. The study concludes with identification of key enabling technologies and identifies a plan to develop a POC model.

  17. Landfill site selection using geographic information system and analytical hierarchy process: A case study Al-Hillah Qadhaa, Babylon, Iraq.

    PubMed

    Chabuk, Ali; Al-Ansari, Nadhir; Hussain, Hussain Musa; Knutsson, Sven; Pusch, Roland

    2016-05-01

    Al-Hillah Qadhaa is located in the central part of Iraq. It covers an area of 908 km(2) with a total population of 856,804 inhabitants. This Qadhaa is the capital of Babylon Governorate. Presently, no landfill site exists in that area based on scientific site selection criteria. For this reason, an attempt has been carried out to find the best locations for landfills. A total of 15 variables were considered in this process (groundwater depth, rivers, soil types, agricultural land use, land use, elevation, slope, gas pipelines, oil pipelines, power lines, roads, railways, urban centres, villages and archaeological sites) using a geographic information system. In addition, an analytical hierarchy process was used to identify the weight for each variable. Two suitable candidate landfill sites were determined that fulfil the requirements with an area of 9.153 km(2) and 8.204 km(2) These sites can accommodate solid waste till 2030.

  18. An Application of Fuzzy Analytic Hierarchy Process (FAHP) for Evaluating Students' Project

    ERIC Educational Resources Information Center

    Çebi, Ayça; Karal, Hasan

    2017-01-01

    In recent years, artificial intelligence applications for understanding the human thinking process and transferring it to virtual environments come into prominence. The fuzzy logic which paves the way for modeling human behaviors and expressing even vague concepts mathematically, and is also regarded as an artificial intelligence technique has…

  19. Analytical study of space processing of immiscible materials for superconductors and electrical contacts

    NASA Technical Reports Server (NTRS)

    Gelles, S. H.; Collings, E. W.; Abbott, W. H.; Maringer, R. E.

    1977-01-01

    The results of a study conducted to determine the role space processing or materials research in space plays in the superconductor and electrical contact industries are presented. Visits were made to manufacturers, users, and research organizations connected with these products to provide information about the potential benefits of the space environment and to exchange views on the utilization of space facilities for manufacture, process development, or research. In addition, space experiments were suggested which could result in improved terrestrial processes or products. Notable examples of these are, in the case of superconductors, the development of Nb-bronze alloys (Tsuei alloys) and, in the electrical contact field, the production of Ag-Ni or Ag-metal oxide alloys with controlled microstructure for research and development activities as well as for product development. A preliminary experimental effort to produce and evaluate rapidly cooled Pb-Zn and Cu-Nb-Sn alloys in order to understand the relationship between microstructure and superconducting properties and to simulate the fine structure potentially achievable by space processing was also described.

  20. Armstrong Laboratory (AL) Analytical Services Process Improvement Team (PIT) - Air Force Team Quality Award Application

    DTIC Science & Technology

    1994-01-01

    describe this process in detail 6. Identify key parameters for measuring customer satisfaction ; establish targets for improvement whenever possible...parameters for measuring customer satisfaction ; establish targets for improvement whenever possible. .Hints !Example wich parameers are most important POSSIBLE... measuring customer satisfaction : Dec 92 Need/Purpose: To find customer’s key desires on our services provided. How: Team discussed customer feedback and