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Sample records for analytic network process

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

    PubMed

    Liao, Sen-Kuei; Chang, Kuei-Lun

    2009-01-01

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

  2. Choosing a municipal landfill site by analytic network process

    NASA Astrophysics Data System (ADS)

    Banar, Mufide; Kose, Barbaros Murat; Ozkan, Aysun; Poyraz Acar, Ilgin

    2007-04-01

    In this study, analytic network process (ANP), one of the multi-criteria decision making (MCDM) tools has been used to choose one of the four alternative landfill sites for the city of Eskisehir, Turkey. For this purpose, Super Decision Software has been used and benefit opportunity cost and risk (BOCR) analysis has been done to apply ANP. In BOCR analysis, each alternative site has been evaluated in terms of its benefits, costs and risks; the opportunity cluster has been examined under the benefit cluster. In this context, technical, economical and social assessments have been done for the site selection of sanitary landfill. Also, results have been compared with analytic hierarchy process (AHP) which is another MCDM technique used in the study conducted before. Finally, the current site has been determined as the most appropriate site in both methods. These methods have not been commonly used in the discipline of environmental engineering but it is believed to be an important contribution for decision makers.

  3. 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. PMID:19197656

  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. 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.

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

    PubMed

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

    2015-11-01

    The selection of the most appropriate wastewater treatment (WWT) technology is a complex problem since many alternatives are available and many criteria are involved in the decision-making process. To deal with this challenge, the analytic network process (ANP) is applied for the first time to rank a set of seven WWT technology set-ups for secondary treatment in small communities. A major advantage of ANP is that it incorporates interdependent relationships between elements. Results illustrated that extensive technologies, constructed wetlands and pond systems are the most preferred alternatives by WWT experts. The sensitivity analysis performed verified that the ranking of WWT alternatives is very stable since constructed wetlands are almost always placed in the first position. This paper showed that ANP analysis is suitable to deal with complex decision-making problems, such as the selection of the most appropriate WWT system contributing to better understand the multiple interdependences among elements involved in the assessment. PMID:26119382

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

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

    SciTech Connect

    Gomez-Navarro, Tomas; Diaz-Martin, Diego

    2009-09-15

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

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. Networked analytical sample management system

    SciTech Connect

    Kerrigan, W.J.; Spencer, W.A.

    1986-01-01

    Since 1982, the Savannah River Laboratory (SRL) has operated a computer-controlled analytical sample management system. The system, pogrammed in COBOL, runs on the site IBM 3081 mainframe computer. The system provides for the following subtasks: sample logging, analytical method assignment, worklist generation, cost accounting, and results reporting. Within these subtasks the system functions in a time-sharing mode. Communications between subtasks are done overnight in a batch mode. The system currently supports management of up to 3000 samples a month. Each sample requires, on average, three independent methods. Approximately 100 different analytical techniques are available for customized input of data. The laboratory has implemented extensive computer networking using Ethernet. Electronic mail, RS/1, and online literature searches are in place. Based on our experience with the existing sample management system, we have begun a project to develop a second generation system. The new system will utilize the panel designs developed for the present LIMS, incorporate more realtime features, and take advantage of the many commercial LIMS systems.

  16. Authenticity and the analytic process.

    PubMed

    Boccara, Paolo; Gaddini, Andrea; Riefolo, Giuseppe

    2009-12-01

    In this paper we first make a differentiation between phenomena that can be defined as spontaneous and others that can be defined as authentic. We then attempt to present authenticity as a process rather than an outcome. Finally, we try to understand the location of authentic phenomena in the sensorial and pre-symbolic communicative register. We situate authentic phenomena in the register of sensorial and pre-symbolic communication. The authentic process becomes manifest, step by step in the analytic process (Borgogno, 1999), through the vivid iconic and sensorial elements that happen to cross the analytic field. Through two brief clinical vignettes, we seek to document the progression of the analytic process, in one case through the analyst's capacity for rêverie (Bion, 1962; Ogden, 1994, 1997; Ferro, 2002, 2007), and in the other through the sensorial elements with which analyst and patient are able to tune in to each other.

  17. The analytic network process for the pharmaceutical sector: Multi criteria decision making to select the suitable method for the preparation of nanoparticles

    PubMed Central

    2012-01-01

    Background This paper presents the methodology for assessing and selecting the most appropriate procedure for the preparation of nanoparticles by implementing the analytical network process. The commonly utilized nanoparticle preparation methods are Polymer Precipitation, Interfacial polymer deposition, Complex Coacervation, Cross linking, Emulsion solvent diffusion, Homogenization and Polymerization method. There are numerous parameters to be considered in groundwork of nanoparticles that departs the conclusion manufacturer in bias. One has to address a number of components in alignment to determine and choose the optimum conclusion choices, because an unsuitable conclusion could lead to the eventual merchandise having to be formulated and developed again. For this cause in this paper, we study selecting the most appropriate procedure for the preparation of nanoparticles utilizing one of the multi criteria-decision making techniques, Analytic Network Process. Methodology The main goal was determined. The criteria and sub-criteria that affect the main goal were determined. The alternatives for the problem were determined. The interactions between criteria, sub-criteria, and alternatives respect to the main goal were determined. The super matrixes according to the network were assembled and then weighted super matrix and limit super matrix were then constructed. The values of this limit matrix are the desired priorities of the elements with respect to the goal. The alterative with the highest priority was finally chosen as the best alternative. Results The emulsion solvent diffusion technique (M-5) has the highest value (0.434379) among the alternative methods that are applicable to the preparation of the nanoparticles. The second highest is Polymer Precipitation (M-1) with a value of 0.178798, and the lowest value or last choice is Cross Linking (M-4) with a value of only 0.024516. The alternative with the highest priority would achieve the goal, i.e., the best

  18. 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.

  19. Algorithmic and analytical methods in network biology.

    PubMed

    Koyutürk, Mehmet

    2010-01-01

    During the genomic revolution, algorithmic and analytical methods for organizing, integrating, analyzing, and querying biological sequence data proved invaluable. Today, increasing availability of high-throughput data pertaining to functional states of biomolecules, as well as their interactions, enables genome-scale studies of the cell from a systems perspective. The past decade witnessed significant efforts on the development of computational infrastructure for large-scale modeling and analysis of biological systems, commonly using network models. Such efforts lead to novel insights into the complexity of living systems, through development of sophisticated abstractions, algorithms, and analytical techniques that address a broad range of problems, including the following: (1) inference and reconstruction of complex cellular networks; (2) identification of common and coherent patterns in cellular networks, with a view to understanding the organizing principles and building blocks of cellular signaling, regulation, and metabolism; and (3) characterization of cellular mechanisms that underlie the differences between living systems, in terms of evolutionary diversity, development and differentiation, and complex phenotypes, including human disease. These problems pose significant algorithmic and analytical challenges because of the inherent complexity of the systems being studied; limitations of data in terms of availability, scope, and scale; intractability of resulting computational problems; and limitations of reference models for reliable statistical inference. This article provides a broad overview of existing algorithmic and analytical approaches to these problems, highlights key biological insights provided by these approaches, and outlines emerging opportunities and challenges in computational systems biology.

  20. Algorithmic and analytical methods in network biology

    PubMed Central

    Koyutürk, Mehmet

    2011-01-01

    During genomic revolution, algorithmic and analytical methods for organizing, integrating, analyzing, and querying biological sequence data proved invaluable. Today, increasing availability of high-throughput data pertaining functional states of biomolecules, as well as their interactions, enables genome-scale studies of the cell from a systems perspective. The past decade witnessed significant efforts on the development of computational infrastructure for large-scale modeling and analysis of biological systems, commonly using network models. Such efforts lead to novel insights into the complexity of living systems, through development of sophisticated abstractions, algorithms, and analytical techniques that address a broad range of problems, including the following: (1) inference and reconstruction of complex cellular networks; (2) identification of common and coherent patterns in cellular networks, with a view to understanding the organizing principles and building blocks of cellular signaling, regulation, and metabolism; and (3) characterization of cellular mechanisms that underlie the differences between living systems, in terms of evolutionary diversity, development and differentiation, and complex phenotypes, including human disease. These problems pose significant algorithmic and analytical challenges because of the inherent complexity of the systems being studied; limitations of data in terms of availability, scope, and scale; intractability of resulting computational problems; and limitations of reference models for reliable statistical inference. This article provides a broad overview of existing algorithmic and analytical approaches to these problems, highlights key biological insights provided by these approaches, and outlines emerging opportunities and challenges in computational systems biology. PMID:20836029

  1. 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.

  2. 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.

  3. 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. PMID:27376847

  4. 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.

  5. Analytical Computation of the Epidemic Threshold on Temporal Networks

    NASA Astrophysics Data System (ADS)

    Valdano, Eugenio; Ferreri, Luca; Poletto, Chiara; Colizza, Vittoria

    2015-04-01

    The time variation of contacts in a networked system may fundamentally alter the properties of spreading processes and affect the condition for large-scale propagation, as encoded in the epidemic threshold. Despite the great interest in the problem for the physics, applied mathematics, computer science, and epidemiology communities, a full theoretical understanding is still missing and currently limited to the cases where the time-scale separation holds between spreading and network dynamics or to specific temporal network models. We consider a Markov chain description of the susceptible-infectious-susceptible process on an arbitrary temporal network. By adopting a multilayer perspective, we develop a general analytical derivation of the epidemic threshold in terms of the spectral radius of a matrix that encodes both network structure and disease dynamics. The accuracy of the approach is confirmed on a set of temporal models and empirical networks and against numerical results. In addition, we explore how the threshold changes when varying the overall time of observation of the temporal network, so as to provide insights on the optimal time window for data collection of empirical temporal networked systems. Our framework is of both fundamental and practical interest, as it offers novel understanding of the interplay between temporal networks and spreading dynamics.

  6. 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

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

    PubMed

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

    2014-04-01

    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.

  8. 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…

  9. 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.

  10. 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.

  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. 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.

  13. 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.

  14. 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.

  15. Analytic sequential methods for detecting network intrusions

    NASA Astrophysics Data System (ADS)

    Chen, Xinjia; Walker, Ernest

    2014-05-01

    In this paper, we propose an analytic sequential methods for detecting port-scan attackers which routinely perform random "portscans" of IP addresses to find vulnerable servers to compromise. In addition to rigorously control the probability of falsely implicating benign remote hosts as malicious, our method performs significantly faster than other current solutions. We have developed explicit formulae for quick determination of the parameters of the new detection algorithm.

  16. 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.

  17. Exploring the Analytical Processes of Intelligence Analysts

    SciTech Connect

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

    2009-04-04

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

  18. 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.

  19. Network Analytical Tool for Monitoring Global Food Safety Highlights China

    PubMed Central

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

    2009-01-01

    Background The Beijing Declaration on food safety and security was signed by over fifty countries with the aim of developing comprehensive programs for monitoring food safety and security on behalf of their citizens. Currently, comprehensive systems for food safety and security are absent in many countries, and the systems that are in place have been developed on different principles allowing poor opportunities for integration. Methodology/Principal Findings We have developed a user-friendly analytical tool based on network approaches for instant customized analysis of food alert patterns in the European dataset from the Rapid Alert System for Food and Feed. Data taken from alert logs between January 2003 – August 2008 were processed using network analysis to i) capture complexity, ii) analyze trends, and iii) predict possible effects of interventions by identifying patterns of reporting activities between countries. The detector and transgressor relationships are readily identifiable between countries which are ranked using i) Google's PageRank algorithm and ii) the HITS algorithm of Kleinberg. The program identifies Iran, China and Turkey as the transgressors with the largest number of alerts. However, when characterized by impact, counting the transgressor index and the number of countries involved, China predominates as a transgressor country. Conclusions/Significance This study reports the first development of a network analysis approach to inform countries on their transgressor and detector profiles as a user-friendly aid for the adoption of the Beijing Declaration. The ability to instantly access the country-specific components of the several thousand annual reports will enable each country to identify the major transgressors and detectors within its trading network. Moreover, the tool can be used to monitor trading countries for improved detector/transgressor ratios. PMID:19688088

  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. Parallel processing in immune networks

    NASA Astrophysics Data System (ADS)

    Agliari, Elena; Barra, Adriano; Bartolucci, Silvia; Galluzzi, Andrea; Guerra, Francesco; Moauro, Francesco

    2013-04-01

    In this work, we adopt a statistical-mechanics approach to investigate basic, systemic features exhibited by adaptive immune systems. The lymphocyte network made by B cells and T cells is modeled by a bipartite spin glass, where, following biological prescriptions, links connecting B cells and T cells are sparse. Interestingly, the dilution performed on links is shown to make the system able to orchestrate parallel strategies to fight several pathogens at the same time; this multitasking capability constitutes a remarkable, key property of immune systems as multiple antigens are always present within the host. We also define the stochastic process ruling the temporal evolution of lymphocyte activity and show its relaxation toward an equilibrium measure allowing statistical-mechanics investigations. Analytical results are compared with Monte Carlo simulations and signal-to-noise outcomes showing overall excellent agreement. Finally, within our model, a rationale for the experimentally well-evidenced correlation between lymphocytosis and autoimmunity is achieved; this sheds further light on the systemic features exhibited by immune networks.

  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.

    PubMed

    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. Parallel processing neural networks

    SciTech Connect

    Zargham, M.

    1988-09-01

    A model for Neural Network which is based on a particular kind of Petri Net has been introduced. The model has been implemented in C and runs on the Sequent Balance 8000 multiprocessor, however it can be directly ported to different multiprocessor environments. The potential advantages of using Petri Nets include: (1) the overall system is often easier to understand due to the graphical and precise nature of the representation scheme, (2) the behavior of the system can be analyzed using Petri Net theory. Though, the Petri Net is an obvious choice as a basis for the model, the basic Petri Net definition is not adequate to represent the neuronal system. To eliminate certain inadequacies more information has been added to the Petri Net model. In the model, a token represents either a processor or a post synaptic potential. Progress through a particular Neural Network is thus graphically depicted in the movement of the processor tokens through the Petri Net.

  6. Analytical network-averaging of the tube model:. Rubber elasticity

    NASA Astrophysics Data System (ADS)

    Khiêm, Vu Ngoc; Itskov, Mikhail

    2016-10-01

    In this paper, a micromechanical model for rubber elasticity is proposed on the basis of analytical network-averaging of the tube model and by applying a closed-form of the Rayleigh exact distribution function for non-Gaussian chains. This closed-form is derived by considering the polymer chain as a coarse-grained model on the basis of the quantum mechanical solution for finitely extensible dumbbells (Ilg et al., 2000). The proposed model includes very few physically motivated material constants and demonstrates good agreement with experimental data on biaxial tension as well as simple shear tests.

  7. 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.

  8. 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.

  9. Visual analytics for discovering node groups in complex networks

    NASA Astrophysics Data System (ADS)

    Nishikawa, Takashi

    2011-03-01

    Given the abundance of relational data from a variety of sources, it is becoming increasingly more important to be able to discover hidden structures in the topology of real-world complex networks. In this talk, I will extend the usual definition of groups as densely connected sets of nodes and show that many real networks have groups distinguished by a diverse combinations of node properties, but not by the density of links alone. To overcome the virtually unlimited ways to potentially distinguish groups, we have developed an exploratory analysis tool that exploit human visual ability. In this visual analytical approach, the user input from visual interaction is integrated into the analysis to discover unknown group structures, rather than simply detecting a known type of structure. I will also address the problem of determining an appropriate number of groups, when it is not known a priori. I will demonstrate that our method can effectively find and characterize a variety of group structures in model and real-world networks, including community and k -partite structures defined by link density, as well as groups distinguished by combinations of other node properties. Funded by FODAVA NSF-DMS-0808860.

  10. Analytical transmission electron microscopy in minerals processing

    SciTech Connect

    Fraser, H.L.; Hsieh, K.C.; Twigg, M.E.

    1981-01-01

    A review of the possibilities of performing microchemical analysis in thin sections using a combination of scanning transmission electron microscopy and energy dispersive spectroscopy of x-rays is given. Particular attention is paid to the factors that limit accurate analysis at the highest spatial resolution. As an example of the use of these techniques applied to a potential problem in minerals processing, the identification of pyrite and pyrrhotite particles in Illinois, Herrin number 6 coal is presented.

  11. 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.

  12. [Cognitive processes and neuronal networks].

    PubMed

    Ohayon, M

    1990-10-01

    It is clear that computers are but a poor brain models: the nervous system has many "processors" (neurons) in parallel, whereas von Neuman's machines work sequentially on a single processor. In complex systems, emergent properties cannot be inferred from the behaviour of single elements. Anthills display collective "meaningful" moves, while each ant seems to obey local interactions only. Likewise, large parallel networks of processing elements elicit emergent properties. Like brains, some of them are self-organizing systems. In large parallel processing networks, each unit performs an elementary computation: adding inputs from other units. Large nets display surprising spontaneous computational abilities: associative memories, classes, generalizations may be seen as emergent properties of the network. Symbols are dynamical entities, whose handing is driven by local interactions of activation/inhibition of related representations. In such models, representations (memories) are distributed in the whole network, as stable configurations. Indeed, the basic properties of representation in connectionist models seem closer to human mental objects than the classic Artificial Intelligence concepts. Connectionist models have been used in many fields, namely simulations of real neural networks, pattern recognition and artificial vision, speech recognition, language understanding and knowledge representation, problem solving... Connectionist models have been thus used in neurobiology as well as cognition. One basic structure seems indeed able to account for a range of cognitive functions, from perception to problem solving and high level cognitive tasks. Nevertheless studies about "pathological" networks are yet rare, still an open field... We explore some of these fields. PMID:1965482

  13. [Cognitive processes and neuronal networks].

    PubMed

    Ohayon, M

    1990-10-01

    It is clear that computers are but a poor brain models: the nervous system has many "processors" (neurons) in parallel, whereas von Neuman's machines work sequentially on a single processor. In complex systems, emergent properties cannot be inferred from the behaviour of single elements. Anthills display collective "meaningful" moves, while each ant seems to obey local interactions only. Likewise, large parallel networks of processing elements elicit emergent properties. Like brains, some of them are self-organizing systems. In large parallel processing networks, each unit performs an elementary computation: adding inputs from other units. Large nets display surprising spontaneous computational abilities: associative memories, classes, generalizations may be seen as emergent properties of the network. Symbols are dynamical entities, whose handing is driven by local interactions of activation/inhibition of related representations. In such models, representations (memories) are distributed in the whole network, as stable configurations. Indeed, the basic properties of representation in connectionist models seem closer to human mental objects than the classic Artificial Intelligence concepts. Connectionist models have been used in many fields, namely simulations of real neural networks, pattern recognition and artificial vision, speech recognition, language understanding and knowledge representation, problem solving... Connectionist models have been thus used in neurobiology as well as cognition. One basic structure seems indeed able to account for a range of cognitive functions, from perception to problem solving and high level cognitive tasks. Nevertheless studies about "pathological" networks are yet rare, still an open field... We explore some of these fields.

  14. 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. PMID:24051769

  15. 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

  16. 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. PMID:25331503

  17. 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.

  18. 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. PMID:24355839

  19. 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.

  20. Analytical advantages of multivariate data processing. One, two, three, infinity?

    PubMed

    Olivieri, Alejandro C

    2008-08-01

    Multidimensional data are being abundantly produced by modern analytical instrumentation, calling for new and powerful data-processing techniques. Research in the last two decades has resulted in the development of a multitude of different processing algorithms, each equipped with its own sophisticated artillery. Analysts have slowly discovered that this body of knowledge can be appropriately classified, and that common aspects pervade all these seemingly different ways of analyzing data. As a result, going from univariate data (a single datum per sample, employed in the well-known classical univariate calibration) to multivariate data (data arrays per sample of increasingly complex structure and number of dimensions) is known to provide a gain in sensitivity and selectivity, combined with analytical advantages which cannot be overestimated. The first-order advantage, achieved using vector sample data, allows analysts to flag new samples which cannot be adequately modeled with the current calibration set. The second-order advantage, achieved with second- (or higher-) order sample data, allows one not only to mark new samples containing components which do not occur in the calibration phase but also to model their contribution to the overall signal, and most importantly, to accurately quantitate the calibrated analyte(s). No additional analytical advantages appear to be known for third-order data processing. Future research may permit, among other interesting issues, to assess if this "1, 2, 3, infinity" situation of multivariate calibration is really true. PMID:18613646

  1. 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.

  2. 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.

  3. Optimizing an Immersion ESL Curriculum Using Analytic Hierarchy Process

    ERIC Educational Resources Information Center

    Tang, Hui-Wen Vivian

    2011-01-01

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

  4. Using the Analytic Hierarchy Process to Analyze Multiattribute Decisions.

    ERIC Educational Resources Information Center

    Spires, Eric E.

    1991-01-01

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

  5. 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…

  6. 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…

  7. 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.

  8. 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

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

    PubMed

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

    2015-01-01

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

  10. An analytical approach to photonic reservoir computing - a network of SOA's - for noisy speech recognition

    NASA Astrophysics Data System (ADS)

    Salehi, Mohammad Reza; Abiri, Ebrahim; Dehyadegari, Louiza

    2013-10-01

    This paper seeks to investigate an approach of photonic reservoir computing for optical speech recognition on an examination isolated digit recognition task. An analytical approach in photonic reservoir computing is further drawn on to decrease time consumption, compared to numerical methods; which is very important in processing large signals such as speech recognition. It is also observed that adjusting reservoir parameters along with a good nonlinear mapping of the input signal into the reservoir, analytical approach, would boost recognition accuracy performance. Perfect recognition accuracy (i.e. 100%) can be achieved for noiseless speech signals. For noisy signals with 0-10 db of signal to noise ratios, however, the accuracy ranges observed varied between 92% and 98%. In fact, photonic reservoir application demonstrated 9-18% improvement compared to classical reservoir networks with hyperbolic tangent nodes.

  11. 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

  12. 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.

  13. 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. PMID:24390714

  14. 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.

  15. 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.

  16. 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.

  17. "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.

  18. 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.

  19. 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.

  20. 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

  1. Analytic method for calculating properties of random walks on networks

    NASA Technical Reports Server (NTRS)

    Goldhirsch, I.; Gefen, Y.

    1986-01-01

    A method for calculating the properties of discrete random walks on networks is presented. The method divides complex networks into simpler units whose contribution to the mean first-passage time is calculated. The simplified network is then further iterated. The method is demonstrated by calculating mean first-passage times on a segment, a segment with a single dangling bond, a segment with many dangling bonds, and a looplike structure. The results are analyzed and related to the applicability of the Einstein relation between conductance and diffusion.

  2. 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

  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. 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.

  5. Pre-analytic process control: projecting a quality image.

    PubMed

    Serafin, Mark D

    2006-01-01

    Within the health-care system, the term "ancillary department" often describes the laboratory. Thus, laboratories may find it difficult to define their image and with it, customer perception of department quality. Regulatory requirements give laboratories who so desire an elegant way to address image and perception issues--a comprehensive pre-analytic system solution. Since large laboratories use such systems--laboratory service manuals--I describe and illustrate the process for the benefit of smaller facilities. There exist resources to help even small laboratories produce a professional service manual--an elegant solution to image and customer perception of quality. PMID:17005095

  6. 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.

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

    NASA Technical Reports Server (NTRS)

    Rubin, I.

    1978-01-01

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

  8. Analytical solution of average path length for Apollonian networks

    NASA Astrophysics Data System (ADS)

    Zhang, Zhongzhi; Chen, Lichao; Zhou, Shuigeng; Fang, Lujun; Guan, Jihong; Zou, Tao

    2008-01-01

    With the help of recursion relations derived from the self-similar structure, we obtain the solution of average path length, dmacr t , for Apollonian networks. In contrast to the well-known numerical result dmacr t∝(lnNt)3/4 [J. S. Andrade, Jr. , Phys. Rev. Lett. 94, 018702 (2005)], our rigorous solution shows that the average path length grows logarithmically as dmacr t∝lnNt in the infinite limit of network size Nt . The extensive numerical calculations completely agree with our closed-form solution.

  9. Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

    PubMed Central

    Schilbach, Leonhard; Müller, Veronika I.; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto

    2014-01-01

    Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology. PMID:24759619

  10. Balanced Input Allows Optimal Encoding in a Stochastic Binary Neural Network Model: An Analytical Study

    PubMed Central

    Deco, Gustavo; Hugues, Etienne

    2012-01-01

    Recent neurophysiological experiments have demonstrated a remarkable effect of attention on the underlying neural activity that suggests for the first time that information encoding is indeed actively influenced by attention. Single cell recordings show that attention reduces both the neural variability and correlations in the attended condition with respect to the non-attended one. This reduction of variability and redundancy enhances the information associated with the detection and further processing of the attended stimulus. Beyond the attentional paradigm, the local activity in a neural circuit can be modulated in a number of ways, leading to the general question of understanding how the activity of such circuits is sensitive to these relatively small modulations. Here, using an analytically tractable neural network model, we demonstrate how this enhancement of information emerges when excitatory and inhibitory synaptic currents are balanced. In particular, we show that the network encoding sensitivity -as measured by the Fisher information- is maximized at the exact balance. Furthermore, we find a similar result for a more realistic spiking neural network model. As the regime of balanced inputs has been experimentally observed, these results suggest that this regime is functionally important from an information encoding standpoint. PMID:22359550

  11. 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

  12. 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

  13. In-Database Raster Analytics: Map Algebra and Parallel Processing in Oracle Spatial Georaster

    NASA Astrophysics Data System (ADS)

    Xie, Q. J.; Zhang, Z. Z.; Ravada, S.

    2012-07-01

    Over the past decade several products have been using enterprise database technology to store and manage geospatial imagery and raster data inside RDBMS, which in turn provides the best manageability and security. With the data volume growing exponentially, real-time or near real-time processing and analysis of such big data becomes more challenging. Oracle Spatial GeoRaster, different from most other products, takes the enterprise database-centric approach for both data management and data processing. This paper describes one of the central components of this database-centric approach: the processing engine built completely inside the database. Part of this processing engine is raster algebra, which we call the In-database Raster Analytics. This paper discusses the three key characteristics of this in-database analytics engine and the benefits. First, it moves the data processing closer to the data instead of moving the data to the processing, which helps achieve greater performance by overcoming the bottleneck of computer networks. Second, we designed and implemented a new raster algebra expression language. This language is based on PL/SQL and is currently focused on the "local" function type of map algebra. This language includes general arithmetic, logical and relational operators and any combination of them, which dramatically improves the analytical capability of the GeoRaster database. The third feature is the implementation of parallel processing of such operations to further improve performance. This paper also presents some sample use cases. The testing results demonstrate that this in-database approach for raster analytics can effectively help solve the biggest performance challenges we are facing today with big raster and image data.

  14. 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.

  15. 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.

  16. Neural Network Computing and Natural Language Processing.

    ERIC Educational Resources Information Center

    Borchardt, Frank

    1988-01-01

    Considers the application of neural network concepts to traditional natural language processing and demonstrates that neural network computing architecture can: (1) learn from actual spoken language; (2) observe rules of pronunciation; and (3) reproduce sounds from the patterns derived by its own processes. (Author/CB)

  17. 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.

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

    PubMed Central

    Simpson, Matthew J.; Morrow, Liam C.

    2015-01-01

    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. PMID:26064648

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Electrogenerated thin films of microporous polymer networks with remarkably increased electrochemical response to nitroaromatic analytes.

    PubMed

    Palma-Cando, Alex; Scherf, Ullrich

    2015-06-01

    Thin films of microporous polymer networks (MPNs) have been generated by electrochemical polymerization of a series of multifunctional carbazole-based monomers. The microporous films show high Brunauer-Emmett-Teller (BET) surface areas up to 1300 m2 g(-1) as directly measured by krypton sorption experiments. A correlation between the number of polymerizable carbazole units of the monomer and the resulting surface area is observed. Electrochemical sensing experiments with 1,3,5-trinitrobenzene as prototypical nitroaromatic analyte demonstrate an up to 180 times increased current response of MPN-modified glassy carbon electrodes in relation to the nonmodified electrode. The phenomenon probably involves intermolecular interactions between the electron-poor nitroaromatic analytes and the electron-rich, high surface area microporous deposits, with the electrochemical reduction at the MPN-modified electrodes being an adsorption-controlled process for low scan rates. We expect a high application potential of such MPN-modified electrodes for boosting the sensitivity of electrochemical sensor devices. PMID:25946727

  5. 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.

  6. 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.

  7. Controlled English to facilitate human/machine analytical processing

    NASA Astrophysics Data System (ADS)

    Braines, Dave; Mott, David; Laws, Simon; de Mel, Geeth; Pham, Tien

    2013-06-01

    Controlled English is a human-readable information representation format that is implemented using a restricted subset of the English language, but which is unambiguous and directly accessible by simple machine processes. We have been researching the capabilities of CE in a number of contexts, and exploring the degree to which a flexible and more human-friendly information representation format could aid the intelligence analyst in a multi-agent collaborative operational environment; especially in cases where the agents are a mixture of other human users and machine processes aimed at assisting the human users. CE itself is built upon a formal logic basis, but allows users to easily specify models for a domain of interest in a human-friendly language. In our research we have been developing an experimental component known as the "CE Store" in which CE information can be quickly and flexibly processed and shared between human and machine agents. The CE Store environment contains a number of specialized machine agents for common processing tasks and also supports execution of logical inference rules that can be defined in the same CE language. This paper outlines the basic architecture of this approach, discusses some of the example machine agents that have been developed, and provides some typical examples of the CE language and the way in which it has been used to support complex analytical tasks on synthetic data sources. We highlight the fusion of human and machine processing supported through the use of the CE language and CE Store environment, and show this environment with examples of highly dynamic extensions to the model(s) and integration between different user-defined models in a collaborative setting.

  8. 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

  9. Optimization of analytical laboratory work using computer networking and databasing

    SciTech Connect

    Upp, D.L.; Metcalf, R.A.

    1996-06-01

    The Health Physics Analysis Laboratory (HPAL) performs around 600,000 analyses for radioactive nuclides each year at Los Alamos National Laboratory (LANL). Analysis matrices vary from nasal swipes, air filters, work area swipes, liquids, to the bottoms of shoes and cat litter. HPAL uses 8 liquid scintillation counters, 8 gas proportional counters, and 9 high purity germanium detectors in 5 laboratories to perform these analyses. HPAL has developed a computer network between the labs and software to produce analysis results. The software and hardware package includes barcode sample tracking, log-in, chain of custody, analysis calculations, analysis result printing, and utility programs. All data are written to a database, mirrored on a central server, and eventually written to CD-ROM to provide for online historical results. This system has greatly reduced the work required to provide for analysis results as well as improving the quality of the work performed.

  10. 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.

  11. Using online analytical processing to manage emergency department operations.

    PubMed

    Gordon, Bradley D; Asplin, Brent R

    2004-11-01

    The emergency department (ED) is a unique setting in which to explore and evaluate the utility of information technology to improve health care operations. A potentially useful software tool in managing this complex environment is online analytical processing (OLAP). An OLAP system has the ability to provide managers, providers, and researchers with the necessary information to make decisions quickly and effectively by allowing them to examine patterns and trends in operations and patient flow. OLAP software quickly summarizes and processes data acquired from a variety of data sources, including computerized ED tracking systems. It allows the user to form a comprehensive picture of the ED from both system-wide and patient-specific perspectives and to interactively view the data using an approach that meets his or her needs. This article describes OLAP software tools and provides examples of potential OLAP applications for care improvement projects, primarily from the perspective of the ED. While OLAP is clearly a helpful tool in the ED, it is far more useful when integrated into the larger continuum of health information systems across a hospital or health care delivery system. PMID:15528586

  12. 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.

  13. Mapping stochastic processes onto complex networks

    NASA Astrophysics Data System (ADS)

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

    2009-07-01

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

  14. Analytic Concepts and the Relation Between Content and Process in Science Curricula.

    ERIC Educational Resources Information Center

    Smith, Edward L.

    The interrelation of science content and process is discussed in terms of analytic and systemic concepts. Analytic concepts identify the type or form of systemic concepts found in particular disciplines. In terms of analytic concepts, science processes such as observation, deduction, and prediction can be identified and defined as operations…

  15. 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.

  16. 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…

  17. Evaluating supplier quality performance using analytical hierarchy process

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

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

    SciTech Connect

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

    2010-10-15

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

  19. 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.

  20. Consistent analytic approach to the efficiency of collisional Penrose process

    NASA Astrophysics Data System (ADS)

    Harada, Tomohiro; Ogasawara, Kota; Miyamoto, Umpei

    2016-07-01

    We propose a consistent analytic approach to the efficiency of collisional Penrose process in the vicinity of a maximally rotating Kerr black hole. We focus on a collision with arbitrarily high center-of-mass energy, which occurs if either of the colliding particles has its angular momentum fine-tuned to the critical value to enter the horizon. We show that if the fine-tuned particle is ingoing on the collision, the upper limit of the efficiency is (2 +√{3 })(2 -√{2 })≃2.186 , while if the fine-tuned particle is bounced back before the collision, the upper limit is (2 +√{3 })2≃13.93 . Despite earlier claims, the former can be attained for inverse Compton scattering if the fine-tuned particle is massive and starts at rest at infinity, while the latter can be attained for various particle reactions, such as inverse Compton scattering and pair annihilation, if the fine-tuned particle is either massless or highly relativistic at infinity. We discuss the difference between the present and earlier analyses.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  2. 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.

  3. Dynamic process modeling with recurrent neural networks

    SciTech Connect

    You, Yong; Nikolaou, M. . Dept. of Chemical Engineering)

    1993-10-01

    Mathematical models play an important role in control system synthesis. However, due to the inherent nonlinearity, complexity and uncertainty of chemical processes, it is usually difficult to obtain an accurate model for a chemical engineering system. A method of nonlinear static and dynamic process modeling via recurrent neural networks (RNNs) is studied. An RNN model is a set of coupled nonlinear ordinary differential equations in continuous time domain with nonlinear dynamic node characteristics as well as both feed forward and feedback connections. For such networks, each physical input to a system corresponds to exactly one input to the network. The system's dynamics are captured by the internal structure of the network. The structure of RNN models may be more natural and attractive than that of feed forward neural network models, but computation time for training is longer. Simulation results show that RNNs can learn both steady-state relationships and process dynamics of continuous and batch, single-input/single-output and multi-input/multi-output systems in a simple and direct manner. Training of RNNs shows only small degradation in the presence of noise in the training data. Thus, RNNs constitute a feasible alternative to layered feed forward back propagation neural networks in steady-state and dynamic process modeling and model-based control.

  4. An analytic explanation of the stellar initial mass function from the theory of spatial networks

    NASA Astrophysics Data System (ADS)

    Klishin, Andrei; Chilingarian, Igor

    2015-08-01

    The distribution of stars by mass or the stellar initial mass function (IMF) that has been intensively studied in the Milky Way and other galaxies is the key property regulating star formation and galaxy evolution. The mass function of prestellar dense cores (DCMF) is an IMF precursor that has a similar shape, a broken power law with a sharp decline at low masses, but offset to higher masses. Results from numerical simulations of star formation qualitatively resemble an observed IMF/DCMF, however, most analytic IMF theories critically depend on the empirically chosen input spectrum of mass fluctuations which evolve into dense cores and, subsequently, stars. Here we propose an analytic approach by representing a system of dense cores accreting gas from the surrounding diffuse interstellar medium (ISM) as a spatial network growing by preferential attachment and assuming that the ISM density has a self-similar fractal distribution following the Kolmogorov turbulence theory. We obtain a scale free power law with the exponent that is not related to the input fluctuation mass spectrum but depends only on the fractal distribution dimensionalities of infalling gas (Dp) and turbulent ISM (Dm=2.35). It can be as steep as -3.24 (uniform volume density Dp=3) and becomes Salpeter (α=-2.35) for Dp=2.5 that corresponds to a variety of Brownian processes in physics. Our theory reproduces the observed DCMF shape over three orders of magnitude in mass, and it rules out a low mass star dominated "bottom-heavy" IMF shape unless the same steep slope holds at the higher masses.

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

    DOEpatents

    Roach, Patrick J.; Laskin, Julia; Laskin, Alexander

    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.

  6. Stabilization of avalanche processes on dynamical networks

    NASA Astrophysics Data System (ADS)

    Savitskaya, N. E.

    2016-02-01

    The stabilization of avalanches on dynamical networks has been studied. Dynamical networks are networks where the structure of links varies in time owing to the presence of the individual "activity" of each site, which determines the probability of establishing links with other sites per unit time. An interesting case where the times of existence of links in a network are equal to the avalanche development times has been examined. A new mathematical model of a system with the avalanche dynamics has been constructed including changes in the network on which avalanches are developed. A square lattice with a variable structure of links has been considered as a dynamical network within this model. Avalanche processes on it have been simulated using the modified Abelian sandpile model and fixed-energy sandpile model. It has been shown that avalanche processes on the dynamical lattice under study are more stable than a static lattice with respect to the appearance of catastrophic events. In particular, this is manifested in a decrease in the maximum size of an avalanche in the Abelian sandpile model on the dynamical lattice as compared to that on the static lattice. For the fixed-energy sandpile model, it has been shown that, in contrast to the static lattice, where an avalanche process becomes infinite in time, the existence of avalanches finite in time is always possible.

  7. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

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

  8. 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

  9. 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.

  10. 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.”

  11. 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.

  12. Analytical solutions of infiltration process under ponding irrigation

    NASA Astrophysics Data System (ADS)

    Chen, Jiann-Mou; Tan, Yih-Chi

    2005-11-01

    The objective of this paper is to simulate the progress of the soil water content distribution in the soil profile with a water table at the bottom of the soil profile during ponding irrigation. This simulation can be done by solving the two-dimensional Richards's equation for the assimilation of the advancing water jet, which uses the conditions of the two exponential functional forms k = ks e and = r + (s - r) e to represent the hydraulic conductivity and volumetric water content, with the pressure as the third variable. We assume that the ground surface becomes ponded and saturated as soon as the water flux passes the dry ground surface. By the technique of transformation, the analytical solution of these two-dimensional Richards' equations has enabled figures of volumetric water content distribution to be obtained in successive time periods after irrigation. For the example of loam soil, it can simulate the variation of volumetric water content during and after irrigation in the soil profile. The analytical solutions of this paper reflect the real situation simulated, and can be applied to verify those complicated solutions from other analytical models. Copyright

  13. Inferring sparse networks for noisy transient processes.

    PubMed

    Tran, Hoang M; Bukkapatnam, Satish T S

    2016-01-01

    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 l1-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 l1-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. PMID:26916813

  14. 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.

  15. 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.

  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. 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.

  18. 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.

  19. 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)

  20. A Novel Analytical Approach to Pulsatile Blood Flow in the Arterial Network.

    PubMed

    Flores, Joaquín; Alastruey, Jordi; Corvera Poiré, Eugenia

    2016-10-01

    Haemodynamic simulations using one-dimensional (1-D) computational models exhibit many of the features of the systemic circulation under normal and diseased conditions. We propose a novel linear 1-D dynamical theory of blood flow in networks of flexible vessels that is based on a generalized Darcy's model and for which a full analytical solution exists in frequency domain. We assess the accuracy of this formulation in a series of benchmark test cases for which computational 1-D and 3-D solutions are available. Accordingly, we calculate blood flow and pressure waves, and velocity profiles in the human common carotid artery, upper thoracic aorta, aortic bifurcation, and a 20-artery model of the aorta and its larger branches. Our analytical solution is in good agreement with the available solutions and reproduces the main features of pulse waveforms in networks of large arteries under normal physiological conditions. Our model reduces computational time and provides a new approach for studying arterial pulse wave mechanics; e.g.,  the analyticity of our model allows for a direct identification of the role played by physical properties of the cardiovascular system on the pressure waves.

  1. Analytical method for promoting process capability of shock absorption steel.

    PubMed

    Sung, Wen-Pei; Shih, Ming-Hsiang; Chen, Kuen-Suan

    2003-01-01

    Mechanical properties and low cycle fatigue are two factors that must be considered in developing new type steel for shock absorption. Process capability and process control are significant factors in achieving the purpose of research and development programs. Often-used evaluation methods failed to measure process yield and process centering; so this paper uses Taguchi loss function as basis to establish an evaluation method and the steps for assessing the quality of mechanical properties and process control of an iron and steel manufacturer. The establishment of this method can serve the research and development and manufacturing industry and lay a foundation in enhancing its process control ability to select better manufacturing processes that are more reliable than decision making by using the other commonly used methods.

  2. 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

  3. 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.

  4. Resting-brain functional connectivity predicted by analytic measures of network communication

    PubMed Central

    Goñi, Joaquín; van den Heuvel, Martijn P.; Avena-Koenigsberger, Andrea; Velez de Mendizabal, Nieves; Betzel, Richard F.; Griffa, Alessandra; Hagmann, Patric; Corominas-Murtra, Bernat; Thiran, Jean-Philippe; Sporns, Olaf

    2014-01-01

    The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures—search information and path transitivity—which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways. PMID:24379387

  5. 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…

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

    SciTech Connect

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

    1980-01-01

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

  7. 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.

  8. Quantum Processes and Dynamic Networks in Physical and Biological Systems.

    NASA Astrophysics Data System (ADS)

    Dudziak, Martin Joseph

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

  9. 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.

  10. 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…

  11. 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.

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

    PubMed

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

    2012-06-26

    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

  13. 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.

  14. Large-scale sequencing and analytical processing of ESTs.

    PubMed

    Mitreva, Makedonka; Mardis, Elaine R

    2009-01-01

    Expressed sequence tags (ESTs) have proven to be one of the most rapid and cost-effective routes to gene discovery for eukaryotic genomes. Furthermore, their multipurpose uses, such as in probe design for microarrays, determining alternative splicing, verifying open reading frames, and confirming exon/intron and gene boundaries, to name a few, further justify their inclusion in many genomic characterization projects. Hence, there has been a constant increase in the number of ESTs deposited into the dbEST division of GenBank. This trend also correlates to ever-improving molecular techniques for obtaining biological material, performing RNA extraction, and constructing cDNA libraries, and predominantly to ever-evolving sequencing chemistry and instrumentation, as well as to decreased sequencing costs. This chapter describes large-scale sequencing of ESTs on two distinct platforms: the ABI 3730xl and the 454 Life Sciences GS20 sequencers, and the corresponding processes of sequence extraction, processing, and submissions to public databases. While the conventional 3730xl sequencing process is described, starting with the plating of an already-existing cDNA library, the section on 454 GS20 pyrosequencing also includes a method for generating full-length cDNA sequences. With appropriate bioinformatics tools, each of these platforms either used independently or coupled together provide a powerful combination for comprehensive exploration of an organism's transcriptome.

  15. 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.

  16. 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. PMID:19000078

  17. MatrixFlow: Temporal Network Visual Analytics to Track Symptom Evolution during Disease Progression

    PubMed Central

    Perer, Adam; Sun, Jimeng

    2012-01-01

    Objective: To develop a visual analytic system to help medical professionals improve disease diagnosis by providing insights for understanding disease progression. Methods: We develop MatrixFlow, a visual analytic system that takes clinical event sequences of patients as input, constructs time-evolving networks and visualizes them as a temporal flow of matrices. MatrixFlow provides several interactive features for analysis: 1) one can sort the events based on the similarity in order to accentuate underlying cluster patterns among those events; 2) one can compare co-occurrence events over time and across cohorts through additional line graph visualization. Results: MatrixFlow is applied to visualize heart failure (HF) symptom events extracted from a large cohort of HF cases and controls (n=50,625), which allows medical experts to reach insights involving temporal patterns and clusters of interest, and compare cohorts in novel ways that may lead to improved disease diagnoses. Conclusions: MatrixFlow is an interactive visual analytic system that allows users to quickly discover patterns in clinical event sequences. By unearthing the patterns hidden within and displaying them to medical experts, users become empowered to make decisions influenced by historical patterns. PMID:23304345

  18. 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.

  19. 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.

  20. 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

  1. Analytical and experimental studies for thermal plasma processing of materials

    NASA Astrophysics Data System (ADS)

    Work continued on thermal plasma processing of materials. This quarter, ceramic powders of carbides, aluminum nitride, oxides, solids solutions, magnetic and non magnetic spinels, superconductors, and composites have been successfully synthesized in a Triple DC Torch Plasma Jet Reactor (TTPR) and in a single DC Plasma Jet Reactor. All the ceramic powders with the exception of AIN were synthesized using a novel injection method developed to overcome the problems associated with solid injection, in particular for the single DC plasma jet reactor, and to realize the benefits of gas phase reactions. Also, initial experiments have been performed for the deposition of diamond coatings on Si wafers using the TTPR with methane as the carbon source. Well faceted diamond crystallites were deposited on the surface of the wafers, forming a continuous one particle thick coating. For measuring temperature and velocity fields in plasma systems, enthalpy probes have been developed and tested. The validity has been checked by performing energy and mass flux balances in an argon plasma jet operated in argon atmosphere. Total Gibbs free energy minimization calculations using a quasi-equilibrium modification have been applied to simulate several chemical reactions. Plasma reactor modelling has been performed for the counter-flow liquid injection plasma synthesis experiment. Plasma diagnostics has been initiated to determine the pressure gradient in the coalesced part of the plasma jet. The pressure gradient drives the diffusion of chemical species which ultimately controls the chemical reactions.

  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. PMID:27389569

  3. Information processing in the separated hemispheres of callosotomy patients: does the analytic-holistic dichotomy hold?

    PubMed

    Trope, I; Rozin, P; Kemler Nelson, D; Gur, R C

    1992-07-01

    The characterization of the left and right cerebral hemispheres as analytic and holistic, respectively, was evaluated with callosotomy patients. This distinction was operationalized by reference to the work of Garner, Kemler Nelson, and their colleagues on separable (analytic) and integral (holistic) dimensions of cognition. In one experiment, patients were asked to make similarity judgments when faced with triads of stimuli such that one pair matched on a criterial attribute (analytic) and another pair showed a family resemblance (holistic). The right hemisphere showed a stronger bias to judge on the basis of the criterial attribute. In a second experiment, each hemisphere was engaged separately in a concept formation task. Depending on the exemplars in a particular set, analytic or holistic processing was seen in either hemisphere. However, the left hemisphere was more likely to engage in analytic processing. The results suggest that both hemispheres are capable of either type of processing and may use either mode, depending on the nature of the task and stimulus material. Thus, the analytic/holistic distinction may not provide a simple, generalizable description of information processing differences between the two hemispheres.

  4. 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.

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

    PubMed

    Kim, Hongkeun

    2016-01-01

    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. PMID:26562053

  6. Habituation of attentional networks during emotion processing.

    PubMed

    Feinstein, Justin S; Goldin, Philippe R; Stein, Murray B; Brown, Gregory G; Paulus, Martin P

    2002-07-19

    Dysfunctional emotion processing is a key aspect of many neuropsychiatric disorders. This dysfunction may be due to an abnormal magnitude of neural substrate activation during emotion processing or due to an altered time course of the neural substrate response. To better understand the temporal characteristics of the neural substrate activation underlying implicit emotion processing, nine healthy female controls were repeatedly exposed to pictures of affective faces while performing a gender identification task in an fMRI. As the salience of the stimuli decreased with repeated exposure, brain areas implicated in a right hemispheric spatial attention network (including the posterior parietal cortex (BA 40) and the frontal eye fields (BA 6)) habituated while brain areas lateralized to the left hemisphere (including the angular gyrus (BA 39), posterior superior temporal gyrus (BA 39) and insula (BA 13)) sensitized. These results provide strong evidence that the time course of activation is a critical component when assessing the function of neural substrates underlying emotion processing (specifically whether habituation is altered) in neuro-psychiatric patients. PMID:12151781

  7. 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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Vargas Toro, Agustín.

    2014-05-01

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

  10. 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).

  11. 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.

  12. 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

  13. 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.

  14. 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.

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

    PubMed Central

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

    2016-01-01

    Introduction 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. Aim This study was undertaken to analyse and assess the quality parameters in pre-analytical phase in a histopathology laboratory. Materials and Methods 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. Results 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

  16. Process analytical tools for monitoring, understanding, and control of pharmaceutical fluidized bed granulation: A review.

    PubMed

    Burggraeve, Anneleen; Monteyne, Tinne; Vervaet, Chris; Remon, Jean Paul; De Beer, Thomas

    2013-01-01

    Fluidized bed granulation is a widely applied wet granulation technique in the pharmaceutical industry to produce solid dosage forms. The process involves the spraying of a binder liquid onto fluidizing powder particles. As a result, the (wetted) particles collide with each other and form larger permanent aggregates (granules). After spraying the required amount of granulation liquid, the wet granules are rapidly dried in the fluid bed granulator. Since the FDA launched its Process Analytical Technology initiative (and even before), a wide range of analytical process sensors has been used for real-time monitoring and control of fluid bed granulation processes. By applying various data analysis techniques to the multitude of data collected from the process analyzers implemented in fluid bed granulators, a deeper understanding of the process has been achieved. This review gives an overview of the process analytical technologies used during fluid bed granulation to monitor and control the process. The fundamentals of the mechanisms contributing to wet granule growth and the characteristics of fluid bed granulation processing are briefly discussed. This is followed by a detailed overview of the in-line applied process analyzers, contributing to improved fluid bed granulation understanding, modeling, control, and endpoint detection. Analysis and modeling tools enabling the extraction of the relevant information from the complex data collected during granulation and the control of the process are highlighted.

  17. 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.

  18. 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.

  19. 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

  20. Survey on Neural Networks Used for Medical Image Processing

    PubMed Central

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

    2010-01-01

    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. PMID:26740861

  1. 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…

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

    ERIC Educational Resources Information Center

    DuBois, Frank L.

    1999-01-01

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

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

    ERIC Educational Resources Information Center

    Liberatore, Matthew J.; Nydick, Robert L.

    1997-01-01

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

  4. Sequence and Transfer in Children's Learning of the Analytic Process of Geographic Inquiry

    ERIC Educational Resources Information Center

    Crabtree, Charlotte

    1976-01-01

    Tests whether children's learnings in one of the social sciences, geography, are as hypothesized, hierarchically dependent; that is, whether learning of each in a series of central, analytic processes in one of the social sciences facilitates, through positive transfer, the learning of each succeeding higher-order capability in the field.…

  5. 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...

  6. 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. PMID:24725069

  7. 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

  8. Energy from true in situ processing of Antrim shale: Sampling and analytical systems

    NASA Astrophysics Data System (ADS)

    Pihlaja, R. K.

    1980-08-01

    Reliable on-line analysis of production gas composition is fundamental to the success of an in situ extraction experiment in Antrim shale. An automted sampling and analysis system designed to meet this need provided high quality analytical data for three extraction trials without a single day when no data were taken. The production gas samples were routinely analyzed by both gas chromatography and a bank of continuous on-line process gas analyzers. The process gas analyzers measured CO, CO2, total hydrocarbons and O2 continuously. The process gas analyzers were shown to be especially well suited for this application because of their fast response. The GC data provided itemized composition details as well as the independent check of process analyzer data. The combination of the two analytical techniques and automated data handling yielded a versatile and powerful system.

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

    PubMed

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

    2015-08-01

    The distinction between intuitive and analytic thinking is common in psychology. However, while often being quite clear on the characteristics of the two processes ('Type 1' processes are fast, autonomous, intuitive, etc. and 'Type 2' processes are slow, deliberative, analytic, etc.), dual-process theorists have been heavily criticized for being unclear on the factors that determine when an individual will think analytically or rely on their intuition. We address this issue by introducing a three-stage model that elucidates the bottom-up factors that cause individuals to engage Type 2 processing. According to the model, multiple Type 1 processes may be cued by a stimulus (Stage 1), leading to the potential for conflict detection (Stage 2). If successful, conflict detection leads to Type 2 processing (Stage 3), which may take the form of rationalization (i.e., the Type 1 output is verified post hoc) or decoupling (i.e., the Type 1 output is falsified). We tested key aspects of the model using a novel base-rate task where stereotypes and base-rate probabilities cued the same (non-conflict problems) or different (conflict problems) responses about group membership. Our results support two key predictions derived from the model: (1) conflict detection and decoupling are dissociable sources of Type 2 processing and (2) conflict detection sometimes fails. We argue that considering the potential stages of reasoning allows us to distinguish early (conflict detection) and late (decoupling) sources of analytic thought. Errors may occur at both stages and, as a consequence, bias arises from both conflict monitoring and decoupling failures. PMID:26091582

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

    PubMed

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

    2015-08-01

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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Discontinuous phase transition in a core contact process on complex networks

    NASA Astrophysics Data System (ADS)

    Chae, Huiseung; Yook, Soon-Hyung; Kim, Yup

    2015-02-01

    To understand the effect of generalized infection processes, we suggest and study the core contact process (CCP) on complex networks. In CCP an uninfected node is infected when at least k different infected neighbors of the node select the node for the infection. The healing process is the same as that of the normal CP. It is analytically and numerically shown that discontinuous transitions occur in CCP on random networks and scale-free networks depending on infection rate and initial density of infected nodes. The discontinuous transitions include hybrid transitions with β = 1/2 and β = 1. The asymptotic behavior of the phase boundary related to the initial density is found analytically and numerically. The mapping between CCP with k and static (k+1)-core percolation is supposed from the (k+1)-core structure in the active phase and the hybrid transition with β = 1/2. From these properties of CCP one can see that CCP is one of the dynamical processes for the k-core structure on real networks.

  16. 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.

  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. 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.

  19. A procedural evaluation of an analytic-deliberative process: the Columbia River Comprehensive Impact Assessment.

    PubMed

    Kinney, Aimee Guglielmo; Leschine, Thomas M

    2002-02-01

    The U.S. Department of Energy's Columbia River Comprehensive Impact Assessment (CRCIA) was an ambitious attempt to direct its cleanup of the Hanford Nuclear Reservation toward the most significant risks to the Columbia River resulting from past plutonium production. DOE's approach was uncommonly open, including tribal, regulatory agency, and other Hanford interest group representatives on the board that was to develop the assessment approach. The CRCIA process had attributes of the "analytic-deliberative" process for risk assessment recommended by the National Research Council. Nevertheless, differences between the DOE and other participants over what was meant by the term "comprehensive" in the group's charge, coupled with differing perceptions of the likely effectiveness of remediation efforts in reducing risks, were never resolved. The CRCIA effort became increasingly fragmented and the role its products were to play in influencing future clean-up decisions increasingly ambiguous. A procedural evaluation of the CRCIA process, based on Thomas Webler's procedural normative model of public participation, reveals numerous instances in which theoretical-normative discourse disconnects occurred. These had negative implications for both the basic procedural dimensions of Webler's model-fairness and competence. Tribal and other interest group representatives lacked the technical resources necessary to make or challenge what philosopher Jurgens Habermas terms cognitive validity claims, while DOE and its contractors did not challenge normative claims made by tribal representatives. The results are cautionary for implementation of the analytic-deliberative process. They highlight the importance of bringing rigor to the evaluation of the quality of the deliberation component of risk characterization via the analytic-deliberative process, as well as to the analytic component.

  20. 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.

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Effects of pre-analytical processes on blood samples used in metabolomics studies.

    PubMed

    Yin, Peiyuan; Lehmann, Rainer; Xu, Guowang

    2015-07-01

    Every day, analytical and bio-analytical chemists make sustained efforts to improve the sensitivity, specificity, robustness, and reproducibility of their methods. Especially in targeted and non-targeted profiling approaches, including metabolomics analysis, these objectives are not easy to achieve; however, robust and reproducible measurements and low coefficients of variation (CV) are crucial for successful metabolomics approaches. Nevertheless, all efforts from the analysts are in vain if the sample quality is poor, i.e. if preanalytical errors are made by the partner during sample collection. Preanalytical risks and errors are more common than expected, even when standard operating procedures (SOP) are used. This risk is particularly high in clinical studies, and poor sample quality may heavily bias the CV of the final analytical results, leading to disappointing outcomes of the study and consequently, although unjustified, to critical questions about the analytical performance of the approach from the partner who provided the samples. This review focuses on the preanalytical phase of liquid chromatography-mass spectrometry-driven metabolomics analysis of body fluids. Several important preanalytical factors that may seriously affect the profile of the investigated metabolome in body fluids, including factors before sample collection, blood drawing, subsequent handling of the whole blood (transportation), processing of plasma and serum, and inadequate conditions for sample storage, will be discussed. In addition, a detailed description of latent effects on the stability of the blood metabolome and a suggestion for a practical procedure to circumvent risks in the preanalytical phase will be given.

  9. 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.

  10. Parallel processing of ADS40 images on PC network

    NASA Astrophysics Data System (ADS)

    Qiu, Feng; Duan, Yansong; Zhang, Jianqing

    2009-10-01

    In this paper, we aim to design a parallel processing system based on economic hardware environment to optimize photogrammetric process of Leica ADS40 images considering ideas and methods of parallel computing. We adopt parallel computing PCAM principle to design and implement a test system for parallel processing of ADS40 images. The test system consists of common personal computers and local gigabits network. It can make full use of network computing and storage resources under a economical and practical cost to deal with ADS40 images. Experiment shows that it achieves significant improvement of processing efficiency. Furthermore, the robustness and compatibility of this system is much higher than stand alone computer system because of system's redundancy based on network. In conclusion, parallel processing system based on PC network brings us a much more efficiency solution of ADS40's photogrammetric production.

  11. 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.

  12. Energy from true in situ processing of Antrim shale: sampling and analytical systems

    SciTech Connect

    Pihlaja, R.K.

    1980-08-01

    Reliable on-line analysis of production gas composition is fundamental to the success of an in situ extraction experiment in Antrim shale. An automated sampling and analysis system designed to meet this need has provided high quality analytical data for three extraction trials without a single day when no data were taken. The production gas samples were routinely analyzed by both gas chromatography (GC) and a bank of continuous on-line process gas analyzers. The GC's analyzed for H/sub 2/, O/sub 2/ + Ar, N/sub 2/, CO, CO/sub 2/, SO/sub 2/, H/sub 2/S, individual C/sub 1/ - C/sub 5/ hydrocarbon species, and lumped C/sub 6/ + hydrocarbon species, each analysis requiring up to an hour to run. The process gas analyzers measured CO, CO/sub 2/, total hydrocarbons (% vol CH/sub 4/ equivalent), and O/sub 2/ continuously. The process gas analyzers were shown to be especially well suited for this application because of their fast response. The GC data provided itemized composition details as well as an independent check of process analyzer data. Sample selection, data collection and processing from both the GC's and process gas analyzers was handled by a Perkin Elmer Sigma-10 minicomputer. The combination of the two analytical techniques and automated data handling yielded a versatile and powerful system. The production gas sampling system demonstrated the feasibility of transmitting a properly treated gas sample through a long (1000 ft) 1/8'' diameter sample line. The small bore tubing allowed the analytical instruments to be located a safe distance away from the well heads and yet maintain a reasonably short sample transport lag time without handling large volumes of gas.

  13. Electro-spun organic nanofibers elaboration process investigations using comparative analytical solutions.

    PubMed

    Colantoni, A; Boubaker, K

    2014-01-30

    In this paper Enhanced Variational Iteration Method, EVIM is proposed, along with the BPES, for solving Bratu equation which appears in the particular elecotrospun nanofibers fabrication process framework. Elecotrospun organic nanofibers, with diameters less than 1/4 microns have been used in non-wovens and filtration industries for a broad range of filtration applications in the last decade. Electro-spinning process has been associated to Bratu equation through thermo-electro-hydrodynamics balance equations. Analytical solutions have been proposed, discussed and compared.

  14. Improved analytical model for deep drawing processes of rotationally symmetric cups

    NASA Astrophysics Data System (ADS)

    Doege, E.; Behrens, B.-A.; Springub, B.

    2004-06-01

    In order to verify the measured flow curve and friction coefficient as input data for FE-simulations an improved analytical model for deep drawing processes of rotationally symmetric cups has been developed at the IFUM. The progression of the deep drawing force during the process is calculated depending on the stresses in the flange and the area of the die radius, the frictional and re-bending force by application of the "principle of virtual work". By using the "plastic instability" theory a failure criteria predicting the drawing limit ratio has been worked out.

  15. 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.

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

    SciTech Connect

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

    1991-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Shen, Ji; Sung, Shannon; Zhang, Dongmei

    2015-11-01

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

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

    PubMed

    Liu, Min; Zhang, Chunsun; Liu, Feifei

    2015-09-01

    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. PMID:26388382

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

    PubMed

    Liu, Min; Zhang, Chunsun; Liu, Feifei

    2015-09-01

    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.

  20. 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. PMID:27038840

  1. 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.

  2. 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.

  3. 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.

  4. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  5. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  6. 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.

  7. 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.

  8. 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.

  9. Engineering processes for the African VLBI network

    NASA Astrophysics Data System (ADS)

    Thondikulam, Venkatasubramani L.; Loots, Anita; Gaylard, Michael

    2013-04-01

    The African VLBI Network (AVN) is an initiative by the SKA-SA and HartRAO, business units of the National Research Foundation (NRF), Department of Science and Technology (DST), South Africa. The aim is to fill the existing gap of Very Long Baseline Interferometry (VLBI)-capable radio telescopes in the African continent by a combination of new build as well as conversion of large redundant telecommunication antennas through an Inter-Governmental collaborative programme in Science and Technology. The issue of human capital development in the Continent in the techniques of radio astronomy engineering and science is a strong force to drive the project and is expected to contribute significantly to the success of Square Kilometer Array (SKA) in the Continent.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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. PMID:25350022

  15. Research of the Urban-Rural Integration Evaluation Indicator System Based on Analytic Hierarchy Process

    NASA Astrophysics Data System (ADS)

    Zhe, Wang

    It's a key problem need to be solved in the urban-rural integration research to scientifically evaluate the development level of urban-rural integration. Based on the analysis of many factors influencing the urban-rural integration, this article is conducting an empirical research of the evaluation indicator system, as well as applying analytic hierarchy process (AHP). By the means of structuring the judgment matrix, and conducting a consistency test, both the eigenvectors corresponding to the judgment matrix and the specific index weight can be obtained.

  16. 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.

  17. 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.

  18. 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).

  19. 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. PMID:22319375

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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. PMID:24468350

  8. Analytical simulation of thermal processes under laser light interaction with multilayered biological tissue

    NASA Astrophysics Data System (ADS)

    Barun, Vladimir V.; Ivanov, Arkady P.

    2005-08-01

    An analytical procedure to study linear thermal processes in multilayered biological tissues irradiated by a laser beam is proposed. The procedure is based on the simplified representation of the heat source function after the irradiation. The Green function of both temporal and radial coordinates of the thermal problem is analytically derived in the paper. It enables one to easy simulate spatial and temporal temperature distributions in tissue by a simple convolution. Pulsed or continuous-wave laser beams with any radial structures can be treated. The validity of the approximations assumed to get the Green function is verified by comparing the simulations with published data on both light and thermal fields in tissues. Rather a good agreement is shown. Specific attention is paid to the most critical approximation, namely to the separation of radial and depth coordinates in the thermal source function. The applicability of such an approach is discussed and quantitatively checked by evaluating the temporal dynamics of radial light and heat spot spreading. The procedure is used to study thermal processes in irradiated skin layers under wide variations of optical parameters of the problem. Sample results on the heating effects of a sensitizer used for photodynamic therapy are illustrated.

  9. 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.

  10. [Network analysis of ethanol precipitation process for Schisandrae chinensis fructus].

    PubMed

    Zhong, Yi; Zhu, Jie-Qiang; Fan, Xiao-Hui; Kang, Li-Yuan; Li, Zheng

    2014-09-01

    A set of central composite design experiments were designed by using four factors which were ethanol amount, ethanol concentration, refrigeration temperature and refrigeration time. The relation between these factors with the target variables of the retention rate of schizandrol A, the soluble solids content, the removal rate of fructose and the removal rate of glucose were analyzed with Bayesian networks, and ethanol amount and ethanol concentration were found as the critical process parameters. Then a network model was built with 2 inputs and 4 outputs using back propagation artificial neural networks which was optimized by genetic algorithms. The R2 and MSE from the training set were 0.983 8 and 0.001 1. The R2 and MSE from the test set were 0.975 9 and 0.001 8. The results showed that network analysis method could be used for modeling of Schisandrae Chinensis Fructus ethanol precipitation process and identify critical operating parameters. PMID:25522613

  11. 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

  12. 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

  13. 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.

  14. Analytical Model for the Diffusion Process in a In-Situ Combustion Tube

    NASA Astrophysics Data System (ADS)

    Gutierrez, Patricia; Reyes, Adrian

    2015-03-01

    The in-situ combustion process (ISC) is basically an air or oxygen enriched gas injection oil recovery process, inside an extraction well. In contrast to a conventional gas injection process, an ISC process consists in using heat to create a combustion front that raises the fuel temperature, decreasing its viscosity, making extraction easier. The oil is taken toward the productor by means of a vigorous gas thrust as well as a water thrust. To improve and enhance this technique in the field wells, it has been widely perform experimental laboratory tests, in which an in-situ combustion tube is designed to simulate the extraction process. In the present work we propose to solve analytically the problem, with a parabolic partial differential equation associated to the convection-diffusion phenomenon, equation which describes the in-situ combustion process. The whole mathematical problem is established by completing this equation with the correspong boundary and initial conditions, the thickness of the combustion zone, flow velocity, and more parameters. The theoretically obtained results are compared with those reported in literature. We further, fit the parameter of our model to the mentioned data taken from the literature.

  15. Heuristic and analytic processes in reasoning: an event-related potential study of belief bias.

    PubMed

    Banks, Adrian P; Hope, Christopher

    2014-03-01

    Human reasoning involves both heuristic and analytic processes. This study of belief bias in relational reasoning investigated whether the two processes occur serially or in parallel. Participants evaluated the validity of problems in which the conclusions were either logically valid or invalid and either believable or unbelievable. Problems in which the conclusions presented a conflict between the logically valid response and the believable response elicited a more positive P3 than problems in which there was no conflict. This shows that P3 is influenced by the interaction of belief and logic rather than either of these factors on its own. These findings indicate that belief and logic influence reasoning at the same time, supporting models in which belief-based and logical evaluations occur in parallel but not theories in which belief-based heuristic evaluations precede logical analysis.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. BiNA: a visual analytics tool for biological network data.

    PubMed

    Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael

    2014-01-01

    Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA--the Biological Network Analyzer--a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/.

  1. 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. PMID:26214013

  2. 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.

  3. Inferring Transition Rates of Networks from Populations in Continuous-Time Markov Processes.

    PubMed

    Dixit, Purushottam D; Jain, Abhinav; Stock, Gerhard; Dill, Ken A

    2015-11-10

    We are interested inferring rate processes on networks. In particular, given a network's topology, the stationary populations on its nodes, and a few global dynamical observables, can we infer all the transition rates between nodes? We draw inferences using the principle of maximum caliber (maximum path entropy). We have previously derived results for discrete-time Markov processes. Here, we treat continuous-time processes, such as dynamics among metastable states of proteins. The present work leads to a particularly important analytical result: namely, that when the network is constrained only by a mean jump rate, the rate matrix is given by a square-root dependence of the rate, kab ∝ (πb/πa)(1/2), on πa and πb, the stationary-state populations at nodes a and b. This leads to a fast way to estimate all of the microscopic rates in the system. As an illustration, we show that the method accurately predicts the nonequilibrium transition rates in an in silico gene expression network and transition probabilities among the metastable states of a small peptide at equilibrium. We note also that the method makes sensible predictions for so-called extra-thermodynamic relationships, such as those of Bronsted, Hammond, and others. PMID:26574334

  4. 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.

  5. 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.

  6. Three-dimensional analytical infinite order sudden quantum theory for triatomic indirect photodissociation processes

    NASA Astrophysics Data System (ADS)

    Grinberg, Horacio; Freed, Karl F.; Williams, Carl J.

    1997-08-01

    Our previously developed analytical infinite order sudden (IOS) quantum theory of triatomic photodissociation is extended to describe indirect photodissociation processes through a real or virtual intermediate state. The theory uses the IOS approximation for the dynamics in the final dissociative channels and an Airy function approximation for the continuum states. These approximations enable us to evaluate the multi-dimensional non-separable transition amplitudes analytically (as one-dimensional quadratures), despite the different natural coordinates for the initial bound, the intermediate resonant, and the final dissociative states. The fragment internal energy distributions are described as a function of the initial and final quantum states and the photon excitation energy. The theory readily permits the evaluation of rotational distributions for high values of the total angular momentum J in the initial bound molecular state, a feature that would be very difficult with close-coupled methods. In paper II we apply the theory to describe the photofragment yield spectrum of NOCl in the region of the T1(13A″)←S0(11A') transition.

  7. Performance of the analytical solutions for Taylor dispersion process in open channel flow

    NASA Astrophysics Data System (ADS)

    Zeng, L.; Wu, Zi; Fu, Xudong; Wang, Guangqian

    2015-09-01

    The present paper provides a systematical analysis for concentration distribution of Taylor dispersion in laminar open channel flow, seeking fundamental understandings for the physical process of solute transport that generally applies to natural rivers. As a continuation and a direct numerical verification of the previous theoretical work (Wu, Z., Chen, G.Q., 2014. Journal of Hydrology, 519: 1974-1984.), in this paper we attempt to understand that to what extent the obtained analytical solutions are valid for the multi-dimensional concentration distribution, which is vital for the key conclusion of the so-called slow-decaying transient effect. It is shown that as a first estimation, even asymptotically, the longitudinal skewness of the concentration distribution should be incorporated to predict the vertical concentration correctly. Thus the traditional truncation of the concentration expansion is considered to be insufficient for the first estimation. The analytical solution by the two-scale perturbation analysis with modifications up to the second order is shown to be a most economical solution to give a reasonably good prediction.

  8. Nonlinear identification of process dynamics using neural networks

    SciTech Connect

    Parlos, A.G.; Atiya, A.F.; Chong, K.T. . Dept. of Nuclear Engineering); Tsai, W.K. )

    1992-01-01

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

  9. Temporal properties of dynamic processes on complex networks

    NASA Astrophysics Data System (ADS)

    Turalska, Malgorzata A.

    Many social, biological and technological systems can be viewed as complex networks with a large number of interacting components. However despite recent advancements in network theory, a satisfactory description of dynamic processes arising in such cooperative systems is a subject of ongoing research. In this dissertation the emergence of dynamical complexity in networks of interacting stochastic oscillators is investigated. In particular I demonstrate that networks of two and three state stochastic oscillators present a second-order phase transition with respect to the strength of coupling between individual units. I show that at the critical point fluctuations of the global order parameter are characterized by an inverse-power law distribution and I assess their renewal properties. Additionally, I study the effect that different types of perturbation have on dynamical properties of the model. I discuss the relevance of those observations for the transmission of information between complex systems.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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. PMID:23661007

  17. 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.

  18. 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. PMID:26955599

  19. An analytical calculation of neighbourhood order probabilities for high dimensional Poissonian processes and mean field models

    NASA Astrophysics Data System (ADS)

    Sangaletti Terçariol, César Augusto; de Moura Kiipper, Felipe; Souto Martinez, Alexandre

    2007-03-01

    Consider that the coordinates of N points are randomly generated along the edges of a d-dimensional hypercube (random point problem). The probability P(d,N)m,n that an arbitrary point is the mth nearest neighbour to its own nth nearest neighbour (Cox probabilities) plays an important role in spatial statistics. Also, it has been useful in the description of physical processes in disordered media. Here we propose a simpler derivation of Cox probabilities, where we stress the role played by the system dimensionality d. In the limit d → ∞, the distances between pair of points become independent (random link model) and closed analytical forms for the neighbourhood probabilities are obtained both for the thermodynamic limit and finite-size system. Breaking the distance symmetry constraint drives us to the random map model, for which the Cox probabilities are obtained for two cases: whether a point is its own nearest neighbour or not.

  20. 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.

  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.

    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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Normal aging modulates prefrontoparietal networks underlying multiple memory processes

    PubMed Central

    Sambataro, Fabio; Safrin, Martin; Lemaitre, Herve S.; Steele, Sonya U.; Das, Saumitra B.; Callicott, Joseph H; Weinberger, Daniel R.; Mattay, Venkata S.

    2012-01-01

    Functional decline of brain regions underlying memory processing represents a hallmark of cognitive aging. Although a rich literature documents age-related differences in several memory domains, the effect of aging on networks that underlie multiple memory processes has been relatively unexplored. Here we used functional magnetic resonance imaging during working memory and incidental episodic encoding memory to investigate patterns of age-related differences in activity and functional covariance patterns common across multiple memory domains. Relative to younger subjects, older subjects showed increased activation in left dorso-lateral prefrontal cortex along with decreased deactivation in the posterior cingulate. Older subjects showed greater functional covariance during both memory tasks in a set of regions that included a positive prefronto-parietal-occipital networkas well as a negative network that spanned the default mode regions. These findings suggest that the memory process-invariant recruitment of brain regions within prefronto-parietal-occipital network increases with aging.Our results are in line with the dedifferentiation hypothesis of neurocognitive aging, thereby suggesting a decreased specialization of the brain networks supporting different memory networks. PMID:22909094

  7. 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.

  8. Analytic treatment of tipping points for social consensus in large random networks.

    PubMed

    Zhang, W; Lim, C; Szymanski, B K

    2012-12-01

    We introduce a homogeneous pair approximation to the naming game (NG) model by deriving a six-dimensional Open Dynamics Engine (ODE) for the two-word naming game. Our ODE reveals the change in dynamical behavior of the naming game as a function of the average degree {k} of an uncorrelated network. This result is in good agreement with the numerical results. We also analyze the extended NG model that allows for presence of committed nodes and show that there is a shift of the tipping point for social consensus in sparse networks. PMID:23367920

  9. Analytic treatment of tipping points for social consensus in large random networks.

    PubMed

    Zhang, W; Lim, C; Szymanski, B K

    2012-12-01

    We introduce a homogeneous pair approximation to the naming game (NG) model by deriving a six-dimensional Open Dynamics Engine (ODE) for the two-word naming game. Our ODE reveals the change in dynamical behavior of the naming game as a function of the average degree {k} of an uncorrelated network. This result is in good agreement with the numerical results. We also analyze the extended NG model that allows for presence of committed nodes and show that there is a shift of the tipping point for social consensus in sparse networks.

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. 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…

  15. 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.

  16. Analytically Solvable Model of Spreading Dynamics with Non-Poissonian Processes

    NASA Astrophysics Data System (ADS)

    Jo, Hang-Hyun; Perotti, Juan I.; Kaski, Kimmo; Kertész, János

    2014-01-01

    Non-Poissonian bursty processes are ubiquitous in natural and social phenomena, yet little is known about their effects on the large-scale spreading dynamics. In order to characterize these effects, we devise an analytically solvable model of susceptible-infected spreading dynamics in infinite systems for arbitrary inter-event time distributions and for the whole time range. Our model is stationary from the beginning, and the role of the lower bound of inter-event times is explicitly considered. The exact solution shows that for early and intermediate times, the burstiness accelerates the spreading as compared to a Poisson-like process with the same mean and same lower bound of inter-event times. Such behavior is opposite for late-time dynamics in finite systems, where the power-law distribution of inter-event times results in a slower and algebraic convergence to a fully infected state in contrast to the exponential decay of the Poisson-like process. We also provide an intuitive argument for the exponent characterizing algebraic convergence.

  17. Analytical Design of Robust Multi-loop PI Controller for Multi-time Delay Processes

    NASA Astrophysics Data System (ADS)

    Vu, Truong Nguyen Luan; Lee, Moonyong

    In this chapter, a robust design of multi-loop PI controller for multivariable processes in the presence of the multiplicative input uncertainty is presented. The method consists of two major steps: firstly, the analytical tuning rules of multi-loop PI controller are derived based on the direct synthesis and IMC-PID approach. Then, in the second step, the robust stability analysis is utilized for enhancing the robustness of proposed PI control systems. The most important feature of the proposed method is that the tradeoff between the robust stability and performance can be established by adjusting only one design parameter (i.e., the closed-loop time constant) via structured singular value synthesis. To verify the superiority of the proposed method, simulation studies have been conducted on a variety of the nominal processes and their plant-model mismatch cases. The results demonstrate that the proposed design method guarantees the robustness under the perturbation on each of the process parameters simultaneously.

  18. [Changes in positive mood states by analytic and creative information processing].

    PubMed

    Otto, J H; Schmitz, B B

    1993-01-01

    Reviews concerning research on the influence of mood on behavior show (a) that mainly the influence of mood on behavior was investigated and (b) that achievements in memory and cognitive tasks were of central concern (Fiedler, 1988; Isen, 1987). Social behavior was analyzed as a function of these factors. Recent reviews restrict themselves to positive feeling states. Summarizing, Fiedler (1988) describes the information processing style in positive feeling states as "loosening" to capture its qualitative aspects. This study investigates the opposite direction of influence, i.e. the effect of cognitive style on positive feeling states. This study restricts itself to positive feeling states. The compatibility thesis which postulates a necessary interaction of feeling state and information processing style is tested. Equivalent states and productions have to go together to generate the mood effects. In a 2 x 2 x 5 mixed design 70 female students (non-psychologists) served as subjects. Using a 20-minute mood induction procedure (autobiographical recollection methodology) a positive or neutral feeling state was elicited in half of the participants. During the next 10 minutes half of each group worked either on a verbal creativity test (Schoppe, 1975) or on an intelligence test (Amthauer, 1973) to establish an creative or analytic style of information processing. Repeated sampling of a measurement repetition factor served as baseline assessments, manipulation checks, and measurements of the feeling states during the task completion of the creativity or intelligence test. The feeling states were assessed by means of a short version (BSK-1982) of the "Eigenschaftswörterliste" (Janke & Debus, 1978). The results confirm the compatibility thesis. Only the group in which a positive feeling state and a creative processing style interact reported a positive mood throughout the task completion. Unexpectedly, a slight deterioration of mood was found in the group with a neutral

  19. 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

  20. 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…

  1. Multi-loop networked process control: a synchronized approach.

    PubMed

    Das, M; Ghosh, R; Goswami, B; Chandra, A K; Balasubramanian, R; Luksch, P; Gupta, A

    2009-01-01

    Modern day process control uses digital controllers which are based on the principle of distributed rather than centralized control. Distributing controllers, sensors and actuators across a plant entails considerable wiring which can be reduced substantially by integrating the components of a control loop over a network. The other advantages include greater flexibility and higher reliability with lower hardware redundancy. The controllers and sensors are on a network and can take over the function of a failed component automatically, without the need of manual reconfiguration, thus eliminating the need of having a redundant component for each and every component. Though elaborate techniques have been developed for Single Input Single Output (SISO) systems, the major challenge lies in extending these ideas to control a practical process plant where de-centralized control is actually achieved through control of individual SISO control loops derived through de-coupling of the original system. Multiple loops increase network load and hence the sampling times associated with the control loops and makes synchronization difficult. This paper presents a methodology by which network based process control can be applied to practical process plants, with a simple direct synchronization mechanism. PMID:19028386

  2. 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…

  3. An Image Database on a Parallel Processing Network.

    ERIC Educational Resources Information Center

    Philip, G.; And Others

    1991-01-01

    Describes the design and development of an image database for photographs in the Ulster Museum (Northern Ireland) that used parallelism from a transputer network. Topics addressed include image processing techniques; documentation needed for the photographs, including indexing, classifying, and cataloging; problems; hardware and software aspects;…

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

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

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

  5. 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.

  6. 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.

  7. Multimedia information processing in the SWAN mobile networked computing system

    NASA Astrophysics Data System (ADS)

    Agrawal, Prathima; Hyden, Eoin; Krzyzanowsji, Paul; Srivastava, Mani B.; Trotter, John

    1996-03-01

    Anytime anywhere wireless access to databases, such as medical and inventory records, can simplify workflow management in a business, and reduce or even eliminate the cost of moving paper documents. Moreover, continual progress in wireless access technology promises to provide per-user bandwidths of the order of a few Mbps, at least in indoor environments. When combined with the emerging high-speed integrated service wired networks, it enables ubiquitous and tetherless access to and processing of multimedia information by mobile users. To leverage on this synergy an indoor wireless network based on room-sized cells and multimedia mobile end-points is being developed at AT&T Bell Laboratories. This research network, called SWAN (Seamless Wireless ATM Networking), allows users carrying multimedia end-points such as PDAs, laptops, and portable multimedia terminals, to seamlessly roam while accessing multimedia data streams from the wired backbone network. A distinguishing feature of the SWAN network is its use of end-to-end ATM connectivity as opposed to the connectionless mobile-IP connectivity used by present day wireless data LANs. This choice allows the wireless resource in a cell to be intelligently allocated amongst various ATM virtual circuits according to their quality of service requirements. But an efficient implementation of ATM in a wireless environment requires a proper mobile network architecture. In particular, the wireless link and medium-access layers need to be cognizant of the ATM traffic, while the ATM layers need to be cognizant of the mobility enabled by the wireless layers. This paper presents an overview of SWAN's network architecture, briefly discusses the issues in making ATM mobile and wireless, and describes initial multimedia applications for SWAN.

  8. Investigation of potential analytical methods for redox control of the vitrification process. [Moessbauer

    SciTech Connect

    Goldman, D.S.

    1985-11-01

    An investigation was conducted to evaluate several analytical techniques to measure ferrous/ferric ratios in simulated and radioactive nuclear waste glasses for eventual redox control of the vitrification process. Redox control will minimize the melt foaming that occurs under highly oxidizing conditions and the metal precipitation that occurs under highly reducing conditions. The analytical method selected must have a rapid response for production problems with minimal complexity and analyst involvement. The wet-chemistry, Moessbauer spectroscopy, glass color analysis, and ion chromatography techniques were explored, with particular emphasis being placed on the Moessbauer technique. In general, all of these methods can be used for nonradioactive samples. The Moessbauer method can readily analyze glasses containing uranium and thorium. A shielded container was designed and built to analyze fully radioactive glasses with the Moessbauer spectrometer in a hot cell environment. However, analyses conducted with radioactive waste glasses containing /sup 90/Sr and /sup 137/Cs were unsuccessful, presumably due to background radiation problems caused by the samples. The color of glass powder can be used to analyze the ferrous/ferric ratio for low chromium glasses, but this method may not be as precise as the others. Ion chromatography was only tested on nonradioactive glasses, but this technique appears to have the required precision due to its analysis of both Fe/sup +2/ and Fe/sup +3/ and its anticipated adaptability for radioactivity samples. This development would be similar to procedures already in use for shielded inductively coupled plasma emission (ICP) spectrometry. Development of the ion chromatography method is therefore recommended; conventional wet-chemistry is recommended as a backup procedure.

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

    PubMed

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

    2015-04-01

    An analytical method for (14)C in environmental water based on a wet-oxidation process was developed. The method can be used to determine the activity concentrations of organic and inorganic (14)C in environmental water, or total (14)C, including in drinking water, surface water, rainwater and seawater. The wet-oxidation of the organic component allows the conversion of organic carbon to an inorganic form, and the extraction of the inorganic (14)C can be achieved by acidification and nitrogen purging. Environmental water with a volume of 20 L can be used for the wet-oxidation and extraction, and a detection limit of about 0.02 Bq/g(C) can be achieved for water with carbon content above 15 mg(C)/L, obviously lower than the natural level of (14)C in the environment. The collected carbon is sufficient for measurement with a low level liquid scintillation counter (LSC) for typical samples. Extraction or recovery experiments for inorganic carbon and organic carbon from typical materials, including analytical reagents of organic benzoquinone, sucrose, glutamic acid, nicotinic acid, humic acid, ethane diol, et cetera., were conducted with excellent results based on measurement on a total organic carbon analyzer and LSC. The recovery rate for inorganic carbon ranged tween 98.7%-99.0% with a mean of 98.9(± 0.1)%, for organic carbon recovery ranged between 93.8% and 100.0% with a mean of 97.1(± 2.6)%. Verification and an uncertainty budget of the method are also presented for a representative environmental water. The method is appropriate for (14)C analysis in environmental water, and can be applied also to the analysis of liquid effluent from nuclear facilities. PMID:25590997

  10. 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.

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

    PubMed

    Punithavathani, D Shalini; Radley, Sheryl

    2014-01-01

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

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

    PubMed Central

    Punithavathani, D. Shalini; Radley, Sheryl

    2014-01-01

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

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

    PubMed

    Punithavathani, D Shalini; Radley, Sheryl

    2014-01-01

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

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

    PubMed

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

    2014-08-01

    HIV stigma is rooted in culture and, therefore, it is essential to investigate it within the context of culture. The objective of this study was to examine the interrelationships among individualism-collectivism, HIV stigma, and social network support. A social network study was conducted among 118 people living with HIVAIDS in China, who were infected by commercial plasma donation, a nonstigmatized behavior. The Individualism-Collectivism Interpersonal Assessment Inventory (ICIAI) was used to measure cultural norms and values in the context of three social groups, family members, friends, and neighbors. Path analyses revealed (1) a higher level of family ICIAI was significantly associated with a higher level of HIV self-stigma (β=0.32); (2) a higher level of friend ICIAI was associated with a lower level of self-stigma (β=-035); (3) neighbor ICIAI was associated with public stigma (β=-0.61); (4) self-stigman was associated with social support from neighbors (β=-0.27); and (5) public stigma was associated with social support from neighbors (β=-0.24). This study documents that HIV stigma may mediate the relationship between collectivist culture and social network support, providing an empirical basis for interventions to include aspects of culture into HIV intervention strategies. PMID:24853730

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

    PubMed

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

    2014-08-01

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

  16. 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

  17. 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

  18. Congestion estimation technique in the optical network unit registration process.

    PubMed

    Kim, Geunyong; Yoo, Hark; Lee, Dongsoo; Kim, Youngsun; Lim, Hyuk

    2016-07-01

    We present a congestion estimation technique (CET) to estimate the optical network unit (ONU) registration success ratio for the ONU registration process in passive optical networks. An optical line terminal (OLT) estimates the number of collided ONUs via the proposed scheme during the serial number state. The OLT can obtain congestion level among ONUs to be registered such that this information may be exploited to change the size of a quiet window to decrease the collision probability. We verified the efficiency of the proposed method through simulation and experimental results.

  19. Applying Trusted Network Technology To Process Control Systems

    NASA Astrophysics Data System (ADS)

    Okhravi, Hamed; Nicol, David

    Interconnections between process control networks and enterprise networks expose instrumentation and control systems and the critical infrastructure components they operate to a variety of cyber attacks. Several architectural standards and security best practices have been proposed for industrial control systems. However, they are based on older architectures and do not leverage the latest hardware and software technologies. This paper describes new technologies that can be applied to the design of next generation security architectures for industrial control systems. The technologies are discussed along with their security benefits and design trade-offs.

  20. Reaction-diffusion processes on interconnected scale-free networks

    NASA Astrophysics Data System (ADS)

    Garas, Antonios

    2015-08-01

    We study the two-particle annihilation reaction A +B →∅ on interconnected scale-free networks, using different interconnecting strategies. We explore how the mixing of particles and the process evolution are influenced by the number of interconnecting links, by their functional properties, and by the interconnectivity strategies in use. We show that the reaction rates on this system are faster than what was observed in other topologies, due to the better particle mixing that suppresses the segregation effect, in line with previous studies performed on single scale-free networks.

  1. 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.

  2. Process analytical technology (PAT): quantification approaches in terahertz spectroscopy for pharmaceutical application.

    PubMed

    Wu, Huiquan; Heilweil, Edwin J; Hussain, Ajaz S; Khan, Mansoor A

    2008-02-01

    Terahertz (THz) spectroscopy and chemometric analysis of resultant absorption spectra in the 30-500 cm(-1) range has been applied to perform quantitative determination of both active ingredient and excipient concentrations of tablets. Tests were performed on a series of tablets composed of various concentrations and processes of theophylline formulated with lactose, magnesium stearate, starch or Avicel, and as a function of tablet hardness. Transmission spectra of polyethylene pellets derived from each of the samples were analyzed using three approaches. Spectral superposition method was used as an indirect measure to examine whether and when the interaction among various pharmaceutical components and the tableting history could be considered insignificant for quantification purpose. Spectral characteristic peak method was able to correlate peak maxima with correction for tablets having the same hardness. Multivariate analysis (PCR and PLS 1) was capable of correlating THz spectra with tablet concentrations. The predicted concentrations of independent samples using multivariate models agreed well with nominal concentrations. The best correlations were obtained using multivariate analysis. With these studies, the advantage of using multivariate approach was demonstrated for process analytical technology (PAT) application. Further, the feasibility of integrating THz spectroscopy and chemometrics for the purpose of quantifying pharmaceutical tablet concentrations was demonstrated. PMID:17722101

  3. 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.

  4. A coordinate-based meta-analytic model of trauma processing in posttraumatic stress disorder.

    PubMed

    Ramage, Amy E; Laird, Angela R; Eickhoff, Simon B; Acheson, Ashley; Peterson, Alan L; Williamson, Douglas E; Telch, Michael J; Fox, Peter T

    2013-12-01

    Posttraumatic stress disorder (PTSD) has a well-defined set of symptoms that can be elicited during traumatic imagery tasks. For this reason, trauma imagery tasks are often employed in functional neuroimaging studies. Here, coordinate-based meta-analysis (CBM) was used to pool eight studies applying traumatic imagery tasks to identify sites of task-induced activation in 170 PTSD patients and 104 healthy controls. In this way, right anterior cingulate (ACC), right posterior cingulate (PCC), and left precuneus (Pcun) were identified as regions uniquely active in PTSD patients relative to healthy controls. To further characterize these regions, their normal interactions, and their typical functional roles, meta-analytic connectivity modeling (MACM) with behavioral filtering was applied. MACM indicated that the PCC and Pcun regions were frequently co-active and associated with processing of cognitive information, particularly in explicit memory tasks. Emotional processing was particularly associated with co-activity of the ACC and PCC, as mediated by the thalamus. By narrowing the regions of interest to those commonly active across multiple studies (using CBM) and developing a priori hypotheses about directed probabilistic dependencies amongst these regions, this proposed model-when applied in the context of graphical and causal modeling-should improve model fit and thereby increase statistical power for detecting differences between subject groups and between treatments in neuroimaging studies of PTSD.

  5. 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.

  6. Analytic hierarchy process helps select site for limestone quarry expansion in Barbados.

    PubMed

    Dey, Prasanta Kumar; Ramcharan, Eugene K

    2008-09-01

    Site selection is a key activity for quarry expansion to support cement production, and is governed by factors such as resource availability, logistics, costs, and socio-economic-environmental factors. Adequate consideration of all the factors facilitates both industrial productivity and sustainable economic growth. This study illustrates the site selection process that was undertaken for the expansion of limestone quarry operations to support cement production in Barbados. First, alternate sites with adequate resources to support a 25-year development horizon were identified. Second, technical and socio-economic-environmental factors were then identified. Third, a database was developed for each site with respect to each factor. Fourth, a hierarchical model in analytic hierarchy process (AHP) framework was then developed. Fifth, the relative ranking of the alternate sites was then derived through pair wise comparison in all the levels and through subsequent synthesizing of the results across the hierarchy through computer software (Expert Choice). The study reveals that an integrated framework using the AHP can help select a site for the quarry expansion project in Barbados.

  7. 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.

  8. 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.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Ferreira, Silvio C.; Martins, Marcelo L.

    2007-09-01

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

  12. Neural network modeling of the laser material-removal process

    NASA Astrophysics Data System (ADS)

    Yousef, Basem F.; Knopf, George K.; Bordatchev, Evgueni V.; Nikumb, Suwas K.

    2001-12-01

    Industrial lasers are used extensively in modern manufacturing for a variety of applications because these tools provide a highly focused energy source that can be easily transmitted and manipulated for micro-machining. The quantity of material removed and the roughness of the finished surface are a function of the crater geometry formed by a laser pulse with specific energy (power). Laser micro-machining is, however, a complex nonlinear process with numerous stochastic parameters related to the laser apparatus and the material specimen. Consequently, the operator must manually set the process control parameters by trial and error. This paper describes how an artificial neural network can be used to create a nonlinear model of the laser material-removal process in order to automate micro-machining tasks. The multi-layered neural network predicts the pulse energy needed to create a crater of specific depth and average diameter. Laser pulses of different energy levels are impinged on the surface of the test material in order to investigate the effect of pulse energy on the resulting crater geometry and volume of material removed. Experimentally acquired data from several sample materials are used to train and test the network's performance. The key system inputs for the modeler are mean depth of crater and mean diameter of crater, and the system outputs are pulse energy, variance of depth and variance of diameter. The preliminary study using the experimentally acquired data demonstrates that the proposed network can simulate the behavior of the physical process to a high degree of accuracy. Future work involves investigating the effect of different input parameters on the output behavior of the process in hopes that the process performance, and the final product quality, can be improved.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  14. Qualia Could Arise from Information Processing in Local Cortical Networks

    PubMed Central

    Orpwood, Roger

    2013-01-01

    Re-entrant feedback, either within sensory cortex or arising from prefrontal areas, has been strongly linked to the emergence of consciousness, both in theoretical and experimental work. This idea, together with evidence for local micro-consciousness, suggests the generation of qualia could in some way result from local network activity under re-entrant activation. This paper explores the possibility by examining the processing of information by local cortical networks. It highlights the difference between the information structure (how the information is physically embodied), and the information message (what the information is about). It focuses on the network’s ability to recognize information structures amongst its inputs under conditions of extensive local feedback, and to then assign information messages to those structures. It is shown that if the re-entrant feedback enables the network to achieve an attractor state, then the message assigned in any given pass of information through the network is a representation of the message assigned in the previous pass-through of information. Based on this ability the paper argues that as information is repeatedly cycled through the network, the information message that is assigned evolves from a recognition of what the input structure is, to what it is like, to how it appears, to how it seems. It could enable individual networks to be the site of qualia generation. The paper goes on to show networks in cortical layers 2/3 and 5a have the connectivity required for the behavior proposed, and reviews some evidence for a link between such local cortical cyclic activity and conscious percepts. It concludes with some predictions based on the theory discussed. PMID:23504586

  15. Optimising chemical named entity recognition with pre-processing analytics, knowledge-rich features and heuristics

    PubMed Central

    2015-01-01

    Background The development of robust methods for chemical named entity recognition, a challenging natural language processing task, was previously hindered by the lack of publicly available, large-scale, gold standard corpora. The recent public release of a large chemical entity-annotated corpus as a resource for the CHEMDNER track of the Fourth BioCreative Challenge Evaluation (BioCreative IV) workshop greatly alleviated this problem and allowed us to develop a conditional random fields-based chemical entity recogniser. In order to optimise its performance, we introduced customisations in various aspects of our solution. These include the selection of specialised pre-processing analytics, the incorporation of chemistry knowledge-rich features in the training and application of the statistical model, and the addition of post-processing rules. Results Our evaluation shows that optimal performance is obtained when our customisations are integrated into the chemical entity recogniser. When its performance is compared with that of state-of-the-art methods, under comparable experimental settings, our solution achieves competitive advantage. We also show that our recogniser that uses a model trained on the CHEMDNER corpus is suitable for recognising names in a wide range of corpora, consistently outperforming two popular chemical NER tools. Conclusion The contributions resulting from this work are two-fold. Firstly, we present the details of a chemical entity recognition methodology that has demonstrated performance at a competitive, if not superior, level as that of state-of-the-art methods. Secondly, the developed suite of solutions has been made publicly available as a configurable workflow in the interoperable text mining workbench Argo. This allows interested users to conveniently apply and evaluate our solutions in the context of other chemical text mining tasks. PMID:25810777

  16. Network Detection in Raster Data Using Marked Point Processes

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  17. Epidemic processes over adaptive state-dependent networks

    NASA Astrophysics Data System (ADS)

    Ogura, Masaki; Preciado, Victor M.

    2016-06-01

    In this paper we study the dynamics of epidemic processes taking place in adaptive networks of arbitrary topology. We focus our study on the adaptive susceptible-infected-susceptible (ASIS) model, where healthy individuals are allowed to temporarily cut edges connecting them to infected nodes in order to prevent the spread of the infection. In this paper we derive a closed-form expression for a lower bound on the epidemic threshold of the ASIS model in arbitrary networks with heterogeneous node and edge dynamics. For networks with homogeneous node and edge dynamics, we show that the resulting lower bound is proportional to the epidemic threshold of the standard SIS model over static networks, with a proportionality constant that depends on the adaptation rates. Furthermore, based on our results, we propose an efficient algorithm to optimally tune the adaptation rates in order to eradicate epidemic outbreaks in arbitrary networks. We confirm the tightness of the proposed lower bounds with several numerical simulations and compare our optimal adaptation rates with popular centrality measures.

  18. Data processing at the SSC with structured neural networks

    SciTech Connect

    Lackner, K.S.; Sandberg, V.D.; Sharp, D.H.

    1990-01-01

    SSC detectors will place extreme demands on data processing systems. One must reduce the data flux to manageable proportions at the earliest possible stage. This observations has led us to emphasize low-level data processing and track reconstruction. We report progress in three areas: A network compiler has been designed which generates programmable and trainable tree-structured nets; algorithms for track reconstruction have been designed and implemented in such nets; exploratory studies have been made on the use of such nets to carry out low-level processing on hardware components of a central detector. 6 refs., 1 fig.

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

    NASA Astrophysics Data System (ADS)

    Meng, Qing-Kuan; Zhu, Jian-Yang

    2009-08-01

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

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

    PubMed

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

    2013-03-01

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

  1. Reaction-diffusion processes and metapopulation models in heterogeneous networks

    NASA Astrophysics Data System (ADS)

    Colizza, Vittoria; Pastor-Satorras, Romualdo; Vespignani, Alessandro

    2007-04-01

    Dynamical reaction-diffusion processes and metapopulation models are standard modelling approaches for a wide array of phenomena in which local quantities-such as density, potentials and particles-diffuse and interact according to the physical laws. Here, we study the behaviour of the basic reaction-diffusion process (given by the reaction steps B-->A and B+A-->2B) defined on networks with heterogeneous topology and no limit on the nodes' occupation number. We investigate the effect of network topology on the basic properties of the system's phase diagram and find that the network heterogeneity sustains the reaction activity even in the limit of a vanishing density of particles, eventually suppressing the critical point in density-driven phase transitions, whereas phase transition and critical points independent of the particle density are not altered by topological fluctuations. This work lays out a theoretical and computational microscopic framework for the study of a wide range of realistic metapopulation and agent-based models that include the complex features of real-world networks.

  2. Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

    NASA Astrophysics Data System (ADS)

    Kirst, Christoph

    It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

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

    PubMed

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

    2014-09-01

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

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

    PubMed

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

    2015-03-25

    Reference standard is critical for ensuring reliable and accurate method performance. One important issue is how to select the ideal one from the alternatives. Unlike the optimization of parameters, the criteria of the reference standard are always immeasurable. The aim of this paper is to recommend a quantitative approach for the selection of reference standard during method development based on the analytical hierarchy process (AHP) as a decision-making tool. Six alternative single reference standards were assessed in quantitative analysis of six phenolic acids from Salvia Miltiorrhiza and its preparations by using ultra-performance liquid chromatography. The AHP model simultaneously considered six criteria related to reference standard characteristics and method performance, containing feasibility to obtain, abundance in samples, chemical stability, accuracy, precision and robustness. The priority of each alternative was calculated using standard AHP analysis method. The results showed that protocatechuic aldehyde is the ideal reference standard, and rosmarinic acid is about 79.8% ability as the second choice. The determination results successfully verified the evaluation ability of this model. The AHP allowed us comprehensive considering the benefits and risks of the alternatives. It was an effective and practical tool for optimization of reference standards during method development. PMID:25636165

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

    SciTech Connect

    Ho, Chao Chung

    2011-07-15

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

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

    PubMed Central

    Maranate, Thaya; Pongpullponsak, Adisak; Ruttanaumpawan, Pimon

    2015-01-01

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

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

    PubMed

    Liao, Wen-Hwa; Qiu, Wan-Li

    2016-01-01

    Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture. PMID:27441149

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

    PubMed

    Ho, Chao Chung

    2011-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Wasielewska, K.; Ganzha, M.

    2012-10-01

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

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

    PubMed

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

    2015-03-25

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

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

    PubMed

    Liao, Wen-Hwa; Qiu, Wan-Li

    2016-01-01

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

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

    PubMed

    Wang, Dapeng; Zhang, Lan

    2015-01-01

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

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

    PubMed Central

    Wang, Dapeng; Zhang, Lan

    2015-01-01

    With explosive development in Chinese economy and science and technology, people’s pursuit of health becomes more and more intense, therefore Chinese resident sports fitness activities have been rapidly developed. However, different fitness events popularity degrees and effects on body energy consumption are different, so bases on this, the paper researches on fitness behaviors and gets Chinese residents sports fitness behaviors exercise guide, which provides guidance for propelling to national fitness plan’s implementation and improving Chinese resident fitness scientization. The paper starts from the perspective of energy consumption, it mainly adopts experience method, determines Chinese resident favorite sports fitness event energy consumption through observing all kinds of fitness behaviors energy consumption, and applies fuzzy analytic hierarchy process to make evaluation on bicycle riding, shadowboxing practicing, swimming, rope skipping, jogging, running, aerobics these seven fitness events. By calculating fuzzy rate model’s membership and comparing their sizes, it gets fitness behaviors that are more helpful for resident health, more effective and popular. Finally, it gets conclusions that swimming is a best exercise mode and its membership is the highest. Besides, the memberships of running, rope skipping and shadowboxing practicing are also relative higher. It should go in for bodybuilding by synthesizing above several kinds of fitness events according to different physical conditions; different living conditions so that can better achieve the purpose of fitness exercises. PMID:26981163

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

    PubMed

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

    2003-12-01

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

  17. Estimation of the soil strength parameters in Tertiary volcanic regolith (NE Turkey) using analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Ersoy, Hakan; Karsli, Melek Betül; Çellek, Seda; Kul, Bilgehan; Baykan, İdris; Parsons, Robert L.

    2013-12-01

    Costly and time consuming testing techniques and the difficulties in providing undisturbed samples for these tests have led researchers to estimate strength parameters of soils with simple index tests. However, the paper focuses on estimation of strength parameters of soils as a function of the index properties. Analytical hierarchy process and multiple regression analysis based methodology were performed on datasets obtained from soil tests on 41 samples in Tertiary volcanic regolith. While the hierarchy model focused on determining the most important index properties affecting on strength parameters, regression analysis established meaningful relationships between strength parameters and index properties. The negative polynomial correlations between the friction angle and plasticity properties, and the positive exponential relations between the cohesion and plasticity properties were determined. These relations are characterized by a regression coefficient of 0.80. However, Terzaghi bearing capacity formulas were used to test the model. It is important to see whether there is any statistically significant relation between the calculated and the observed bearing capacity values for model testing. Based on the model, the positive linear correlation characterized by the regression coefficient of 0.86 were determined between bearing capacity values obtained by direct and indirect methods.

  18. Combined surface analytical methods to characterize degradative processes in anti-stiction films in MEMS devices.

    SciTech Connect

    Tallant, David Robert; Zavadil, Kevin Robert; Ohlhausen, James Anthony; Hankins, Matthew Granholm; Kent, Michael Stuart

    2005-03-01

    The performance and reliability of microelectromechanical (MEMS) devices can be highly dependent on the control of the surface energetics in these structures. Examples of this sensitivity include the use of surface modifying chemistries to control stiction, to minimize friction and wear, and to preserve favorable electrical characteristics in surface micromachined structures. Silane modification of surfaces is one classic approach to controlling stiction in Si-based devices. The time-dependent efficacy of this modifying treatment has traditionally been evaluated by studying the impact of accelerated aging on device performance and conducting subsequent failure analysis. Our interest has been in identifying aging related chemical signatures that represent the early stages of processes like silane displacement or chemical modification that eventually lead to device performance changes. We employ a series of classic surface characterization techniques along with multivariate statistical methods to study subtle changes in the silanized silicon surface and relate these to degradation mechanisms. Examples include the use of spatially resolved time-of-flight secondary ion mass spectrometric, photoelectron spectroscopic, photoluminescence imaging, and scanning probe microscopic techniques to explore the penetration of water through a silane monolayer, the incorporation of contaminant species into a silane monolayer, and local displacement of silane molecules from the Si surface. We have applied this analytical methodology at the Si coupon level up to MEMS devices. This approach can be generalized to other chemical systems to address issues of new materials integration into micro- and nano-scale systems.

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

    PubMed

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

    2003-12-01

    The composition of drilling muds is based on a mixture of clays and additives in a base fluid. There are three generic categories of base fluid--water, oil, and synthetic. Water-based fluids (WBFs) are relatively environmentally benign, but drilling performance is better with oil-based fluids (OBFs). The oil and gas industry developed synthetic-based fluids (SBFs), such as vegetable esters, olefins, ethers, and others, which provide drilling performance comparable to OBFs, but with lower environmental and occupational health effects. The primary objective of this paper is to present a methodology to guide decision-making in the selection and evaluation of three generic types of drilling fluids using a risk-based analytic hierarchy process (AHP). In this paper a comparison of drilling fluids is made considering various activities involved in the life cycle of drilling fluids. This paper evaluates OBFs, WBFs, and SBFs based on four major impacts--operations, resources, economics, and liabilities. Four major activities--drilling, discharging offshore, loading and transporting, and disposing onshore--cause the operational impacts. Each activity involves risks related to occupational injuries (safety), general public health, environmental impact, and energy use. A multicriteria analysis strategy was used for the selection and evaluation of drilling fluids using a risk-based AHP. A four-level hierarchical structure is developed to determine the final relative scores, and the SBFs are found to be the best option. PMID:15160901

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

    PubMed

    Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan

    2013-03-01

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

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

    PubMed

    Velmurugan, R; Selvamuthukumar, S; Manavalan, R

    2011-11-01

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

  2. Cultural congruence with psychotherapy efficacy: A network meta-analytic examination in China.

    PubMed

    Xu, Hui; Tracey, Terence J G

    2016-04-01

    We used network meta-analysis to examine the relative efficacy of 3 treatment modalities in China (i.e., cognitive-psychoeducational therapy, humanistic-experiential therapy, and indigenous therapy) on the basis of a comprehensive review of randomized control trials (n = 235). The cultural congruence hypothesis derived from the contextual model argues that psychotherapy efficacy varies by the extent to which therapy modalities match the cultural context in its description of pathology and healing modalities. Given the experiential-subjective emphasis of Chinese culture, we proposed indigenous therapy and humanistic-experiential therapy being more effective than cognitive-psychoeducational therapy. Results based on indirect and direct comparisons supported the hypothesized differences in effectiveness. Treatments that more closely matched Chinese understandings of pathology and change experience were more effective. The practical and theoretical implications of the present study were discussed along with limitations. PMID:26914062

  3. Estimating complicated baselines in analytical signals using the iterative training of Bayesian regularized artificial neural networks.

    PubMed

    Mani-Varnosfaderani, Ahmad; Kanginejad, Atefeh; Gilany, Kambiz; Valadkhani, Abolfazl

    2016-10-12

    The present work deals with the development of a new baseline correction method based on the comparative learning capabilities of artificial neural networks. The developed method uses the Bayes probability theorem for prevention of the occurrence of the over-fitting and finding a generalized baseline. The developed method has been applied on simulated and real metabolomic gas-chromatography (GC) and Raman data sets. The results revealed that the proposed method can be used to handle different types of baselines with cave, convex, curvelinear, triangular and sinusoidal patterns. For further evaluation of the performances of this method, it has been compared with benchmarking baseline correction methods such as corner-cutting (CC), morphological weighted penalized least squares (MPLS), adaptive iteratively-reweighted penalized least squares (airPLS) and iterative polynomial fitting (iPF). In order to compare the methods, the projected difference resolution (PDR) criterion has been calculated for the data before and after the baseline correction procedure. The calculated values of PDR after the baseline correction using iBRANN, airPLS, MPLS, iPF and CC algorithms for the GC metabolomic data were 4.18, 3.64, 3.88, 1.88 and 3.08, respectively. The obtained results in this work demonstrated that the developed iterative Bayesian regularized neural network (iBRANN) method in this work thoroughly detects the baselines and is superior over the CC, MPLS, airPLS and iPF techniques. A graphical user interface has been developed for the suggested algorithm and can be used for easy implementation of the iBRANN algorithm for the correction of different chromatography, NMR and Raman data sets. PMID:27662759

  4. Estimating complicated baselines in analytical signals using the iterative training of Bayesian regularized artificial neural networks.

    PubMed

    Mani-Varnosfaderani, Ahmad; Kanginejad, Atefeh; Gilany, Kambiz; Valadkhani, Abolfazl

    2016-10-12

    The present work deals with the development of a new baseline correction method based on the comparative learning capabilities of artificial neural networks. The developed method uses the Bayes probability theorem for prevention of the occurrence of the over-fitting and finding a generalized baseline. The developed method has been applied on simulated and real metabolomic gas-chromatography (GC) and Raman data sets. The results revealed that the proposed method can be used to handle different types of baselines with cave, convex, curvelinear, triangular and sinusoidal patterns. For further evaluation of the performances of this method, it has been compared with benchmarking baseline correction methods such as corner-cutting (CC), morphological weighted penalized least squares (MPLS), adaptive iteratively-reweighted penalized least squares (airPLS) and iterative polynomial fitting (iPF). In order to compare the methods, the projected difference resolution (PDR) criterion has been calculated for the data before and after the baseline correction procedure. The calculated values of PDR after the baseline correction using iBRANN, airPLS, MPLS, iPF and CC algorithms for the GC metabolomic data were 4.18, 3.64, 3.88, 1.88 and 3.08, respectively. The obtained results in this work demonstrated that the developed iterative Bayesian regularized neural network (iBRANN) method in this work thoroughly detects the baselines and is superior over the CC, MPLS, airPLS and iPF techniques. A graphical user interface has been developed for the suggested algorithm and can be used for easy implementation of the iBRANN algorithm for the correction of different chromatography, NMR and Raman data sets.

  5. Diffusion Processes on Power-Law Small-World Networks

    NASA Astrophysics Data System (ADS)

    Kozma, Balazs; Hastings, Matthew B.; Korniss, G.

    2005-03-01

    We consider diffusion driven processes on power-law small-world networks: a random walk process related to folded polymers and surface growth related to synchronization problems. The random links introduced in small-world networks often lead to mean-field coupling (as if the random links were annealed) but in some systems mean-field predictions break down, like diffusion in one dimension. This break-down can be understood treating the random links perturbatively where the mean field prediction appears as the lowest order term of a naive perturbation expansion. Our results were obtained using self-consistent perturbation theory ootnotetextB. Kozma, M. B. Hastings, and G. Korniss, Phys. Rev. Lett. 92, 108701 (2004). and can also be understood in terms of a scaling theory. We find a rich phase diagram, with different transient and recurrent phases, including a critical line with continuously varying exponents.

  6. Process for forming synapses in neural networks and resistor therefor

    DOEpatents

    Fu, Chi Y.

    1996-01-01

    Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

  7. Process for forming synapses in neural networks and resistor therefor

    DOEpatents

    Fu, C.Y.

    1996-07-23

    Customizable neural network in which one or more resistors form each synapse is disclosed. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength. 5 figs.

  8. Automatic Synthesis and Deployment of Intensional Kahn Process Networks

    NASA Astrophysics Data System (ADS)

    Peralta, Manuel; Mukhopadhyay, Supratik; Bharadwaj, Ramesh

    In this paper we introduce and study, theoretically, a clean slate "formal" foundational approach for developing and deploying high-assurance distributed embedded systems deployed in mission-critical applications. We propose a simple formal distributed asynchronous framework extending Kahn Process Networks with intensional specification. More precisely, we present a model-driven approach based on a platform-independent language and an intensional specification logic that allows us to synthesize distributed agents that can handle interactions with external resources asynchronously, ensure enforcement of information flow and security policies, and have the ability to deal with failures of resources. Our approach allows rapid development and automated deployment of formally verified embedded networked systems that provide guarantees that clients' requirements will be met and QoS guarantees will be respected. Moreover, it allows modeling (and programming) reliable distributed systems for multi-core hosts. Such a capability makes our framework suitable for next generation grid computing systems where multi-core individual hosts need to be utilized for improving scalability.Given an intensional logical specification of a distributed embedded system, that includes Quality of Service (QoS) requirements, a set of software resources and devices available in a network, and their formal interface specifications, a deductive system can automatically generate distributed extended Kahn processes and their deployment information in such a way that the application requirements - including QoS requirements - are guaranteed to be met. The generated processes use the inputs of the sensors/meters/probes and the management policies of the customer to generate real-time control decisions for managing the system. The processes are deployed automatically on a distributed network involving sensors/meters/probes tracking system parameters, actuators controlling devices, and diverse computing

  9. Rethinking of the heuristic-analytic dual process theory: a comment on Wada and Nittono (2004) and the reasoning process in the Wason selection task.

    PubMed

    Cardaci, Maurizio; Misuraca, Raffaella

    2005-08-01

    This paper raises some methodological problems in the dual process explanation provided by Wada and Nittono for their 2004 results using the Wason selection task. We maintain that the Nittono rethinking approach is weak and that it should be refined to grasp better the evidence of analytic processes.

  10. Efficient Signal Processing in Random Networks that Generate Variability: A Comparison of Internally Generated and Externally Induced Variability

    NASA Astrophysics Data System (ADS)

    Dasgupta, Sakyasingha; Nishikawa, Isao; Aihara, Kazuyuki; Toyoizumi, Taro

    Source of cortical variability and its influence on signal processing remain an open question. We address the latter, by studying two types of balanced randomly connected networks of quadratic I-F neurons, with irregular spontaneous activity: (a) a deterministic network with strong connections generating noise by chaotic dynamics (b) a stochastic network with weak connections receiving noisy input. They are analytically tractable in the limit of large network-size and channel time-constant. Despite different sources of noise, spontaneous activity of these networks are identical unless majority of neurons are simultaneously recorded. However, the two networks show remarkably different sensitivity to external stimuli. In the former, input reverberates internally and can be read out over long time, but in the latter, inputs rapidly decay. This is further enhanced with activity-dependent plasticity at input synapses producing marked difference in decoding inputs from neural activity. We show, this leads to distinct performance of the two networks to integrate temporally separate signals from multiple sources, with the deterministic chaotic network activity serving as reservoir for Monte Carlo sampling to perform near optimal Bayesian integration, unlike its stochastic counterpart.

  11. Reaction-diffusion processes in scale-free networks

    NASA Astrophysics Data System (ADS)

    Gallos, Lazaros K.; Argyrakis, Panos

    2003-05-01

    In this work we investigate the dynamics of reaction-diffusion processes on scale-free networks. Particles of two types, A and B, are randomly distributed on such a network and diffuse using random walk models by hopping to nearest neighbor nodes only. Here we treat the case where one species is immobile and the other is mobile. The immobile species acts as a trap, i.e. when particles of the other species encounter a trap node they are immediately annihilated. We numerically compute Φ(n,c), the survival probability of mobile species at time n, as a function of the concentration of trap nodes, c. We compare our results to the mean-field result (Rosenstock approximation), and the exact result for lattices of Donsker-Varadhan. We find that for high connectivity networks and high trap concentrations the mean-field result of a simple exponential decay is also valid here. But for low connectivity networks and low c the behavior is much more complicated. We explain these trends in terms of the number of sites visited, S(n), the system size, and the concentration of traps.

  12. On the use of the activation energy concept to investigate analyte and network deformations in entangled polymer solution capillary electrophoresis of synthetic polyelectrolytes.

    PubMed

    Cottet, H; Gareil, P

    2001-01-01

    The activation energy associated with the electrophoretic migration of an analyte under given electrolyte conditions can be accessed through the determination of the analyte electrophoretic mobility at various temperatures. In the case of the electrophoretic separation of polyelectrolytes in the presence of an entangled polymer network, activation energy can be regarded as the energy needed by the analyte to overcome the obstacles created by the separating network. Any deformation undergone by the analyte or the network is expected to induce a decrease in the activation energy. In this work, the electrophoretic mobilities of poly(styrenesulfonates) (PSSs) of various molecular weights (Mr 16 x 10(3) to 990 x 10(3)) were determined in entangled polyethylene oxide (PEO) solutions as a function of temperature (in the 17-60 degrees C range) and the PSS activation energies were calculated. The influences of the PSS molecular weight, blob sizes zetab of the separating network (related to the PEO concentration), ionic strength of the electrolyte and electric field strength (75-600 V/cm) were investigated. The results were interpreted in terms of analyte and network deformations and were confronted with those previously obtained for DNA migration in polymer solutions and chemical gels. For a radius of gyration Rgzetab, suggesting PSS and network deformations in the latter case. Increasing ionic strength resulted in an increase in the PSS activation energy, because of the decrease of their radii of gyration, which makes them less deformable. Finally, the activation energies of all the PSSs are a decreasing function of field strength and at high field strength tend to reach a constant value close to that for a small molecule.

  13. Analytical Hierarchy Process modeling for malaria risk zones in Vadodara district, Gujarat

    NASA Astrophysics Data System (ADS)

    Bhatt, B.; Joshi, J. P.

    2014-11-01

    Malaria epidemic is one of the complex spatial problems around the world. According to WHO, an estimated 6, 27, 000 deaths occurred due to malaria in 2012. In many developing nations with diverse ecological regions, it is still a large cause of human mortality. Owing to the incompleteness of epidemiological data and their spatial origin, the quantification of disease incidence burdening basic public health planning is a major constrain especially in developing countries. The present study focuses on the integrated Geospatial and Multi-Criteria Evaluation (AHP) technique to determine malaria risk zones. The study is conducted in Vadodara district, including 12 Taluka among which 4 Taluka are predominantly tribal. The influence of climatic and physical environmental factors viz., rainfall, hydro geomorphology; drainage, elevation, and land cover are used to score their share in the evaluation of malariogenic condition. This was synthesized on the basis of preference over each factor and the total weights of each data and data layer were computed and visualized. The district was divided into three viz., high, moderate and low risk zones .It was observed that a geographical area of 1885.2sq.km comprising 30.3% fall in high risk zone. The risk zones identified on the basis of these parameters and assigned weights shows a close resemblance with ground condition. As the API distribution for 2011overlaid corresponds to the risk zones identified. The study demonstrates the significance and prospect of integrating Geospatial tools and Analytical Hierarchy Process for malaria risk zones and dynamics of malaria transmission.

  14. Application of analytical hierarchy process for effective selection of agricultural best management practices.

    PubMed

    Giri, Subhasis; Nejadhashemi, A Pouyan

    2014-01-01

    In this study an analytical hierarchy process (AHP) was used for ranking best management practices (BMPs) in the Saginaw River Watershed based on environmental, economic and social factors. Three spatial targeting methods were used for placement of BMPs on critical source areas (CSAs). The environment factors include sediment, total nitrogen, and total phosphorus reductions at the subbasin level and the watershed outlet. Economic factors were based on total BMP cost, including installation, maintenance, and opportunity costs. Social factors were divided into three favorability rankings (most favorable, moderately favorable, and least favorable) based on area allocated to each BMP. Equal weights (1/3) were considered for the three main factors while calculating the BMP rank by AHP. In this study three scenarios were compared. A comprehensive approach in which environmental, economic, and social aspects are simultaneously considered (Scenario 1) versus more traditional approaches in which both environmental and economic aspects were considered (Scenario 2) or only environmental aspects (sediment, TN, and TP) were considered (Scenario 3). In Scenario 1, only stripcropping (moderately favorable) was selected on all CSAs at the subbasin level, whereas stripcropping (49-69% of CSAs) and residue management (most favorable, 31-51% of CSAs) were selected by AHP based on the watershed outlet and three spatial targeting methods. In Scenario 2, native grass was eliminated by moderately preferable BMPs (stripcropping) both at the subbasin and watershed outlet levels due the lower BMP implementations cost compared to native grass. Finally, in Scenario 3, at subbasin level, the least socially preferable BMP (native grass) was selected in 100% of CSAs due to greater pollution reduction capacity compared to other BMPs. At watershed level, nearly 50% the CSAs selected stripcropping, and the remaining 50% of CSAs selected native grass and residue management equally. PMID:24309231

  15. Land suitability assessment on a watershed of Loess Plateau using the analytic hierarchy process.

    PubMed

    Yi, Xiaobo; Wang, Li

    2013-01-01

    In order to reduce soil erosion and desertification, the Sloping Land Conversion Program has been conducted in China for more than 15 years, and large areas of farmland have been converted to forest and grassland. However, this large-scale vegetation-restoration project has faced some key problems (e.g. soil drying) that have limited the successful development of the current ecological-recovery policy. Therefore, it is necessary to know about the land use, vegetation, and soil, and their inter-relationships in order to identify the suitability of vegetation restoration. This study was conducted at the watershed level in the ecologically vulnerable region of the Loess Plateau, to evaluate the land suitability using the analytic hierarchy process (AHP). The results showed that (1) the area unsuitable for crops accounted for 73.3% of the watershed, and the main factors restricting cropland development were soil physical properties and soil nutrients; (2) the area suitable for grassland was about 86.7% of the watershed, with the remaining 13.3% being unsuitable; (3) an area of 3.95 km(2), accounting for 66.7% of the watershed, was unsuitable for forest. Overall, the grassland was found to be the most suitable land-use to support the aims of the Sloping Land Conversion Program in the Liudaogou watershed. Under the constraints of soil water shortage and nutrient deficits, crops and forests were considered to be inappropriate land uses in the study area, especially on sloping land. When selecting species for re-vegetation, non-native grass species with high water requirements should be avoided so as to guarantee the sustainable development of grassland and effective ecological functioning. Our study provides local land managers and farmers with valuable information about the inappropriateness of growing trees in the study area along with some information on species selection for planting in the semi-arid area of the Loess Plateau.

  16. Tattoo and taboo: on the meaning of tattoos in the analytic process.

    PubMed

    Karacaoglan, Uta

    2012-02-01

    Tattooing projects a visual image in transference to form a backdrop for the most salient unconscious inner conflicts arising during an ongoing analytic process. Like a snapshot, the tattoo is a dialectic record of the mother-father relationship, of desires for closeness and distance, commonality and difference, identification and individuation. As Walter Benjamin famously stated about the nature of visual images in his Arcades Project, the tattoo represents "dialectics at a standstill." What seems paramount to the patient who participates in the act of tattooing is the need for stasis and immutability, as if bringing unconscious conflicts to "standstill" were to deliver a sense of stability. Unconsciously, the need is triggered by a threat to the inner stability resulting from fear of violating a taboo escalating to the point that fears of abandonment and fusion become unbearable. On the one hand, the tattoo is a visual symbolization of a taboo transgression; on the other hand, it activates the same through an act of self-injury that resembles the magical ritual acts of indigenous peoples' use of tattoos. The taboo thus serves as an ersatz for the actual violation of the taboo in real life, so that the tattoo may be ascribed a magical significance or totemic function. And yet the tattoo's success as a vehicle for constructing a transitional object is always contingent on the tangible manipulation of the skin conjoined with the creation of a symbolizing visual image. The image then acts like a "patch" to repair holes blown into Winnicott's "potential space" and to reconstruct it.

  17. Land Suitability Assessment on a Watershed of Loess Plateau Using the Analytic Hierarchy Process

    PubMed Central

    Yi, Xiaobo; Wang, Li

    2013-01-01

    In order to reduce soil erosion and desertification, the Sloping Land Conversion Program has been conducted in China for more than 15 years, and large areas of farmland have been converted to forest and grassland. However, this large-scale vegetation-restoration project has faced some key problems (e.g. soil drying) that have limited the successful development of the current ecological-recovery policy. Therefore, it is necessary to know about the land use, vegetation, and soil, and their inter-relationships in order to identify the suitability of vegetation restoration. This study was conducted at the watershed level in the ecologically vulnerable region of the Loess Plateau, to evaluate the land suitability using the analytic hierarchy process (AHP). The results showed that (1) the area unsuitable for crops accounted for 73.3% of the watershed, and the main factors restricting cropland development were soil physical properties and soil nutrients; (2) the area suitable for grassland was about 86.7% of the watershed, with the remaining 13.3% being unsuitable; (3) an area of 3.95 km2, accounting for 66.7% of the watershed, was unsuitable for forest. Overall, the grassland was found to be the most suitable land-use to support the aims of the Sloping Land Conversion Program in the Liudaogou watershed. Under the constraints of soil water shortage and nutrient deficits, crops and forests were considered to be inappropriate land uses in the study area, especially on sloping land. When selecting species for re-vegetation, non-native grass species with high water requirements should be avoided so as to guarantee the sustainable development of grassland and effective ecological functioning. Our study provides local land managers and farmers with valuable information about the inappropriateness of growing trees in the study area along with some information on species selection for planting in the semi-arid area of the Loess Plateau. PMID:23922723

  18. Tattoo and taboo: on the meaning of tattoos in the analytic process.

    PubMed

    Karacaoglan, Uta

    2012-02-01

    Tattooing projects a visual image in transference to form a backdrop for the most salient unconscious inner conflicts arising during an ongoing analytic process. Like a snapshot, the tattoo is a dialectic record of the mother-father relationship, of desires for closeness and distance, commonality and difference, identification and individuation. As Walter Benjamin famously stated about the nature of visual images in his Arcades Project, the tattoo represents "dialectics at a standstill." What seems paramount to the patient who participates in the act of tattooing is the need for stasis and immutability, as if bringing unconscious conflicts to "standstill" were to deliver a sense of stability. Unconsciously, the need is triggered by a threat to the inner stability resulting from fear of violating a taboo escalating to the point that fears of abandonment and fusion become unbearable. On the one hand, the tattoo is a visual symbolization of a taboo transgression; on the other hand, it activates the same through an act of self-injury that resembles the magical ritual acts of indigenous peoples' use of tattoos. The taboo thus serves as an ersatz for the actual violation of the taboo in real life, so that the tattoo may be ascribed a magical significance or totemic function. And yet the tattoo's success as a vehicle for constructing a transitional object is always contingent on the tangible manipulation of the skin conjoined with the creation of a symbolizing visual image. The image then acts like a "patch" to repair holes blown into Winnicott's "potential space" and to reconstruct it. PMID:22320133

  19. Applying the Analytic Hierarchy Process to Oil Sands Environmental Compliance Risk Management

    NASA Astrophysics Data System (ADS)

    Roux, Izak Johannes, III

    Oil companies in Alberta, Canada, invested $32 billion on new oil sands projects in 2013. Despite the size of this investment, there is a demonstrable deficiency in the uniformity and understanding of environmental legislation requirements that manifest into increased project compliance risks. This descriptive study developed 2 prioritized lists of environmental regulatory compliance risks and mitigation strategies and used multi-criteria decision theory for its theoretical framework. Information from compiled lists of environmental compliance risks and mitigation strategies was used to generate a specialized pairwise survey, which was piloted by 5 subject matter experts (SMEs). The survey was validated by a sample of 16 SMEs, after which the Analytic Hierarchy Process (AHP) was used to rank a total of 33 compliance risks and 12 mitigation strategy criteria. A key finding was that the AHP is a suitable tool for ranking of compliance risks and mitigation strategies. Several working hypotheses were also tested regarding how SMEs prioritized 1 compliance risk or mitigation strategy compared to another. The AHP showed that regulatory compliance, company reputation, environmental compliance, and economics ranked the highest and that a multi criteria mitigation strategy for environmental compliance ranked the highest. The study results will inform Alberta oil sands industry leaders about the ranking and utility of specific compliance risks and mitigations strategies, enabling them to focus on actions that will generate legislative and public trust. Oil sands leaders implementing a risk management program using the risks and mitigation strategies identified in this study will contribute to environmental conservation, economic growth, and positive social change.

  20. Land suitability assessment on a watershed of Loess Plateau using the analytic hierarchy process.

    PubMed

    Yi, Xiaobo; Wang, Li

    2013-01-01

    In order to reduce soil erosion and desertification, the Sloping Land Conversion Program has been conducted in China for more than 15 years, and large areas of farmland have been converted to forest and grassland. However, this large-scale vegetation-restoration project has faced some key problems (e.g. soil drying) that have limited the successful development of the current ecological-recovery policy. Therefore, it is necessary to know about the land use, vegetation, and soil, and their inter-relationships in order to identify the suitability of vegetation restoration. This study was conducted at the watershed level in the ecologically vulnerable region of the Loess Plateau, to evaluate the land suitability using the analytic hierarchy process (AHP). The results showed that (1) the area unsuitable for crops accounted for 73.3% of the watershed, and the main factors restricting cropland development were soil physical properties and soil nutrients; (2) the area suitable for grassland was about 86.7% of the watershed, with the remaining 13.3% being unsuitable; (3) an area of 3.95 km(2), accounting for 66.7% of the watershed, was unsuitable for forest. Overall, the grassland was found to be the most suitable land-use to support the aims of the Sloping Land Conversion Program in the Liudaogou watershed. Under the constraints of soil water shortage and nutrient deficits, crops and forests were considered to be inappropriate land uses in the study area, especially on sloping land. When selecting species for re-vegetation, non-native grass species with high water requirements should be avoided so as to guarantee the sustainable development of grassland and effective ecological functioning. Our study provides local land managers and farmers with valuable information about the inappropriateness of growing trees in the study area along with some information on species selection for planting in the semi-arid area of the Loess Plateau. PMID:23922723

  1. APPLICATION OF THE ANALYTIC HIERARCHY PROCESS TO COMPARE ALTERNATIVES FOR THE LONG-TERM MANAGEMENT OF SURPLUS MERCURY

    EPA Science Inventory

    This paper describes a systematic method for comparing options for the long-term management of surplus elemental mercury in the U.S., using the Analytic Hierarchy Process (AHP) as embodied in commercially available Expert Choice software. A limited scope multi-criteria decision-a...

  2. Marketing Mix Formulation for Higher Education: An Integrated Analysis Employing Analytic Hierarchy Process, Cluster Analysis and Correspondence Analysis

    ERIC Educational Resources Information Center

    Ho, Hsuan-Fu; Hung, Chia-Chi

    2008-01-01

    Purpose: The purpose of this paper is to examine how a graduate institute at National Chiayi University (NCYU), by using a model that integrates analytic hierarchy process, cluster analysis and correspondence analysis, can develop effective marketing strategies. Design/methodology/approach: This is primarily a quantitative study aimed at…

  3. Tough, processable semi-interpenetrating polymer networks from monomer reactants

    NASA Technical Reports Server (NTRS)

    Pater, Ruth H. (Inventor)

    1994-01-01

    A high temperature semi-interpenetrating polymer network (semi-IPN) was developed which had significantly improved processability, damage tolerance, and mechanical performance, when compared to the commercial Thermid materials. This simultaneous semi-IPN was prepared by mixing the monomer precursors of Thermid AL-600 (a thermoset) and NR-150B2 (a thermoplastic) and allowing the monomers to react randomly upon heating. This reaction occurs at a rate which decreases the flow and broadens the processing window. Upon heating at a higher temperature, there is an increase in flow. Because of the improved flow properties, broadened processing window and enhanced toughness, high strength polymer matrix composites, adhesives and molded articles can now be prepared from the acetylene end-capped polyimides which were previously inherently brittle and difficult to process.

  4. Reservoir computing: a photonic neural network for information processing

    NASA Astrophysics Data System (ADS)

    Paquot, Yvan; Dambre, Joni; Schrauwen, Benjamin; Haelterman, Marc; Massar, Serge

    2010-06-01

    At the boundaries between photonics and dynamic systems theory, we combine recent advances in neural networks with opto-electronic nonlinearities to demonstrate a new way to perform optical information processing. The concept of reservoir computing arose recently as a powerful solution to the issue of training recurrent neural networks. Indeed, it is comparable to, or even outperforms, other state of the art solutions for tasks such as speech recognition or time series prediction. As it is based on a static topology, it allows making the most of very simple physical architectures having complex nonlinear dynamics. The method is inherently robust to noise and does not require explicit programming operations. It is therefore particularly well adapted for analog realizations. Among the various implementations of the concept that have been proposed, we focus on the field of optics. Our experimental reservoir computer is based on opto-electronic technology, and can be viewed as an intermediate step towards an all optical device. Our fiber optics system is based on a nonlinear feedback loop operating at the threshold of chaos. In its present preliminary stage it is already capable of complicated tasks like modeling nonlinear systems with memory. Our aim is to demonstrate that such an analog reservoir can have performances comparable to state of the art digital implementations of Neural Networks. Furthermore, our system can in principle be operated at very high frequencies thanks to the high speed of photonic devices. Thus one could envisage targeting applications such as online information processing in broadband telecommunications.

  5. Real-time hierarchically distributed processing network interaction simulation

    NASA Technical Reports Server (NTRS)

    Zimmerman, W. F.; Wu, C.

    1987-01-01

    The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

  6. Cancel and rethink in the Wason selection task: further evidence for the heuristic-analytic dual process theory.

    PubMed

    Wada, Kazushige; Nittono, Hiroshi

    2004-06-01

    The reasoning process in the Wason selection task was examined by measuring card inspection times in the letter-number and drinking-age problems. 24 students were asked to solve the problems presented on a computer screen. Only the card touched with a mouse pointer was visible, and the total exposure time of each card was measured. Participants were allowed to cancel their previous selections at any time. Although rethinking was encouraged, the cards once selected were rarely cancelled (10% of the total selections). Moreover, most of the cancelled cards were reselected (89% of the total cancellations). Consistent with previous findings, inspection times were longer for selected cards than for nonselected cards. These results suggest that card selections are determined largely by initial heuristic processes and rarely reversed by subsequent analytic processes. The present study gives further support for the heuristic-analytic dual process theory.

  7. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  8. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  9. Elementary processes governing the evolution of road networks

    PubMed Central

    Strano, Emanuele; Nicosia, Vincenzo; Latora, Vito; Porta, Sergio; Barthélemy, Marc

    2012-01-01

    Urbanisation is a fundamental phenomenon whose quantitative characterisation is still inadequate. We report here the empirical analysis of a unique data set regarding almost 200 years of evolution of the road network in a large area located north of Milan (Italy). We find that urbanisation is characterised by the homogenisation of cell shapes, and by the stability throughout time of high–centrality roads which constitute the backbone of the urban structure, confirming the importance of historical paths. We show quantitatively that the growth of the network is governed by two elementary processes: (i) ‘densification’, corresponding to an increase in the local density of roads around existing urban centres and (ii) ‘exploration’, whereby new roads trigger the spatial evolution of the urbanisation front. The empirical identification of such simple elementary mechanisms suggests the existence of general, simple properties of urbanisation and opens new directions for its modelling and quantitative description. PMID:22389765

  10. The Martian valley networks: Origin by niveo-fluvial processes

    NASA Technical Reports Server (NTRS)

    Rice, J. W., Jr.

    1993-01-01

    The valley networks may hold the key to unlocking the paleoclimatic history of Mars. These enigmatic landforms may be regarded as the Martian equivalent of the Rosetta Stone. Therefore, a more thorough understanding of their origin and evolution is required. However, there is still no consensus among investigators regarding the formation (runoff vs. sapping) of these features. Recent climatic modeling precludes warm (0 degrees C) globally averaged surface temperatures prior to 2 b.y. when solar luminosity was 25-30 percent less than present levels. This paper advocates snowmelt as the dominant process responsible for the formation of the dendritic valley networks. Evidence for Martian snowfall and subsequent melt has been discussed in previous studies.

  11. Risk assessment in the upstream crude oil supply chain: Leveraging analytic hierarchy process

    NASA Astrophysics Data System (ADS)

    Briggs, Charles Awoala

    For an organization to be successful, an effective strategy is required, and if implemented appropriately the strategy will result in a sustainable competitive advantage. The importance of decision making in the oil industry is reflected in the magnitude and nature of the industry. Specific features of the oil industry supply chain, such as its longer chain, the complexity of its transportation system, its complex production and storage processes, etc., pose challenges to its effective management. Hence, understanding the risks, the risk sources, and their potential impacts on the oil industry's operations will be helpful in proposing a risk management model for the upstream oil supply chain. The risk-based model in this research uses a three-level analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to underline the importance of risk analysis and risk management in the upstream crude oil supply chain. Level 1 represents the overall goal of risk management; Level 2 is comprised of the various risk factors; and Level 3 represents the alternative criteria of the decision maker as indicated on the hierarchical structure of the crude oil supply chain. Several risk management experts from different oil companies around the world were surveyed, and six major types of supply chain risks were identified: (1) exploration and production, (2) environmental and regulatory compliance, (3) transportation, (4) availability of oil, (5) geopolitical, and (6) reputational. Also identified are the preferred methods of managing risks which include; (1) accept and control the risks, (2) avoid the risk by stopping the activity, or (3) transfer or share the risks to other companies or insurers. The results from the survey indicate that the most important risk to manage is transportation risk with a priority of .263, followed by exploration/production with priority of .198, with an overall inconsistency of .03. With respect to major objectives the most

  12. Competing spreading processes on multiplex networks: Awareness and epidemics

    NASA Astrophysics Data System (ADS)

    Granell, Clara; Gómez, Sergio; Arenas, Alex

    2014-07-01

    Epidemiclike spreading processes on top of multilayered interconnected complex networks reveal a rich phase diagram of intertwined competition effects. A recent study by the authors [C. Granell et al., Phys. Rev. Lett. 111, 128701 (2013)., 10.1103/PhysRevLett.111.128701] presented an analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the spreading of information awareness to prevent infection, on top of multiplex networks. The results in the case in which awareness implies total immunization to the disease revealed the existence of a metacritical point at which the critical onset of the epidemics starts, depending on completion of the awareness process. Here we present a full analysis of these critical properties in the more general scenario where the awareness spreading does not imply total immunization, and where infection does not imply immediate awareness of it. We find the critical relation between the two competing processes for a wide spectrum of parameters representing the interaction between them. We also analyze the consequences of a massive broadcast of awareness (mass media) on the final outcome of the epidemic incidence. Importantly enough, the mass media make the metacritical point disappear. The results reveal that the main finding, i.e., existence of a metacritical point, is rooted in the competition principle and holds for a large set of scenarios.

  13. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  14. Precision and bias of selected analytes reported by the National Atmospheric Deposition Program and National Trends Network, 1983; and January 1980 through September 1984

    USGS Publications Warehouse

    Schroder, L.J.; Bricker, A.W.; Willoughby, T.C.

    1985-01-01

    Blind-audit samples with known analyte concentrations have been prepared by the U.S. Geological Survey and distributed to the National Atmospheric Deposition Program 's Central Analytical Laboratory. The difference between the National Atmospheric Deposition Program and National Trends Network reported analyte concentrations and known analyte concentrations have been calculated, and the bias has been determined. Calcium, magnesium , sodium, and chloride were biased at the 99-percent confidence limit; potassium and sulfate were unbiased at the 99-percent confidence limit, for 1983 results. Relative-percent differences between the measured and known analyte concentration for calcium , magnesium, sodium, potassium, chloride, and sulfate have been calculated for 1983. The median relative percent difference for calcium was 17.0; magnesium was 6.4; sodium was 10.8; potassium was 6.4; chloride was 17.2; and sulfate was -5.3. These relative percent differences should be used to correct the 1983 data before user-analysis of the data. Variances have been calculated for calcium, magnesium, sodium, potassium, chloride, and sulfate determinations. These variances should be applicable to natural-sample analyte concentrations reported by the National Atmospheric Deposition Program and National Trends Network for calendar year 1983. (USGS)

  15. Assessment of economic instruments for countries with low municipal waste management performance: An approach based on the analytic hierarchy process.

    PubMed

    Kling, Maximilian; Seyring, Nicole; Tzanova, Polia

    2016-09-01

    Economic instruments provide significant potential for countries with low municipal waste management performance in decreasing landfill rates and increasing recycling rates for municipal waste. In this research, strengths and weaknesses of landfill tax, pay-as-you-throw charging systems, deposit-refund systems and extended producer responsibility schemes are compared, focusing on conditions in countries with low waste management performance. In order to prioritise instruments for implementation in these countries, the analytic hierarchy process is applied using results of a literature review as input for the comparison. The assessment reveals that pay-as-you-throw is the most preferable instrument when utility-related criteria are regarded (wb = 0.35; analytic hierarchy process distributive mode; absolute comparison) mainly owing to its waste prevention effect, closely followed by landfill tax (wb = 0.32). Deposit-refund systems (wb = 0.17) and extended producer responsibility (wb = 0.16) rank third and fourth, with marginal differences owing to their similar nature. When cost-related criteria are additionally included in the comparison, landfill tax seems to provide the highest utility-cost ratio. Data from literature concerning cost (contrary to utility-related criteria) is currently not sufficiently available for a robust ranking according to the utility-cost ratio. In general, the analytic hierarchy process is seen as a suitable method for assessing economic instruments in waste management. Independent from the chosen analytic hierarchy process mode, results provide valuable indications for policy-makers on the application of economic instruments, as well as on their specific strengths and weaknesses. Nevertheless, the instruments need to be put in the country-specific context along with the results of this analytic hierarchy process application before practical decisions are made. PMID:27121417

  16. Near Real Time Analytics of Human Sensor Networks in the Realm of Big Data

    NASA Astrophysics Data System (ADS)

    Aulov, O.; Halem, M.

    2012-12-01

    With the prolific development of social media, emergency responders have an increasing interest in harvesting social media from outlets such as Flickr, Twitter, and Facebook, in order to assess the scale and specifics of extreme events including wild fires, earthquakes, terrorist attacks, oil spills, etc. A number of experimental platforms have successfully been implemented to demonstrate the utilization of social media data in extreme events, including Twitter Earthquake Detector, which relied on tweets for earthquake monitoring; AirTwitter, which used tweets for air quality reporting; and our previous work, using Flickr data as boundary value forcings to improve the forecast of oil beaching in the aftermath of the Deepwater Horizon oil spill. The majority of these platforms addressed a narrow, specific type of emergency and harvested data from a particular outlet. We demonstrate an interactive framework for monitoring, mining and analyzing a plethora of heterogeneous social media sources for a diverse range of extreme events. Our framework consists of three major parts: a real time social media aggregator, a data processing and analysis engine, and a web-based visualization and reporting tool. The aggregator gathers tweets, Facebook comments from fan pages, Google+ posts, forum discussions, blog posts (such as LiveJournal and Blogger.com), images from photo-sharing platforms (such as Flickr, Picasa), videos from video-sharing platforms (youtube, Vimeo), and so forth. The data processing and analysis engine pre-processes the aggregated information and annotates it with geolocation and sentiment information. In many cases, the metadata of the social media posts does not contain geolocation information—-however, a human reader can easily guess from the body of the text what location is discussed. We are automating this task by use of Named Entity Recognition (NER) algorithms and a gazetteer service. The visualization and reporting tool provides a web-based, user

  17. Cascade process modeling with mechanism-based hierarchical neural networks.

    PubMed

    Cong, Qiumei; Yu, Wen; Chai, Tianyou

    2010-02-01

    Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

  18. State-trace analysis: dissociable processes in a connectionist network?

    PubMed

    Yeates, Fayme; Wills, Andy J; Jones, Fergal W; McLaren, Ian P L

    2015-07-01

    Some argue the common practice of inferring multiple processes or systems from a dissociation is flawed (Dunn, 2003). One proposed solution is state-trace analysis (Bamber, 1979), which involves plotting, across two or more conditions of interest, performance measured by either two dependent variables, or two conditions of the same dependent measure. The resulting analysis is considered to provide evidence that either (a) a single process underlies performance (one function is produced) or (b) there is evidence for more than one process (more than one function is produced). This article reports simulations using the simple recurrent network (SRN; Elman, 1990) in which changes to the learning rate produced state-trace plots with multiple functions. We also report simulations using a single-layer error-correcting network that generate plots with a single function. We argue that the presence of different functions on a state-trace plot does not necessarily support a dual-system account, at least as typically defined (e.g. two separate autonomous systems competing to control responding); it can also indicate variation in a single parameter within theories generally considered to be single-system accounts. PMID:25307272

  19. Silicon nanophotonic networks for quantum optical information processing

    NASA Astrophysics Data System (ADS)

    Hach, Edwin E.

    2016-05-01

    Silicon nanophotonics show a lot of promise as the basic architecture for quantum information processing devices. This is particularly the case in relation to the scalability of such devices. During this talk I will review our simple theoretical model of a structure that we have identified as a `fundamental circuit element' for linear optical quantum information processing in silicon nanophotonics. In particular, we have shown that, owing to an effect we call Passive Quantum Optical Feedback (PQOF), the topology of this circuit element allows for certain possible operational advantages, in addition to inherent scalability, not expected in bulk linear optics. I will emphasize the extension of our work to larger networks, including the Knill-Laflamme-Milburn (KLM) Controlled-Not (CNOT) gate and its important constituent, the so-called Nonlinear Sign (NS) shifter. Further, I will discuss our ongoing effort to design and optimize scalable networks that seem to have useful applications in quantum metrology and sensing. In developing the discussion, I will examine recent developments related to incorporation of losses and spectral properties in such a way as to generalize our simple, continuous-wave (cw) model of essentially lossless operation. I will also discuss on-chip generation and control of entangled photons within the nanophotonic material itself, especially as related to potentially useful applications in information processing.

  20. Statistical process control using optimized neural networks: a case study.

    PubMed

    Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

    2014-09-01

    The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. PMID:24210290

  1. Defining desired genetic gains for rainbow trout breeding objective using analytic hierarchy process.

    PubMed

    Sae-Lim, P; Komen, H; Kause, A; van Arendonk, J A M; Barfoot, A J; Martin, K E; Parsons, J E

    2012-06-01

    Distributing animals from a single breeding program to a global market may not satisfy all producers, as they may differ in market objectives and farming environments. Analytic hierarchy process (AHP) is used to estimate preferences, which can be aggregated to consensus preference values using weighted goal programming (WGP). The aim of this study was to use an AHP-WGP based approach to derive desired genetic gains for rainbow trout breeding and to study whether breeding trait preferences vary depending on commercial products and farming environments. Two questionnaires were sent out. Questionnaire-A (Q-A) was distributed to 178 farmers from 5 continents and used to collect information on commercial products and farming environments. In this questionnaire, farmers were asked to rank the 6 most important traits for genetic improvement from a list of 13 traits. Questionnaire B (Q-B) was sent to all farmers who responded to Q-A (53 in total). For Q-B, preferences of the 6 traits were obtained using pairwise comparison. Preference intensity was given to quantify (in % of a trait mean; G%) the degree to which 1 trait is preferred over the other. Individual preferences, social preferences, and consensus preferences (Con-P) were estimated using AHP and WGP. Desired gains were constructed by multiplying Con-P by G%. The analysis revealed that the 6 most important traits were thermal growth coefficient (TGC), survival (Surv), feed conversion ratio (FCR), condition factor (CF), fillet percentage (FIL%), and late maturation (LMat). Ranking of traits based on average Con-P values were Surv (0.271), FCR (0.246), TGC (0.246), LMat (0.090), FIL% (0.081), and CF (0.067). Corresponding desired genetic gains (in % of trait mean) were 1.63, 1.87, 1.67, 1.29, 0.06, and 0.33%, respectively. The results from Con-P values show that trait preferences may vary for different types of commercial production or farming environments. This study demonstrated that combination of AHP and WGP can

  2. Universality classes of the generalized epidemic process on random networks.

    PubMed

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

    2016-05-01

    We present a self-contained discussion of the universality classes of the generalized epidemic process (GEP) on Poisson random networks, which is a simple model of social contagions with cooperative effects. These effects lead to rich phase transitional behaviors that include continuous and discontinuous transitions with tricriticality in between. With the help of a comprehensive finite-size scaling theory, we numerically confirm static and dynamic scaling behaviors of the GEP near continuous phase transitions and at tricriticality, which verifies the field-theoretical results of previous studies. We also propose a proper criterion for the discontinuous transition line, which is shown to coincide with the bond percolation threshold.

  3. Universality classes of the generalized epidemic process on random networks

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    We present a self-contained discussion of the universality classes of the generalized epidemic process (GEP) on Poisson random networks, which is a simple model of social contagions with cooperative effects. These effects lead to rich phase transitional behaviors that include continuous and discontinuous transitions with tricriticality in between. With the help of a comprehensive finite-size scaling theory, we numerically confirm static and dynamic scaling behaviors of the GEP near continuous phase transitions and at tricriticality, which verifies the field-theoretical results of previous studies. We also propose a proper criterion for the discontinuous transition line, which is shown to coincide with the bond percolation threshold.

  4. Universality classes of the generalized epidemic process on random networks.

    PubMed

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

    2016-05-01

    We present a self-contained discussion of the universality classes of the generalized epidemic process (GEP) on Poisson random networks, which is a simple model of social contagions with cooperative effects. These effects lead to rich phase transitional behaviors that include continuous and discontinuous transitions with tricriticality in between. With the help of a comprehensive finite-size scaling theory, we numerically confirm static and dynamic scaling behaviors of the GEP near continuous phase transitions and at tricriticality, which verifies the field-theoretical results of previous studies. We also propose a proper criterion for the discontinuous transition line, which is shown to coincide with the bond percolation threshold. PMID:27300907

  5. Learning Analytics: A Case Study of the Process of Design of Visualizations

    ERIC Educational Resources Information Center

    Olmos, Martin; Corrin, Linda

    2012-01-01

    The ability to visualize student engagement and experience data provides valuable opportunities for learning support and curriculum design. With the rise of the use of learning analytics to provide "actionable intelligence" on students' learning, the challenge is to create visualizations of the data, which are clear and useful to the intended…

  6. Modeling Nitrogen Processing in Northeast US River Networks

    NASA Astrophysics Data System (ADS)

    Whittinghill, K. A.; Stewart, R.; Mineau, M.; Wollheim, W. M.; Lammers, R. B.

    2013-12-01

    Due to increased nitrogen (N) pollution from anthropogenic sources, the need for aquatic ecosystem services such as N removal has also increased. River networks provide a buffering mechanism that retains or removes anthropogenic N inputs. However, the effectiveness of N removal in rivers may decline with increased loading and, consequently, excess N is eventually delivered to estuaries. We used a spatially distributed river network N removal model developed within the Framework for Aquatic Modeling in the Earth System (FrAMES) to examine the geography of N removal capacity of Northeast river systems under various land use and climate conditions. FrAMES accounts for accumulation and routing of runoff, water temperatures, and serial biogeochemical processing using reactivity derived from the Lotic Intersite Nitrogen Experiment (LINX2). Nonpoint N loading is driven by empirical relationships with land cover developed from previous research in Northeast watersheds. Point source N loading from wastewater treatment plants is estimated as a function of the population served and the volume of water discharged. We tested model results using historical USGS discharge data and N data from historical grab samples and recently initiated continuous measurements from in-situ aquatic sensors. Model results for major Northeast watersheds illustrate hot spots of ecosystem service activity (i.e. N removal) using high-resolution maps and basin profiles. As expected, N loading increases with increasing suburban or agricultural land use area. Network scale N removal is highest during summer and autumn when discharge is low and river temperatures are high. N removal as the % of N loading increases with catchment size and decreases with increasing N loading, suburban land use, or agricultural land use. Catchments experiencing the highest network scale N removal generally have N inputs (both point and non-point sources) located in lower order streams. Model results can be used to better

  7. Spiking modular neural networks: A neural network modeling approach for hydrological processes

    NASA Astrophysics Data System (ADS)

    Parasuraman, Kamban; Elshorbagy, Amin; Carey, Sean K.

    2006-05-01

    Artificial Neural Networks (ANNs) have been widely used for modeling hydrological processes that are embedded with high nonlinearity in both spatial and temporal scales. The input-output functional relationship does not remain the same over the entire modeling domain, varying at different spatial and temporal scales. In this study, a novel neural network model called the spiking modular neural networks (SMNNs) is proposed. An SMNN consists of an input layer, a spiking layer, and an associator neural network layer. The modular nature of the SMNN helps in finding domain-dependent relationships. The performance of the model is evaluated using two distinct case studies. The first case study is that of streamflow modeling, and the second case study involves modeling of eddy covariance-measured evapotranspiration. Two variants of SMNNs were analyzed in this study. The first variant employs a competitive layer as the spiking layer, and the second variant employs a self-organizing map as the spiking layer. The performance of SMNNs is compared to that of a regular feed forward neural network (FFNN) model. Results from the study demonstrate that SMNNs performed better than FFNNs for both the case studies. Results from partitioning analysis reveal that, compared to FFNNs, SMNNs are effective in capturing the dynamics of high flows. In modeling evapotranspiration, it is found that net radiation and ground temperature alone can be used to model the evaporation flux effectively. The SMNNs are shown to be effective in discretizing the complex mapping space into simpler domains that can be learned with relative ease.

  8. Incomplete and noisy network data as a percolation process

    PubMed Central

    Stumpf, Michael P. H.; Wiuf, Carsten

    2010-01-01

    We discuss the ramifications of noisy and incomplete observations of network data on the existence of a giant connected component (GCC). The existence of a GCC in a random graph can be described in terms of a percolation process, and building on general results for classes of random graphs with specified degree distributions we derive percolation thresholds above which GCCs exist. We show that sampling and noise can have a profound effect on the perceived existence of a GCC and find that both processes can destroy it. We also show that the absence of a GCC puts a theoretical upper bound on the false-positive rate and relate our percolation analysis to experimental protein–protein interaction data. PMID:20378609

  9. Incomplete fuzzy data processing systems using artificial neural network

    NASA Technical Reports Server (NTRS)

    Patyra, Marek J.

    1992-01-01

    In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

  10. Analytic expressions for the proximity energy, the fusion process and the α emission

    NASA Astrophysics Data System (ADS)

    Moustabchir, R.; Royer, G.

    2001-02-01

    The entrance and exit channels through quasimolecular shapes are compatible with the experimental data on fusion, light nucleus and α emissions when the proximity energy is taken into account. Analytic expressions allowing to determine rapidly this proximity energy are presented as well as formulas for the fusion barrier heights and radii and for the α emission barriers. Predictions for half-lives of exotic α emissions are proposed.

  11. Enhanced surface sampler and process for collection and release of analytes

    DOEpatents

    Addleman, Raymond S; Atkinson, David A; Bays, John T; Chouyyok, Wilaiwan; Cinson, Anthony D; Ewing, Robert G; Gerasimenko, Aleksandr A

    2015-02-03

    An enhanced swipe sampler and method of making are described. The swipe sampler is made of a fabric containing selected glass, metal oxide, and/or oxide-coated glass or metal fibers. Fibers are modified with silane ligands that are directly attached to the surface of the fibers to functionalize the sampling surface of the fabric. The swipe sampler collects various target analytes including explosives and other threat agents on the surface of the sampler.

  12. Dynamic Processes in Network Goods: Modeling, Analysis and Applications

    ERIC Educational Resources Information Center

    Paothong, Arnut

    2013-01-01

    The network externality function plays a very important role in the study of economic network industries. Moreover, the consumer group dynamic interactions coupled with network externality concept is going to play a dominant role in the network goods in the 21st century. The existing literature is stemmed on a choice of externality function with…

  13. Managing the Pre- and Post-analytical Phases of the Total Testing Process

    PubMed Central

    2012-01-01

    For many years, the clinical laboratory's focus on analytical quality has resulted in an error rate of 4-5 sigma, which surpasses most other areas in healthcare. However, greater appreciation of the prevalence of errors in the pre- and post-analytical phases and their potential for patient harm has led to increasing requirements for laboratories to take greater responsibility for activities outside their immediate control. Accreditation bodies such as the Joint Commission International (JCI) and the College of American Pathologists (CAP) now require clear and effective procedures for patient/sample identification and communication of critical results. There are a variety of free on-line resources available to aid in managing the extra-analytical phase and the recent publication of quality indicators and proposed performance levels by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) working group on laboratory errors and patient safety provides particularly useful benchmarking data. Managing the extra-laboratory phase of the total testing cycle is the next challenge for laboratory medicine. By building on its existing quality management expertise, quantitative scientific background and familiarity with information technology, the clinical laboratory is well suited to play a greater role in reducing errors and improving patient safety outside the confines of the laboratory. PMID:22259773

  14. Using Fuzzy Analytic Hierarchy Process multicriteria and Geographical information system for coastal vulnerability analysis in Morocco: The case of Mohammedia

    NASA Astrophysics Data System (ADS)

    Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha

    2016-04-01

    This paper shows a method to assess the vulnerability of coastal risks such as coastal erosion or submarine applying Fuzzy Analytic Hierarchy Process (FAHP) and spatial analysis techniques with Geographic Information System (GIS). The coast of the Mohammedia located in Morocco was chosen as the study site to implement and validate the proposed framework by applying a GIS-FAHP based methodology. The coastal risk vulnerability mapping follows multi-parametric causative factors as sea level rise, significant wave height, tidal range, coastal erosion, elevation, geomorphology and distance to an urban area. The Fuzzy Analytic Hierarchy Process methodology enables the calculation of corresponding criteria weights. The result shows that the coastline of the Mohammedia is characterized by a moderate, high and very high level of vulnerability to coastal risk. The high vulnerability areas are situated in the east at Monika and Sablette beaches. This technical approach is based on the efficiency of the Geographic Information System tool based on Fuzzy Analytical Hierarchy Process to help decision maker to find optimal strategies to minimize coastal risks.

  15. Optoelectronic signal processing using finite impulse response neural networks

    NASA Astrophysics Data System (ADS)

    H. B. Xavier da Silveira, Paulo Eduardo

    2001-08-01

    This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse response adaptive filters and neural networks-the algorithmic building blocks-are introduced, followed by a description of finite impulse response neural networks. This introduction is followed by a historical background, describing early optoelectronic implementations of these algorithms. Next, different algorithms capable of temporal back-propagation are derived in detail, including a novel modification to the conventional algorithm, called delayed-feedback back- propagation. Based on these algorithms, different optoelectronic processors making use of adaptive volume holograms and three-dimensional optical processing are developed. Two single-layer architectures are presented: the input delay plane architecture and the output delay plane architecture. By combining them it is possible to implement both forward and backward propagation in two complementary multi-layer architectures: the first making use of the conventional temporal back-propagation and the second making use of delayed feedback back-propagation. Next, emphasis is given to a specific application: the processing of signals from adaptive antenna arrays. This research is initiated by computer simulations of different scenarios with multiple broadband signals and jammers, in planar and circular arrays, studying issues such as the effect of modulator non-linearities to the performance of the array, and the relation between the number of jammers and the final nulling depth. Two sets of simulations are presented: the first set applied to RF antenna arrays and the

  16. Receptive amusia: evidence for cross-hemispheric neural networks underlying music processing strategies.

    PubMed

    Schuppert, M; Münte, T F; Wieringa, B M; Altenmüller, E

    2000-03-01

    Perceptual musical functions were investigated in patients suffering from unilateral cerebrovascular cortical lesions. Using MIDI (Musical Instrument Digital Interface) technique, a standardized short test battery was established that covers local (analytical) as well as global perceptual mechanisms. These represent the principal cognitive strategies in melodic and temporal musical information processing (local, interval and rhythm; global, contour and metre). Of the participating brain-damaged patients, a total of 69% presented with post-lesional impairments in music perception. Left-hemisphere-damaged patients showed significant deficits in the discrimination of local as well as global structures in both melodic and temporal information processing. Right-hemisphere-damaged patients also revealed an overall impairment of music perception, reaching significance in the temporal conditions. Detailed analysis outlined a hierarchical organization, with an initial right-hemisphere recognition of contour and metre followed by identification of interval and rhythm via left-hemisphere subsystems. Patterns of dissociated and associated melodic and temporal deficits indicate autonomous, yet partially integrated neural subsystems underlying the processing of melodic and temporal stimuli. In conclusion, these data contradict a strong hemispheric specificity for music perception, but indicate cross-hemisphere, fragmented neural substrates underlying local and global musical information processing in the melodic and temporal dimensions. Due to the diverse profiles of neuropsychological deficits revealed in earlier investigations as well as in this study, individual aspects of musicality and musical behaviour very likely contribute to the definite formation of these widely distributed neural networks.

  17. An Algorithm for Network Real Time Kinematic Processing

    NASA Astrophysics Data System (ADS)

    Malekzadeh, A.; Asgari, J.; Amiri-Simkooei, A. R.

    2015-12-01

    NRTK1 is an efficient method to achieve precise real time positioning from GNSS measurements. In this paper we attempt to improve NRTK algorithm by introducing a new strategy. In this strategy a precise relocation of master station observations is performed using Sagnac effect. After processing the double differences, the tropospheric and ionospheric errors of each baseline can be estimated separately. The next step is interpolation of these errors for the atmospheric errors mitigation of desired baseline. Linear and kriging interpolation methods are implemented in this study. In the new strategy the RINEX2 data of the master station is re-located and is converted to the desired virtual observations. Then the interpolated corrections are applied to the virtual observations. The results are compared by the classical method of VRS generation. 1 Network Real Time Kinematic 2 Receiver Independent Exchange Format

  18. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    PubMed

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  19. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

    PubMed Central

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  20. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    PubMed

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  1. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy. PMID:27136863

  2. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

  3. An analytical framework for assessing drug and therapeutics committee structure and work processes in tertiary Brazilian hospitals.

    PubMed

    Lima-Dellamora, Elisangela da Costa; Caetano, Rosângela; Gustafsson, Lars L; Godman, Brian B; Patterson, Ken; Osorio-de-Castro, Claudia Garcia Serpa

    2014-09-01

    University teaching hospitals usually provide tertiary care and are subject to early adoption of new technologies, which may compromise healthcare systems when uncritically adopted. Knowledge on the decision-making process - drug selection by drug selection committees or DTCs - is crucial to improve the quality of care. There are no models for studying the selection of drugs in Brazilian healthcare services. This study aims to discuss DTC structure and the processes regarding adoption of medicines in tertiary university hospitals in Brazil and to propose an analytical structure for providing direction for the future. State of the art content regarding drug selection processes and DTC procedures was reviewed in three databases. Information on the medicine selection process in a Brazilian gold standard teaching hospital was collected through observations and a review of existing procedures. A structured discussion on medicine selection and DTC procedures in tertiary hospitals ensued. This discussion resulted in findings that were organized in three dimensions, composing an analytical framework for the application in tertiary Brazilian hospitals (i) motivations for the adoption of drugs; (ii) necessary structural and organizational aspects for decision-making; and (iii) criteria and methods employed by the decision-making process. We believe that the suggested framework is compatible with tertiary Brazilian hospitals, because a gold standard in the country was able to conduct all its procedures in the light of WHO and international recommendations. We hope to contribute in producing knowledge which may hopefully be adopted in tertiary hospitals across Brazil.

  4. An alternative analytical formulation for the Voigt function applied to resonant effects in nuclear processes

    NASA Astrophysics Data System (ADS)

    Palma, Daniel A. P.; Gonçalves, Alessandro da C.; Martinez, Aquilino S.

    2011-10-01

    The Voigt function H( a, v) is defined as the convolution of the Gaussian and Lorentzian functions. Recent papers puplished in different areas of physics emphasize the importance of the fast and accurate calculation of the Voigt function for different orders of magnitude of variables a and v. An alternative analytical formulation for the Voigt function is proposed in this paper. This formulation is based on the solution of the non-homogeneous ordinary differential equation, satisfied by the Voigt function, using the Frobenius and parameter variation methods. The functional form of the Voigt function, as proposed, proved simple and precise. Systematic tests are accomplished demonstrating some advantages with other existent methods in the literature and with the numeric method of reference.

  5. Development of a frit 202 analytic standard for the Defense Waste Processing Facility

    SciTech Connect

    Schumacher, R.F.; Hardy, B.J.; Sproull, J.F.

    1997-03-30

    During the qualification of Frit 202 samples for the `DWPF Cold Runs`, the need for a reliable chemical frit standard became apparent. A standard was prepared by obtaining a quantity of Frit 202 and grinding into a fine powder. This material was homogenized as one slurry material volume, spray dried to prevent segregation, and hydraulically pressed into discs. These discs were fired and packaged into eleven sub-lots containing approximately 2,000 discs per sub-lot. A number of samples were obtained and analyzed by two analytic laboratories. The chemical analyses were carefully reviewed and evaluated by several statistical means. While there were several statistically significant variations between the sub-lots, it is believed that those variations are partially caused by the variability of the analytic method. These discs should provide a reliable standard for future chemical analyses of DWPF Frits similar in comparison to Frit 202. It is recommended that these discs be used as a standard material included with the representative frit sample to the independent chemical analysis laboratory, and the order of use of these standards be from sub-lot eleven to sub-lot four. It is further recommended that the NIST standard material (93a) be employed along with the 202 standard until confidence in the new standard is gained. The NIST standard should also be used when initial use of a new sub-lot is begun. this procedure should continue to the end of the DWPF program or such time as the chemical composition of the frit is extensively modified.

  6. The Scaling of Human Contacts and Epidemic Processes in Metapopulation Networks

    NASA Astrophysics Data System (ADS)

    Tizzoni, Michele; Sun, Kaiyuan; Benusiglio, Diego; Karsai, Márton; Perra, Nicola

    2015-10-01

    We study the dynamics of reaction-diffusion processes on heterogeneous metapopulation networks where interaction rates scale with subpopulation sizes. We first present new empirical evidence, based on the analysis of the interactions of 13 million users on Twitter, that supports the scaling of human interactions with population size with an exponent γ ranging between 1.11 and 1.21, as observed in recent studies based on mobile phone data. We then integrate such observations into a reaction- diffusion metapopulation framework. We provide an explicit analytical expression for the global invasion threshold which sets a critical value of the diffusion rate below which a contagion process is not able to spread to a macroscopic fraction of the system. In particular, we consider the Susceptible-Infectious-Recovered epidemic model. Interestingly, the scaling of human contacts is found to facilitate the spreading dynamics. This behavior is enhanced by increasing heterogeneities in the mobility flows coupling the subpopulations. Our results show that the scaling properties of human interactions can significantly affect dynamical processes mediated by human contacts such as the spread of diseases, ideas and behaviors.

  7. The Scaling of Human Contacts and Epidemic Processes in Metapopulation Networks.

    PubMed

    Tizzoni, Michele; Sun, Kaiyuan; Benusiglio, Diego; Karsai, Márton; Perra, Nicola

    2015-01-01

    We study the dynamics of reaction-diffusion processes on heterogeneous metapopulation networks where interaction rates scale with subpopulation sizes. We first present new empirical evidence, based on the analysis of the interactions of 13 million users on Twitter, that supports the scaling of human interactions with population size with an exponent γ ranging between 1.11 and 1.21, as observed in recent studies based on mobile phone data. We then integrate such observations into a reaction- diffusion metapopulation framework. We provide an explicit analytical expression for the global invasion threshold which sets a critical value of the diffusion rate below which a contagion process is not able to spread to a macroscopic fraction of the system. In particular, we consider the Susceptible-Infectious-Recovered epidemic model. Interestingly, the scaling of human contacts is found to facilitate the spreading dynamics. This behavior is enhanced by increasing heterogeneities in the mobility flows coupling the subpopulations. Our results show that the scaling properties of human interactions can significantly affect dynamical processes mediated by human contacts such as the spread of diseases, ideas and behaviors. PMID:26478209

  8. The Scaling of Human Contacts and Epidemic Processes in Metapopulation Networks

    PubMed Central

    Tizzoni, Michele; Sun, Kaiyuan; Benusiglio, Diego; Karsai, Márton; Perra, Nicola

    2015-01-01

    We study the dynamics of reaction-diffusion processes on heterogeneous metapopulation networks where interaction rates scale with subpopulation sizes. We first present new empirical evidence, based on the analysis of the interactions of 13 million users on Twitter, that supports the scaling of human interactions with population size with an exponent γ ranging between 1.11 and 1.21, as observed in recent studies based on mobile phone data. We then integrate such observations into a reaction- diffusion metapopulation framework. We provide an explicit analytical expression for the global invasion threshold which sets a critical value of the diffusion rate below which a contagion process is not able to spread to a macroscopic fraction of the system. In particular, we consider the Susceptible-Infectious-Recovered epidemic model. Interestingly, the scaling of human contacts is found to facilitate the spreading dynamics. This behavior is enhanced by increasing heterogeneities in the mobility flows coupling the subpopulations. Our results show that the scaling properties of human interactions can significantly affect dynamical processes mediated by human contacts such as the spread of diseases, ideas and behaviors. PMID:26478209

  9. Aggregation Processes on Networks: Deterministic Equations, Stochastic Model and Numerical Simulation

    SciTech Connect

    Guias, Flavius

    2008-09-01

    We introduce an infinite system of equations modeling the time evolution of the growth process of a network. The nodes are characterized by their degree k(set-membership sign)N and a fitness parameter f(set-membership sign)[0,h]. Every new node which emerges becomes a fitness f' according to a given distribution P and attaches to an existing node with fitness f and degree k at rate fA{sub k}, where A{sub k} are positive coefficients, growing sub-linearly in k. If the parameter f takes only one value, the dynamics of this process can be described by a variant of the Becker-Doering equations, where the l growth of the size of clusters of size k occurs only with increment 1. In contrast l to the established Becker-Doering equations, the system considered here is nonconservative, since mass (i.e. links) is continuously added. Nevertheless, it has the property of linearity, which is a natural consequence of the process which is being modeled. The purpose of this paper is to construct a solution of the system based on a stochastic approximation algorithm, which allows also a numerical simulation in order to get insight into its qualitative behaviour. In particular we show analytically and numerically the property of Bose-Einstein condensation, which was observed in the literature on random graphs and which can be described as an emergence of a huge cluster which captures a macroscopic fraction of the total link density.

  10. Connectivity of the subthalamic nucleus and globus pallidus pars interna to regions within the speech network: a meta-analytic connectivity study.

    PubMed

    Manes, Jordan L; Parkinson, Amy L; Larson, Charles R; Greenlee, Jeremy D; Eickhoff, Simon B; Corcos, Daniel M; Robin, Donald A

    2014-07-01

    Cortico-basal ganglia connections are involved in a range of behaviors within motor, cognitive, and emotional domains; however, the whole-brain functional connections of individual nuclei are poorly understood in humans. The first aim of this study was to characterize and compare the connectivity of the subthalamic nucleus (STN) and globus pallidus pars interna (GPi) using meta-analytic connectivity modeling. Structure-based activation likelihood estimation meta-analyses were performed for STN and GPi seeds using archived functional imaging coordinates from the BrainMap database. Both regions coactivated with caudate, putamen, thalamus, STN, GPi, and GPe, SMA, IFG, and insula. Contrast analyses also revealed coactivation differences within SMA, IFG, insula, and premotor cortex. The second aim of this study was to examine the degree of overlap between the connectivity maps derived for STN and GPi and a functional activation map representing the speech network. To do this, we examined the intersection of coactivation maps and their respective contrasts (STN > GPi and GPi > STN) with a coordinate-based meta-analysis of speech function. In conjunction with the speech map, both STN and GPi coactivation maps revealed overlap in the anterior insula with GPi map additionally showing overlap in the supplementary motor area (SMA). Among cortical regions activated by speech tasks, STN was found to have stronger connectivity than GPi with regions involved in cognitive linguistic processes (pre-SMA, dorsal anterior insula, and inferior frontal gyrus), while GPi demonstrated stronger connectivity to regions involved in motor speech processes (middle insula, SMA, and premotor cortex). PMID:25050431

  11. Pre-PCR processing in bioterrorism preparedness: improved diagnostic capabilities for laboratory response networks.

    PubMed

    Hedman, Johannes; Knutsson, Rickard; Ansell, Ricky; Rådström, Peter; Rasmusson, Birgitta

    2013-09-01

    Diagnostic DNA analysis using polymerase chain reaction (PCR) has become a valuable tool for rapid detection of biothreat agents. However, analysis is often challenging because of the limited size, quality, and purity of the biological target. Pre-PCR processing is an integrated concept in which the issues of analytical limit of detection and simplicity for automation are addressed in all steps leading up to PCR amplification--that is, sampling, sample treatment, and the chemical composition of PCR. The sampling method should maximize target uptake and minimize uptake of extraneous substances that could impair the analysis--so-called PCR inhibitors. In sample treatment, there is a trade-off between yield and purity, as extensive purification leads to DNA loss. A cornerstone of pre-PCR processing is to apply DNA polymerase-buffer systems that are tolerant to specific sample impurities, thereby lowering the need for expensive purification steps and maximizing DNA recovery. Improved awareness among Laboratory Response Networks (LRNs) regarding pre-PCR processing is important, as ineffective sample processing leads to increased cost and possibly false-negative or ambiguous results, hindering the decision-making process in a bioterrorism crisis. This article covers the nature and mechanisms of PCR-inhibitory substances relevant for agroterrorism and bioterrorism preparedness, methods for quality control of PCR reactions, and applications of pre-PCR processing to optimize and simplify the analysis of various biothreat agents. Knowledge about pre-PCR processing will improve diagnostic capabilities of LRNs involved in the response to bioterrorism incidents.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Cascading processes on multiplex networks: Impact of weak layers

    NASA Astrophysics Data System (ADS)

    Lee, Kyu-Min; Goh, Kwang-Il

    Many real-world complex systems such as biological and socio-technological systems consist of manifold layers in multiplex networks. The multiple network layers give rise to the nonlinear effect for the emergent dynamics of systems. Especially, the weak layers plays the significant role in nonlinearity of multiplex networks, which can be neglected in single-layer network framework overlaying all layers. Here we present a simple model of cascades on multiplex networks of heterogeneous layers. The model is simulated on the multiplex network of international trades. We found that the multiplex model produces more catastrophic cascading failures which were the result of collective behaviors from coupling layers rather than the simple summation effect. Therefore risks can be systematically underestimated in simply overlaid network system because the impact of weak layers is overlooked. Our simple theoretical model would have some implications to investigate and design optimal real-world complex systems.

  14. Toward the automation of road networks extraction processes

    NASA Astrophysics Data System (ADS)

    Leymarie, Frederic; Boichis, Nicolas; Airault, Sylvain; Jamet, Olivier

    1996-12-01

    Syseca and IGN are working on various steps in the ongoing march from digital photogrammetry to the semi-automation and ultimately the full automation of data manipulation, i.e., capture and analysis. The immediate goals are to reduce the production costs and the data availability delays. Within this context, we have tackle the distinctive problem of 'automated road network extraction.' The methodology adopted is to first study semi-automatic solutions which probably increase the global efficiency of human operators in topographic data capture; in a second step, automatic solutions are designed based upon the gained experience. We report on different (semi-)automatic solutions for the road following algorithm. One key aspect of our method is to have the stages of 'detection' and 'geometric recovery' cooperate together while remaining distinct. 'Detection' is based on a local (texture) analysis of the image, while 'geometric recovery' is concerned with the extraction of 'road objects' for both monocular and stereo information. 'Detection' is a low-level visual process, 'reasoning' directly at the level of image intensities, while the mid-level visual process, 'geometric recovery', uses contextual knowledge about roads, both generic, e.g. parallelism of borders, and specific, e.g. using previously extracted road segments and disparities. We then pursue our 'march' by reporting on steps we are exploring toward full automation. We have in particular made attempts at tackling the automation of the initialization step to start searching in a valid direction.

  15. High level cognitive information processing in neural networks

    NASA Technical Reports Server (NTRS)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

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

    PubMed

    Kermajani, Hamidreza; Gomez, Carles

    2014-07-07

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

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

    PubMed

    Kermajani, Hamidreza; Gomez, Carles

    2014-01-01

    The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently developed by the Internet Engineering Task Force (IETF). Given its crucial role in enabling the Internet of Things, a significant amount of research effort has already been devoted to RPL. However, the RPL network convergence process has not yet been investigated in detail. In this paper we study the influence of the main RPL parameters and mechanisms on the network convergence process of this protocol in IEEE 802.15.4 multihop networks. We also propose and evaluate a mechanism that leverages an option available in RPL for accelerating the network convergence process. We carry out extensive simulations for a wide range of conditions, considering different network scenarios in terms of size and density. Results show that network convergence performance depends dramatically on the use and adequate configuration of key RPL parameters and mechanisms. The findings and contributions of this work provide a RPL configuration guideline for network convergence performance tuning, as well as a characterization of the related performance trade-offs. PMID:25004154

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

    PubMed Central

    Kermajani, Hamidreza; Gomez, Carles

    2014-01-01

    The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently developed by the Internet Engineering Task Force (IETF). Given its crucial role in enabling the Internet of Things, a significant amount of research effort has already been devoted to RPL. However, the RPL network convergence process has not yet been investigated in detail. In this paper we study the influence of the main RPL parameters and mechanisms on the network convergence process of this protocol in IEEE 802.15.4 multihop networks. We also propose and evaluate a mechanism that leverages an option available in RPL for accelerating the network convergence process. We carry out extensive simulations for a wide range of conditions, considering different network scenarios in terms of size and density. Results show that network convergence performance depends dramatically on the use and adequate configuration of key RPL parameters and mechanisms. The findings and contributions of this work provide a RPL configuration guideline for network convergence performance tuning, as well as a characterization of the related performance trade-offs. PMID:25004154

  19. [Discussion on Quality Evaluation Method of Medical Device During Life-Cycle in Operation Based on the Analytic Hierarchy Process].

    PubMed

    Zheng, Caixian; Zheng, Kun; Shen, Yunming; Wu, Yunyun

    2016-01-01

    The content related to the quality during life-cycle in operation of medical device includes daily use, repair volume, preventive maintenance, quality control and adverse event monitoring. In view of this, the article aims at discussion on the quality evaluation method of medical devices during their life cycle in operation based on the Analytic Hierarchy Process (AHP). The presented method is proved to be effective by evaluating patient monitors as example. The method presented in can promote and guide the device quality control work, and it can provide valuable inputs to decisions about purchase of new device. PMID:27197489

  20. Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

    PubMed

    da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

    2005-01-01

    This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment.

  1. Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

    PubMed

    da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

    2005-01-01

    This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment. PMID:17281912

  2. A Semi-Analytic Study of Feedback Processes and Metallicity Profiles in Disc Galaxies

    NASA Astrophysics Data System (ADS)

    Sandford, Nathan Ross; Lu, Yu

    2016-01-01

    The metallicity gradients of disc galaxies contain valuable information about the physics governing their formation and evolution. The observed metallicity profiles have negative gradients that are steeper at high redshifts, indicating an inside-out formation of disc galaxies. We improve on our semi-analytic galaxy formation model (Lu, Mo & Wechsler 2015) by incorporating the radial distribution of metals into the model. With the improved model, we explore how feedback scenarios affect metallicity gradients. The model features 3 feedback scenarios: An Ejective (EJ) model, which includes ejective supernova (SN) feedback, a PRe-Heating (PR) model, which assumes that the intergalactic medium is preheated, preventing it from collapsing onto galaxies, and a Re-Incorporation (RI) model, which also includes strong outflows but allows ejected gas to re-accrete onto the galaxies. We compare the models with observations from Ho et al. (2015) and find that while all models struggle to match the observed metallicity gradient-stellar mass relationship, the PR model predicts metallicity gradients that best match observations. We also find that the RI model predicts a flat gradient because its outflow and re-accretion replenish the disc uniformly with newly accreted enriched gas, erasing the mark of inside-out formation. Our findings suggest feedback plays a key role in shaping the metallicity gradients of disc galaxies and require more detailed theoretical modeling to understand them.

  3. Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics

    PubMed Central

    Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S.-Y.; Assam, Pryseley N.; Claridge-Chang, Adam

    2015-01-01

    Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms. PMID:26647168

  4. Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

    PubMed

    Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S-Y; Assam, Pryseley N; Claridge-Chang, Adam

    2015-12-01

    Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms. PMID:26647168

  5. Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

    NASA Astrophysics Data System (ADS)

    Brennan, Sean R.; Torgersen, Christian E.; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K.; Schindler, Daniel E.

    2016-05-01

    A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called "isoscapes," form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

  6. Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

    USGS Publications Warehouse

    Brennan, Sean R.; Torgersen, Christian; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K; Schindler, Daniel E.

    2016-01-01

    A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

  7. Technosocial Predictive Analytics for Illicit Nuclear Trafficking

    SciTech Connect

    Sanfilippo, Antonio P.; Butner, R. Scott; Cowell, Andrew J.; Dalton, Angela C.; Haack, Jereme N.; Kreyling, Sean J.; Riensche, Roderick M.; White, Amanda M.; Whitney, Paul D.

    2011-03-29

    Illicit nuclear trafficking networks are a national security threat. These networks can directly lead to nuclear proliferation, as state or non-state actors attempt to identify and acquire nuclear weapons-related expertise, technologies, components, and materials. The ability to characterize and anticipate the key nodes, transit routes, and exchange mechanisms associated with these networks is essential to influence, disrupt, interdict or destroy the function of the networks and their processes. The complexities inherent to the characterization and anticipation of illicit nuclear trafficking networks requires that a variety of modeling and knowledge technologies be jointly harnessed to construct an effective analytical and decision making workflow in which specific case studies can be built in reasonable time and with realistic effort. In this paper, we explore a solution to this challenge that integrates evidentiary and dynamic modeling with knowledge management and analytical gaming, and demonstrate its application to a geopolitical region at risk.

  8. Complex Network Structure Influences Processing in Long-Term and Short-Term Memory

    ERIC Educational Resources Information Center

    Vitevitch, Michael S.; Chan, Kit Ying; Roodenrys, Steven

    2012-01-01

    Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological…

  9. Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks.

    PubMed

    Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

    2014-01-01

    A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits.

  10. Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks

    PubMed Central

    Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

    2014-01-01

    A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic–phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits. PMID:24723897

  11. Resynchronization in neuronal network divided by femtosecond laser processing.

    PubMed

    Hosokawa, Chie; Kudoh, Suguru N; Kiyohara, Ai; Taguchi, Takahisa

    2008-05-01

    We demonstrated scission of a living neuronal network on multielectrode arrays (MEAs) using a focused femtosecond laser and evaluated the resynchronization of spontaneous electrical activity within the network. By an irradiation of femtosecond laser into hippocampal neurons cultured on a multielectrode array dish, neurites were cut at the focal point. After the irradiation, synchronization of neuronal activity within the network drastically decreased over the divided area, indicating diminished functional connections between neurons. Cross-correlation analysis revealed that spontaneous activity between the divided areas gradually resynchronized within 10 days. These findings indicate that hippocampal neurons have the potential to regenerate functional connections and to reconstruct a network by self-assembly. PMID:18418255

  12. Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks.

    PubMed

    Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

    2014-01-01

    A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits. PMID:24723897

  13. Analytical considerations and dimensionless analysis for a description of particle interactions in high pressure processes

    NASA Astrophysics Data System (ADS)

    Rauh, Cornelia; Delgado, Antonio

    2010-12-01

    High pressures of up to several hundreds of MPa are utilized in a wide range of applications in chemical, bio-, and food engineering, aiming at selective control of (bio-)chemical reactions. Non-uniformity of process conditions may threaten the safety and quality of the resulting products because processing conditions such as pressure, temperature, and treatment history are crucial for the course of (bio-)chemical reactions. Therefore, thermofluid-dynamical phenomena during the high pressure process have to be examined, and numerical tools to predict process uniformity and to optimize the processes have to be developed. Recently applied mathematical models and numerical simulations of laboratory and industrial scale high pressure processes investigating the mentioned crucial phenomena are based on continuum balancing models of thermofluid dynamics. Nevertheless, biological systems are complex fluids containing the relevant (bio-)chemical compounds (enzymes and microorganisms). These compounds are particles that interact with the surrounding medium and between each other. This contribution deals with thermofluid-dynamical interactions of the relevant particulate (bio-)chemical compounds (enzymes and microorganisms) with the surrounding fluid. By consideration of characteristic time and length scales and particle forces, the motion of the (bio-)chemical compounds is characterized.

  14. Study of an ultrasound-based process analytical tool for homogenization of nanoparticulate pharmaceutical vehicles.

    PubMed

    Cavegn, Martin; Douglas, Ryan; Akkermans, Guy; Kuentz, Martin

    2011-08-01

    There are currently no adequate process analyzers for nanoparticulate viscosity enhancers. This article aims to evaluate ultrasonic resonator technology as a monitoring tool for homogenization of nanoparticulate gels. Aqueous dispersions of colloidal microcrystalline cellulose (MCC) and a mixture of clay particles with xanthan gum were compared with colloidal silicon dioxide in oil. The processing was conducted using a laboratory-scale homogenizing vessel. The study investigated first the homogenization kinetics of the different systems to focus then on process factors in the case of colloidal MCC. Moreover, rheological properties were analyzed offline to assess the structure of the resulting gels. Results showed the suitability of ultrasound velocimetry to monitor the homogenization process. The obtained data were fitted using a novel heuristic model. It was possible to identify characteristic homogenization times for each formulation. The subsequent study of the process factors demonstrated that ultrasonic process analysis was equally sensitive as offline rheological measurements in detecting subtle manufacturing changes. It can be concluded that the ultrasonic method was able to successfully assess homogenization of nanoparticulate viscosity enhancers. This novel technique can become a vital tool for development and production of pharmaceutical suspensions in the future.

  15. On-board processing satellite network architecture and control study

    NASA Technical Reports Server (NTRS)

    Campanella, S. Joseph; Pontano, B.; Chalmers, H.

    1987-01-01

    For satellites to remain a vital part of future national and international communications, system concepts that use their inherent advantages to the fullest must be created. Network architectures that take maximum advantage of satellites equipped with onboard processing are explored. Satellite generations must accommodate various services for which satellites constitute the preferred vehicle of delivery. Such services tend to be those that are widely dispersed and present thin to medium loads to the system. Typical systems considered are thin and medium route telephony, maritime, land and aeronautical radio, VSAT data, low bit rate video teleconferencing, and high bit rate broadcast of high definition video. Delivery of services by TDMA and FDMA multiplexing techniques and combinations of the two for individual and mixed service types are studied. The possibilities offered by onboard circuit switched and packet switched architectures are examined and the results strongly support a preference for the latter. A detailed design architecture encompassing the onboard packet switch and its control, the related demand assigned TDMA burst structures, and destination packet protocols for routing traffic are presented. Fundamental onboard hardware requirements comprising speed, memory size, chip count, and power are estimated. The study concludes with identification of key enabling technologies and identifies a plan to develop a POC model.

  16. Prediction of plasma processes using neural network and genetic algorithm

    NASA Astrophysics Data System (ADS)

    Kim, Byungwhan; Bae, Jungki

    2005-10-01

    Using genetic algorithm (GA) and backpropagation neural network (BPNN), computer models of plasma processes were constructed. The GA was applied to optimize five training factors simultaneously. The presented technique was evaluated with plasma etch data, characterized by a statistical experimental design. The etching was conducted in an inductively coupled plasma etch system. The etch outputs to model include aluminum (Al) etch rate, Al selectivity, silica profile angle, and DC bias. GA-BPNN models demonstrated improved predictions of more than 20% for all etch outputs but the DC bias. This indicates that a simultaneous optimization of training factors is more effective in improving the prediction performance of BPNN model than a sequential optimization of individual training factor. Compared to GA-BPNN models constructed in a previous training set, the presented models also yielded a much improved prediction of more than 35% for all etch outputs. The proven improvement indicates that the presented training set is more effective to improve GA-BPNN models.

  17. Morphological Processing as We Know It: An Analytical Review of Morphological Effects in Visual Word Identification

    PubMed Central

    Amenta, Simona; Crepaldi, Davide

    2012-01-01

    The last 40 years have witnessed a growing interest in the mechanisms underlying the visual identification of complex words. A large amount of experimental data has been amassed, but although a growing number of studies are proposing explicit theoretical models for their data, no comprehensive theory has gained substantial agreement among scholars in the field. We believe that this is due, at least in part, to the presence of several controversial pieces of evidence in the literature and, consequently, to the lack of a well-defined set of experimental facts that any theory should be able to explain. With this review, we aim to delineate the state of the art in the research on the visual identification of complex words. By reviewing major empirical evidences in a number of different paradigms such as lexical decision, word naming, and masked and unmasked priming, we were able to identify a series of effects that we judge as reliable or that were consistently replicated in different experiments, along with some more controversial data, which we have tried to resolve and explain. We concentrated on behavioral and electrophysiological studies on inflected, derived, and compound words, so as to span over all types of complex words. The outcome of this work is an analytical summary of well-established facts on the most relevant morphological issues, such as regularity, morpheme position coding, family size, semantic transparency, morpheme frequency, suffix allomorphy, and productivity, morphological entropy, and morpho-orthographic parsing. In discussing this set of benchmark effects, we have drawn some methodological considerations on why contrasting evidence might have emerged, and have tried to delineate a target list for the construction of a new all-inclusive model of the visual identification of morphologically complex words. PMID:22807919

  18. Applying decision-making tools to national e-waste recycling policy: an example of Analytic Hierarchy Process.

    PubMed

    Lin, Chun-Hsu; Wen, Lihchyi; Tsai, Yue-Mi

    2010-05-01

    As policy making is in essence a process of discussion, decision-making tools have in many cases been proposed to resolve the differences of opinion among the different parties. In our project that sought to promote a country's performance in recycling, we used the Analytic Hierarchy Process (AHP) to evaluate the possibilities and determine the priority of the addition of new mandatory recycled waste, also referred to as Due Recycled Wastes, from candidate waste appliances. The evaluation process started with the collection of data based on telephone interviews and field investigations to understand the behavior of consumers as well as their overall opinions regarding the disposal of certain waste appliances. With the data serving as background information, the research team then implemented the Analytic Hierarchy Process using the information that formed an incomplete hierarchy structure in order to determine the priority for recycling. Since the number of objects to be evaluated exceeded the number that the AHP researchers had suggested, we reclassified the objects into four groups and added one more level of pair-wise comparisons, which substantially reduced the inconsistency in the judgment of the AHP participants. The project was found to serve as a flexible and achievable application of AHP to the environmental policy-making process. In addition, based on the project's outcomes derived from the project as a whole, the research team drew conclusions regarding the government's need to take back 15 of the items evaluated, and suggested instruments that could be used or recycling regulations that could be changed in the future. Further analysis on the top three items recommended by the results of the evaluation for recycling, namely, Compact Disks, Cellular Phones and Computer Keyboards, was then conducted to clarify their concrete feasibility. After the trial period for recycling ordered by the Taiwan Environmental Protection Administration, only Computer

  19. Applying decision-making tools to national e-waste recycling policy: an example of Analytic Hierarchy Process.

    PubMed

    Lin, Chun-Hsu; Wen, Lihchyi; Tsai, Yue-Mi

    2010-05-01

    As policy making is in essence a process of discussion, decision-making tools have in many cases been proposed to resolve the differences of opinion among the different parties. In our project that sought to promote a country's performance in recycling, we used the Analytic Hierarchy Process (AHP) to evaluate the possibilities and determine the priority of the addition of new mandatory recycled waste, also referred to as Due Recycled Wastes, from candidate waste appliances. The evaluation process started with the collection of data based on telephone interviews and field investigations to understand the behavior of consumers as well as their overall opinions regarding the disposal of certain waste appliances. With the data serving as background information, the research team then implemented the Analytic Hierarchy Process using the information that formed an incomplete hierarchy structure in order to determine the priority for recycling. Since the number of objects to be evaluated exceeded the number that the AHP researchers had suggested, we reclassified the objects into four groups and added one more level of pair-wise comparisons, which substantially reduced the inconsistency in the judgment of the AHP participants. The project was found to serve as a flexible and achievable application of AHP to the environmental policy-making process. In addition, based on the project's outcomes derived from the project as a whole, the research team drew conclusions regarding the government's need to take back 15 of the items evaluated, and suggested instruments that could be used or recycling regulations that could be changed in the future. Further analysis on the top three items recommended by the results of the evaluation for recycling, namely, Compact Disks, Cellular Phones and Computer Keyboards, was then conducted to clarify their concrete feasibility. After the trial period for recycling ordered by the Taiwan Environmental Protection Administration, only Computer

  20. Learning Process of a Stochastic Feed-Forward Neural Network

    NASA Astrophysics Data System (ADS)

    Fujiki, Sumiyoshi; Fujiki, Nahomi

    1995-03-01

    A positive reinforcement type learning algorithm is formulated for a stochastic feed-forward neural network by minimizing a relative entropic measure, and a learning equation similar to that of the Boltzmann machine is obtained. The learning of the network actually shows a similar result to that of the Boltzmann machine in the classification problems of AND and XOR, by numerical experiments.

  1. Modeling the School System Adoption Process for Library Networking.

    ERIC Educational Resources Information Center

    Kester, Diane Katherine Davies

    The successful inclusion of school library media centers in fully articulated networks involves considerable planning and organization for technological change. In this study a preliminary model of the stages of school system participation in library networks was developed with the major activities for each stage identified. The model follows…

  2. Evaluation of the effect of a health education campaign of HIV by using an analytical hierarchy process method.

    PubMed

    Tan, Xiaodong; Lin, Jianyan; Wang, Fengjie; Luo, Hong; Luo, Lan; Wu, Lei

    2007-09-01

    This study was designed to understand the status of HIV/AIDS knowledge, attitude and practice (KAP) among different populations and to provide scientific evidences for further health education. Three rounds of questionnaires were administered among service industry workers who were selected through stratified cluster sampling. Study subjects included hotel attendants, employees of beauty parlors and service workers of transportation industry. Data were analyzed using the analytical hierarchy process. All demonstrated high KAP overall. Synthetic scoring indexes of the three surveys were above 75%. However, the correct response rate on questions whether mosquito bite can transmit HIV/AIDS and what is the relationship between STD with HIV was unsatisfactory (lower than expected); and their attitudes towards people living with HIV and AIDS need to be improved. Moreover, the effect of health education on these groups was unclear. In conclusion, analytical hierarchy process is a valid method in estimating overall effect of HIV/AIDS health education. Although the present status of HIV/AIDS KAP among the service industry workers was relatively good, greater efforts should be made to improve their HIV transmission knowledge, attitude and understanding of the relationship between STDs and HIV.

  3. MALDI based identification of soybean protein markers--possible analytical targets for allergen detection in processed foods.

    PubMed

    Cucu, Tatiana; De Meulenaer, Bruno; Devreese, Bart

    2012-02-01

    Soybean (Glycine max) is extensively used all over the world due to its nutritional qualities. However, soybean is included in the "big eight" list of food allergens. According to the EU directive 2007/68/EC, food products containing soybeans have to be labeled in order to protect the allergic consumers. Nevertheless, soybeans can still inadvertently be present in food products. The development of analytical methods for the detection of traces of allergens is important for the protection of allergic consumers. Mass spectrometry of marker proteolytical fragments of protein allergens is growingly recognized as a detection method in food control. However, quantification of soybean at the peptide level is hindered due to limited information regarding specific stable markers derived after proteolytic digestion. The aim of this study was to use MALDI-TOF/MS and MS/MS as a fast screening tool for the identification of stable soybean derived tryptic markers which were still identifiable even if the proteins were subjected to various changes at the molecular level through a number of reactions typically occurring during food processing (denaturation, the Maillard reaction and oxidation). The peptides (401)Val-Arg(410) from the G1 glycinin (Gly m 6) and the (518)Gln-Arg(528) from the α' chain of the β-conglycinin (Gly m 5) proved to be the most stable. These peptides hold potential to be used as targets for the development of new analytical methods for the detection of soybean protein traces in processed foods. PMID:22212959

  4. MALDI based identification of soybean protein markers--possible analytical targets for allergen detection in processed foods.

    PubMed

    Cucu, Tatiana; De Meulenaer, Bruno; Devreese, Bart

    2012-02-01

    Soybean (Glycine max) is extensively used all over the world due to its nutritional qualities. However, soybean is included in the "big eight" list of food allergens. According to the EU directive 2007/68/EC, food products containing soybeans have to be labeled in order to protect the allergic consumers. Nevertheless, soybeans can still inadvertently be present in food products. The development of analytical methods for the detection of traces of allergens is important for the protection of allergic consumers. Mass spectrometry of marker proteolytical fragments of protein allergens is growingly recognized as a detection method in food control. However, quantification of soybean at the peptide level is hindered due to limited information regarding specific stable markers derived after proteolytic digestion. The aim of this study was to use MALDI-TOF/MS and MS/MS as a fast screening tool for the identification of stable soybean derived tryptic markers which were still identifiable even if the proteins were subjected to various changes at the molecular level through a number of reactions typically occurring during food processing (denaturation, the Maillard reaction and oxidation). The peptides (401)Val-Arg(410) from the G1 glycinin (Gly m 6) and the (518)Gln-Arg(528) from the α' chain of the β-conglycinin (Gly m 5) proved to be the most stable. These peptides hold potential to be used as targets for the development of new analytical methods for the detection of soybean protein traces in processed foods.

  5. Processing and quantification of x-ray energy dispersive spectra in the Analytical Electron Microscope

    SciTech Connect

    Zaluzec, N.J.

    1988-08-01

    Spectral processing in x-ray energy dispersive spectroscopy deals with the extraction of characteristic signals from experimental data. In this text, the four basic procedures for this methodology are reviewed and their limitations outlined. Quantification, on the other hand, deals with the interpretation of the information obtained from spectral processing. Here the limitations are for the most part instrumental in nature. The prospects of higher voltage operation does not, in theory, present any new problems and may in fact prove to be more desirable assuming that electron damage effects do not preclude analysis. 28 refs., 6 figs.

  6. Decision making using AHP (Analytic Hierarchy Process) and fuzzy set theory in waste management

    SciTech Connect

    Chung, J.Y.; Lee, K.J.; Kim, C.D.

    1995-12-31

    The major problem is how to consider the differences in opinions, when many experts are involved in decision making process. This paper provides a simple general methodology to treat the differences in various opinions. The authors determined the grade of membership through the process of magnitude estimation derived from pairwise comparisons and AHP developed by Saaty. They used fuzzy set theory to consider the differences in opinions and obtain the priorities for each alternative. An example, which can be applied to radioactive waste management, also was presented. The result shows a good agreement with the results of averaging methods.

  7. A unified framework of interplay between two spreading processes in multiplex networks

    NASA Astrophysics Data System (ADS)

    Wei, Xiang; Chen, Shihua; Wu, Xiaoqun; Feng, Jianwen; Lu, Jun-an

    2016-04-01

    Different spreading processes may interplay and display rich intertwined effects in multiplex networks. In this study, a model is proposed that consists of a two-layer network and two spreading processes respectively spread by each layer. The proposed framework can unify three scenarios for various mutual influences between the two spreading processes. The epidemic thresholds of interacting networks are contrasted and proven using the corresponding isolated networks for three scenarios: competing spreading processes, cooperative spreading processes and the combination of the two. The following conclusions resulted from this work with these three scenarios. First, the epidemic threshold of the interacting two-layer networks can be increased for two competing spreading processes; second, the epidemic threshold of the interacting two-layer networks can be decreased for two cooperative spreading processes; third, when the spreading process in one layer restrains the spreading process in the other layer, and the spreading process in the latter reinforces that in the former, the epidemic threshold of the former layer can be increased and that of the latter layer can be decreased for the interacting networks in comparison to the corresponding isolated networks. Simulations accurately verified the stated results.

  8. Analytical study of space processing of immiscible materials for superconductors and electrical contacts

    NASA Technical Reports Server (NTRS)

    Gelles, S. H.; Collings, E. W.; Abbott, W. H.; Maringer, R. E.

    1977-01-01

    The results of a study conducted to determine the role space processing or materials research in space plays in the superconductor and electrical contact industries are presented. Visits were made to manufacturers, users, and research organizations connected with these products to provide information about the potential benefits of the space environment and to exchange views on the utilization of space facilities for manufacture, process development, or research. In addition, space experiments were suggested which could result in improved terrestrial processes or products. Notable examples of these are, in the case of superconductors, the development of Nb-bronze alloys (Tsuei alloys) and, in the electrical contact field, the production of Ag-Ni or Ag-metal oxide alloys with controlled microstructure for research and development activities as well as for product development. A preliminary experimental effort to produce and evaluate rapidly cooled Pb-Zn and Cu-Nb-Sn alloys in order to understand the relationship between microstructure and superconducting properties and to simulate the fine structure potentially achievable by space processing was also described.

  9. An Objective Approach to Faculty Promotion and Tenure by the Analytical Hierarchy Process.

    ERIC Educational Resources Information Center

    Saaty, Thomas L.; Ramanujam, Vasudevan

    1983-01-01

    A faculty evaluation system that classified performance factors within a hierarchy and weights each, producing a final composite set for each faculty member, is explained and illustrated. The process is recommended for more objective and consistent decision-making about faculty tenure. (MSE)

  10. Effects of video-game play on information processing: a meta-analytic investigation.

    PubMed

    Powers, Kasey L; Brooks, Patricia J; Aldrich, Naomi J; Palladino, Melissa A; Alfieri, Louis

    2013-12-01

    Do video games enhance cognitive functioning? We conducted two meta-analyses based on different research designs to investigate how video games impact information-processing skills (auditory processing, executive functions, motor skills, spatial imagery, and visual processing). Quasi-experimental studies (72 studies, 318 comparisons) compare habitual gamers with controls; true experiments (46 studies, 251 comparisons) use commercial video games in training. Using random-effects models, video games led to improved information processing in both the quasi-experimental studies, d = 0.61, 95% CI [0.50, 0.73], and the true experiments, d = 0.48, 95% CI [0.35, 0.60]. Whereas the quasi-experimental studies yielded small to large effect sizes across domains, the true experiments yielded negligible effects for executive functions, which contrasted with the small to medium effect sizes in other domains. The quasi-experimental studies appeared more susceptible to bias than were the true experiments, with larger effects being reported in higher-tier than in lower-tier journals, and larger effects reported by the most active research groups in comparison with other labs. The results are further discussed with respect to other moderators and limitations in the extant literature. PMID:23519430

  11. Effects of video-game play on information processing: a meta-analytic investigation.

    PubMed

    Powers, Kasey L; Brooks, Patricia J; Aldrich, Naomi J; Palladino, Melissa A; Alfieri, Louis

    2013-12-01

    Do video games enhance cognitive functioning? We conducted two meta-analyses based on different research designs to investigate how video games impact information-processing skills (auditory processing, executive functions, motor skills, spatial imagery, and visual processing). Quasi-experimental studies (72 studies, 318 comparisons) compare habitual gamers with controls; true experiments (46 studies, 251 comparisons) use commercial video games in training. Using random-effects models, video games led to improved information processing in both the quasi-experimental studies, d = 0.61, 95% CI [0.50, 0.73], and the true experiments, d = 0.48, 95% CI [0.35, 0.60]. Whereas the quasi-experimental studies yielded small to large effect sizes across domains, the true experiments yielded negligible effects for executive functions, which contrasted with the small to medium effect sizes in other domains. The quasi-experimental studies appeared more susceptible to bias than were the true experiments, with larger effects being reported in higher-tier than in lower-tier journals, and larger effects reported by the most active research groups in comparison with other labs. The results are further discussed with respect to other moderators and limitations in the extant literature.

  12. Development of process parameters for 22 nm PMOS using 2-D analytical modeling

    SciTech Connect

    Maheran, A. H. Afifah; Menon, P. S.; Shaari, S.; Ahmad, I.; Faizah, Z. A. Noor

    2015-04-24

    The complementary metal-oxide-semiconductor field effect transistor (CMOSFET) has become major challenge to scaling and integration. Innovation in transistor structures and integration of novel materials are necessary to sustain this performance trend. CMOS variability in the scaling technology becoming very important concern due to limitation of process control; over statistically variability related to the fundamental discreteness and materials. Minimizing the transistor variation through technology optimization and ensuring robust product functionality and performance is the major issue.In this article, the continuation study on process parameters variations is extended and delivered thoroughly in order to achieve a minimum leakage current (I{sub LEAK}) on PMOS planar transistor at 22 nm gate length. Several device parameters are varies significantly using Taguchi method to predict the optimum combination of process parameters fabrication. A combination of high permittivity material (high-k) and metal gate are utilized accordingly as gate structure where the materials include titanium dioxide (TiO{sub 2}) and tungsten silicide (WSi{sub x}). Then the L9 of the Taguchi Orthogonal array is used to analyze the device simulation where the results of signal-to-noise ratio (SNR) of Smaller-the-Better (STB) scheme are studied through the percentage influences of the process parameters. This is to achieve a minimum I{sub LEAK} where the maximum predicted I{sub LEAK} value by International Technology Roadmap for Semiconductors (ITRS) 2011 is said to should not above 100 nA/µm. Final results shows that the compensation implantation dose acts as the dominant factor with 68.49% contribution in lowering the device’s leakage current. The absolute process parameters combination results in I{sub LEAK} mean value of 3.96821 nA/µm where is far lower than the predicted value.

  13. Development of process parameters for 22 nm PMOS using 2-D analytical modeling

    NASA Astrophysics Data System (ADS)

    Maheran, A. H. Afifah; Menon, P. S.; Ahmad, I.; Shaari, S.; Faizah, Z. A. Noor

    2015-04-01

    The complementary metal-oxide-semiconductor field effect transistor (CMOSFET) has become major challenge to scaling and integration. Innovation in transistor structures and integration of novel materials are necessary to sustain this performance trend. CMOS variability in the scaling technology becoming very important concern due to limitation of process control; over statistically variability related to the fundamental discreteness and materials. Minimizing the transistor variation through technology optimization and ensuring robust product functionality and performance is the major issue.In this article, the continuation study on process parameters variations is extended and delivered thoroughly in order to achieve a minimum leakage current (ILEAK) on PMOS planar transistor at 22 nm gate length. Several device parameters are varies significantly using Taguchi method to predict the optimum combination of process parameters fabrication. A combination of high permittivity material (high-k) and metal gate are utilized accordingly as gate structure where the materials include titanium dioxide (TiO2) and tungsten silicide (WSix). Then the L9 of the Taguchi Orthogonal array is used to analyze the device simulation where the results of signal-to-noise ratio (SNR) of Smaller-the-Better (STB) scheme are studied through the percentage influences of the process parameters. This is to achieve a minimum ILEAK where the maximum predicted ILEAK value by International Technology Roadmap for Semiconductors (ITRS) 2011 is said to should not above 100 nA/µm. Final results shows that the compensation implantation dose acts as the dominant factor with 68.49% contribution in lowering the device's leakage current. The absolute process parameters combination results in ILEAK mean value of 3.96821 nA/µm where is far lower than the predicted value.

  14. Landfill site selection using geographic information system and analytical hierarchy process: A case study Al-Hillah Qadhaa, Babylon, Iraq.

    PubMed

    Chabuk, Ali; Al-Ansari, Nadhir; Hussain, Hussain Musa; Knutsson, Sven; Pusch, Roland

    2016-05-01

    Al-Hillah Qadhaa is located in the central part of Iraq. It covers an area of 908 km(2) with a total population of 856,804 inhabitants. This Qadhaa is the capital of Babylon Governorate. Presently, no landfill site exists in that area based on scientific site selection criteria. For this reason, an attempt has been carried out to find the best locations for landfills. A total of 15 variables were considered in this process (groundwater depth, rivers, soil types, agricultural land use, land use, elevation, slope, gas pipelines, oil pipelines, power lines, roads, railways, urban centres, villages and archaeological sites) using a geographic information system. In addition, an analytical hierarchy process was used to identify the weight for each variable. Two suitable candidate landfill sites were determined that fulfil the requirements with an area of 9.153 km(2) and 8.204 km(2) These sites can accommodate solid waste till 2030.

  15. Students' Personal Networks in Virtual and Personal Learning Environments: A Case Study in Higher Education Using Learning Analytics Approach

    ERIC Educational Resources Information Center

    Casquero, Oskar; Ovelar, Ramón; Romo, Jesús; Benito, Manuel; Alberdi, Mikel

    2016-01-01

    The main objective of this paper is to analyse the effect of the affordances of a virtual learning environment and a personal learning environment (PLE) in the configuration of the students' personal networks in a higher education context. The results are discussed in light of the adaptation of the students to the learning network made up by two…

  16. Using Graph-Based Assessments within Socratic Tutorials to Reveal and Refine Students' Analytical Thinking about Molecular Networks

    ERIC Educational Resources Information Center

    Trujillo, Caleb; Cooper, Melanie M.; Klymkowsky, Michael W.

    2012-01-01

    Biological systems, from the molecular to the ecological, involve dynamic interaction networks. To examine student thinking about networks we used graphical responses, since they are easier to evaluate for implied, but unarticulated assumptions. Senior college level molecular biology students were presented with simple molecular level scenarios;…

  17. Analytical methods and monitoring system for E-beam flue gas treatment process

    NASA Astrophysics Data System (ADS)

    Licki, J.; Chmielewski, A. G.; Iller, E.; Zakrzewska-Trznadel, G.; Tokunaga, O.; Hashimoto, S.

    1998-06-01

    The results of reliable and precise measurement of gas composition in different key points of e-beam installation are necessary for its proper operation and control. Only the composition of flue gas coming into installation is adequate to composition of flue gas emitted from coal-fired boiler. At other points of e-b installation the gas composition is strongly modified by process conditions therefore specific measuring system (sampling and conditioning system and set of gas analyzers) for its determination are required. In the paper system for gas composition measurement at inlet and outlet of e-b installation are described. Process parameters are continuously monitoring by CEM system and occasionally by the grab sample system. Both system have been tested at pilot plant at EPS Kawȩczyn.

  18. Decision making software for effective selection of treatment train alternative for wastewater using analytical hierarchy process.

    PubMed

    Prasad, A D; Tembhurkar, A R

    2013-10-01

    Proper selection of treatment process and synthesis of treatment train is complex engineering activity requires crucial decision making during planning and designing of any Wastewater Treatment Plant (WWTP). Earlier studies on process selection mainly considered cost as the most important selection criteria and number of studies focused on cost optimization models using dynamic programming, geometric programming and nonlinear programming. However, it has been noticed that traditional cost analysis alone cannot be applied to evaluate Treatment Train (TT) alternatives, as number of important non-tangible factors cannot be easily expressed in monetary units. Recently researches focus on use of multi-criteria technique for selection of treatment process. AHP provides a powerful tool for multi-hierarchy and multi-variable system overcoming limitation of traditional techniques. The AHP model designed to facilitate proper decision making and reduce the margin of errors during optimization due to number of parameters in the hierarchy levels has been used in this study. About 14 important factors and 13 sub factors were identified for the selection of treatment alternatives for wastewater and sludge stream although cost is one of the most important selection criteria. The present paper provides details of developing a soft-tool called "ProSelArt" using an AHP model aiding for proper decision making. PMID:25906585

  19. Implementation of an Analytical Raman Scattering Correction for Satellite Ocean-Color Processing

    NASA Technical Reports Server (NTRS)

    McKinna, Lachlan I. W.; Werdell, P. Jeremy; Proctor, Christopher W.

    2016-01-01

    Raman scattering of photons by seawater molecules is an inelastic scattering process. This effect can contribute significantly to the water-leaving radiance signal observed by space-borne ocean-color spectroradiometers. If not accounted for during ocean-color processing, Raman scattering can cause biases in derived inherent optical properties (IOPs). Here we describe a Raman scattering correction (RSC) algorithm that has been integrated within NASA's standard ocean-color processing software. We tested the RSC with NASA's Generalized Inherent Optical Properties algorithm (GIOP). A comparison between derived IOPs and in situ data revealed that the magnitude of the derived backscattering coefficient and the phytoplankton absorption coefficient were reduced when the RSC was applied, whilst the absorption coefficient of colored dissolved and detrital matter remained unchanged. Importantly, our results show that the RSC did not degrade the retrieval skill of the GIOP. In addition, a timeseries study of oligotrophic waters near Bermuda showed that the RSC did not introduce unwanted temporal trends or artifacts into derived IOPs.

  20. Implementation of an analytical Raman scattering correction for satellite ocean-color processing.

    PubMed

    McKinna, Lachlan I W; Werdell, P Jeremy; Proctor, Christopher W

    2016-07-11

    Raman scattering of photons by seawater molecules is an inelastic scattering process. This effect can contribute significantly to the water-leaving radiance signal observed by space-borne ocean-color spectroradiometers. If not accounted for during ocean-color processing, Raman scattering can cause biases in derived inherent optical properties (IOPs). Here we describe a Raman scattering correction (RSC) algorithm that has been integrated within NASA's standard ocean-color processing software. We tested the RSC with NASA's Generalized Inherent Optical Properties algorithm (GIOP). A comparison between derived IOPs and in situ data revealed that the magnitude of the derived backscattering coefficient and the phytoplankton absorption coefficient were reduced when the RSC was applied, whilst the absorption coefficient of colored dissolved and detrital matter remained unchanged. Importantly, our results show that the RSC did not degrade the retrieval skill of the GIOP. In addition, a time-series study of oligotrophic waters near Bermuda showed that the RSC did not introduce unwanted temporal trends or artifacts into derived IOPs.

  1. Active content determination of pharmaceutical tablets using near infrared spectroscopy as Process Analytical Technology tool.

    PubMed

    Chavez, Pierre-François; Sacré, Pierre-Yves; De Bleye, Charlotte; Netchacovitch, Lauranne; Mantanus, Jérôme; Motte, Henri; Schubert, Martin; Hubert, Philippe; Ziemons, Eric

    2015-11-01

    The aim of this study was to develop Near infrared (NIR) methods to determine the active content of non-coated pharmaceutical tablets manufactured from a proportional tablet formulation. These NIR methods intend to be used for the monitoring of the active content of tablets during the tableting process. Firstly, methods were developed in transmission and reflection modes to quantify the API content of the lowest dosage strength. Secondly, these methods were fully validated for a concentration range of 70-130% of the target active content using the accuracy profile approach based on β-expectation tolerance intervals. The model using the transmission mode showed a better ability to predict the right active content compared to the reflection one. However, the ability of the reflection mode to quantify the API content in the highest dosage strength was assessed. Furthermore, the NIR method based on the transmission mode was successfully used to monitor at-line the tablet active content during the tableting process, providing better insight of the API content during the process. This improvement of control of the product quality provided by this PAT method is thoroughly compliant with the Quality by Design (QbD) concept. Finally, the transfer of the transmission model from the off-line to an on-line spectrometer was efficiently investigated. PMID:26452969

  2. Active content determination of pharmaceutical tablets using near infrared spectroscopy as Process Analytical Technology tool.

    PubMed

    Chavez, Pierre-François; Sacré, Pierre-Yves; De Bleye, Charlotte; Netchacovitch, Lauranne; Mantanus, Jérôme; Motte, Henri; Schubert, Martin; Hubert, Philippe; Ziemons, Eric

    2015-11-01

    The aim of this study was to develop Near infrared (NIR) methods to determine the active content of non-coated pharmaceutical tablets manufactured from a proportional tablet formulation. These NIR methods intend to be used for the monitoring of the active content of tablets during the tableting process. Firstly, methods were developed in transmission and reflection modes to quantify the API content of the lowest dosage strength. Secondly, these methods were fully validated for a concentration range of 70-130% of the target active content using the accuracy profile approach based on β-expectation tolerance intervals. The model using the transmission mode showed a better ability to predict the right active content compared to the reflection one. However, the ability of the reflection mode to quantify the API content in the highest dosage strength was assessed. Furthermore, the NIR method based on the transmission mode was successfully used to monitor at-line the tablet active content during the tableting process, providing better insight of the API content during the process. This improvement of control of the product quality provided by this PAT method is thoroughly compliant with the Quality by Design (QbD) concept. Finally, the transfer of the transmission model from the off-line to an on-line spectrometer was efficiently investigated.

  3. Implementation of an analytical Raman scattering correction for satellite ocean-color processing.

    PubMed

    McKinna, Lachlan I W; Werdell, P Jeremy; Proctor, Christopher W

    2016-07-11

    Raman scattering of photons by seawater molecules is an inelastic scattering process. This effect can contribute significantly to the water-leaving radiance signal observed by space-borne ocean-color spectroradiometers. If not accounted for during ocean-color processing, Raman scattering can cause biases in derived inherent optical properties (IOPs). Here we describe a Raman scattering correction (RSC) algorithm that has been integrated within NASA's standard ocean-color processing software. We tested the RSC with NASA's Generalized Inherent Optical Properties algorithm (GIOP). A comparison between derived IOPs and in situ data revealed that the magnitude of the derived backscattering coefficient and the phytoplankton absorption coefficient were reduced when the RSC was applied, whilst the absorption coefficient of colored dissolved and detrital matter remained unchanged. Importantly, our results show that the RSC did not degrade the retrieval skill of the GIOP. In addition, a time-series study of oligotrophic waters near Bermuda showed that the RSC did not introduce unwanted temporal trends or artifacts into derived IOPs. PMID:27410899

  4. The analytical model for vortex ring pinch-off process based on the energy extremum principle

    NASA Astrophysics Data System (ADS)

    Xiang, Yang; Liu, Hong; Qin, Suyang; Wang, Fuxin

    2015-11-01

    The discovery of vortex ring pinch-off is greatly helpful for us to understand the mechanism of optimal vortex formation, which further implies the optimal biological propulsion for animals. The vortex ring pinch-off implies its limiting formation and is dominated by the energy extremum principle. However, it is found that vortex ring pinch-off is a continuous process rather than a transient timescale. Therefore, we are wondering that how to identify the onset and end of pinch-off process. Based on the Kelvin-Benjamin variational principle, a dimensionless energy number is adopted to characterize the energy evolution of vortex rings. The vortex ring flow fields are obtained by DPIV with the piston-cylinder setup, and their geometric structures are identified using its Lagrangian coherent structures. The results show that the dimensionless energy numbers with the steady translating vortex rings share a critical value. It is then demonstrated that the dimensionless energy number dominates the onset and the end of pinch-off process. Besides, the onset and end of pinch-off can also be identified using LCSs. Additionally, based on the dimensionless energy number or LCSs, the corresponding vortex ring formation times(L/D) for the onset or the end of pinch-off are consistent.

  5. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    SciTech Connect

    Saini, K. K.; Saini, Sanju

    2008-10-07

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  6. Analytical determination of the suitability of different processes for the treatment of odorous waste gas.

    PubMed

    Ranau, R; Kleeberg, K K; Schlegelmilch, M; Streese, J; Stegmann, R; Steinhart, H

    2005-01-01

    In order to determine the efficiency of different treatment systems for the reduction of odorous emissions, a gas chromatographic method followed by simultaneous mass spectrometry and olfactometry (GC-MS/O) was developed. Samples from a coffee bean roasting and a fat and oil processing plant were analyzed, respectively. The results were compared with the data obtained by olfactometric measurements. At a coffee bean roasting plant, cooling gases were analyzed prior to and after treatment in a full scale bioscrubber. The GC-MS/O analysis showed that the amounts of aldehydes and ketones decreased after treatment of cooling gases of coffee bean roasting in the bioscrubber, whereas the contents of the heterocyclic compounds, like pyridine and the pyrazines, and acetophenone and guaiacol remained almost unchanged. The amounts of dimethyl disulfide, 3-hydroxy-2-butanone, and the carboxylic acids increased after bioscrubber treatment. Furthermore, the performance of each stage of a combined experimental plant for the treatment of exhaust air of fat and oil processing was investigated. This treatment plant consisted of a bioscrubber, a biofilter, and an activated carbon adsorber. The important odor-active compounds of the exhaust air of fat and oil processing were the typical fat oxidation products (aldehydes, ketones) and with lower importance 2-pentylfuran, a few terpenes and aromates. Again, the key odor-active compounds, aldehydes and ketones, were degraded in the bioscrubber. Further degradation of aliphatic, unsaturated, methylated, and cyclic alkanes, as well as aromates, terpenes, and furans by the biofilter was observed. After the last treatment stage, the activated carbon filter, only small amounts of aliphatic, unsaturated, methylated, and cyclic alkanes and aromates remained in the waste gas. For both applications, the results of the developed GC-MS/O method correlated very well with olfactometric measurements.

  7. Software Analytical Instrument for Assessment of the Process of Casting Slabs

    SciTech Connect

    Franek, Zdenek; Kavicka, Frantisek; Stetina, Josef; Masarik, Milos

    2010-06-15

    The paper describes the original proposal of ways of solution and function of the program equipment for assessment of the process of casting slabs. The program system LITIOS was developed and implemented in EVRAZ Vitkovice Steel Ostrava on the equipment of continuous casting of steel (further only ECC). This program system works on the data warehouse of technological parameters of casting and quality parameters of slabs. It enables an ECC technologist to analyze the course of casting melt and with using statistics methods to set the influence of single technological parameters on the duality of final slabs. The system also enables long term monitoring and optimization of the production.

  8. Quality-by-design: an integrated process analytical technology approach to determine the nucleation and growth mechanisms during a dynamic pharmaceutical coprecipitation process.

    PubMed

    Wu, Huiquan; Khan, Mansoor A

    2011-05-01

    The objective of this study was to demonstrate the feasibility of using an integrated process analytical technology (PAT) approach to determine nucleation and growth mechanisms of a dynamic naproxen (drug)-Eudragit L100 (polymer) coprecipitation process. The influence of several thermodynamically important formulation and process variables (drug/polymer ratio, alcohol, and water usages) on coprecipitation process characteristics was investigated via real-time in situ focused beam reflectance measurement (FBRM) monitoring and near real-time particle vision microscopy measurement. The final products were characterized by near-infrared (NIR) spectroscopy and NIR chemical imaging microscopy. The coprecipitation nucleation induction time (t(ind) ) was measured by both FBRM trend statistics and process trajectory method, respectively. Furthermore, nucleation kinetics was evaluated based on t(ind) measurement and corresponding supersaturation ratio (S) estimated. It was found that plots of ln(t(ind) ) versus (ln(2) S)(-1) consist of two linear segments and are consistent with classical primary nucleation mechanisms. Apparently, the coprecipitation process is governed by heterogeneous primary nucleation mechanism at low S (14 ≤ S ≤ 503) and by homogeneous primary nucleation mechanism at high S (1216 ≤ S ≤ 3649). Off-line characterizations collectively supported this statement. Therefore, it demonstrated that integration real-time PAT process monitoring with first-principles modeling and off-line product characterization could enhance understanding to coprecipitation process dynamics and nucleation/growth mechanisms, which is impossible via off-line techniques alone.

  9. Dense distributed processing in a hindlimb scratch motor network.

    PubMed

    Guzulaitis, Robertas; Alaburda, Aidas; Hounsgaard, Jorn

    2014-08-01

    In reduced preparations, hindlimb movements can be generated by a minimal network of neurons in the limb innervating spinal segments. The network of neurons that generates real movements is less well delineated. In an ex vivo carapace-spinal cord preparation from adult turtles (Trachemys scripta elegans), we show that ventral horn interneurons in mid-thoracic spinal segments are functionally integrated in the hindlimb scratch network. First, mid-thoracic interneurons receive intense synaptic input during scratching and behave like neurons in the hindlimb enlargement. Second, some mid-thoracic interneurons activated during scratching project descending axons toward the hindlimb enlargement. Third, elimination of mid-thoracic segments leads to a weakening of scratch rhythmicity. We conclude that densely innervated interneurons in mid-thoracic segments contribute to hindlimb scratching and may be part of a distributed motor network that secures motor coherence.

  10. Problematizing the Processes of Participation in Networks: Working through the Rhetoric

    ERIC Educational Resources Information Center

    Ferreira, Jo-Anne; Davis, Julie

    2012-01-01

    Participation in networks, both as a concept and process, is widely supported in environmental education as a democratic and equitable pathway to individual and social change for sustainability. However, the processes of participation in networks are rarely problematized. Rather, it is assumed that we inherently know how to participate in…

  11. Cognitive Components of a Mathematical Processing Network in 9-Year-Old Children

    ERIC Educational Resources Information Center

    Szucs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

    2014-01-01

    We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are…

  12. Neural network post-processing of grayscale optical correlator

    NASA Technical Reports Server (NTRS)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  13. CONCH: A Visual Basic program for interactive processing of ion-microprobe analytical data

    NASA Astrophysics Data System (ADS)

    Nelson, David R.

    2006-11-01

    A Visual Basic program for flexible, interactive processing of ion-microprobe data acquired for quantitative trace element, 26Al- 26Mg, 53Mn- 53Cr, 60Fe- 60Ni and U-Th-Pb geochronology applications is described. Default but editable run-tables enable software identification of secondary ion species analyzed and for characterization of the standard used. Counts obtained for each species may be displayed in plots against analysis time and edited interactively. Count outliers can be automatically identified via a set of editable count-rejection criteria and displayed for assessment. Standard analyses are distinguished from Unknowns by matching of the analysis label with a string specified in the Set-up dialog, and processed separately. A generalized routine writes background-corrected count rates, ratios and uncertainties, plus weighted means and uncertainties for Standards and Unknowns, to a spreadsheet that may be saved as a text-delimited file. Specialized routines process trace-element concentration, 26Al- 26Mg, 53Mn- 53Cr, 60Fe- 60Ni, and Th-U disequilibrium analysis types, and U-Th-Pb isotopic data obtained for zircon, titanite, perovskite, monazite, xenotime and baddeleyite. Correction to measured Pb-isotopic, Pb/U and Pb/Th ratios for the presence of common Pb may be made using measured 204Pb counts, or the 207Pb or 208Pb counts following subtraction from these of the radiogenic component. Common-Pb corrections may be made automatically, using a (user-specified) common-Pb isotopic composition appropriate for that on the sample surface, or for that incorporated within the mineral at the time of its crystallization, depending on whether the 204Pb count rate determined for the Unknown is substantially higher than the average 204Pb count rate for all session standards. Pb/U inter-element fractionation corrections are determined using an interactive log e-log e plot of common-Pb corrected 206Pb/ 238U ratios against any nominated fractionation-sensitive species pair

  14. Process and analytical studies of enhanced low severity co-processing using selective coal pretreatment. Final technical report

    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.

  15. Investigation of the Application of Process Analytical Technology for a Laser Welding Process in Medical Device Manufacturing

    NASA Astrophysics Data System (ADS)

    Moore, Sean; Conneely, Alan; Stenzel, Eric; Murphy, Eamonn

    In FDA regulated medical device manufacturing, real time inspection of manufactured product is limited by the requirement to destructively test random samples of the product post production. Infra Red thermography offers the ability to non-destructively test, key critical to quality attributes of medical devices during laser welding and facilitates real time statistical process control for enhanced product quality and yield. This paper will present results of research work focused on non-destructive methods using Infra Red Thermography to potentially replace destructive methods of assessment for laser welded joints in stent delivery catheters. The approach utilizes designed experiments in conjunction with IR assessment and also identifies some limitations of the proposed method.

  16. DEFENSE WASTE PROCESSING FACILITY ANALYTICAL METHOD VERIFICATION FOR THE SLUDGE BATCH 5 QUALIFICATION SAMPLE

    SciTech Connect

    Click, D; Tommy Edwards, T; Henry Ajo, H

    2008-07-25

    For each sludge batch that is processed in the Defense Waste Processing Facility (DWPF), the Savannah River National Laboratory (SRNL) performs confirmation of the applicability of the digestion method to be used by the DWPF lab for elemental analysis of Sludge Receipt and Adjustment Tank (SRAT) receipt samples and SRAT product process control samples. DWPF SRAT samples are typically dissolved using a room temperature HF-HNO3 acid dissolution (i.e., DWPF Cold Chem Method, see Procedure SW4-15.201) and then analyzed by inductively coupled plasma - atomic emission spectroscopy (ICP-AES). This report contains the results and comparison of data generated from performing the Aqua Regia (AR), Sodium Peroxide/Hydroxide Fusion (PF) and DWPF Cold Chem (CC) method digestion of Sludge Batch 5 (SB5) SRAT Receipt and SB5 SRAT Product samples. The SB5 SRAT Receipt and SB5 SRAT Product samples were prepared in the SRNL Shielded Cells, and the SRAT Receipt material is representative of the sludge that constitutes the SB5 Batch composition. This is the sludge in Tank 51 that is to be transferred into Tank 40, which will contain the heel of Sludge Batch 4 (SB4), to form the SB5 Blend composition. The results for any one particular element should not be used in any way to identify the form or speciation of a particular element in the sludge or used to estimate ratios of compounds in the sludge. A statistical comparison of the data validates the use of the DWPF CC method for SB5 Batch composition. However, the difficulty that was encountered in using the CC method for SB4 brings into question the adequacy of CC for the SB5 Blend. Also, it should be noted that visible solids remained in the final diluted solutions of all samples digested by this method at SRNL (8 samples total), which is typical for the DWPF CC method but not seen in the other methods. Recommendations to the DWPF for application to SB5 based on studies to date: (1) A dissolution study should be performed on the WAPS

  17. Chemical and process mineralogical characterizations of spent lithium-ion batteries: an approach by multi-analytical techniques.

    PubMed

    Zhang, Tao; He, Yaqun; Wang, Fangfang; Ge, Linhan; Zhu, Xiangnan; Li, Hong

    2014-06-01

    Mineral processing operation is a critical step in any recycling process to realize liberation, separation and concentration of the target parts. Developing effective recycling methods to recover all the valuable parts from spent lithium-ion batteries is in great necessity. The aim of this study is to carefully undertake chemical and process mineralogical characterizations of spent lithium-ion batteries by coupling several analytical techniques to provide basic information for the researches on effective mechanical crushing and separation methods in recycling process. The results show that the grade of Co, Cu and Al is fairly high in spent lithium ion batteries and up to 17.62 wt.%, 7.17 wt.% and 21.60 wt.%. Spent lithium-ion batteries have good selective crushing property, the crushed products could be divided into three parts, they are Al-enriched fraction (+2 mm), Cu and Al-enriched fraction (-2+0.25 mm) and Co and graphite-enriched fraction (-0.25 mm). The mineral phase and chemical state analysis reveal the electrode materials recovered from -0.25 mm size fraction keep the original crystal forms and chemical states in lithium-ion batteries, but the surface of the powders has been coated by a certain kind of hydrocarbon. Based on these results a flowsheet to recycle spent LiBs is proposed.

  18. An Analytical Framework for Studying Small-Number Effects in Catalytic Reaction Networks: A Probability Generating Function Approach to Chemical Master Equations

    PubMed Central

    Nakagawa, Masaki; Togashi, Yuichi

    2016-01-01

    Cell activities primarily depend on chemical reactions, especially those mediated by enzymes, and this has led to these activities being modeled as catalytic reaction networks. Although deterministic ordinary differential equations of concentrations (rate equations) have been widely used for modeling purposes in the field of systems biology, it has been pointed out that these catalytic reaction networks may behave in a way that is qualitatively different from such deterministic representation when the number of molecules for certain chemical species in the system is small. Apart from this, representing these phenomena by simple binary (on/off) systems that omit the quantities would also not be feasible. As recent experiments have revealed the existence of rare chemical species in cells, the importance of being able to model potential small-number phenomena is being recognized. However, most preceding studies were based on numerical simulations, and theoretical frameworks to analyze these phenomena have not been sufficiently developed. Motivated by the small-number issue, this work aimed to develop an analytical framework for the chemical master equation describing the distributional behavior of catalytic reaction networks. For simplicity, we considered networks consisting of two-body catalytic reactions. We used the probability generating function method to obtain the steady-state solutions of the chemical master equation without specifying the parameters. We obtained the time evolution equations of the first- and second-order moments of concentrations, and the steady-state analytical solution of the chemical master equation under certain conditions. These results led to the rank conservation law, the connecting state to the winner-takes-all state, and analysis of 2-molecules M-species systems. A possible interpretation of the theoretical conclusion for actual biochemical pathways is also discussed. PMID:27047384

  19. An Analytical Framework for Studying Small-Number Effects in Catalytic Reaction Networks: A Probability Generating Function Approach to Chemical Master Equations.

    PubMed

    Nakagawa, Masaki; Togashi, Yuichi

    2016-01-01

    Cell activities primarily depend on chemical reactions, especially those mediated by enzymes, and this has led to these activities being modeled as catalytic reaction networks. Although deterministic ordinary differential equations of concentrations (rate equations) have been widely used for modeling purposes in the field of systems biology, it has been pointed out that these catalytic reaction networks may behave in a way that is qualitatively different from such deterministic representation when the number of molecules for certain chemical species in the system is small. Apart from this, representing these phenomena by simple binary (on/off) systems that omit the quantities would also not be feasible. As recent experiments have revealed the existence of rare chemical species in cells, the importance of being able to model potential small-number phenomena is being recognized. However, most preceding studies were based on numerical simulations, and theoretical frameworks to analyze these phenomena have not been sufficiently developed. Motivated by the small-number issue, this work aimed to develop an analytical framework for the chemical master equation describing the distributional behavior of catalytic reaction networks. For simplicity, we considered networks consisting of two-body catalytic reactions. We used the probability generating function method to obtain the steady-state solutions of the chemical master equation without specifying the parameters. We obtained the time evolution equations of the first- and second-order moments of concentrations, and the steady-state analytical solution of the chemical master equation under certain conditions. These results led to the rank conservation law, the connecting state to the winner-takes-all state, and analysis of 2-molecules M-species systems. A possible interpretation of the theoretical conclusion for actual biochemical pathways is also discussed.

  20. Sources and processes of contaminant loss from an intensively grazed catchment inferred from patterns in discharge and concentration of thirteen analytes using high intensity sampling

    NASA Astrophysics Data System (ADS)

    Holz, G. K.

    2010-03-01

    SummaryContaminants in water from intensively grazed catchments have been shown to cause significant environmental impacts. Effective intervention to reduce contaminant loads depends on identifying their sources and processes of mobilisation and transport. In this study, flow ( Q) and analyte concentrations ( CA) from a 12 ha catchment in north-west Tasmania used for grazing dairy cattle were monitored at a fine temporal scale and used to infer sources and processes of loss. Three groups of analytes identified based on CA- Q relationships, which included hysteresis loops, demonstrated that the TP group (TP, DRP, TSS, TN, E.coli and Enterococcus) was transported by surface runoff processes while the behaviour of the NO 3 group (NO 3, TDS, Ca, Mg, Na) was explained by subsurface processes and pathways. The NH 4 group (NH 4, K) was dominated by the addition of large quantities of analyte from grazing. In addition to the CA- Q relationships, concentrations of most analytes decreased linearly over each season of runoff. NH 4 and K concentrations decreased exponentially following grazing events while TP concentrations decreased linearly. The study demonstrated the importance of understanding surface water and groundwater interactions and that relationships between runoff events, analyte concentrations and management as revealed by a fine temporal sampling regime may yield significant insights to sources and processes of loss of analytes in surface flow, at a given scale.