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Sample records for analytic network process

  1. Evaluation of remedial countermeasures using the analytic network process.

    PubMed

    Promentilla, M A B; Furuichi, T; Ishii, K; Tanikawa, N

    2006-01-01

    The aim of this paper is to present an evaluation method to aid decision makers in the prioritization and selection of appropriate countermeasures at the planning stage of site remediation. We introduced a hierarchical network (hiernet) decision structure and applied the Analytic Network Process (ANP) supermatrix approach to measure the relative desirability of the remedial alternatives using the decision maker's value judgment as input. A simplified illustrative example is presented to elucidate the process, as it is being applied to evaluate the feasible remedial countermeasures of a contaminated site caused by uncontrolled landfill. Four decision models derived from the generalized hiernet were examined to describe the effect of hierarchic functional dependence, inner dependence and feedback cycle on the derivation of the priority weights. The ANP could provide a more flexible analytical framework to break down one's judgment through a more elaborate structure in a systematic way to understand the complexity of the decision problem. The proposed method therefore may not only aid in selecting the best alternative but also may help to facilitate communication to understand why an alternative is preferred over the other alternatives through the analysis of the derived weights and its underlying decision structure.

  2. 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.

  3. Measurement of company effectiveness using analytic network process method

    NASA Astrophysics Data System (ADS)

    Goran, Janjić; Zorana, Tanasić; Borut, Kosec

    2017-06-01

    The sustainable development of an organisation is monitored through the organisation's performance, which beforehand incorporates all stakeholders' requirements in its strategy. The strategic management concept enables organisations to monitor and evaluate their effectiveness along with efficiency by monitoring of the implementation of set strategic goals. In the process of monitoring and measuring effectiveness, an organisation can use multiple-criteria decision-making methods as help. This study uses the method of analytic network process (ANP) to define the weight factors of the mutual influences of all the important elements of an organisation's strategy. The calculation of an organisation's effectiveness is based on the weight factors and the degree of fulfilment of the goal values of the strategic map measures. New business conditions influence the changes in the importance of certain elements of an organisation's business in relation to competitive advantage on the market, and on the market, increasing emphasis is given to non-material resources in the process of selection of the organisation's most important measures.

  4. 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.

  5. 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...

  6. 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...

  7. Analytical results for stochastically growing networks: Connection to the zero-range process

    NASA Astrophysics Data System (ADS)

    Mohanty, P. K.; Jalan, Sarika

    2008-04-01

    We introduce a stochastic model of growing networks where both the number of new nodes which join the network and the number of connections vary stochastically. We provide an exact mapping between this model and the zero-range process, and calculate analytically the degree distribution for any given evolution rule. We argue that this mapping can be used to infer a possible evolution rule for any given network. This is being demonstrated for a protein-protein interaction network of Saccharomyces cerevisiae.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. 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.

  15. 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.

  16. 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…

  17. 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

  18. Visual analytics of brain networks.

    PubMed

    Li, Kaiming; Guo, Lei; Faraco, Carlos; Zhu, Dajiang; Chen, Hanbo; Yuan, Yixuan; Lv, Jinglei; Deng, Fan; Jiang, Xi; Zhang, Tuo; Hu, Xintao; Zhang, Degang; Miller, L Stephen; Liu, Tianming

    2012-05-15

    Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. Visual Analytics of Brain Networks

    PubMed Central

    Li, Kaiming; Guo, Lei; Faraco, Carlos; Zhu, Dajiang; Chen, Hanbo; Yuan, Yixuan; Lv, Jinglei; Deng, Fan; Jiang, Xi; Zhang, Tuo; Hu, Xintao; Zhang, Degang; Miller, L Stephen; Liu, Tianming

    2014-01-01

    Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. PMID:22414991

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

    NASA Astrophysics Data System (ADS)

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

    2017-08-01

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

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

    Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar

    2017-09-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

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

    PubMed Central

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

    2014-01-01

    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. PMID:24501275

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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…

  16. 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…

  17. The Analytic Hierarchy Process and Participatory Decisionmaking

    Treesearch

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

    1995-01-01

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

  18. Analytical calculation of fragmentation transitions in adaptive networks

    NASA Astrophysics Data System (ADS)

    Böhme, Gesa A.; Gross, Thilo

    2011-03-01

    In adaptive networks, fragmentation transitions have been observed in which the network breaks into disconnected components. We present an analytical approach for calculating the transition point in general adaptive network models. Using the example of an adaptive voter model, we demonstrate that the proposed approach yields good agreement with numerical results.

  19. 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.

  20. 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.

  1. 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.

  2. 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…

  3. Analytic information processing style in epilepsy patients.

    PubMed

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

    2017-08-01

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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Computational neural networks driving complex analytical problem solving.

    PubMed

    Hanrahan, Grady

    2010-06-01

    Neural network computing demonstrates advanced analytical problem solving abilities to meet the demands of modern chemical research. (To listen to a podcast about this article, please go to the Analytical Chemistry multimedia page at pubs.acs.org/page/ancham/audio/index.html .).

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Network analytical tool for monitoring global food safety highlights China.

    PubMed

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

    2009-08-18

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

  17. US EPA's National Dioxin Air Monitoring Network: Analytical ...

    EPA Pesticide Factsheets

    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 locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry, and animal feed crops are grown; (2) to provide measurements of atmospheric levels in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations and is achieving congener-specific detection lmits of 0.1 fg/m3 for 2,3,7,8-TCDD and 10 fg/m3 for OCDD. With respect to coplanar PCBs, the detection limits are generally higher due to the presence of background levels in the air during the preparation and processing of the samples. Achieving these extremely low levels of detection present a host of analytical issues. Among these issues are the methods used to establish ultra-trace detection limits, measures to ensure against and monitor for breakthrough of native analytes when sampling large volumes of air, and procedures for handling and e

  18. Applications of process analytical technology to crystallization processes.

    PubMed

    Yu, Lawrence X; Lionberger, Robert A; Raw, Andre S; D'Costa, Rosario; Wu, Huiquan; Hussain, Ajaz S

    2004-02-23

    Crystallizations of pharmaceutical active ingredients, particularly those that posses multiple polymorphic forms, are among the most critical and least understood pharmaceutical manufacturing processes. Many process and product failures can be traced to a poor understanding and control of crystallization processes. The Food and Drug Administration's process analytical technology (PAT) initiative is a collaborative effort with industry to introduce new and efficient manufacturing technologies into the pharmaceutical industry. PAT's are systems for design, analysis, and control of manufacturing processes. They aim to assure high quality through timely measurements of critical quality and performance attributes of raw materials, in-process materials, and final products. Implementation of PAT involves scientifically based process design and optimization, appropriate sensor technologies, statistical and information tools (chemometrics), and feedback process control strategies working together to produce quality products. This review introduces the concept of PAT and discusses its application to crystallization processes through review of several case studies. A variety of in situ analytical methods combined with chemometric tools for analysis of multivariate process information provide a basis for future improvements in modeling, simulation, and control of crystallization processes.

  19. 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.

  20. 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

  1. 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.

  2. Is Analytic Information Processing a Feature of Expertise in Medicine?

    ERIC Educational Resources Information Center

    McLaughlin, Kevin; Rikers, Remy M.; Schmidt, Henk G.

    2008-01-01

    Diagnosing begins by generating an initial diagnostic hypothesis by automatic information processing. Information processing may stop here if the hypothesis is accepted, or analytical processing may be used to refine the hypothesis. This description portrays analytic processing as an optional extra in information processing, leading us to…

  3. 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.

  4. 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.

  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. Copyright © 2016 Institute of Psychoanalysis.

  6. 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.

  7. Analytical framework for recurrence network analysis of time series

    NASA Astrophysics Data System (ADS)

    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.

  8. 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.

  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. Analytic standard errors for exploratory process factor analysis.

    PubMed

    Zhang, Guangjian; Browne, Michael W; Ong, Anthony D; Chow, Sy Miin

    2014-07-01

    Exploratory process factor analysis (EPFA) is a data-driven latent variable model for multivariate time series. This article presents analytic standard errors for EPFA. Unlike standard errors for exploratory factor analysis with independent data, the analytic standard errors for EPFA take into account the time dependency in time series data. In addition, factor rotation is treated as the imposition of equality constraints on model parameters. Properties of the analytic standard errors are demonstrated using empirical and simulated data.

  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. Fast analytical scatter estimation using graphics processing units.

    PubMed

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

    2015-01-01

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

  18. DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks.

    PubMed

    Pezzotti, Nicola; Hollt, Thomas; Gemert, Jan van; Lelieveldt, Boudewijn P F; Eisemann, Elmar; Vilanova, Anna

    2017-08-29

    Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The network architecture parameters such as the number of layers or the number of filters per layer and their interconnections are essential for good performance. Even though basic design guidelines exist, designing a neural network is an iterative trial-and-error process that takes days or even weeks to perform due to the large datasets used for training. In this paper, we present DeepEyes, a Progressive Visual Analytics system that supports the design of neural networks during training. We present novel visualizations, supporting the identification of layers that learned a stable set of patterns and, therefore, are of interest for a detailed analysis. The system facilitates the identification of problems, such as superfluous filters or layers, and information that is not being captured by the network. We demonstrate the effectiveness of our system through multiple use cases, showing how a trained network can be compressed, reshaped and adapted to different problems.

  19. 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

  20. 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*).

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Is a pre-analytical process for urinalysis required?

    PubMed

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

    2017-10-01

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

  6. Coupling entropy of co-processing model on social networks

    NASA Astrophysics Data System (ADS)

    Zhang, Zhanli

    2015-08-01

    Coupling entropy of co-processing model on social networks is investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. In order to understand the evolution of the co-processing and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the coupling entropy comprehending the structural characteristics and information propagation on social network. Based on the analysis of the co-processing model, we analyze the coupling impact of the structural factor and information propagating factor on the coupling entropy, where the analytical results fit well with the numerical ones on scale-free social networks.

  7. 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.

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

    PubMed Central

    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. PMID:25477812

  9. 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.

  10. Where the action is: the enacted dimension of analytic process.

    PubMed

    Katz, G A

    1998-01-01

    Enacted processes--variously addressed in the current literature by such terms as enactment, actualization, and interaction--represent the conceptual reuniting of Freud's concepts of transference and acting out. These various concepts include a recognition that transference may be represented not only on the verbally symbolized level but also on the enacted level, through psychic organizations and processes that use behavior, silence, and even speech as symbolic vehicles. Countertransference too finds representation within the enacted realm, in response to and in concert with the patient's enacted processes, though in more attenuated fashion. Enacted transference-countertransference processes are conceptualized as a continuously evolving second dimension of analytic treatment. This enacted dimension of analytic process exists alongside, and inextricably interwoven with, the treatment's verbal content, with characteristics unique to each analytic dyad. It occurs naturally and inevitably, without conscious awareness or intent, and is outside the domain of explicit technical interventions. The observable outcroppings or end points of processes within the enacted dimension are what are currently referred to as enactments. Attention to these unintended but meaningful and often elaborately developed characteristics of the treatment process furthers our understanding of the therapeutic action of psychoanalysis. The process of integrating the enacted with the verbal dimension of treatment enables the analysand to achieve higher levels of psychic organization.

  11. 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.

  12. 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.

  13. Interpersonal Processes in Psychoanalytic, Cognitive Analytical and Cognitive Behavioural Therapy.

    ERIC Educational Resources Information Center

    Habicht, Manuela H.

    The aim of the review was to compare interpersonal processes in psychoanalytic therapy, cognitive analytical therapy, and cognitive-behavioral therapy. Since the emphasis is on psychodynamic therapy, Freud's conceptualization of the phenomenon of transference is discussed. Countertransference as an unconscious and defensive reaction to the…

  14. 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…

  15. 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

  16. 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…

  17. 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…

  18. 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.…

  19. 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.

  20. Characterizing Teamwork in Cardiovascular Care Outcomes: A Network Analytics Approach.

    PubMed

    Carson, Matthew B; Scholtens, Denise M; Frailey, Conor N; Gravenor, Stephanie J; Powell, Emilie S; Wang, Amy Y; Kricke, Gayle Shier; Ahmad, Faraz S; Mutharasan, R Kannan; Soulakis, Nicholas D

    2016-11-01

    The nature of teamwork in healthcare is complex and interdisciplinary, and provider collaboration based on shared patient encounters is crucial to its success. Characterizing the intensity of working relationships with risk-adjusted patient outcomes supplies insight into provider interactions in a hospital environment. We extracted 4 years of patient, provider, and activity data for encounters in an inpatient cardiology unit from Northwestern Medicine's Enterprise Data Warehouse. We then created a provider-patient network to identify healthcare providers who jointly participated in patient encounters and calculated satisfaction rates for provider-provider pairs. We demonstrated the application of a novel parameter, the shared positive outcome ratio, a measure that assesses the strength of a patient-sharing relationship between 2 providers based on risk-adjusted encounter outcomes. We compared an observed collaboration network of 334 providers and 3453 relationships to 1000 networks with shared positive outcome ratio scores based on randomized outcomes and found 188 collaborative relationships between pairs of providers that showed significantly higher than expected patient satisfaction ratings. A group of 22 providers performed exceptionally in terms of patient satisfaction. Our results indicate high variability in collaboration scores across the network and highlight our ability to identify relationships with both higher and lower than expected scores across a set of shared patient encounters. Satisfaction rates seem to vary across different teams of providers. Team collaboration can be quantified using a composite measure of collaboration across provider pairs. Tracking provider pair outcomes over a sufficient set of shared encounters may inform quality improvement strategies such as optimizing team staffing, identifying characteristics and practices of high-performing teams, developing evidence-based team guidelines, and redesigning inpatient care processes.

  1. Wearable Networked Sensing for Human Mobility and Activity Analytics: A Systems Study

    PubMed Central

    Dong, Bo; Biswas, Subir

    2014-01-01

    This paper presents implementation details, system characterization, and the performance of a wearable sensor network that was designed for human activity analysis. Specific machine learning mechanisms are implemented for recognizing a target set of activities with both out-of-body and on-body processing arrangements. Impacts of energy consumption by the on-body sensors are analyzed in terms of activity detection accuracy for out-of-body processing. Impacts of limited processing abilities in the on-body scenario are also characterized in terms of detection accuracy, by varying the background processing load in the sensor units. Through a rigorous systems study, it is shown that an efficient human activity analytics system can be designed and operated even under energy and processing constraints of tiny on-body wearable sensors. PMID:25530911

  2. 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

  3. Rapid and continuous analyte processing in droplet microfluidic devices

    DOEpatents

    Strey, Helmut; Kimmerling, Robert; Bakowski, Tomasz

    2017-04-18

    The compositions and methods described herein are designed to introduce functionalized microparticles into droplets that can be manipulated in microfluidic devices by fields, including electric (dielectrophoretic) or magnetic fields, and extracted by splitting a droplet to separate the portion of the droplet that contains the majority of the microparticles from the part that is largely devoid of the microparticles. Within the device, channels are variously configured at Y- or T junctions that facilitate continuous, serial isolation and dilution of analytes in solution. The devices can be limited in the sense that they can be designed to output purified analytes that are then further analyzed in separate machines or they can include additional channels through which purified analytes can be further processed and analyzed.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Automated refinement and inference of analytical models for metabolic networks

    PubMed Central

    Schmidt, Michael D; Vallabhajosyula, Ravishankar R; Jenkins, Jerry W; Hood, Jonathan E; Soni, Abhishek S; Wikswo, John P; Lipson, Hod

    2013-01-01

    The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model – suggesting nonlinear terms and structural modifications – or even constructing a new model that agrees with the system’s time-series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real-time. PMID:21832805

  9. Automated refinement and inference of analytical models for metabolic networks

    NASA Astrophysics Data System (ADS)

    Schmidt, Michael D.; Vallabhajosyula, Ravishankar R.; Jenkins, Jerry W.; Hood, Jonathan E.; Soni, Abhishek S.; Wikswo, John P.; Lipson, Hod

    2011-10-01

    The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model--suggesting nonlinear terms and structural modifications--or even constructing a new model that agrees with the system's time series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real time.

  10. 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.

  11. Cooperative spreading processes in multiplex networks

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  12. Analytical Solution of Smoluchowski Equations in Aggregation–Fragmentation Processes

    NASA Astrophysics Data System (ADS)

    Sekiyama, Makoto; Ohtsuki, Toshiya; Yamamoto, Hiroshi

    2017-10-01

    The z-transform technique is used to analyze Smoluchowski equations of aggregation-fragmentation processes where the selection of aggregation clusters, a decomposed cluster and a generated cluster is entirely random and independent of cluster size. An analytic form of asymptotic behavior for a cluster size distribution function is derived on the basis of approximation where lower-order terms in the average cluster size are neglected. The obtained results agree well with numerical ones.

  13. 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/.

  14. Quantitative high throughput analytics to support polysaccharide production process development.

    PubMed

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

    2014-05-19

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

  15. "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.

  16. 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.

  17. An analytical description of transient thermal processes in harmonic crystals

    NASA Astrophysics Data System (ADS)

    Kuzkin, V. A.; Krivtsov, A. M.

    2017-05-01

    We consider two transient thermal processes in uniformly heated harmonic crystals: (i) equalibration of kinetic and potential energies and (ii) redistribution of the kinetic energy among the spatial directions. Equations describing these two processes in two-dimensional and three-dimensional crystals are derived. Analytical solutions of these equations for the square and triangular lattices are obtained. It is shown that the characteristic time of the transient processes is of the order of ten periods of atomic vibrations. The difference between the kinetic and potential energies oscillates in time. For the triangular lattice, amplitude of the oscillations decays inversely proportional to time, while for the square lattice it decays inversely proportional to the square root of time. In general, there is no equipartition of the kinetic energy among spatial directions, i.e. the kinetic temperature demonstrates tensor properties. In addition, the covariance of velocities of different particles is nonzero even at the steady state. The analytical results are supported by numerical simulations. It is also shown that the obtained solutions accurately describe the transient thermal processes in weakly nonlinear crystals at short times.

  18. 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

  19. 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.

  20. Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

    SciTech Connect

    Sahoo, Satiprasad; Dhar, Anirban; Kar, Amlanjyoti

    2016-01-15

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

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. The implementation of a system for managing analytical quality in networked laboratories.

    PubMed

    Jassam, Nuthar; Lindsay, Chris; Harrison, Kevin; Thompson, Douglas; Bosomworth, Mike P; Barth, Julian H

    2011-03-01

    In a network of laboratories analytical variability between instruments, even of the same type, may exist for reasons beyond the control of laboratory staff. Controlling variability is a prerequisite for the application of shared reference ranges and for ensuring the transferability of patient test results. Controlling variability requires a robust, non-conventional quality system to detect poor performance of analysers that are geographically distant. Essential to this quality system is a set of well-defined quality specifications. The approach used in our study started with (1) selection of a model for quality specifications based on biological variation; the 'three-level model' (TLM) was selected on the basis of its flexibility to accommodate various levels of analytical performance; (2) determination of the performance characteristics of the 71 analytes measured in core biochemistry in terms of imprecision and bias; (3) defining quality requirements in the form of imprecision, bias and total error for 71 analytes measured routinely in core biochemistry; and (4) developing software to assist a consistent wide application of the quality specifications and to monitor analytical indices to the common quality specifications. In this paper we describe how we have implemented this model across our network. Forty-six of the 71 analytes in our core laboratory repertoire were allocated to the TLM. We were able to demonstrate equivalence of results on all analysers, for 42 out of 46 analytes allocated to this model. We propose that other networked laboratories should investigate the suitability of this quality system for use in their network.

  7. 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.

  8. Social Network Supported Process Recommender System

    PubMed Central

    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. PMID:24672309

  9. 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.

  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. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed

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

    2008-08-12

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

  8. Autocatalytic genetic networks modeled by piecewise-deterministic Markov processes.

    PubMed

    Zeiser, Stefan; Franz, Uwe; Liebscher, Volkmar

    2010-02-01

    In the present work we propose an alternative approach to model autocatalytic networks, called piecewise-deterministic Markov processes. These were originally introduced by Davis in 1984. Such a model allows for random transitions between the active and inactive state of a gene, whereas subsequent transcription and translation processes are modeled in a deterministic manner. We consider three types of autoregulated networks, each based on a positive feedback loop. It is shown that if the densities of the stationary distributions exist, they are the solutions of a system of equations for a one-dimensional correlated random walk. These stationary distributions are determined analytically. Further, the distributions are analyzed for different simulation periods and different initial concentration values by numerical means. We show that, depending on the network structure, beside a binary response also a graded response is observable.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. Statistical signal processing in sensor networks

    NASA Astrophysics Data System (ADS)

    Guerriero, Marco

    In this dissertation we focus on decentralized signal processing in Sensor Networks (SN). Four topics are studied: (i) Direction of Arrival (DOA) estimation using a Wireless Sensor network (WSN), (ii) multiple target tracking in large SN, (iii) decentralized target detection in SN and (iv) decentralized sequential detection in SN with communication constraints. The first topic of this thesis addresses the problem of estimating the DOA of an acoustic wavefront using a a WSN made of isotropic (hence individually useless) sensors. The WSN was designed according to the SENMA (SEnsor Network with Mobile Agents) architecture with a mobile agent (MA) that successively queries the sensors lying inside its field of view. We propose both fast/simple and optimal DOA-estimation schemes, and an optimization of the MAs observation management is also carried out, with the surprising finding that the MA ought to orient itself at an oblique angle to the expected DOA, rather than directly toward it. We also consider the extension to multiple sources; intriguingly, per-source DOA accuracy is higher when there is more than one source. In all cases, performance is investigated by simulation and compared, when appropriate, with asymptotic bounds; these latter are usually met after a moderate number of MA dwells. In the second topic, we study the problem of tracking multiple targets in large SN. While these networks hold significant potential for surveillance, it is of interest to address fundamental limitations in large-scale implementations. We first introduce a simple analytical tracker performance model. Analysis of this model suggests that scan-based tracking performance improves with increasing numbers of sensors, but only to a certain point beyond which degradation is observed. Correspondingly, we address model-based optimization of the local sensor detection threshold and the number of sensors. Next, we propose a two-stage tracking approach (fuse-before-track) as a possible

  14. Real-Time Process Analytics in Emergency Healthcare.

    PubMed

    Koufi, Vassiliki; Malamateniou, Flora; Prentza, Adrianna; Vassilacopoulos, George

    2017-01-01

    Emergency medical systems (EMS) are considered to be amongst the most crucial systems as they involve a variety of activities which are performed from the time of a call to an ambulance service till the time of patient's discharge from the emergency department of a hospital. These activities are closely interrelated so that collaboration and coordination becomes a vital issue for patients and for emergency healthcare service performance. The utilization of standard workflow technology in the context of Service Oriented Architecture can provide an appropriate technological infrastructure for defining and automating EMS processes that span organizational boundaries so that to create and empower collaboration and coordination among the participating organizations. In such systems, the utilization of leading-edge analytics tools can prove important as it can facilitate real-time extraction and visualization of useful insights from the mountains of generated data pertaining to emergency case management. This paper presents a framework which provides healthcare professionals with just-in-time insight within and across emergency healthcare processes by performing real-time analysis on process-related data in order to better support decision making and identify potential critical risks that may affect the provision of emergency care to patients.

  15. An analytical model for a class of processor-memory interconnection networks

    SciTech Connect

    Conterno, R.; Melen, R.

    1987-11-01

    The performance of a delta interconnection network for multiprocessors is evaluated in a circuit switching environment. An error is pointed out in previous literature and an exact analytical model is given for regeneration systems, where a connection request is considered lost if not immediately granted. An approximated numerical method is suggested for the correction of the analytical results, which gave outputs in very good agreement with the simulation of real systems where requests are maintained.

  16. 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.

  17. 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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. 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

  19. Networks for image acquisition, processing and display

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.

    1990-01-01

    The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

  20. Wavelet networks for face processing.

    PubMed

    Krüger, V; Sommer, G

    2002-06-01

    Wavelet networks (WNs) were introduced in 1992 as a combination of artificial neural radial basis function (RBF) networks and wavelet decomposition. Since then, however, WNs have received only a little attention. We believe that the potential of WNs has been generally underestimated. WNs have the advantage that the wavelet coefficients are directly related to the image data through the wavelet transform. In addition, the parameters of the wavelets in the WNs are subject to optimization, which results in a direct relation between the represented function and the optimized wavelets, leading to considerable data reduction (thus making subsequent algorithms much more efficient) as well as to wavelets that can be used as an optimized filter bank. In our study we analyze some WN properties and highlight their advantages for object representation purposes. We then present a series of results of experiments in which we used WNs for face tracking. We exploit the efficiency that is due to data reduction for face recognition and face-pose estimation by applying the optimized-filter-bank principle of the WNs.

  1. Wavelet networks for face processing

    NASA Astrophysics Data System (ADS)

    Krüger, V.; Sommer, G.

    2002-06-01

    Wavelet networks (WNs) were introduced in 1992 as a combination of artificial neural radial basis function (RBF) networks and wavelet decomposition. Since then, however, WNs have received only a little attention. We believe that the potential of WNs has been generally underestimated. WNs have the advantage that the wavelet coefficients are directly related to the image data through the wavelet transform. In addition, the parameters of the wavelets in the WNs are subject to optimization, which results in a direct relation between the represented function and the optimized wavelets, leading to considerable data reduction (thus making subsequent algorithms much more efficient) as well as to wavelets that can be used as an optimized filter bank. In our study we analyze some WN properties and highlight their advantages for object representation purposes. We then present a series of results of experiments in which we used WNs for face tracking. We exploit the efficiency that is due to data reduction for face recognition and face-pose estimation by applying the optimized-filter-bank principle of the WNs.

  2. DDN: a caBIG® analytical tool for differential network analysis.

    PubMed

    Zhang, Bai; Tian, Ye; Jin, Lu; Li, Huai; Shih, Ie-Ming; Madhavan, Subha; Clarke, Robert; Hoffman, Eric P; Xuan, Jianhua; Hilakivi-Clarke, Leena; Wang, Yue

    2011-04-01

    Differential dependency network (DDN) is a caBIG® (cancer Biomedical Informatics Grid) analytical tool for detecting and visualizing statistically significant topological changes in transcriptional networks representing two biological conditions. Developed under caBIG®'s In Silico Research Centers of Excellence (ISRCE) Program, DDN enables differential network analysis and provides an alternative way for defining network biomarkers predictive of phenotypes. DDN also serves as a useful systems biology tool for users across biomedical research communities to infer how genetic, epigenetic or environment variables may affect biological networks and clinical phenotypes. Besides the standalone Java application, we have also developed a Cytoscape plug-in, CytoDDN, to integrate network analysis and visualization seamlessly. The Java and MATLAB source code can be downloaded at the authors' web site http://www.cbil.ece.vt.edu/software.htm.

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

    PubMed Central

    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. PMID:24558409

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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…

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

    PubMed

    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.

  11. 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.

  12. 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.

  13. Online Continuous Trace Process Analytics Using Multiplexing Gas Chromatography.

    PubMed

    Wunsch, Marco R; Lehnig, Rudolf; Trapp, Oliver

    2017-04-04

    The analysis of impurities at a trace level in chemical products, nutrition additives, and drugs is highly important to guarantee safe products suitable for consumption. However, trace analysis in the presence of a dominating component can be a challenging task because of noncompatible linear detection ranges or strong signal overlap that suppresses the signal of interest. Here, we developed a technique for quantitative analysis using multiplexing gas chromatography (mpGC) for continuous and completely automated process trace analytics exemplified for the analysis of a CO2 stream in a production plant for detection of benzene, toluene, ethylbenzene, and the three structural isomers of xylene (BTEX) in the concentration range of 0-10 ppb. Additional minor components are methane and methanol with concentrations up to 100 ppm. The sample is injected up to 512 times according to a pseudorandom binary sequence (PRBS) with a mean frequency of 0.1 Hz into a gas chromatograph equipped with a flame ionization detector (FID). A superimposed chromatogram is recorded which is deconvoluted into an averaged chromatogram with Hadamard transformation. Novel algorithms to maintain the data acquisition rate of the detector by application of Hadamard transformation and to suppress correlation noise induced by components with much higher concentrations than the target substances are shown. Compared to conventional GC-FID, the signal-to-noise ratio has been increased by a factor of 10 with mpGC-FID. Correspondingly, the detection limits for BTEX in CO2 have been lowered from 10 to 1 ppb each. This has been achieved despite the presence of detectable components (methane and methanol) with a concentration about 1000 times higher than the target substances. The robustness and reliability of mpGC has been proven in a two-month field test in a chemical production plant.

  14. 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.

  15. 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.

  16. Coevolution of functional flow processing networks

    NASA Astrophysics Data System (ADS)

    Kaluza, Pablo

    2017-04-01

    We present a study about the construction of functional flow processing networks that produce prescribed output patterns (target functions). The constructions are performed with a process of mutations and selections by an annealing-like algorithm. We consider the coevolution of the prescribed target functions during the optimization processes. We propose three different paths for these coevolutions in order to evolve from a simple initial function to a more complex final one. We compute several network properties during the optimizations by using the different path-coevolutions as mean values over network ensembles. As a function of the number of iterations of the optimization we find a similar behavior like a phase transition in the network structures. This result can be seen clearly in the mean motif distributions of the constructed networks. Coevolution allows to identify that feed-forward loops are responsible for the development of the temporal response of these systems. Finally, we observe that with a large number of iterations the optimized networks present similar properties despite the path-coevolution we employed.

  17. Testing the accuracy of analytical estimates of spare capacity in protected-mesh networks

    NASA Astrophysics Data System (ADS)

    Forst, Brian; Grover, Wayne D.

    2006-10-01

    Recently, two different investigators published analytical models to predict the spare capacity requirements of shared-mesh survivable networks. If accurate, such estimators could be used in network planning and technology-selection applications in network-operating companies, displacing or reducing the need for detailed design studies. However, relatively few test-case results involving irregular topology and demands were provided, and some possibly significant idealizations were involved. We have therefore conducted a further series of tests of the equations to more widely assess the general accuracy of the results and to be aware of the possible limitations to their use. We review and implement the equations in question and compare their predictions, along with two well-known simple estimators, to the properties of integer linear programming (ILP)-based network design solutions for three families of protected-mesh networks. In all, 1464 detailed network designs are used as 'truth' tests for the equations over a systematically varying range of network topologies and demand patterns. On this set of trials the new mathematical models were rarely within 10% accuracy and typically had up to 30% error. By dissecting some specific cases we gain insights as to why average-case mathematical models of such a network-dependent phenomenon are unlikely to be reliable. Insights into the effects of network nodal degree, demand variance, hop and distance topologies, and topology dependence are also given.

  18. In-Network Processing of Joins in Wireless Sensor Networks

    PubMed Central

    Kang, Hyunchul

    2013-01-01

    The join or correlated filtering of sensor readings is one of the fundamental query operations in wireless sensor networks (WSNs). Although the join in centralized or distributed databases is a well-researched problem, join processing in WSNs has quite different characteristics and is much more difficult to perform due to the lack of statistics on sensor readings and the resource constraints of sensor nodes. Since data transmission is orders of magnitude more costly than processing at a sensor node, in-network processing of joins is essential. In this paper, the state-of-the-art techniques for join implementation in WSNs are surveyed. The requirements and challenges, join types, and components of join implementation are described. The open issues for further research are identified. PMID:23478603

  19. 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.”

  20. 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.

  1. 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.

  2. 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.

  3. Strategic Assay Selection for analytics in high-throughput process development: case studies for downstream processing of monoclonal antibodies.

    PubMed

    Konstantinidis, Spyridon; Kong, Simyee; Chhatre, Sunil; Velayudhan, Ajoy; Heldin, Eva; Titchener-Hooker, Nigel

    2012-10-01

    During bioprocess development a potentially large number of analytes require measurement. Selection of the best set of analytical methods to deploy can reduce the analytical requirements for process investigation but currently relies on application of heuristics. This paper introduces a generic methodology, Strategic Assay Selection, for screening a large number of analytical methods to produce a subset of analytics that best suit high-throughput studies. The methodology uses a stochastic ranking approach where analytics are ranked based on their holistic performance in a set of criteria. Strategic Assay Selection can be used to help minimizing the impact of analytics in the generation of bottlenecks often encountered during high-throughput process development studies. This is illustrated by using a typical downstream purification process for a monoclonal antibody product. A list of assays is populated for routinely measured analytes across the different units of operation followed by the calculation of their performances in four criteria. The methodology is then applied to select analytics testing for three analytes and the results are analyzed to demonstrate how it can lead to the selection of analytical methods with the most favorable features. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. VELA Network Evaluation and Automatic Processing Research

    DTIC Science & Technology

    1974-12-31

    VELA NETWORK EVALUATION AND AUTOMATIC PROCESSING RESEARCH William H. Swindell Texas Instruments, Incorporated Prepared for: Air Force Technical...Incorporated Equipment Group Dallas, Texas 75222 CONTROLLING OFFICE NAME AND ADDRESS Advanced Research Projects Agency Nuclear Monitor mg... RESEARCH 1. D D TEXAS INSTRUMENTS INCORPORATED Equipment Group Post Office Box 6015 Dallas, Texas 75222 Prepared for AIR FORCE TECHNICAL

  5. 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.

  6. 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.

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

    ERIC Educational Resources Information Center

    Yin, Qingli

    2013-01-01

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

  8. Processing of calamine with modern analytical techniques: Processed with Huanglian Decoction () and Sanhuang Decoction ().

    PubMed

    Meng, Xiang-Long; Ma, Jun-Nan; Guo, Xiao-Hui; Liu, Bing-Chen; Cui, Nan-Nan; Li, Kun; Zhang, Shuo-Sheng

    2017-07-28

    To determine the pyrolysis characteristics of calcined and processed calamine, qualitatively and quantitatively compare the contents of related elements, morphology and functional groups of the pyrolysis products dried at different heating temperatures and explore the critical temperature and the optimal drying temperature for the process of calamine with Huanglian Decoction (HLD, ) and San Huang Decoction (SHD, ). Pyrolysis products were prepared by programmable and constantly heating the calcined and processed calamine to or at different heating temperatures. Thermogravimetry (TG) was used to test their pyrolysis characteristics. Fourier transform infrared spectroscopy and scanning electron microscopeenergy dispersive spectrometer were used to determine their morphology, functional groups and element contents. Page model was used to investigate the constant drying kinetics of processed calamine. The adding of HLD or SHD to calcined calamine (CC) can slow its weight loss in drying pyrolysis process. The temperature ranges where HLD and SHD can affect its weight loss were 65-150 °C and 74-180 °C, respectively. The drying temperature was optimized as 90 °C. The drying kinetic for the processed calamine fits Page model shows good linearity. The critical temperature and the optimal drying temperature where HLD and SHD can affect the weight loss rate in the process of calamine were explored using the theories and methods of both biophysical chemistry and processing of Chinese materia medica. This work provides a good example for the study of the process of other Chinese medicines using modern analytical techniques.

  9. 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.

  10. 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.

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

    PubMed

    Mudumbai, Seshadri; Ayer, Ferenc; Stefanko, Jerry

    2017-08-01

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

  12. 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.

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

    PubMed

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

    2016-08-01

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

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Packet switched networks with photonic code processing

    NASA Astrophysics Data System (ADS)

    Rosas-Fernandez, J. B.; Chen, L. R.; LaRochelle, S.; Leon-Garcia, A.; Plant, D.; Rusch, L. A.

    2006-09-01

    In this paper we present our study of all optical label encoding and ultrafast processing to route packets through optical networks. Our investigations include new network topologies, novel photonic components and performance analysis. We propose a label stacked packet switching system using spectral amplitude codes (SAC) as labels. We have developed enabling technologies to realize key photonic components for generation, correlation (identification) and conversion (swapping) of SAC-labels. We generate and identify the labels with fibre Bragg gratings (FBGs) encoders used in transmission. Furthermore, we demonstrate a static, all-photonic code-label converter based on a semiconductor fiber ring laser that can be used for label swapping of SAC-labels. We also address the design of dedicated receivers for optical burst detection. For this, we propose a novel architecture for a burst mode receiver module. In the system studies, we have shown by simulations that the throughput of standard Ethernet passive optical networks (E-PONs) can be substantially increased by the use of data encoded with SACs to achieve optical code division multiple access over passive optical networks (OCDMA-PONs). In the paper, we present recent results for all of these photonic technologies and we discuss how they can enable flexible packet switched networks.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Chiadamrong, N.; Piyathanavong, V.

    2017-04-01

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

  1. 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)

  2. 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.

  3. Generalized k-core pruning process on directed networks

    NASA Astrophysics Data System (ADS)

    Zhao, Jin-Hua

    2017-06-01

    The resilience of a complex interconnected system concerns the size of the macroscopic functioning node clusters after external perturbations based on a random or designed scheme. For a representation of interconnected systems with directional or asymmetrical interactions among constituents, the directed network is a convenient choice. Yet, how the interaction directions affect the network resilience still lacks a thorough exploration. Here, we study the resilience of directed networks with a generalized k-core pruning process as a simple failure procedure based on both the in- and out-degrees of nodes, in which any node with an in-degree  < k_in or an out-degree  < k_ou is removed iteratively. With an explicitly analytical framework, we can predict the relative sizes of residual node clusters on uncorrelated directed random graphs. We show that the discontinuous transitions rise for cases with k_in ≥slant 2 or k_ou ≥slant 2 , and the unidirectional interactions among nodes drive the networks more vulnerable against perturbations based on in- and out-degrees separately.

  4. 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.

  5. 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. Published by Elsevier B.V.

  6. 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.

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    Blakeslee, R. J.; Bailey, J. C.; Pinto, O.; Athayde, A.; Renno, N.; Weidman, C. D.

    2003-01-01

    A four station Advanced Lightning Direction Finder (ALDF) network was established in the state of Rondonia in western Brazil in 1999 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 in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the Internet. The network, which is still operational, was deployed to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite that was launched in November 1997. The measurements are also being used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-time series observations produced by this network will help establish a regional lightning climatological database, supplementing other databases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at the NASA/Marshall Space Flight Center have been applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The data will also be corrected for the network detection efficiency. The processing methodology and the results from the analysis of four years of network operations will be presented.

  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. Time-to-event analysis with artificial neural networks: an integrated analytical and rule-based study for breast cancer.

    PubMed

    Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Hane Aung, M S; Chabaud, Sylvie; Bachelot, Thomas; Perol, David; Gargi, Thérèse; Bourdès, Valérie; Bonnevay, Stéphane; Négrier, Sylvie

    2008-01-01

    This paper presents an analysis of censored survival data for breast cancer specific mortality and disease-free survival. There are three stages to the process, namely time-to-event modelling, risk stratification by predicted outcome and model interpretation using rule extraction. Model selection was carried out using the benchmark linear model, Cox regression but risk staging was derived with Cox regression and with Partial Logistic Regression Artificial Neural Networks regularised with Automatic Relevance Determination (PLANN-ARD). This analysis compares the two approaches showing the benefit of using the neural network framework especially for patients at high risk. The neural network model also has results in a smooth model of the hazard without the need for limiting assumptions of proportionality. The model predictions were verified using out-of-sample testing with the mortality model also compared with two other prognostic models called TNG and the NPI rule model. Further verification was carried out by comparing marginal estimates of the predicted and actual cumulative hazards. It was also observed that doctors seem to treat mortality and disease-free models as equivalent, so a further analysis was performed to observe if this was the case. The analysis was extended with automatic rule generation using Orthogonal Search Rule Extraction (OSRE). This methodology translates analytical risk scores into the language of the clinical domain, enabling direct validation of the operation of the Cox or neural network model. This paper extends the existing OSRE methodology to data sets that include continuous-valued variables.

  11. 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.

  12. 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.

  13. 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.

  14. 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…

  15. 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…

  16. 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.

  17. 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.

  18. 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

  19. Exact performance analytical model for spectrum allocation in flexible grid optical networks

    NASA Astrophysics Data System (ADS)

    Yu, Yiming; Zhang, Jie; Zhao, Yongli; Li, Hui; Ji, Yuefeng; Gu, Wanyi

    2014-03-01

    Dynamic flexible grid optical networks have gained much attention because of the advantages of high spectrum efficiency and flexibility, while the performance analysis will be more complex compared with fixed grid optical networks. An analytical Markov model is first presented in the paper, which can exactly describe the stochastic characteristics of the spectrum allocation in flexible grid optical networks considering both random-fit and first-fit resource assignment policies. We focus on the effect of spectrum contiguous constraint which has not been systematically studied in respect of mathematical modeling, and three major properties of the model are presented and analyzed. The model can expose key performance features and act as the foundation of modeling the Routing and Spectrum Assignment (RSA) problem with diverse topologies. Two heuristic algorithms are also proposed to make it more tractable. Finally, several key parameters, such as blocking probability, resource utilization rate and fragmentation rate are presented and computed, and the corresponding Monte Carlo simulation results match closely with analytical results, which prove the correctness of this mathematical model.

  20. 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…

  1. 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…

  2. 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…

  3. 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

  4. General analytical solutions for DC/AC circuit-network analysis

    NASA Astrophysics Data System (ADS)

    Rubido, Nicolás; Grebogi, Celso; Baptista, Murilo S.

    2017-06-01

    In this work, we present novel general analytical solutions for the currents that are developed in the edges of network-like circuits when some nodes of the network act as sources/sinks of DC or AC current. We assume that Ohm's law is valid at every edge and that charge at every node is conserved (with the exception of the source/sink nodes). The resistive, capacitive, and/or inductive properties of the lines in the circuit define a complex network structure with given impedances for each edge. Our solution for the currents at each edge is derived in terms of the eigenvalues and eigenvectors of the Laplacian matrix of the network defined from the impedances. This derivation also allows us to compute the equivalent impedance between any two nodes of the circuit and relate it to currents in a closed circuit which has a single voltage generator instead of many input/output source/sink nodes. This simplifies the treatment that could be done via Thévenin's theorem. Contrary to solving Kirchhoff's equations, our derivation allows to easily calculate the redistribution of currents that occurs when the location of sources and sinks changes within the network. Finally, we show that our solutions are identical to the ones found from Circuit Theory nodal analysis.

  5. 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.

  6. Students' science process skill and analytical thinking ability in chemistry learning

    NASA Astrophysics Data System (ADS)

    Irwanto, Rohaeti, Eli; Widjajanti, Endang; Suyanta

    2017-08-01

    Science process skill and analytical thinking ability are needed in chemistry learning in 21st century. Analytical thinking is related with science process skill which is used by students to solve complex and unstructured problems. Thus, this research aims to determine science process skill and analytical thinking ability of senior high school students in chemistry learning. The research was conducted in Tiga Maret Yogyakarta Senior High School, Indonesia, at the middle of the first semester of academic year 2015/2016 is using the survey method. The survey involved 21 grade XI students as participants. Students were given a set of test questions consists of 15 essay questions. The result indicated that the science process skill and analytical thinking ability were relatively low ie. 30.67%. Therefore, teachers need to improve the students' cognitive and psychomotor domains effectively in learning process.

  7. 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.

  8. 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.

  9. A guide for the application of analytics on healthcare processes: A dynamic view on patient pathways.

    PubMed

    Lismont, Jasmien; Janssens, Anne-Sophie; Odnoletkova, Irina; Vanden Broucke, Seppe; Caron, Filip; Vanthienen, Jan

    2016-10-01

    The aim of this study is to guide healthcare instances in applying process analytics on healthcare processes. Process analytics techniques can offer new insights in patient pathways, workflow processes, adherence to medical guidelines and compliance with clinical pathways, but also bring along specific challenges which will be examined and addressed in this paper. The following methodology is proposed: log preparation, log inspection, abstraction and selection, clustering, process mining, and validation. It was applied on a case study in the type 2 diabetes mellitus domain. Several data pre-processing steps are applied and clarify the usefulness of process analytics in a healthcare setting. Healthcare utilization, such as diabetes education, is analyzed and compared with diabetes guidelines. Furthermore, we take a look at the organizational perspective and the central role of the GP. This research addresses four challenges: healthcare processes are often patient and hospital specific which leads to unique traces and unstructured processes; data is not recorded in the right format, with the right level of abstraction and time granularity; an overflow of medical activities may cloud the analysis; and analysts need to deal with data not recorded for this purpose. These challenges complicate the application of process analytics. It is explained how our methodology takes them into account. Process analytics offers new insights into the medical services patients follow, how medical resources relate to each other and whether patients and healthcare processes comply with guidelines and regulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Adverse Event Assessment of Antimuscarinics for Treating Overactive Bladder: A Network Meta-Analytic Approach

    PubMed Central

    Kessler, Thomas M.; Bachmann, Lucas M.; Minder, Christoph; Löhrer, David; Umbehr, Martin; Schünemann, Holger J.; Kessels, Alfons G. H.

    2011-01-01

    Background Overactive bladder (OAB) affects the lives of millions of people worldwide and antimuscarinics are the pharmacological treatment of choice. Meta-analyses of all currently used antimuscarinics for treating OAB found similar efficacy, making the choice dependent on their adverse event profiles. However, conventional meta-analyses often fail to quantify and compare adverse events across different drugs, dosages, formulations, and routes of administration. In addition, the assessment of the broad variety of adverse events is dissatisfying. Our aim was to compare adverse events of antimuscarinics using a network meta-analytic approach that overcomes shortcomings of conventional analyses. Methods Cochrane Incontinence Group Specialized Trials Register, previous systematic reviews, conference abstracts, book chapters, and reference lists of relevant articles were searched. Eligible studies included randomized controlled trials comparing at least one antimuscarinic for treating OAB with placebo or with another antimuscarinic, and adverse events as outcome measures. Two authors independently extracted data. A network meta-analytic approach was applied allowing for joint assessment of all adverse events of all currently used antimuscarinics while fully maintaining randomization. Results 69 trials enrolling 26′229 patients were included. Similar overall adverse event profiles were found for darifenacin, fesoterodine, transdermal oxybutynin, propiverine, solifenacin, tolterodine, and trospium chloride but not for oxybutynin orally administered when currently used starting dosages were compared. Conclusions The proposed generally applicable transparent network meta-analytic approach summarizes adverse events in an easy to grasp way allowing straightforward benchmarking of antimuscarinics for treating OAB in clinical practice. Most currently used antimuscarinics seem to be equivalent first choice drugs to start the treatment of OAB except for oral oxybutynin dosages

  11. 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.

  12. 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. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Analytical theory of polymer-network-mediated interaction between colloidal particles

    PubMed Central

    Di Michele, Lorenzo; Zaccone, Alessio; Eiser, Erika

    2012-01-01

    Nanostructured materials based on colloidal particles embedded in a polymer network are used in a variety of applications ranging from nanocomposite rubbers to organic-inorganic hybrid solar cells. Further, polymer-network-mediated colloidal interactions are highly relevant to biological studies whereby polymer hydrogels are commonly employed to probe the mechanical response of living cells, which can determine their biological function in physiological environments. The performance of nanomaterials crucially relies upon the spatial organization of the colloidal particles within the polymer network that depends, in turn, on the effective interactions between the particles in the medium. Existing models based on nonlocal equilibrium thermodynamics fail to clarify the nature of these interactions, precluding the way toward the rational design of polymer-composite materials. In this article, we present a predictive analytical theory of these interactions based on a coarse-grained model for polymer networks. We apply the theory to the case of colloids partially embedded in cross-linked polymer substrates and clarify the origin of attractive interactions recently observed experimentally. Monte Carlo simulation results that quantitatively confirm the theoretical predictions are also presented. PMID:22679289

  18. Neural image processing by dendritic networks.

    PubMed

    Cuntz, Hermann; Haag, Jürgen; Borst, Alexander

    2003-09-16

    Convolution is one of the most common operations in image processing. Based on experimental findings on motion-sensitive visual interneurons of the fly, we show by realistic compartmental modeling that a dendritic network can implement this operation. In a first step, dendritic electrical coupling between two cells spatially blurs the original motion input. The blurred motion image is then passed onto a third cell via inhibitory dendritic synapses resulting in a sharpening of the signal. This enhancement of motion contrast may be the central element of figure-ground discrimination based on relative motion in the fly.

  19. 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.

  20. 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…

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. Analytical and numerical study of the pressure die casting processes

    NASA Astrophysics Data System (ADS)

    Lopez Rodriguez, Joaquin

    In pressure die casting, the most common defect in manufactured parts is porosity, one of the major causes of which is air entrapment in the molten metal during the injection process. Among other factors, the correct design of the gating and venting systems and an appropriate selection of the operating conditions during the injection phase can contribute to minimizing casting porosity. In the present work, a systematic study of the operating conditions and the characteristics of the injection and venting systems (plunger motion law, initial filling fraction, shot sleeve dimensions, dimension and location of the vents, atmospheric and vacuum venting conditions, etc.) that reduce air entrapment while keeping the injection filling time as low as possible is carried out. Limiting values of the initial filling fraction required for appropriate operating conditions are also determined for wide ranges of acceleration parameters and pouring hole locations. The flow of molten metal inside the injection chamber is analyzed using a two-dimensional finite-element model and a simpler model based on the shallow-water approximation. Two commonly used types of plunger movements are considered, for which results for wave profiles, the volume (area) of entrapped air in the injection chamber, and optimum values of the parameters characterizing the law of plunger motion are presented. A new law of plunger acceleration which would completely eliminate the air from the shot sleeve at the end of the slow phase of injection and minimizes the filling time is derived. The flow through venting systems is analyzed using an unsteady model for both atmospheric and vacuum venting conditions. The model is solved numerically using the method of characteristics. The numerical results of the model agree very well with the results of previous quasi-steady models for conditions for which unsteady effects are negligible, as could be expected. The results presented in this work show that, for broad

  8. 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.

  9. 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.

  10. 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

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

    PubMed

    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.

  12. 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.

  13. 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.

  14. 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).

  15. 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

  16. 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

  17. 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.

  18. ENTVis: A Visual Analytic Tool for Entropy-Based Network Traffic Anomaly Detection.

    PubMed

    Zhou, Fangfang; Huang, Wei; Zhao, Ying; Shi, Yang; Liang, Xing; Fan, Xiaoping

    2015-01-01

    Entropy-based traffic metrics have received substantial attention in network traffic anomaly detection because entropy can provide fine-grained metrics of traffic distribution characteristics. However, some practical issues--such as ambiguity, lack of detailed distribution information, and a large number of false positives--affect the application of entropy-based traffic anomaly detection. In this work, we introduce a visual analytic tool called ENTVis to help users understand entropy-based traffic metrics and achieve accurate traffic anomaly detection. ENTVis provides three coordinated views and rich interactions to support a coherent visual analysis on multiple perspectives: the timeline group view for perceiving situations and finding hints of anomalies, the Radviz view for clustering similar anomalies in a period, and the matrix view for understanding traffic distributions and diagnosing anomalies in detail. Several case studies have been performed to verify the usability and effectiveness of our method. A further evaluation was conducted via expert review.

  19. 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.

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

    PubMed

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

    2016-01-01

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

  1. 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).

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

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

    PubMed

    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.

  11. 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

  12. 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.

  13. 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.

  14. 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,…

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

    Treesearch

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

    1996-01-01

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

  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 Drug...

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

    Treesearch

    Daniel L. Schmoldt; David L. Peterson

    1997-01-01

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

  19. 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

  20. 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.

  1. Personality interacts with implicit affect to predict performance in analytic versus holistic processing.

    PubMed

    Kazén, Miguel; Kuhl, Julius; Quirin, Markus

    2015-06-01

    Both theoretical approaches and empirical evidence suggest that negative affect fosters analytic processing, whereas positive affect fosters holistic processing, but these effects are inconsistent. We aim to show that (a) differences in affect regulation abilities ("action orientation") and (b) implicit more so than self-reported affect assessment need to be considered to advance our understanding of these processes. Forty participants were asked to verify whether a word was correctly or incorrectly spelled to measure analytic processing, as well as to intuitively assess whether sets of three words were coherent (remote associates task) to measure holistic processing. As expected, implicit but not explicit negative affect interacted with low action orientation ("state orientation") to predict higher d' performance in word spelling, whereas implicit but not explicit positive affect interacted with high action orientation to predict higher d' performance in coherence judgments for word triads. Results are interpreted according to personality systems interaction theory. These findings suggest that affect and affect changes should be measured explicitly and implicitly to investigate affect-cognition interactions. Moreover, they suggest that good affect regulators benefit from positive affect for holistic processing, whereas bad affect regulators benefit from negative affect for analytical processing. © 2014 Wiley Periodicals, Inc.

  2. 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.

  3. 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

  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. Analogue implementation of analytic signal processing for pulse-echo systems

    NASA Technical Reports Server (NTRS)

    Gammell, P. M.

    1981-01-01

    An alternative to rectification is proposed for detection of an ultrasonic signal. This method is especially useful in medical and non-destructive evaluation (nde) applications. With this method, the magnitude of the complex analytic signal is used to define the envelope of the ultrasonic waveform. The square of this quantity has been shown elsewhere to be equal to the true rate-of-arrival of energy. An earlier study, using digital data processing, has already demonstrated the superior resolvability of closely spaced interfaces obtained with the analytic signal magnitude, as compared to conventional rectification. Here, an analogue implementation is presented which utilizes single-sideband techniques to obtain both quadrature components of the analytic signal and its magnitude. A conventional transducer, pulser, and receiver are used.

  6. Streamlining the analytical workflow for multiplex MS/MS allergen detection in processed foods.

    PubMed

    Pilolli, Rosa; De Angelis, Elisabetta; Monaci, Linda

    2017-04-15

    Allergenic ingredients in pre-packaged foods are regulated by EU legislation mandating their inclusion on labels. In order to protect allergic consumers, sensitive analytical methods are required for detect allergen traces in different food products. As a follow-up to our previous investigations, an optimized, sensitive, label-free LC-MS/MS method for multiplex detection of five allergenic ingredients in a processed food matrix is proposed. A cookie base was chosen as a complex food matrix and home-made cookies incurred with whole egg, skimmed milk, soy flour, ground hazelnut and ground peanut were prepared at laboratory scale. In order to improve the analytical workflow both protein extraction and purification protocols were optimized and finally a sensitive streamlined SRM based analytical method for allergens detection in incurred cookies was devised. The effect of baking on the detection of selected markers was also investigated. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Understanding variations in pediatric asthma care processes in the emergency department using visual analytics.

    PubMed

    Basole, Rahul C; Braunstein, Mark L; Kumar, Vikas; Park, Hyunwoo; Kahng, Minsuk; Chau, Duen Horng Polo; Tamersoy, Acar; Hirsh, Daniel A; Serban, Nicoleta; Bost, James; Lesnick, Burton; Schissel, Beth L; Thompson, Michael

    2015-03-01

    Health care delivery processes consist of complex activity sequences spanning organizational, spatial, and temporal boundaries. Care is human-directed so these processes can have wide variations in cost, quality, and outcome making systemic care process analysis, conformance testing, and improvement challenging. We designed and developed an interactive visual analytic process exploration and discovery tool and used it to explore clinical data from 5784 pediatric asthma emergency department patients. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. 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.

  9. 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.

  10. 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.

  11. Neural Networks Applied to Signal Processing

    DTIC Science & Technology

    1989-09-01

    identify by block number) FIELD GROUP SUB-GROUP Neural network, backpropagation, conjugato grad- ient method, Fibonacci line search, nonlinear signal...of the First Layer Gradients ............ 31 e. Calculation of the Input Layer Gradient-. ........... 33 i%" 5. Fibonacci Line Search Parameters...conjugate gradient optimization method is presented and then applied to the neu- ral network model. The Fibonacci line search method used in conjunction

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Coupling centrality and authority of co-processing model on complex networks

    NASA Astrophysics Data System (ADS)

    Zhang, Zhanli; Li, Huibin

    2016-04-01

    Coupling centrality and authority of co-processing model on complex networks are investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are obtained to disclose the formation. Considering the influence of a node to the global dynamical behavior, coupling centrality and authority are introduced for each node, which determine the relative importance and authority of nodes in the diffusion process. Furthermore, the experimental results on large-scale complex networks confirm our analytical prediction.

  17. Expediting the formulation development process with the aid of automated dissolution in analytical research and development.

    PubMed

    Sadowitz, J P

    2001-01-01

    The development of drugs in the generic pharmaceutical industry is a highly competitive arena of companies vying for few drug products that are coming off patent. Companies that have been successful in this arena are those that have met or surpassed the critical timeline associated with trial formulation development, analytical method development, and submission batch manufacturing and testing. Barr Laboratories Inc., has been successful in the generic pharmaceutical industry for several reasons, one of which includes automation. The analytical research and development at Barr has employed the use of automated dissolution early in the lifecycle of a potential product. This approach has dramatically reduced the 'time to market' on average for a number of products. The key to this approach is the network infrastructure of the formulation and analytical research and development departments. At Barr, the cooperative ability to work and communicate together has driven the departments to streamline and matrix their work efforts and optimize resources and time. The discussion will reference how Barr has been successful with automation and gives a case study of products that have moved with rapid pace through the development cycle.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Secure complex event processing in a heterogeneous and dynamic network

    NASA Astrophysics Data System (ADS)

    Buddhika, Thilina; Ray, Indrakshi; Linderman, Mark; Jayasumana, Anura

    2014-06-01

    Battlefield monitoring involves collecting streaming data from different sources, transmitting the data over a heterogeneous network, and processing queries in real-time in order to respond to events in a timely manner. Nodes in these networks differ with respect to their trustworthiness, processing, storage, and communication capabilities. Links in the network differ with respect to their communication bandwidth. The topology of the network itself is subject to change, as the nodes and links may become unavailable. Continuous queries executed in such environments must also meet some quality of service (QoS) requirements, such as, response time and throughput. Data streams generated from the various nodes in the network belong to different security levels; consequently, these must be processed in a secure manner without causing unauthorized leakage or modification. Towards this end, we demonstrate how an existing complex event processing system can be extended to execute queries and events in a secure manner in such a dynamic and heterogeneous environment.

  6. 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.

  7. 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.

  8. Curvature-processing network in macaque visual cortex.

    PubMed

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

    2014-08-19

    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.

  9. 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

  10. 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.

  11. 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.

  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. Safety evaluation of Chinese nickel resources based on analytic hierarchy process and fuzzy comprehensive evaluation

    NASA Astrophysics Data System (ADS)

    Lin, Zhifeng

    2017-08-01

    China is now the world’s largest producer and consumer of nickel. As an important strategic metal, nickel is widely used in various industries of national economy. Whether the supply of nickel ore resources is sufficient or not directly restricts the development of downstream industries. It is becoming more and more important to evaluate the safety of nickel resources in our country, and to formulate the corresponding safety strategy. This paper uses fuzzy analytic hierarchy process to evaluate the safety of nickel resources in China, and overcomes the subjectivity and singleness of traditional evaluation methods. On the basis of the analytic hierarchy process to determine the weight, the fuzzy comprehensive evaluation is introduced. At present, the safety situation of nickel resources in our country is in a more dangerous level, and we need to take positive measures to improve it.

  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. 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.

  18. 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.

  19. 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.

  20. 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.

  1. An investigation into some problems in analytical processing of lunar orbiter photography

    NASA Technical Reports Server (NTRS)

    Ghosh, S. K.; Ekenobi, S.

    1972-01-01

    Problems in analytical processing of lunar orbiter photography are discussed. The effects of image motion and image motion compensation on the location of the principal point are analyzed. The effect of the focal plane shutter on the distortion and interior geometry is examined. Real data is used to confirm the workability of a mathematical model and the use of a computer to calibrate spaceborne photographic imagery.

  2. [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.

  3. 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…

  4. 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…

  5. 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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  8. 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.

  9. 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.

  10. A network perspective on the processes of empowered organizations.

    PubMed

    Neal, Zachary P

    2014-06-01

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

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

    PubMed

    Greco, Alberto; Moretti, Stefania

    2017-08-14

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

  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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Basic emotion processing and the adolescent brain: Task demands, analytic approaches, and trajectories of changes.

    PubMed

    Del Piero, Larissa B; Saxbe, Darby E; Margolin, Gayla

    2016-06-01

    Early neuroimaging studies suggested that adolescents show initial development in brain regions linked with emotional reactivity, but slower development in brain structures linked with emotion regulation. However, the increased sophistication of adolescent brain research has made this picture more complex. This review examines functional neuroimaging studies that test for differences in basic emotion processing (reactivity and regulation) between adolescents and either children or adults. We delineated different emotional processing demands across the experimental paradigms in the reviewed studies to synthesize the diverse results. The methods for assessing change (i.e., analytical approach) and cohort characteristics (e.g., age range) were also explored as potential factors influencing study results. Few unifying dimensions were found to successfully distill the results of the reviewed studies. However, this review highlights the potential impact of subtle methodological and analytic differences between studies, need for standardized and theory-driven experimental paradigms, and necessity of analytic approaches that are can adequately test the trajectories of developmental change that have recently been proposed. Recommendations for future research highlight connectivity analyses and non-linear developmental trajectories, which appear to be promising approaches for measuring change across adolescence. Recommendations are made for evaluating gender and biological markers of development beyond chronological age. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. 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.

  1. Basic emotion processing and the adolescent brain: Task demands, analytic approaches, and trajectories of changes

    PubMed Central

    Del Piero, Larissa B.; Saxbe, Darby E.; Margolin, Gayla

    2016-01-01

    Early neuroimaging studies suggested that adolescents show initial development in brain regions linked with emotional reactivity, but slower development in brain structures linked with emotion regulation. However, the increased sophistication of adolescent brain research has made this picture more complex. This review examines functional neuroimaging studies that test for differences in basic emotion processing (reactivity and regulation) between adolescents and either children or adults. We delineated different emotional processing demands across the experimental paradigms in the reviewed studies to synthesize the diverse results. The methods for assessing change (i.e., analytical approach) and cohort characteristics (e.g., age range) were also explored as potential factors influencing study results. Few unifying dimensions were found to successfully distill the results of the reviewed studies. However, this review highlights the potential impact of subtle methodological and analytic differences between studies, need for standardized and theory-driven experimental paradigms, and necessity of analytic approaches that are can adequately test the trajectories of developmental change that have recently been proposed. Recommendations for future research highlight connectivity analyses and nonlinear developmental trajectories, which appear to be promising approaches for measuring change across adolescence. Recommendations are made for evaluating gender and biological markers of development beyond chronological age. PMID:27038840

  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

    2017-07-01

    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. Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

    NASA Astrophysics Data System (ADS)

    Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

    2015-03-01

    Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Information processing by biochemical networks: a dynamic approach

    PubMed Central

    Bowsher, Clive G.

    2011-01-01

    Understanding how information is encoded and transferred by biochemical networks is of fundamental importance in cellular and systems biology. This requires analysis of the relationships between the stochastic trajectories of the constituent molecular (or submolecular) species that comprise the network. We describe how to identify conditional independences between the trajectories or time courses of groups of species. These are robust network properties that provide important insight into how information is processed. An entire network can then be decomposed exactly into modules on informational grounds. In the context of signalling networks with multiple inputs, the approach identifies the routes and species involved in sequential information processing between input and output modules. An algorithm is developed which allows automated identification of decompositions for large networks and visualization using a tree that encodes the conditional independences. Only stoichiometric information is used and neither simulations nor knowledge of rate parameters are required. A bespoke version of the algorithm for signalling networks identifies the routes of sequential encoding between inputs and outputs, visualized as paths in the tree. Application to the toll-like receptor signalling network reveals that inputs can be informative in ways unanticipated by steady-state analyses, that the information processing structure is not well described as a bow tie, and that encoding for the interferon response is unusually sparse compared with other outputs of this innate immune system. PMID:20685691

  9. 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.

  10. Large-Scale Neural Network for Sentence Processing

    ERIC Educational Resources Information Center

    Cooke, Ayanna; Grossman, Murray; DeVita, Christian; Gonzalez-Atavales, Julio; Moore, Peachie; Chen, Willis; Gee, James; Detre, John

    2006-01-01

    Our model of sentence comprehension includes at least grammatical processes important for structure-building, and executive resources such as working memory that support these grammatical processes. We hypothesized that a core network of brain regions supports grammatical processes, and that additional brain regions are activated depending on the…

  11. 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.

  12. 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.

  13. 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.

  14. Analytical process design for chemo-mechanical polishing of glass aspheres

    NASA Astrophysics Data System (ADS)

    Waechter, Daniel; Dambon, Olaf; Klocke, Fritz

    2011-09-01

    This work deals with the chemo-mechanical sub-aperture polishing of glass lenses using spiral tool path and pressure-inflated membrane tools. Current trends in manufacturing precision optics in Europe go to smaller lot sizes and an increasing ratio of custom specific lens design. This requires deterministic processes as well as methods for an analytical process set-up without empirical try-outs. Chemo-mechanical polishing is typically applied for pre-polishing step, which aims for smoothing the surface with moderate shape correction. But due to kinematic effects the spiral-polishing process often shows changes in the radius of curvature, which are right now corrected by empirical try-outs and iterative corrections. This paper suggests an analytical tool for the compensation of these effects and contributes doing so to an efficient pre-polishing of aspheres. A mathematical model calculates the local distribution of material removal. It is based on Preston's equation and takes into account the influence of the major input parameters, such as feed rate, spindle revolutions and spot size. The given results show a significant reduction in shape deviation applying this methods compared to a polishing process without any compensation.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. IJA: An Efficient Algorithm for Query Processing in Sensor Networks

    PubMed Central

    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. PMID:22319375

  3. 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.

  4. 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.

  5. Simulation of dynamic processes with adaptive neural networks.

    SciTech Connect

    Tzanos, C. P.

    1998-02-03

    Many industrial processes are highly non-linear and complex. Their simulation with first-principle or conventional input-output correlation models is not satisfactory, either because the process physics is not well understood, or it is so complex that direct simulation is either not adequately accurate, or it requires excessive computation time, especially for on-line applications. Artificial intelligence techniques (neural networks, expert systems, fuzzy logic) or their combination with simple process-physics models can be effectively used for the simulation of such processes. Feedforward (static) neural networks (FNNs) can be used effectively to model steady-state processes. They have also been used to model dynamic (time-varying) processes by adding to the network input layer input nodes that represent values of input variables at previous time steps. The number of previous time steps is problem dependent and, in general, can be determined after extensive testing. This work demonstrates that for dynamic processes that do not vary fast with respect to the retraining time of the neural network, an adaptive feedforward neural network can be an effective simulator that is free of the complexities introduced by the use of input values at previous time steps.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Comparison of potential method in analytic hierarchy process for multi-attribute of catering service companies

    NASA Astrophysics Data System (ADS)

    Mamat, Siti Salwana; Ahmad, Tahir; Awang, Siti Rahmah

    2017-08-01

    Analytic Hierarchy Process (AHP) is a method used in structuring, measuring and synthesizing criteria, in particular ranking of multiple criteria in decision making problems. On the other hand, Potential Method is a ranking procedure in which utilizes preference graph ς (V, A). Two nodes are adjacent if they are compared in a pairwise comparison whereby the assigned arc is oriented towards the more preferred node. In this paper Potential Method is used to solve problem on a catering service selection. The comparison of result by using Potential method is made with Extent Analysis. The Potential Method is found to produce the same rank as Extent Analysis in AHP.

  14. [Problems in organization of work at laboratories and metrological provision for an analytical process].

    PubMed

    Dolgikh, T I

    2009-08-01

    In the organization of a present-day laboratory, there are 8 fundamental elements that provide its activity and are integrated into the uniform system: safety; the correct organization of work; the range of studies; a current material-and-technical basis; the metrological provision of diagnostic and analytical processes; manpower; and adequate sanitary-and-hygienic and antiepidemic measures. The problems of the laboratory's activity are outlined in the light of implementation of Federal Law on the Uniformity of Measurements under No. 102 - dated June 26, 2008, and ways of their solution are proposed.

  15. 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

    To gain confidence in developing analytical models of the purging process for the cryogenic main propulsion systems of upper stage, two test series were conducted. Test article, a 3.35m long with the diameter of 20 cm incline line, was filled with liquid (LH2)or gaseous hydrogen (GH2) and then purged with gaseous helium (GHe). Total of 10 tests were conducted. Influences of GHe flow rates and initial temperatures were evaluated. Generalized Fluid System Simulation Program (GFSSP), an in-house general-purpose fluid system analyzer, was utilized to model and simulate selective tests.

  16. Optimal selection on water-supply pipe of building based on analytic hierarchy process

    NASA Astrophysics Data System (ADS)

    Wei, Tianyun; Chen, Guiqing

    2017-04-01

    The main problem of pipes used in water-supply system was analyzed, and the commonly used pipe and their main features were introduced in this paper. The principles that the selection on water-supply pipes should follow were pointed out. Analytic Hierarchy Process (AHP) using 9 scaling was applied to optimize water-supply pipes quantitatively. The optimal water-supply pipes were determined according to the sorting result of comprehensive evaluation index. It could provide the reference to select the reasonable water-supply pipes for the engineers.

  17. 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).

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Analytical and Experimental Investigation of Process Loads on Incremental Severe Plastic Deformation

    NASA Astrophysics Data System (ADS)

    Okan Görtan, Mehmet

    2017-05-01

    From the processing point of view, friction is a major problem in the severe plastic deformation (SPD) using equal channel angular pressing (ECAP) process. Incremental ECAP can be used in order to optimize frictional effects during SPD. A new incremental ECAP has been proposed recently. This new process called as equal channel angular swaging (ECAS) combines the conventional ECAP and the incremental bulk metal forming method rotary swaging. ECAS tool system consists of two dies with an angled channel that contains two shear zones. During ECAS process, two forming tool halves, which are concentrically arranged around the workpiece, perform high frequency radial movements with short strokes, while samples are pushed through these. The oscillation direction nearly coincides with the shearing direction in the workpiece. The most important advantages in comparison to conventional ECAP are a significant reduction in the forces in material feeding direction plus the potential to be extended to continuous processing. In the current study, the mechanics of the ECAS process is investigated using slip line field approach. An analytical model is developed to predict process loads. The proposed model is validated using experiments and FE simulations.

  9. Graph Processing for Spatial Network Queries

    DTIC Science & Technology

    2005-10-14

    entire process is performed in parallel on a Beowulf cluster which reduces the computation time substantially. Also discussed are two different methods of...PostGIS [5] extension. The cluster used in the experiments is a 72 node Beowulf cluster. It consists of 63 slave nodes which are 2.2Ghz Intel Pentium

  10. 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. © 2013 Published by Elsevier B.V.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Leveraging network analytics to infer patient syndrome and identify causal genes in rare disease cases.

    PubMed

    Krämer, Andreas; Shah, Sohela; Rebres, Robert Anthony; Tang, Susan; Richards, Daniel Rene

    2017-08-11

    Next-generation sequencing is widely used to identify disease-causing variants in patients with rare genetic disorders. Identifying those variants from whole-genome or exome data can be both scientifically challenging and time consuming. A significant amount of time is spent on variant annotation, and interpretation. Fully or partly automated solutions are therefore needed to streamline and scale this process. We describe Phenotype Driven Ranking (PDR), an algorithm integrated into Ingenuity Variant Analysis, that uses observed patient phenotypes to prioritize diseases and genes in order to expedite causal-variant discovery. Our method is based on a network of phenotype-disease-gene relationships derived from the QIAGEN Knowledge Base, which allows for efficient computational association of phenotypes to implicated diseases, and also enables scoring and ranking. We have demonstrated the utility and performance of PDR by applying it to a number of clinical rare-disease cases, where the true causal gene was known beforehand. It is also shown that PDR compares favorably to a representative alternative tool.

  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. 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

  18. 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

  19. 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.

  20. Flavor pleasantness processing in the ventral emotion network.

    PubMed

    Dalenberg, Jelle R; 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.

  1. 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.

  2. 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.

  3. Rare-region effects in the contact process on networks.

    PubMed

    Juhász, Róbert; Ódor, Géza; Castellano, Claudio; Muñoz, Miguel A

    2012-06-01

    Networks and dynamical processes occurring on them have become a paradigmatic representation of complex systems. Studying the role of quenched disorder, both intrinsic to nodes and topological, is a key challenge. With this in mind, here we analyze the contact process (i.e., the simplest model for propagation phenomena) with node-dependent infection rates (i.e., intrinsic quenched disorder) on complex networks. We find Griffiths phases and other rare-region effects, leading rather generically to anomalously slow (algebraic, logarithmic, etc.) relaxation, on Erdős-Rényi networks. We predict similar effects to exist for other topologies as long as a nonvanishing percolation threshold exists. More strikingly, we find that Griffiths phases can also emerge--even with constant epidemic rates--as a consequence of mere topological heterogeneity. In particular, we find Griffiths phases in finite-dimensional networks as, for instance, a family of generalized small-world networks. These results have a broad spectrum of implications for propagation phenomena and other dynamical processes on networks, and are relevant for the analysis of both models and empirical data.

  4. Node importance for dynamical process on networks: a multiscale characterization.

    PubMed

    Zhang, Jie; Xu, Xiao-Ke; Li, Ping; Zhang, Kai; Small, Michael

    2011-03-01

    Defining the importance of nodes in a complex network has been a fundamental problem in analyzing the structural organization of a network, as well as the dynamical processes on it. Traditionally, the measures of node importance usually depend either on the local neighborhood or global properties of a network. Many real-world networks, however, demonstrate finely detailed structure at various organization levels, such as hierarchy and modularity. In this paper, we propose a multiscale node-importance measure that can characterize the importance of the nodes at varying topological scale. This is achieved by introducing a kernel function whose bandwidth dictates the ranges of interaction, and meanwhile, by taking into account the interactions from all the paths a node is involved. We demonstrate that the scale here is closely related to the physical parameters of the dynamical processes on networks, and that our node-importance measure can characterize more precisely the node influence under different physical parameters of the dynamical process. We use epidemic spreading on networks as an example to show that our multiscale node-importance measure is more effective than other measures.

  5. Analytical and numerical simulations of uplift processes at the Tibet-Sichuan boundary

    NASA Astrophysics Data System (ADS)

    Peng, Diandian; Leng, Wei

    2017-06-01

    Previous studies have shown that the uplift of Tibetan plateau started in response to the collision of Indian plate and Eurasian plate. During this process, the crust of Tibetan plateau has been greatly thickened which leads to significant elevations. The elevation gradient is extremely large at the east boundary of Tibetan plateau where Longmenshan fault exists, dropping from 4500 to 500 m within a distance of 100 km, while it is more gentle at the south and north sides of Sichuan basin. Such a difference of elevation gradient has been explained with a crustal channel flow model. However, previous crustal flow models consider the thickness of the lower crust as a constant which is highly simplified. Therefore, it is essential to build a more realistic crustal flow model, in which the thickness of the lower crust is variable and dependent on the inflow velocity of crustal materials. Here we build up both analytical and numerical models to study the mechanism and process of the uplift of Tibetan plateau at the eastern boundary. The results of the analytical model show that if the thickness of the lower crust can vary during the uplift process, the lower crustal viscosity of the Sichuan basin needs to be 1022 Pas to fit the observed elevation gradient. Such a viscosity is one-order magnitude larger than the previous results. Numerical model results further show that the state of stresses at the plateau boundary changes during uplift processes. Such a stress state change may cause the formation of different fault types in the Longmenshan fault area during its uplift history.

  6. 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.

  7. Parallel plan execution with self-processing networks

    NASA Technical Reports Server (NTRS)

    D'Autrechy, 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.

  8. 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

  9. 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.

  10. 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. (c) 2016 APA, all rights reserved.

  11. Development of Process Analytical Technology (PAT) methods for controlled release pellet coating.

    PubMed

    Avalle, P; Pollitt, M J; Bradley, K; Cooper, B; Pearce, G; Djemai, A; Fitzpatrick, S

    2014-07-01

    This work focused on the control of the manufacturing process for a controlled release (CR) pellet product, within a Quality by Design (QbD) framework. The manufacturing process was Wurster coating: firstly layering active pharmaceutical ingredient (API) onto sugar pellet cores and secondly a controlled release (CR) coating. For each of these two steps, development of a Process Analytical Technology (PAT) method is discussed and also a novel application of automated microscopy as the reference method. Ultimately, PAT methods should link to product performance and the two key Critical Quality Attributes (CQAs) for this CR product are assay and release rate, linked to the API and CR coating steps respectively. In this work, the link between near infra-red (NIR) spectra and those attributes was explored by chemometrics over the course of the coating process in a pilot scale industrial environment. Correlations were built between the NIR spectra and coating weight (for API amount), CR coating thickness and dissolution performance. These correlations allow the coating process to be monitored at-line and so better control of the product performance in line with QbD requirements. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Uncovering the role of elementary processes in network evolution

    PubMed Central

    Ghoshal, Gourab; Chi, Liping; Barabási, Albert-László

    2013-01-01

    The growth and evolution of networks has elicited considerable interest from the scientific community and a number of mechanistic models have been proposed to explain their observed degree distributions. Various microscopic processes have been incorporated in these models, among them, node and edge addition, vertex fitness and the deletion of nodes and edges. The existing models, however, focus on specific combinations of these processes and parameterize them in a way that makes it difficult to elucidate the role of the individual elementary mechanisms. We therefore formulated and solved a model that incorporates the minimal processes governing network evolution. Some contribute to growth such as the formation of connections between existing pair of vertices, while others capture deletion; the removal of a node with its corresponding edges, or the removal of an edge between a pair of vertices. We distinguish between these elementary mechanisms, identifying their specific role on network evolution. PMID:24108146

  13. High-speed parallel-processing networks for advanced architectures

    SciTech Connect

    Morgan, D.R.

    1988-06-01

    This paper describes various parallel-processing architecture networks that are candidates for eventual airborne use. An attempt at projecting which type of network is suitable or optimum for specific metafunction or stand-alone applications is made. However, specific algorithms will need to be developed and bench marks executed before firm conclusions can be drawn. Also, a conceptual projection of how these processors can be built in small, flyable units through the use of wafer-scale integration is offered. The use of the PAVE PILLAR system architecture to provide system level support for these tightly coupled networks is described. The author concludes that: (1) extremely high processing speeds implemented in flyable hardware is possible through parallel-processing networks if development programs are pursued; (2) dramatic speed enhancements through parallel processing requires an excellent match between the algorithm and computer-network architecture; (3) matching several high speed parallel oriented algorithms across the aircraft system to a limited set of hardware modules may be the most cost-effective approach to achieving speed enhancements; and (4) software-development tools and improved operating systems will need to be developed to support efficient parallel-processor use.

  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. 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.

  16. Changes in the Sodium Content of Australian Processed Foods between 1980 and 2013 Using Analytical Data

    PubMed Central

    Zganiacz, Felicity; Wills, Ron B. H.; Mukhopadhyay, Soumi Paul; Arcot, Jayashree; Greenfield, Heather

    2017-01-01

    The objective of this study was to obtain analytical data on the sodium content of a range of processed foods and compare the levels obtained with their label claims and with published data of the same or equivalent processed foods in the 1980s and 1990s to investigate the extent of any change in sodium content in relation to reformulation targets. The sodium contents of 130 Australian processed foods were obtained by inductively coupled plasma optical emission spectrometry (ICP-OES) analysis and compared with previously published data. The sodium content between 1980 and 2013 across all products and by each product category were compared. There was a significant overall sodium reduction of 23%, 181 mg/100 g (p <0.001, 95% CI (Confidence Interval), 90 to 272 mg/100 g), in Australian processed foods since 1980, with a 12% (83 mg/100 g) reduction over the last 18 years. The sodium content of convenience foods (p < 0.001, 95% CI, 94 to 291 mg/100 g) and snack foods (p = 0.017, 95% CI, 44 to 398 mg/100 g) had declined significantly since 1980. Meanwhile, the sodium contents of processed meats (p = 0.655, 95% CI, −121 to 190) and bread and other bakery products (p = 0.115, 95% CI, −22 to 192) had decreased, though not significantly. Conversely, the sodium content of cheese (p = 0.781, 95% CI, −484 to 369 mg/100 g) had increased but also not significantly. Of the 130 products analysed, 62% met Australian reformulation targets. Sodium contents of the processed foods and the overall changes in comparison with previous data indicate a decrease over the 33 years period and suggest that the Australian recommended reformulation targets have been effective. Further sodium reduction of processed foods is still required and continuous monitoring of the reduction of sodium levels in processed foods is needed. PMID:28505147

  17. 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

  18. Numerical and analytical investigation of the chimera state excitation conditions in the Kuramoto-Sakaguchi oscillator network

    NASA Astrophysics Data System (ADS)

    Frolov, Nikita S.; Goremyko, Mikhail V.; Makarov, Vladimir V.; Maksimenko, Vladimir A.; Hramov, Alexander E.

    2017-03-01

    In this paper we study the conditions of chimera states excitation in ensemble of non-locally coupled Kuramoto-Sakaguchi (KS) oscillators. In the framework of current research we analyze the dynamics of the homogeneous network containing identical oscillators. We show the chimera state formation process is sensitive to the parameters of coupling kernel and to the KS network initial state. To perform the analysis we have used the Ott-Antonsen (OA) ansatz to consider the behavior of infinitely large KS network.

  19. 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

  20. 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.

  1. Evaluating Functional Autocorrelation within Spatially Distributed Neural Processing Networks*

    PubMed Central

    Derado, Gordana; Bowman, F. Dubois; Ely, Timothy D.; Kilts, Clinton D.

    2010-01-01

    Data-driven statistical approaches, such as cluster analysis or independent component analysis, applied to in vivo functional neuroimaging data help to identify neural processing networks that exhibit similar task-related or restingstate patterns of activity. Ideally, the measured brain activity for voxels within such networks should exhibit high autocorrelation. An important limitation is that the algorithms do not typically quantify or statistically test the strength or nature of the within-network relatedness between voxels. To extend the results given by such data-driven analyses, we propose the use of Moran’s I statistic to measure the degree of functional autocorrelation within identified neural processing networks and to evaluate the statistical significance of the observed associations. We adapt the conventional definition of Moran’s I, for applicability to neuroimaging analyses, by defining the global autocorrelation index using network-based neighborhoods. Also, we compute network-specific contributions to the overall autocorrelation. We present results from a bootstrap analysis that provide empirical support for the use of our hypothesis testing framework. We illustrate our methodology using positron emission tomography (PET) data from a study that examines the neural representation of working memory among individuals with schizophrenia and functional magnetic resonance imaging (fMRI) data from a study of depression. PMID:21643436

  2. Evaluating Functional Autocorrelation within Spatially Distributed Neural Processing Networks.

    PubMed

    Derado, Gordana; Bowman, F Dubois; Ely, Timothy D; Kilts, Clinton D

    2010-01-01

    Data-driven statistical approaches, such as cluster analysis or independent component analysis, applied to in vivo functional neuroimaging data help to identify neural processing networks that exhibit similar task-related or restingstate patterns of activity. Ideally, the measured brain activity for voxels within such networks should exhibit high autocorrelation. An important limitation is that the algorithms do not typically quantify or statistically test the strength or nature of the within-network relatedness between voxels. To extend the results given by such data-driven analyses, we propose the use of Moran's I statistic to measure the degree of functional autocorrelation within identified neural processing networks and to evaluate the statistical significance of the observed associations. We adapt the conventional definition of Moran's I, for applicability to neuroimaging analyses, by defining the global autocorrelation index using network-based neighborhoods. Also, we compute network-specific contributions to the overall autocorrelation. We present results from a bootstrap analysis that provide empirical support for the use of our hypothesis testing framework. We illustrate our methodology using positron emission tomography (PET) data from a study that examines the neural representation of working memory among individuals with schizophrenia and functional magnetic resonance imaging (fMRI) data from a study of depression.

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

    PubMed

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

    2014-12-01

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

  4. 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.

  5. Introduction to spiking neural networks: Information processing, learning and applications.

    PubMed

    Ponulak, Filip; Kasinski, Andrzej

    2011-01-01

    The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

  6. 77 FR 7214 - Notice of Availability: Programmatic Environmental Assessment for Mail Processing Network...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-10

    ... Availability: Programmatic Environmental Assessment for Mail Processing Network Rationalization Initiative (Formerly Known as the ``Network Optimization'' Initiative), Nationwide AGENCY: Postal Service. ACTION... available a Programmatic Environmental Assessment (PEA) for the Mail Processing Network Rationalization...

  7. 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.

  8. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis.

    PubMed

    Turkay, Cagatay; Kaya, Erdem; Balcisoy, Selim; Hauser, Helwig

    2017-01-01

    In interactive data analysis processes, the dialogue between the human and the computer is the enabling mechanism that can lead to actionable observations about the phenomena being investigated. It is of paramount importance that this dialogue is not interrupted by slow computational mechanisms that do not consider any known temporal human-computer interaction characteristics that prioritize the perceptual and cognitive capabilities of the users. In cases where the analysis involves an integrated computational method, for instance to reduce the dimensionality of the data or to perform clustering, such non-optimal processes are often likely. To remedy this, progressive computations, where results are iteratively improved, are getting increasing interest in visual analytics. In this paper, we present techniques and design considerations to incorporate progressive methods within interactive analysis processes that involve high-dimensional data. We define methodologies to facilitate processes that adhere to the perceptual characteristics of users and describe how online algorithms can be incorporated within these. A set of design recommendations and according methods to support analysts in accomplishing high-dimensional data analysis tasks are then presented. Our arguments and decisions here are informed by observations gathered over a series of analysis sessions with analysts from finance. We document observations and recommendations from this study and present evidence on how our approach contribute to the efficiency and productivity of interactive visual analysis sessions involving high-dimensional data.

  10. Implementation of the analytical hierarchy process with VBA in ArcGIS

    NASA Astrophysics Data System (ADS)

    Marinoni, Oswald

    2004-07-01

    Decisions on landuse have become progressively more difficult in the last decades. The main reasons for this development lie in the increasing population combined with an increasing demand for new land and resources and in the growing consciousness for sustainable land and resource use. The steady reduction of valuable land leads to an increase of conflicts in land use decision-making processes since more interests are being affected and therefore more stakeholders with different land use interests and different valuation criteria are being involved in the decision-making process. In the course of such a decision process all identified criteria are weighted according to their relative importance. But assigning weights to the relevant criteria quickly becomes a difficult task when a greater number of criteria are being considered, especially with regard to land use decisions where decision makers expect some kind of mapped result it is therefore useful to use procedures that not only help to derive criteria weights but also accelerate the visualisation and mapping of land use assessment results. Both aspects can easily be facilitated in a GIS. This paper focuses the development of an ArcGIS VBA macro which enables the user to derive criteria weights with the analytical hierarchy process and which allows a mapping of the land use assessment results by a weighted summation of GIS raster data sets. A dynamic link library for the calculation of the eigenvalues and eigenvectors of a square matrix is provided.

  11. 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.

  12. Representation of visual symbols in the visual word processing network.

    PubMed

    Muayqil, Taim; Davies-Thompson, Jodie; Barton, Jason J S

    2015-03-01

    Previous studies have shown that word processing involves a predominantly left-sided occipitotemporal network. Words are a form of symbolic representation, in that they are arbitrary perceptual stimuli that represent other objects, actions or concepts. Lesions of parts of the visual word processing network can cause alexia, which can be associated with difficulty processing other types of symbols such as musical notation or road signs. We investigated whether components of the visual word processing network were also activated by other types of symbols. In 16 music-literate subjects, we defined the visual word network using fMRI and examined responses to four symbolic categories: visual words, musical notation, instructive symbols (e.g. traffic signs), and flags and logos. For each category we compared responses not only to scrambled stimuli, but also to similar stimuli that lacked symbolic meaning. The left visual word form area and a homologous right fusiform region responded similarly to all four categories, but equally to both symbolic and non-symbolic equivalents. Greater response to symbolic than non-symbolic stimuli occurred only in the left inferior frontal and middle temporal gyri, but only for words, and in the case of the left inferior frontal gyri, also for musical notation. A whole-brain analysis comparing symbolic versus non-symbolic stimuli revealed a distributed network of inferior temporooccipital and parietal regions that differed for different symbols. The fusiform gyri are involved in processing the form of many symbolic stimuli, but not specifically for stimuli with symbolic content. Selectivity for stimuli with symbolic content only emerges in the visual word network at the level of the middle temporal and inferior frontal gyri, but is specific for words and musical notation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. [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.

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

    PubMed Central

    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. PMID:26955599

  20. The development of an integrated assessment instrument for measuring analytical thinking and science process skills

    NASA Astrophysics Data System (ADS)

    Irwanto, Rohaeti, Eli; LFX, Endang Widjajanti; Suyanta

    2017-05-01

    This research aims to develop instrument and determine the characteristics of an integrated assessment instrument. This research uses 4-D model, which includes define, design, develop, and disseminate. The primary product is validated by expert judgment, tested it's readability by students, and assessed it's feasibility by chemistry teachers. This research involved 246 students of grade XI of four senior high schools in Yogyakarta, Indonesia. Data collection techniques include interview, questionnaire, and test. Data collection instruments include interview guideline, item validation sheet, users' response questionnaire, instrument readability questionnaire, and essay test. The results show that the integrated assessment instrument has Aiken validity value of 0.95. Item reliability was 0.99 and person reliability was 0.69. Teachers' response to the integrated assessment instrument is very good. Therefore, the integrated assessment instrument is feasible to be applied to measure the students' analytical thinking and science process skills.

  1. 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

    To gain confidence in developing analytical models of the purging process for the cryogenic main propulsion systems of upper stage, two test series were conducted. The test article, a 3.35 m long with the diameter of 20 cm incline line, was filled with liquid or gaseous hydrogen and then purged with gaseous helium (GHe). 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, modeling descriptions, and the results are presented in the following sections.

  2. 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.

  3. 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.

  4. Extracting insights from electronic health records: case studies, a visual analytics process model, and design recommendations.

    PubMed

    Wang, Taowei David; Wongsuphasawat, Krist; Plaisant, Catherine; Shneiderman, Ben

    2011-10-01

    Current electronic health record (EHR) systems facilitate the storage, retrieval, persistence, and sharing of patient data. However, the way physicians interact with EHRs has not changed much. More specifically, support for temporal analysis of a large number of EHRs has been lacking. A number of information visualization techniques have been proposed to alleviate this problem. Unfortunately, due to their limited application to a single case study, the results are often difficult to generalize across medical scenarios. We present the usage data of Lifelines2 (Wang et al. 2008), our information visualization system, and user comments, both collected over eight different medical case studies. We generalize our experience into a visual analytics process model for multiple EHRs. Based on our analysis, we make seven design recommendations to information visualization tools to explore EHR systems.

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

    PubMed

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

    2015-01-01

    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. The results collected were subjected to an analytic hierarchy process to obtain the weights of the indicators and the proxy variables. 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. 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.

  6. 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

  7. Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

    PubMed Central

    2005-01-01

    Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

  8. 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.

  9. [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.

  10. 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.

  11. 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.

  12. 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

    To gain confidence in developing analytical models of the purging process for the cryogenic main propulsion systems of upper stage, two test series were conducted. The test article, a 3.35 m long with the diameter of 20 cm incline line, was filled with liquid or gaseous hydrogen and then purged with gaseous helium (GHe). 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, modeling descriptions, and the results are presented in the following sections.

  13. 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.

  14. Using the Analytic Hierarchy Process to Derive Health State Utilities from Ordinal Preference Data.

    PubMed

    Reddy, Brian P; Adams, Roisin; Walsh, Cathal; Barry, Michael; Kind, Paul

    2015-09-01

    The EuroQol five-dimensional questionnaire is a standardized instrument used in the economic evaluation of health care to measure health state preferences across disease groups. A time trade-off (TTO) approach is commonly used to elicit preferences from the public. However, there are issues regarding how best to measure worse-than-dead states; at present, extreme valuations are rounded up to more acceptable values. TTO elicitation is also cognitively demanding for respondents and is therefore expensive to investigate. To describe how the analytic hierarchy process approach could be used to generate utilities from the ordinal relationships between the health states instead of the ordinal relationships between health states, allowing potentially useful preference data to be incorporated rather than excluded as they are at present. It was applied to the Measurement and Valuation of Health study data set, measuring health state preferences for the United Kingdom. The analytic hierarchy process approach was explained. Five approaches to structure pairwise comparisons of health state preference were described (two concave, two convex, and one linear). All approaches described predicted the rankings of health states well. However, utilities derived followed an unconventional, bunched shape compared with the original Measurement and Valuation of Health TTO study. An approach was identified by optimizing the parameters, minimizing the sum of squared errors between the ordinal "health state ranking" approach and the original TTO-derived utilities. This approach outlined offers the potential to convert ordinal preference data into cardinal utilities. It is simpler than TTO studies to carry out and removes the need to directly alter results of the preference ranking exercise. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  15. 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.

  16. 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.

  17. 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.

  18. TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations.

    PubMed

    Zhang, Run-Zhi; Yu, Shao-Jun; Bai, Hong; Ning, Kang

    2017-06-06

    With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the "compounds-proteins/genes-diseases" network, and revealing the regulation principles of small molecules in a high-throughput manner, thus would be very effective for the analysis of drug combinations, especially for TCM preparations. In this work, we have proposed the TCM-Mesh system, which records TCM-related information collected from various resources and could serve for network pharmacology analysis for TCM preparations in a high-throughput manner (http://mesh.tcm.microbioinformatics.org/). Currently, the database contains 6,235 herbs, 383,840 compounds, 14,298 genes, 6,204 diseases, 144,723 gene-disease associations, 3,440,231 pairs of gene interactions, 163,221 side effect records and 71 toxic records, and web-based software construct a network between herbs and treated diseases, which will help to understand the underlying mechanisms for TCM preparations at molecular levels. We have used 1,293 FDA-approved drugs, as well as compounds from an herbal material Panax ginseng and a patented drug Liuwei Dihuang Wan (LDW) for evaluating our database. By comparison of different databases, as well as checking against literature, we have demonstrated the completeness, effectiveness, and accuracy of our database.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  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. 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…

  5. 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

  6. 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…

  7. 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)

  8. 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.

  9. 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)

  10. Artificial neural networks in biology and chemistry: the evolution of a new analytical tool.

    PubMed

    Cartwright, Hugh M

    2008-01-01

    Once regarded as an eccentric and unpromising algorithm for the analysis of scientific data, the neural network has been developed in the last decade into a powerful computational tool. Its use now spans all areas of science, from the physical sciences and engineering to the life sciences and allied subjects. Applications range from the assessment of epidemiological data or the deconvolution of spectra to highly practical applications, such as the electronic nose. This introductory chapter considers briefly the growth in the use of neural networks and provides some general background in preparation for the more detailed chapters that follow.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Impact Of The Material Variability On The Stamping Process: Numerical And Analytical Analysis

    NASA Astrophysics Data System (ADS)

    Ledoux, Yann; Sergent, Alain; Arrieux, Robert

    2007-05-01

    The finite element simulation is a very useful tool in the deep drawing industry. It is used more particularly for the development and the validation of new stamping tools. It allows to decrease cost and time for the tooling design and set up. But one of the most important difficulties to have a good agreement between the simulation and the real process comes from the definition of the numerical conditions (mesh, punch travel speed, limit conditions,…) and the parameters which model the material behavior. Indeed, in press shop, when the sheet set changes, often a variation of the formed part geometry is observed according to the variability of the material properties between these different sets. This last parameter represents probably one of the main source of process deviation when the process is set up. That's why it is important to study the influence of material data variation on the geometry of a classical stamped part. The chosen geometry is an omega shaped part because of its simplicity and it is representative one in the automotive industry (car body reinforcement). Moreover, it shows important springback deviations. An isotropic behaviour law is assumed. The impact of the statistical deviation of the three law coefficients characterizing the material and the friction coefficient around their nominal values is tested. A Gaussian distribution is supposed and their impact on the geometry variation is studied by FE simulation. An other approach is envisaged consisting in modeling the process variability by a mathematical model and then, in function of the input parameters variability, it is proposed to define an analytical model which leads to find the part geometry variability around the nominal shape. These two approaches allow to predict the process capability as a function of the material parameter variability.

  16. 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…

  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. 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...

  19. 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...

  20. 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.

  1. Music Signal Processing Using Vector Product Neural Networks

    NASA Astrophysics Data System (ADS)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  2. Strategic clinical networks in Alberta: Structures, processes, and early outcomes.

    PubMed

    Noseworthy, Tom; Wasylak, Tracy; O'Neill, Blair

    2015-11-01

    In June 2012, Alberta Health Services introduced Strategic Clinical Networks (SCNs) as engines of innovation. The SCNs are collaborative clinical teams, with a provincial strategic mandate and with goals of achieving best outcomes, seeking greatest value for money and engaging clinicians in all aspects of the work. The SCNs are led by clinicians, driven by clinical needs, based on measurement and best evidence, and supported by research expertise, infrastructure, quality improvement, and analytic resources. Eleven SCNs are operational, with five others planned. Early measurable value is demonstrable in each. Examples include improving care and outcomes following stroke, reducing use of anti-psychotics in Long-Term Care (LTC), and improving surgical safety through effective implementation of the Safe Surgery Checklist. © 2015 The Canadian College of Health Leaders.

  3. 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.

  4. Analytical validation for a series of marker compounds used to assess renal drug elimination processes.

    PubMed

    McLachlan, A J; Gross, A S; Beal, J L; Minns, I; Tett, S E

    2001-02-01

    Renal drug elimination is determined by glomerular filtration, tubular secretion, and tubular reabsorption. Changes in the integrity of these processes influence renal drug clearance, and these changes may not be detected by conventional measures of renal function such as creatinine clearance. The aim of the current study was to examine the analytic issues needed to develop a cocktail of marker drugs (fluconazole, rac-pindolol, para-aminohippuric acid, sinistrin) to measure simultaneously the mechanisms contributing to renal clearance. High-performance liquid chromatographic methods of analysis for fluconazole, pindolol, para-aminohippuric acid, and creatinine and an enzymatic assay for sinistrin were developed or modified and then validated to allow determination of each of the compounds in both plasma and urine in the presence of all other marker drugs. A pilot clinical study in one volunteer was conducted to ensure that the assays were suitable for quantitating all the marker drugs to the sensitivity and specificity needed to allow accurate determination of individual renal clearances. The performance of all assays (plasma and urine) complied with published validation criteria. All standard curves displayed linearity over the concentration ranges required, with coefficients of correlation greater than 0.99. The precision of the interday and intraday variabilities of quality controls for each marker in plasma and urine were all less than 11.9% for each marker. Recoveries of markers (and internal standards) in plasma and urine were all at least 90%. All markers investigated were shown to be stable when plasma or urine was frozen and thawed. For all the assays developed, there were no interferences from other markers or endogenous substances. In a pilot clinical study, concentrations of all markers could be accurately and reproducibly determined for a sufficient duration of time after administration to calculate accurate renal clearance for each marker. This

  5. 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

  6. 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

  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. Promoting information diffusion through interlayer recovery processes in multiplex networks

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Li, Weihua; Liu, Longzhao; Pei, Sen; Tang, Shaoting; Zheng, Zhiming

    2017-09-01

    For information diffusion in multiplex networks, the effect of interlayer contagion on spreading dynamics has been explored in different settings. Nevertheless, the impact of interlayer recovery processes, i.e., the transition of nodes to stiflers in all layers after they become stiflers in any layer, still remains unclear. In this paper, we propose a modified ignorant-spreader-stifler model of rumor spreading equipped with an interlayer recovery mechanism. We find that the information diffusion can be effectively promoted for a range of interlayer recovery rates. By combining the mean-field approximation and the Markov chain approach, we derive the evolution equations of the diffusion process in two-layer homogeneous multiplex networks. The optimal interlayer recovery rate that achieves the maximal enhancement can be calculated by solving the equations numerically. In addition, we find that the promoting effect on a certain layer can be strengthened if information spreads more extensively within the counterpart layer. When applying the model to two-layer scale-free multiplex networks, with or without degree correlation, similar promoting effect is also observed in simulations. Our work indicates that the interlayer recovery process is beneficial to information diffusion in multiplex networks, which may have implications for designing efficient spreading strategies.

  9. 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.

  10. 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. (c) 2007 Wiley Periodicals, Inc.

  11. 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.

  12. 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.

  13. 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.

  14. 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. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  15. Brain lateralization of holistic versus analytic processing of emotional facial expressions.

    PubMed

    Calvo, Manuel G; Beltrán, David

    2014-05-15

    This study investigated the neurocognitive mechanisms underlying the role of the eye and the mouth regions in the recognition of facial happiness, anger, and surprise. To this end, face stimuli were shown in three formats (whole face, upper half visible, and lower half visible) and behavioral categorization, computational modeling, and ERP (event-related potentials) measures were combined. N170 (150-180 ms post-stimulus; right hemisphere) and EPN (early posterior negativity; 200-300 ms; mainly, right hemisphere) were modulated by expression of whole faces, but not by separate halves. This suggests that expression encoding (N170) and emotional assessment (EPN) require holistic processing, mainly in the right hemisphere. In contrast, the mouth region of happy faces enhanced left temporo-occipital activity (150-180 ms), and also the LPC (late positive complex; centro-parietal) activity (350-450 ms) earlier than the angry eyes (450-600 ms) or other face regions. Relatedly, computational modeling revealed that the mouth region of happy faces was also visually salient by 150 ms following stimulus onset. This suggests that analytical or part-based processing of the salient smile occurs early (150-180 ms) and lateralized (left), and is subsequently used as a shortcut to identify the expression of happiness (350-450 ms). This would account for the happy face advantage in behavioral recognition tasks when the smile is visible. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. 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.

  17. Using the Analytic Hierarchy Process for Prioritizing Imaging Tests in Diagnosis of Suspected Appendicitis.

    PubMed

    Agapova, Maria; Bresnahan, Brian W; Linnau, Ken F; Garrison, Louis P; Higashi, Mitchell; Kessler, Larry; Devine, Beth

    2017-05-01

    In clinical guideline or criteria development processes, such as those used in developing American College of Radiology Appropriateness Criteria (ACR AC), experts subjectively evaluate benefits and risks associated with imaging tests and make complex decisions about imaging recommendations. The analytic hierarchy process (AHP) decomposes complex decisions into structured smaller decisions, incorporates quantitative evidence and qualitative expert opinion, and promotes structured consensus building. AHP may supplement and/or improve the transparency of expert opinion contributions to developing guidelines or criteria. To conduct an empirical test using health services research tools, we convened a mock ACR AC panel of emergency department radiology and nonradiology physicians to evaluate by multicriteria decision analysis, the relative appropriateness of imaging tests for diagnosing suspected appendicitis. Panel members selected benefit-risk criteria via an online survey and assessed contrast-enhanced computed tomography, magnetic resonance imaging, and ultrasound using an AHP-based software. Participants were asked whether the process was manageable, transparent, and improved shared understanding. Priority scores were converted to rankings and compared to the rank order of ACR AC ratings. When compared to magnetic resonance and ultrasound imaging, participants agreed with the ACR AC that contrast-enhanced computed tomography is the most appropriate test. Contrary to the ACR AC ratings, study results suggest that magnetic resonance is preferable to ultrasound. When compared to nonradiologists, radiologists' priority scores reflect a stronger preference for computed tomography. Study participants addressed decision-making challenges using a relatively efficient data collection mechanism, suggesting that AHP may benefit the ACR AC guideline development process in identifying the relative appropriateness of imaging tests. With additional development, AHP may improve

  18. 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

  19. 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

  20. 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.