WorldWideScience

Sample records for networks process capsules

  1. CAPSULE REPORT: EVAPORATION PROCESS

    Science.gov (United States)

    Evaporation has been an established technology in the metal finishing industry for many years. In this process, wastewaters containing reusable materials, such as copper, nickel, or chromium compounds are heated, producing a water vapor that is continuously removed and condensed....

  2. CAPSULE REPORT: REVERSE OSMOSIS PROCESS

    Science.gov (United States)

    A failure analysis has been completed for the reverse osmosis (RO) process. The focus was on process failures that result in releases of liquids and vapors to the environment. The report includes the following: 1) A description of RO and coverage of the principles behind the proc...

  3. Are Social Networking Websites Educational? Information Capsule. Volume 0909

    Science.gov (United States)

    Blazer, Christie

    2009-01-01

    More and more school districts across the country are joining social networking sites, such as Facebook and MySpace. This Information Capsule discusses the frequency with which school districts are using social networking sites, how districts are using the sites, and potential drawbacks associated with their use. Issues for districts to consider…

  4. Reconfigurable network processing platforms

    NARCIS (Netherlands)

    Kachris, C.

    2007-01-01

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

  5. Network pharmacology-based identification of key pharmacological pathways of Yin–Huang–Qing–Fei capsule acting on chronic bronchitis

    Directory of Open Access Journals (Sweden)

    Yu GH

    2016-12-01

    Full Text Available Guohua Yu,1,2,* Yanqiong Zhang,2,* Weiqiong Ren,3 Ling Dong,1 Junfang Li,2,4 Ya Geng,2,5 Yi Zhang,2 Defeng Li,2 Haiyu Xu,2 Hongjun Yang2 1School of Chinese Materia Medica, Beijing University of Chinese Medicine, 2Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 3The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine, Changsha, 4School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, 5School of Basic Medicine, Shandong University of Chinese Medicine, Jinan, China *These authors contributed equally to this work Abstract: For decades in China, the Yin–Huang–Qing–Fei capsule (YHQFC has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL

  6. An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

    International Nuclear Information System (INIS)

    Dimas, George; Iakovidis, Dimitris K; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

    2017-01-01

    Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup. (paper)

  7. An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

    Science.gov (United States)

    Dimas, George; Iakovidis, Dimitris K.; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

    2017-09-01

    Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup.

  8. Modular nuclear fuel element, modular capsule for a such element and fabrication process for a modular capsule

    International Nuclear Information System (INIS)

    Chotard, A.

    1988-01-01

    The nuclear fuel rod is made by a tubular casing closed at both ends and containing a series of modular capsules with little play with the casing and made by a jacket closed by porous plugs at both ends and containing a stack of fuel pellets [fr

  9. Networked business process management

    NARCIS (Netherlands)

    Grefen, P.W.P.J.

    2013-01-01

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

  10. Investigation on shortening fabrication process of instrumented irradiation capsule of JMTR

    International Nuclear Information System (INIS)

    Nagata, Hiroshi; Inoue, Shuichi; Yamaura, Takayuki; Tsuchiya, Kunihiko; Nagao, Yoshiharu

    2013-06-01

    Refurbishment of The Japan Materials Testing Reactor (JMTR) was completed in FY2010. For damage caused by the 2011 off the Pacific coast of Tohoku Earthquake, the repair of facilities was completed in October 2012. Currently, the JMTR is in preparation for restart. Irradiation tests for LWRs safety research, science and technologies and production of RI for medical diagnosis medicine, etc. are expected after the JMTR restart. On the other hand, aiming at the attractive irradiation testing reactor, the usability improvement has been discussed. As a part of the usability improvement, shortening of turnaround time to get irradiation results from an application for irradiation use was discussed focusing on the fabrication process of irradiation capsules, where the fabrication process was analyzed and reviewed by referring a trial fabrication of the mockup capsule. As a result, it was found that the turnaround time can be shortened 2 months from fabrication period of 6 months with communize of irradiation capsule parts, application of ready-made instrumentation including the sheath heater, reconsideration of inspection process, etc. (author)

  11. Network pharmacology-based identification of key pharmacological pathways of Yin-Huang-Qing-Fei capsule acting on chronic bronchitis.

    Science.gov (United States)

    Yu, Guohua; Zhang, Yanqiong; Ren, Weiqiong; Dong, Ling; Li, Junfang; Geng, Ya; Zhang, Yi; Li, Defeng; Xu, Haiyu; Yang, Hongjun

    2017-01-01

    For decades in China, the Yin-Huang-Qing-Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness) of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL-5, IL-10, IL-13, FCER1G, CCL11, and EPX) were demonstrated to be associated with the inflammatory process that occurs during the progression of asthma. Finally, a molecular docking simulation was performed and the results exhibited that 17 pairs of chemical components and candidate YHQFC targets involved in asthma pathway had strong binding efficiencies. In conclusion, this network pharmacology-based investigation revealed that YHQFC may attenuate the inflammatory reaction of chronic bronchitis by regulating its candidate targets, which may be implicated in the major pathological processes of the asthma pathway.

  12. miRNA Regulation Network Analysis in Qianliening Capsule Treatment of Benign Prostatic Hyperplasia

    Directory of Open Access Journals (Sweden)

    Liya Liu

    2015-01-01

    Full Text Available Objective. The objective of this study was to evaluate the molecular mechanism by which Qianliening capsule (QC treats benign prostatic hyperplasia (BPH. Methods. Benign prostatic hyperplasia epithelial cell line BPH-1 was treated with 0, 1.25, 2.5, and 5 mg/mL QC for 48 h, respectively. Evaluation of cell viability and observation of morphologic changes of BPH-1 cell gene expression and miRNA expression profiles were analyzed. Real-time quantitative PCR was used to confirm changes in miRNA and gene expression. GO and KEGG pathway-based approaches were used to investigate biological functions and signaling pathways affected by differentially expressed mRNAs. Results. QC inhibited BPH-1 cell proliferation. Differential expression of 19 upregulated and 2 downregulated miRNAs was observed in QC-treated BPH-1 cells compared to untreated control cells. 107 upregulated and 71 downregulated genes were identified between the two groups. Significantly enriched signaling pathways based on deregulated mRNAs were mainly involved in regulation of cell proliferation, apoptosis, and so on. Additionally, miRNA-mRNA network analysis integrated these miRNAs and genes by outlining interactions of miRNA and related genes. Conclusion. The study was the first report of differentially expressed miRNA and mRNA in QC-treated BPH-1 cells.

  13. [Application of microwave technology in extraction process of Guizhi Fuling capsule].

    Science.gov (United States)

    Wang, Zheng-kuan; Zhou, Mao; Liu, Yuan; Bi, Yu-an; Wang, Zhen-zhong; Xiao, Wei

    2015-06-01

    In this paper, optimization of the conditions of microwave technique in extraction process of Guizhi Fuling capsule in the condition of a pilot scale was carried out. First of all, through the single factor experiment investigation of various factors, the overall impact tendency and range of each factor were determined. Secondly, L9 (3(4)) orthogonal test optimization was used, and the contents of gallic acid in liquid, paeoniflorin, benzoic acid, cinnamic acid, benzoyl paeoniflorin, amygdalin of the liquid medicine were detected. The extraction rate and comprehensive evaluation were calculated with the extraction effect, as the judgment basis. Theoptimum extraction process of Guizhi Fuling capsule by microwave technology was as follows: the ratio of liquid to solid was 6: 1 added to drinking water, the microwave power was 6 kW, extraction time was 20 min for 3 times. The process of the three batch of amplification through verification, the results are stable, and compared with conventional water extraction has the advantages of energy saving, time saving, high efficiency advantages. The above results show the optimum extracting technology of high efficiency, stable and feasible.

  14. Study of a low-dose capsule filling process by dynamic and static tests for advanced process understanding.

    Science.gov (United States)

    Stranzinger, S; Faulhammer, E; Scheibelhofer, O; Calzolari, V; Biserni, S; Paudel, A; Khinast, J G

    2018-04-05

    Precise filling of capsules with doses in the mg-range requires a good understanding of the filling process. Therefore, we investigated the various process steps of the filling process by dynamic and static mode tests. Dynamic tests refer to filling of capsules in a regular laboratory dosator filling machine. Static tests were conducted using a novel filling system developed by us. Three grades of lactose excipients were filled into size 3 capsules with different dosing chamber lengths, nozzle diameters and powder bed heights, and, in the dynamic mode, with two filling speeds (500, 3000 caps/h). The influence of the gap at the bottom of the powder container on the fill weight and variability was assessed. Different gaps resulted in a change in fill weight in all materials, although in different ways. In all cases, the fill weight of highly cohesive Lactohale 220 increased when decreasing the gap. Furthermore, experiments with the stand-alone static test tool indicated that this very challenging powder could successfully be filled without any pre-compression in the range of 5 mg-20 mg with acceptable RSDs. This finding is of great importance since for very fine lactose powders high compression ratios (dosing-chamber-length-to-powder-bed height compression ratios) may result in jamming of the piston. Moreover, it shows that the static mode setup is suitable for studying fill weight and variability. Since cohesive powders, such as Lactohale 220, are hard to fill, we investigated the impact of vibration on the process. Interestingly, we found no correlation between the reported fill weight changes in dynamic mode at 3000 cph and static mode using similar vibration. However, we could show that vibrations during sampling in the static mode dramatically reduced fill weight variability. Overall, our results indicate that by fine-tuning instrumental settings even very challenging powders can be filled with a low-dose dosator capsule filling machine. This study is a

  15. A Wireless Capsule Endoscope System With Low-Power Controlling and Processing ASIC.

    Science.gov (United States)

    Xinkai Chen; Xiaoyu Zhang; Linwei Zhang; Xiaowen Li; Nan Qi; Hanjun Jiang; Zhihua Wang

    2009-02-01

    This paper presents the design of a wireless capsule endoscope system. The proposed system is mainly composed of a CMOS image sensor, a RF transceiver and a low-power controlling and processing application specific integrated circuit (ASIC). Several design challenges involving system power reduction, system miniaturization and wireless wake-up method are resolved by employing optimized system architecture, integration of an area and power efficient image compression module, a power management unit (PMU) and a novel wireless wake-up subsystem with zero standby current in the ASIC design. The ASIC has been fabricated in 0.18-mum CMOS technology with a die area of 3.4 mm * 3.3 mm. The digital baseband can work under a power supply down to 0.95 V with a power dissipation of 1.3 mW. The prototype capsule based on the ASIC and a data recorder has been developed. Test result shows that proposed system architecture with local image compression lead to an average of 45% energy reduction for transmitting an image frame.

  16. Sample Size for Tablet Compression and Capsule Filling Events During Process Validation.

    Science.gov (United States)

    Charoo, Naseem Ahmad; Durivage, Mark; Rahman, Ziyaur; Ayad, Mohamad Haitham

    2017-12-01

    During solid dosage form manufacturing, the uniformity of dosage units (UDU) is ensured by testing samples at 2 stages, that is, blend stage and tablet compression or capsule/powder filling stage. The aim of this work is to propose a sample size selection approach based on quality risk management principles for process performance qualification (PPQ) and continued process verification (CPV) stages by linking UDU to potential formulation and process risk factors. Bayes success run theorem appeared to be the most appropriate approach among various methods considered in this work for computing sample size for PPQ. The sample sizes for high-risk (reliability level of 99%), medium-risk (reliability level of 95%), and low-risk factors (reliability level of 90%) were estimated to be 299, 59, and 29, respectively. Risk-based assignment of reliability levels was supported by the fact that at low defect rate, the confidence to detect out-of-specification units would decrease which must be supplemented with an increase in sample size to enhance the confidence in estimation. Based on level of knowledge acquired during PPQ and the level of knowledge further required to comprehend process, sample size for CPV was calculated using Bayesian statistics to accomplish reduced sampling design for CPV. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  17. Development of a sealing process of capsules for surveillance test tubes of the vessel in nuclear power plants

    International Nuclear Information System (INIS)

    Romero C, J.; Fernandez T, F.; Perez R, N.; Rocamontes A, M.; Garcia R, R.

    2007-01-01

    The surveillance capsule is composed by the support, three capsules for impact test tubes, five capsules for tension test tubes and one porta dosemeters. The capsules for test tubes are of two types: rectangular capsule for Charpy test tubes and cylindrical capsule for tension test tubes. This work describes the development of the welding system to seal the capsules for test tubes that should contain helium of ultra high purity to a pressure of 1 atmosphere. (Author)

  18. Resource optimized TTSH-URA for multimedia stream authentication in swallowable-capsule-based wireless body sensor networks.

    Science.gov (United States)

    Wang, Wei; Wang, Chunqiu; Zhao, Min

    2014-03-01

    To ease the burdens on the hospitalization capacity, an emerging swallowable-capsule technology has evolved to serve as a remote gastrointestinal (GI) disease examination technique with the aid of the wireless body sensor network (WBSN). Secure multimedia transmission in such a swallowable-capsule-based WBSN faces critical challenges including energy efficiency and content quality guarantee. In this paper, we propose a joint resource allocation and stream authentication scheme to maintain the best possible video quality while ensuring security and energy efficiency in GI-WBSNs. The contribution of this research is twofold. First, we establish a unique signature-hash (S-H) diversity approach in the authentication domain to optimize video authentication robustness and the authentication bit rate overhead over a wireless channel. Based on the full exploration of S-H authentication diversity, we propose a new two-tier signature-hash (TTSH) stream authentication scheme to improve the video quality by reducing authentication dependence overhead while protecting its integrity. Second, we propose to combine this authentication scheme with a unique S-H oriented unequal resource allocation (URA) scheme to improve the energy-distortion-authentication performance of wireless video delivery in GI-WBSN. Our analysis and simulation results demonstrate that the proposed TTSH with URA scheme achieves considerable gain in both authenticated video quality and energy efficiency.

  19. Radiation as a processing aid for upgrading gelatin and gelatin capsules

    International Nuclear Information System (INIS)

    Patel, K.M.; Tantry, M.; Sharma, G.; Gopal, N.G.S.

    1979-01-01

    Gelatin for pharmaceutical use should not contain more than 1000 microorganisms per gram and must not contain pathogenic microorganisms like Salmonella species and E.Coli. For some biological studies spore free gelatin is essential. Locally available gelatin and gelatin capsules have been found to contain a good number of microorganisms. Gelatin and its capsules containing different colours were exposed to graded doses of radiation and stored at different temperatures. They were then examined for microbial content, disintegration characteristics, pH, viscosity and colour change. The study shows that radiation treatment is useful to upgrade microbiologically both gelatin and its capsules. This technique provides apparently a useful and economic method for producing spore free gelatin which in commerce is relatively expensive. (auth.)

  20. Radiation as a processing aid for upgrading gelatin and gelatin capsules

    Energy Technology Data Exchange (ETDEWEB)

    Patel, K M; Tantry, M; Sharma, G; Gopal, N G.S. [Bhabha Atomic Research Centre, Bombay (India). ISOMED

    1979-01-01

    Gelatin for pharmaceutical use should not contain more than 1000 microorganisms per gram and must not contain pathogenic microorganisms like Salmonella species and E.Coli. For some biological studies spore free gelatin is essential. Locally available gelatin and gelatin capsules have been found to contain a good number of microorganisms. Gelatin and its capsules containing different colours were exposed to graded doses of radiation and stored at different temperatures. They were then examined for microbial content, disintegration characteristics, pH, viscosity and colour change. The study shows that radiation treatment is useful to upgrade microbiologically both gelatin and its capsules. This technique provides apparently a useful and economic method for producing spore free gelatin which in commerce is relatively expensive.

  1. Network Dynamics of Innovation Processes

    Science.gov (United States)

    Iacopini, Iacopo; Milojević, Staša; Latora, Vito

    2018-01-01

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

  2. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

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

  3. Effect of Corbrin Capsule combined with routine western medicine on the airway remodeling process in patients with stable COPD

    Directory of Open Access Journals (Sweden)

    Su-Li Song

    2017-08-01

    Full Text Available Objective: To explore the effect of Corbrin Capsule combined with routine western medicine on the airway remodeling process in patients with stable COPD. Methods: A total of 120 patients with stable COPD who were treated in the hospital between May 2014 and December 2016 were collected and divided into control group and observation group according to the random number table method, 60 cases in each group. The control group received routine western medicine treatment, and the observation group received Corbrin Capsule combined with routine western medicine treatment. The differences in serum levels of inflammatory factors, growth factors and fibrosis indexes were compared between the two groups before and after treatment. Results: Before treatment, difference in serum levels of inflammatory factors, growth factors and fibrosis indexes were not statistically significant between the two groups of patients. After 8 weeks of treatment, serum IL-2, IL-4, IL-8, IL-18, VEGF, b-FGF, NGF, LN, HA, PⅢNP and C-Ⅳ levels of both groups of patients were significantly lower than those before treatment, and serum IL-2, IL-4, IL-8, IL-18, VEGF, b-FGF, NGF, LN, HA, PⅢNP and C-Ⅳ levels of observation group were lower than those of control group. Conclusion: Corbrin Capsule combined with routine western medicine treatment can effectively inhibit the fibrosis process in patients with stable COPD.

  4. Epidemic processes in complex networks

    OpenAIRE

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

    2015-01-01

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

  5. Capsule Endoscopy

    Science.gov (United States)

    ... because experience with it is limited and traditional upper endoscopy is widely available. Why it's done Your doctor might recommend a capsule endoscopy procedure to: Find the cause of gastrointestinal bleeding. If you have unexplained bleeding in your digestive ...

  6. Epidemic processes in complex networks

    Science.gov (United States)

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

    2015-07-01

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

  7. Optimal use of polyethylene glycol for preparation of small bowel video capsule endoscopy: a network meta-analysis.

    Science.gov (United States)

    Wu, Shan; Gao, Yun-Jie; Ge, Zhi-Zheng

    2017-06-01

    Standardized strategy of bowel preparation before video capsule endoscopy (VCE) remains controversial. This study aimed to assess the ideal dose of PEG, based on small bowel visualization quality (SBVQ), diagnostic yield (DY), and complete rate (CR) of VCE using a network meta-analysis (NMA) of randomized controlled trials (RCTs). This NMA included RCTs comparing any of the following bowel preparation interventions for VCE: fasting overnight ("Fast"), 1 liter PEG ("PEG 1L"), 2-liter PEG ("PEG 2L"), or 4-liter PEG ("PEG 4L"). The authors searched papers in PubMed, Cochrane Library, and Embase as of June 2016. The cumulative ranking (SUCRA) probabilities to rank different doses of PEG and Fast were used. The search engine provided 102 studies. Nine RCTs including 982 patients were incorporated into this analysis. All studies showed low risk of bias of blinding. SUCRA provided an initial ranking among these strategies, in which PEG 2 L showed the best score in SBVQ (PEG 2 L, 89.4%; PEG 1 L, 62.5%; PEG 4 L, 44.0%; Fast, 4.1%) and DY (PEG 2 L, 74.6%; PEG 1 L 28.1%; PEG 4 L 65.9%; Fast 31.4%) of VCE. No significant difference was shown in the analysis of CR. This study recommends PEG 2 L as the ideal dose, which may improve the SBVQ of VCE and, therefore, diagnostic accuracy. Multi-center randomized controlled trials are required to verify these findings.

  8. Formulation, process development and evaluation of artemether and lumefantrine soft gelatin capsule

    Directory of Open Access Journals (Sweden)

    A Patel

    2012-01-01

    Full Text Available Artemether and Lumefantrine capsules are indicated for the treatment of P. falciparum malaria cases resistant to both chloroquine and sulphadoxine, pyrimethamine combination. Both artemether and lumefantrine act as blood schizontocides. Artemether is a sesquiterpene lactone derived from artemisinin. Artemisinin is a compound derived from the sweet wormwood plant and has been used for centuries in traditional Chinese medicine to treat fever. Lumefantrine is a synthetic aryl-amino alcohol antimalarial (quinine, mefloquine and halofantrine are members of the same group. Artemether is absorbed fairly rapidly with peak plasma concentrations reached about 2 hours after dosing. Absorption of lumefantrine, a highly lipophilic compound, starts after a lag period of up to 2 hours, with peak plasma concentration about 6-8 hours after dosing. In order to overcome this problem, we have observed that when the drug is given in the soft gelatin dosage form, the bioavailability of the drug is increased. Thus, increasing the absorption of the drug and peak plasma concentration is reached earlier then the conventional dosage form.

  9. Processes to Open the Container and the Sample Catcher of the Hayabusa Returned Capsule in the Planetary Material Sample Curation Facility of JAXA

    Science.gov (United States)

    Fujimura, A.; Abe, M.; Yada, T.; Nakamura, T.; Noguchi, T.; Okazaki, R.; Ishibashi, Y.; Shirai, K.; Okada, T.; Yano, H.; hide

    2011-01-01

    Japanese spacecraft Hayabusa, which returned from near-Earth-asteroid Itokawa, successfully returned its reentry capsule to the Earth, the Woomera Prohibited Area in Australia in Jun 13th, 2010, as detailed in another paper [1]. The capsule introduced into the Planetary Material Sample Curation Facility in the Sagamihara campus of JAXA in the early morning of June 18th. Hereafter, we describe a series of processes for the returned capsule and the container to recover gas and materials in there. A transportation box of the recovered capsule was cleaned up on its outer surface beforehand and introduced into the class 10,000 clean room of the facility. Then, the capsule was extracted from the box and its plastic bag was opened and checked and photographed the outer surface of the capsule. The capsule was composed of the container, a backside ablator, a side ablator, an electronic box and a supporting frame. The container consists of an outer lid, an inner lid, a frame for latches, a container and a sample catcher, which is composed of room A and B and a rotational cylinder. After the first check, the capsule was packed in a plastic bag with N2 again, and transferred to the Chofu campus in JAXA, where the X-ray CT instrument is situated. The first X-ray CT analysis was performed on the whole returned capsule for confirming the conditions of latches and O-ring seal of the container. The analysis showed that the latches of the container should have worked normally, and that the double Orings of the container seemed to be sealed its sample catcher with no problem. After the first X-ray CT, the capsule was sent back to Sagamihara and introduced in the clean room to exclude the electronic box and the side ablator from the container by hand tools. Then the container with the backside ablator was set firmly to special jigs to fix the lid of container tightly to the container and set to a milling machine. The backside ablator was drilled by the machine to expose heads of bolts

  10. The structures of bacteriophages K1E and K1-5 explain processive degradation of polysaccharide capsules and evolution of new host specificities.

    Science.gov (United States)

    Leiman, Petr G; Battisti, Anthony J; Bowman, Valorie D; Stummeyer, Katharina; Mühlenhoff, Martina; Gerardy-Schahn, Rita; Scholl, Dean; Molineux, Ian J

    2007-08-17

    External polysaccharides of many pathogenic bacteria form capsules protecting the bacteria from the animal immune system and phage infection. However, some bacteriophages can digest these capsules using glycosidases displayed on the phage particle. We have utilized cryo-electron microscopy to determine the structures of phages K1E and K1-5 and thereby establish the mechanism by which these phages attain and switch their host specificity. Using a specific glycosidase, both phages penetrate the capsule and infect the neuroinvasive human pathogen Escherichia coli K1. In addition to the K1-specific glycosidase, each K1-5 particle carries a second enzyme that allows it to infect E. coli K5, whose capsule is chemically different from that of K1. The enzymes are organized into a multiprotein complex attached via an adapter protein to the virus portal vertex, through which the DNA is ejected during infection. The structure of the complex suggests a mechanism for the apparent processivity of degradation that occurs as the phage drills through the polysaccharide capsule. The enzymes recognize the adapter protein by a conserved N-terminal sequence, providing a mechanism for phages to acquire different enzymes and thus to evolve new host specificities.

  11. Cooperative spreading processes in multiplex networks.

    Science.gov (United States)

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

    2016-06-01

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

  12. Signal Processing and Neural Network Simulator

    Science.gov (United States)

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

    1995-04-01

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

  13. A Process Management System for Networked Manufacturing

    Science.gov (United States)

    Liu, Tingting; Wang, Huifen; Liu, Linyan

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

  14. Social Network Supported Process Recommender System

    Directory of Open Access Journals (Sweden)

    Yanming Ye

    2014-01-01

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

  15. Social network supported process recommender system.

    Science.gov (United States)

    Ye, Yanming; Yin, Jianwei; Xu, Yueshen

    2014-01-01

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

  16. Criminal Network Investigation: Processes, Tools, and Techniques

    DEFF Research Database (Denmark)

    Petersen, Rasmus Rosenqvist

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

  17. Mapping stochastic processes onto complex networks

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  18. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

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

  19. Image processing with a cellular nonlinear network

    International Nuclear Information System (INIS)

    Morfu, S.

    2005-01-01

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

  20. Reprocessing process simulation network; PRONET

    International Nuclear Information System (INIS)

    Mitsui, T.; Takada, H.; Kamishima, N.; Tsukamoto, T.; Harada, N.; Fujita, N.; Gonda, K.

    1991-01-01

    The effectiveness of simulation technology and its wide application to nuclear fuel reprocessing plants has been recognized recently. The principal aim of applying simulation is to predict the process behavior accurately based on the quantitative relations among substances in physical and chemical phenomena. Mitsubishi Heavy Industries Ltd. has engaged positively in the development and the application study of this technology. All the software products of its recent activities were summarized in the integrated form named 'PRONET'. The PRONET is classified into two independent software groups from the viewpoint of computer system. One is off-line Process Simulation Group, and the other is Dynamic Real-time Simulator Group. The former is called 'PRONET System', and the latter is called 'PRONET Simulator'. These have several subsystems with the prefix 'MR' meaning Mitsubishi Reprocessing Plant. Each MR subsystem is explained in this report. The technical background, the objective of the PRONET, the system and the function of the PRONET, and the future application to an on-line real-time simulator and the development of MR EXPERT are described. (K.I.)

  1. Social Networking in Schools: Benefits and Risks; Review of the Research; Policy Considerations; and Current Practices. Information Capsule. Volume 1109

    Science.gov (United States)

    Blazer, Christie

    2012-01-01

    The role that social media should play in education is being hotly debated in school districts across the country. The adoption of social networking for educational purposes lags behind the public's general usage because educators fear that students will be exposed to inappropriate online content, unwanted adult interactions, and bullying from…

  2. Optimal Information Processing in Biochemical Networks

    Science.gov (United States)

    Wiggins, Chris

    2012-02-01

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

  3. Aggregates of octenylsuccinate oat β-glucan as novel capsules to stabilize curcumin over food processing, storage and digestive fluids and to enhance its bioavailability.

    Science.gov (United States)

    Liu, J; Lei, L; Ye, F; Zhou, Y; Younis, Heba G R; Zhao, G

    2018-01-24

    Self-aggregates of octenylsuccinate oat β-glucan (A OSG ) have been verified as nanocapsules to load curcumin, a representative of hydrophobic phytochemicals. This study primarily investigated the stability of curcumin-loaded A OSG s over food processing, storage and digestive fluids. Curcumin in A OSG s showed better stability over storage and thermal treatment than its free form. Curcumin loaded in A OSGs stored at 4 °C in the dark exhibited higher stability than that at higher temperatures or exposed to light. Approximately 18% of curcumin was lost after five freeze-thaw cycles. Curcumin in A OSG was more stable than its free form in mimetic intestinal fluids, attesting to the effective protection of A OSG for curcumin over digestive environments. When curcumin-loaded A OSG travelled across mimetic gastric and intestinal fluids, curcumin was tightly accommodated in the capsule, while it rapidly escaped as the capsule reached the colon. Interestingly, the curcumin loaded in A OSG generated higher values of C max and area under the curve than did its free counterpart. These observations showed that A OSG is a powerful vehicle for stabilizing hydrophobic phytochemicals in food processing and storage, facilitating their colon-targeted delivery and enhancing their bioavailability.

  4. Business Process Modeling Languages Supporting Collaborative Networks

    NARCIS (Netherlands)

    Soleimani Malekan, H.; Afsarmanesh, H.; Hammoudi, S.; Maciaszek, L.A.; Cordeiro, J.; Dietz, J.L.G.

    2013-01-01

    Formalizing the definition of Business Processes (BPs) performed within each enterprise is fundamental for effective deployment of their competencies and capabilities within Collaborative Networks (CN). In our approach, every enterprise in the CN is represented by its set of BPs, so that other

  5. Synthesis and Design of Processing Networks

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2012-01-01

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

  6. In-line ATR-UV and Raman Spectroscopy for Monitoring API Dissolution Process During Liquid-Filled Soft-Gelatin Capsule Manufacturing.

    Science.gov (United States)

    Wan, Boyong; Zordan, Christopher A; Lu, Xujin; McGeorge, Gary

    2016-10-01

    Complete dissolution of the active pharmaceutical ingredient (API) is critical in the manufacturing of liquid-filled soft-gelatin capsules (SGC). Attenuated total reflectance UV spectroscopy (ATR-UV) and Raman spectroscopy have been investigated for in-line monitoring of API dissolution during manufacturing of an SGC product. Calibration models have been developed with both techniques for in-line determination of API potency. Performance of both techniques was evaluated and compared. The ATR-UV methodology was found to be able to monitor the dissolution process and determine the endpoint, but was sensitive to temperature variations. The Raman technique was also capable of effectively monitoring the process and was more robust to the temperature variation and process perturbations by using an excipient peak for internal correction. Different data preprocessing methodologies were explored in an attempt to improve method performance.

  7. Generalized epidemic process on modular networks.

    Science.gov (United States)

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

    2014-05-01

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

  8. Interacting Social Processes on Interconnected Networks.

    Directory of Open Access Journals (Sweden)

    Lucila G Alvarez-Zuzek

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

  9. Information governance in dynamic networked business process management

    NARCIS (Netherlands)

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

    2016-01-01

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

  10. Posterior capsule opacification.

    Science.gov (United States)

    Wormstone, I Michael; Wang, Lixin; Liu, Christopher S C

    2009-02-01

    Posterior Capsule Opacification (PCO) is the most common complication of cataract surgery. At present the only means of treating cataract is by surgical intervention, and this initially restores high visual quality. Unfortunately, PCO develops in a significant proportion of patients to such an extent that a secondary loss of vision occurs. A modern cataract operation generates a capsular bag, which comprises a proportion of the anterior and the entire posterior capsule. The bag remains in situ, partitions the aqueous and vitreous humours, and in the majority of cases, houses an intraocular lens. The production of a capsular bag following surgery permits a free passage of light along the visual axis through the transparent intraocular lens and thin acellular posterior capsule. However, on the remaining anterior capsule, lens epithelial cells stubbornly reside despite enduring the rigours of surgical trauma. This resilient group of cells then begin to re-colonise the denuded regions of the anterior capsule, encroach onto the intraocular lens surface, occupy regions of the outer anterior capsule and most importantly of all begin to colonise the previously cell-free posterior capsule. Cells continue to divide, begin to cover the posterior capsule and can ultimately encroach on the visual axis resulting in changes to the matrix and cell organization that can give rise to light scatter. This review will describe the biological mechanisms driving PCO progression and discuss the influence of IOL design, surgical techniques and putative drug therapies in regulating the rate and severity of PCO.

  11. Polydopamine-coated capsules

    Science.gov (United States)

    White, Scott R.; Sottos, Nancy R.; Kang, Sen; Baginska, Marta B.

    2018-04-17

    One aspect of the invention is a polymer material comprising a capsule coated with PDA. In certain embodiments, the capsule encapsulates a functional agent. The encapsulated functional agent may be an indicating agent, healing agent, protecting agent, pharmaceutical drug, food additive, or a combination thereof.

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

    Science.gov (United States)

    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.

  13. Materials, processes, and environmental engineering network

    Science.gov (United States)

    White, Margo M.

    1993-01-01

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

  14. Development of a sealing process of capsules for surveillance test tubes of the vessel in nuclear power plants; Desarrollo de proceso de sellado de capsulas para probetas de vigilancia de la vasija en nucleoelectricas

    Energy Technology Data Exchange (ETDEWEB)

    Romero C, J.; Fernandez T, F.; Perez R, N.; Rocamontes A, M.; Garcia R, R. [ININ, Km 36.5 Carretera Mexico-Toluca, 52750 La Marquesa, Estado de Mexico (Mexico)

    2007-07-01

    The surveillance capsule is composed by the support, three capsules for impact test tubes, five capsules for tension test tubes and one porta dosemeters. The capsules for test tubes are of two types: rectangular capsule for Charpy test tubes and cylindrical capsule for tension test tubes. This work describes the development of the welding system to seal the capsules for test tubes that should contain helium of ultra high purity to a pressure of 1 atmosphere. (Author)

  15. Study on transfer rule of chemical constituents of tianshu capsule in productive process by high-performance liquid chromatography coupled with diode-array detection and quadrupole time-of-flight tandem mass spectrometry

    International Nuclear Information System (INIS)

    Lian, Y.P.; Xie, D.W.; Li, Y.J.; Xiao, W.; Huang, W.Z.; Ding, G.

    2016-01-01

    To develop a sensitive and accurate method for the fingerprint study and transfer rule of chemical constituents from Ligusticum chuanxiong Hort and Gastrodia elata Blume to Tianshu capsule in productive process, a high performance liquid chromatography coupled with diode-array detection and electrospray ionization quadrupole time-of-flight mass spectrometry (LC/QTOF-MS) method was established for analysis. The reference fingerprints of aqueous extract intermediate of medicinal material, alcohol extract intermediate of medicinal material and Tianshu capsule was established. The methodology was studied and the similarity was more than 0.99. The chromatographic methods demonstrated a good precision, repeatability, stability, with relative standard deviations of less than 3 percent for relative retention time and relative peak area. According to these fingerprints, some chemical constituents in the fingerprints were identified or tentatively identified based on their retention time, exact molecular weight and literature. Among of them 26 constituents were from Ligusticum chuanxiong Hort and nine components were from Gastrodia elata Blume. 25 out of 26 compounds had entered a transfer process and 17 compounds were transferred from intermediates to the final preparation, the Tianshu capsule. Thus, it is reasonable enough to use this transfer process to demonstrate the production technology. To sum up, this method is sensitive, accurate and useful,and it could provide us an approach to evaluate the production technology of Tianshu capsule. (author)

  16. Magnetically guided capsule endoscopy.

    Science.gov (United States)

    Shamsudhin, Naveen; Zverev, Vladimir I; Keller, Henrik; Pane, Salvador; Egolf, Peter W; Nelson, Bradley J; Tishin, Alexander M

    2017-08-01

    Wireless capsule endoscopy (WCE) is a powerful tool for medical screening and diagnosis, where a small capsule is swallowed and moved by means of natural peristalsis and gravity through the human gastrointestinal (GI) tract. The camera-integrated capsule allows for visualization of the small intestine, a region which was previously inaccessible to classical flexible endoscopy. As a diagnostic tool, it allows to localize the sources of bleedings in the middle part of the gastrointestinal tract and to identify diseases, such as inflammatory bowel disease (Crohn's disease), polyposis syndrome, and tumors. The screening and diagnostic efficacy of the WCE, especially in the stomach region, is hampered by a variety of technical challenges like the lack of active capsular position and orientation control. Therapeutic functionality is absent in most commercial capsules, due to constraints in capsular volume and energy storage. The possibility of using body-exogenous magnetic fields to guide, orient, power, and operate the capsule and its mechanisms has led to increasing research in Magnetically Guided Capsule Endoscopy (MGCE). This work shortly reviews the history and state-of-art in WCE technology. It highlights the magnetic technologies for advancing diagnostic and therapeutic functionalities of WCE. Not restricting itself to the GI tract, the review further investigates the technological developments in magnetically guided microrobots that can navigate through the various air- and fluid-filled lumina and cavities in the body for minimally invasive medicine. © 2017 American Association of Physicists in Medicine.

  17. Advanced business process management in networked E-business scenarios

    NARCIS (Netherlands)

    Grefen, P.W.P.J.; Türetken, O.

    2017-01-01

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

  18. Soft gelatin capsules (softgels).

    Science.gov (United States)

    Gullapalli, Rampurna Prasad

    2010-10-01

    It is estimated that more than 40% of new chemical entities (NCEs) coming out of the current drug discovery process have poor biopharmaceutical properties, such as low aqueous solubility and/or permeability. These suboptimal properties pose significant challenges for the oral absorption of the compounds and for the development of orally bioavailable dosage forms. Development of soft gelatin capsule (softgel) dosage form is of growing interest for the oral delivery of poorly water soluble compounds (BCS class II or class IV). The softgel dosage form offers several advantages over other oral dosage forms, such as delivering a liquid matrix designed to solubilize and improve the oral bioavailability of a poorly soluble compound as a unit dose solid dosage form, delivering low and ultra-low doses of a compound, delivering a low melting compound, and minimizing potential generation of dust during manufacturing and thereby improving the safety of production personnel. However, due to the very dynamic nature of the softgel dosage form, its development and stability during its shelf-life are fraught with several challenges. The goal of the current review is to provide an in-depth discussion on the softgel dosage form to formulation scientists who are considering developing softgels for therapeutic compounds.

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

    CERN Document Server

    Hu, Fei

    2012-01-01

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

  20. Synthesis and Design of Integrated Process and Water Networks

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  1. Kriteria Pemilihan Pemasok Menggunakan Analytical Network Process

    Directory of Open Access Journals (Sweden)

    Dewi Kurniawati

    2013-01-01

    Full Text Available The selection of supplier is a strategic decision in supply chain which increase competitive advantages. Every manufacture needs to have a standard supplier selection that appropriate with the requirement of the company. The aims of this paper are promoting some criterias of supplier selection and testing whether there are differences interests against priority criteria referred to of strata tenure distinct. Weights and priorities of the criteria tested with a method of analytic network process (ANP are also intended to bring up a relation of mutual influence among the criteria. ANP can be used to help making decision of selection supplier and to manage supply chain performance. This paper shows the criteria that influence are the past perfomance, price, communication systems, and a supplier of professionalism is the priority for the production of the company. In the other hand, the importance of management is the delivery time, consistent quality, price, and number of delivery. The difference in perspective is influenced by the level of interest and different responsibilities. The difference this assessment formed the basis of decision-making and strategic policies of the supply chain according to the condition of the company.

  2. Pre-processing for Triangulation of Probabilistic Networks

    NARCIS (Netherlands)

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

    2001-01-01

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

  3. NIF capsule performance modeling

    Directory of Open Access Journals (Sweden)

    Weber S.

    2013-11-01

    Full Text Available Post-shot modeling of NIF capsule implosions was performed in order to validate our physical and numerical models. Cryogenic layered target implosions and experiments with surrogate targets produce an abundance of capsule performance data including implosion velocity, remaining ablator mass, times of peak x-ray and neutron emission, core image size, core symmetry, neutron yield, and x-ray spectra. We have attempted to match the integrated data set with capsule-only simulations by adjusting the drive and other physics parameters within expected uncertainties. The simulations include interface roughness, time-dependent symmetry, and a model of mix. We were able to match many of the measured performance parameters for a selection of shots.

  4. Multidimensional epidemic thresholds in diffusion processes over interdependent networks

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  5. Towards Business Process Management in networked ecosystems

    NARCIS (Netherlands)

    Johan Versendaal; dr. Martijn Zoet; Jeroen Grondelle

    2014-01-01

    Managing and supporting the collaboration between different actors is key in any organizational context, whether of a hierarchical or a networked nature. In the networked context of ecosystems of service providers and other stakeholders, BPM is faced with different challenges than in a conventional

  6. Optical processing for future computer networks

    Science.gov (United States)

    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.

  7. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  8. Modelling aspects of distributed processing in telecommunication networks

    NARCIS (Netherlands)

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

    1998-01-01

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

  9. DAPNA: an architectural framework for data processing networks

    NARCIS (Netherlands)

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

    2013-01-01

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

  10. Data Farming Process and Initial Network Analysis Capabilities

    Directory of Open Access Journals (Sweden)

    Gary Horne

    2016-01-01

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

  11. Production, deformation and mechanical investigation of magnetic alginate capsules

    Science.gov (United States)

    Zwar, Elena; Kemna, Andre; Richter, Lena; Degen, Patrick; Rehage, Heinz

    2018-02-01

    In this article we investigated the deformation of alginate capsules in magnetic fields. The sensitivity to magnetic forces was realised by encapsulating an oil in water emulsion, where the oil droplets contained dispersed magnetic nanoparticles. We solved calcium ions in the aqueous emulsion phase, which act as crosslinking compounds for forming thin layers of alginate membranes. This encapsulating technique allows the production of flexible capsules with an emulsion as the capsule core. It is important to mention that the magnetic nanoparticles were stable and dispersed throughout the complete process, which is an important difference to most magnetic alginate-based materials. In a series of experiments, we used spinning drop techniques, capsule squeezing experiments and interfacial shear rheology in order to determine the surface Young moduli, the surface Poisson ratios and the surface shear moduli of the magnetically sensitive alginate capsules. In additional experiments, we analysed the capsule deformation in magnetic fields. In spinning drop and capsule squeezing experiments, water droplets were pressed out of the capsules at elevated values of the mechanical load. This phenomenon might be used for the mechanically triggered release of water-soluble ingredients. After drying the emulsion-filled capsules, we produced capsules, which only contained a homogeneous oil phase with stable suspended magnetic nanoparticles (organic ferrofluid). In the dried state, the thin alginate membranes of these particles were rather rigid. These dehydrated capsules could be stored at ambient conditions for several months without changing their properties. After exposure to water, the alginate membranes rehydrated and became flexible and deformable again. During this swelling process, water diffused back in the capsule. This long-term stability and rehydration offers a great spectrum of different applications as sensors, soft actuators, artificial muscles or drug delivery systems.

  12. Developing a network: the PMM process.

    Science.gov (United States)

    Kamara, A

    1997-11-01

    Since 1988, the Prevention of Maternal Mortality (PMM) Network has developed, implemented and evaluated projects that focus directly on prevention of maternal deaths. The Network, which consists of 11 multidisciplinary teams in West Africa and one at Columbia University, grew from discussions between the Carnegie Corporation of New York and researchers at Columbia School of Public Health. Its goals are: to strengthen capacities in developing countries; to provide program models for preventing maternal deaths; and to inform policymakers about the importance of maternal mortality. This paper describes the development and functioning of the Network. The initial steps included identifying interested partners in Africa and encouraging them to form multidisciplinary teams. Each African team received two grants: one to perform a needs assessment and then another to develop and implement projects based on the results. The Columbia team provided technical assistance in a variety of ways, including site visits, workshops and correspondence. Teams tested program models and reported findings both to local policymakers and in international fora. Collaboration with government and community leaders helped facilitate progress at all stages. At the PMM Network Results Conference in 1996, the teams decided to continue their work by forming the Regional PMM (RPMM) Network, an entirely African entity.

  13. Network measures for characterising team adaptation processes

    NARCIS (Netherlands)

    Barth, S.K.; Schraagen, J.M.C.; Schmettow, M.

    2015-01-01

    The aim of this study was to advance the conceptualisation of team adaptation by applying social network analysis (SNA) measures in a field study of a paediatric cardiac surgical team adapting to changes in task complexity and ongoing dynamic complexity. Forty surgical procedures were observed by

  14. Designing neural networks that process mean values of random variables

    International Nuclear Information System (INIS)

    Barber, Michael J.; Clark, John W.

    2014-01-01

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

  15. Designing neural networks that process mean values of random variables

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

    2014-06-13

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

  16. Interestingness-Driven Diffusion Process Summarization in Dynamic Networks

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  17. Parallel Distributed Processing theory in the age of deep networks

    OpenAIRE

    Bowers, Jeffrey

    2017-01-01

    Parallel Distributed Processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely, that all knowledge is coded in a distributed format, and cognition is mediated by non-symbolic computations. These claims have long been debated within cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks le...

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

    Science.gov (United States)

    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.

  19. Production of 131I gelatin capsules

    International Nuclear Information System (INIS)

    Freud, A.; Hirshfeld, N.; Canfi, A.; Melamud, Y.

    1997-01-01

    Radioiodine ( 131 I) hard-gelatin capsules are widely used for the diagnosis and treatment of various thyroid disorders. Until 1980 radioiodine was supplied by us as a liquid dosage. This proved to be a rather inconvenient form since it resulted in inaccurate dosing by the physicians and caused frequent contamination of the patients and the hospital personnel. In an attempt to overcome these problems we have designed and constructed a production facility for capsules in which 1311 is packaged. Because of the extreme precautions necessary in handling radioactive compounds, encapsulation of radioactive materials requires specifically designed production techniques, special instrumentation and unique quality control procedures that are not encountered in the standard capsule production processes in the pharmaceutical industry

  20. Identifying and tracking dynamic processes in social networks

    Science.gov (United States)

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

    2006-05-01

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

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

    Science.gov (United States)

    Neal, Zachary P

    2014-06-01

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

  2. Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

    NARCIS (Netherlands)

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

    2016-01-01

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

  3. Toward an integrated model of capsule regulation in Cryptococcus neoformans.

    Directory of Open Access Journals (Sweden)

    Brian C Haynes

    2011-12-01

    Full Text Available Cryptococcus neoformans is an opportunistic fungal pathogen that causes serious human disease in immunocompromised populations. Its polysaccharide capsule is a key virulence factor which is regulated in response to growth conditions, becoming enlarged in the context of infection. We used microarray analysis of cells stimulated to form capsule over a range of growth conditions to identify a transcriptional signature associated with capsule enlargement. The signature contains 880 genes, is enriched for genes encoding known capsule regulators, and includes many uncharacterized sequences. One uncharacterized sequence encodes a novel regulator of capsule and of fungal virulence. This factor is a homolog of the yeast protein Ada2, a member of the Spt-Ada-Gcn5 Acetyltransferase (SAGA complex that regulates transcription of stress response genes via histone acetylation. Consistent with this homology, the C. neoformans null mutant exhibits reduced histone H3 lysine 9 acetylation. It is also defective in response to a variety of stress conditions, demonstrating phenotypes that overlap with, but are not identical to, those of other fungi with altered SAGA complexes. The mutant also exhibits significant defects in sexual development and virulence. To establish the role of Ada2 in the broader network of capsule regulation we performed RNA-Seq on strains lacking either Ada2 or one of two other capsule regulators: Cir1 and Nrg1. Analysis of the results suggested that Ada2 functions downstream of both Cir1 and Nrg1 via components of the high osmolarity glycerol (HOG pathway. To identify direct targets of Ada2, we performed ChIP-Seq analysis of histone acetylation in the Ada2 null mutant. These studies supported the role of Ada2 in the direct regulation of capsule and mating responses and suggested that it may also play a direct role in regulating capsule-independent antiphagocytic virulence factors. These results validate our experimental approach to dissecting

  4. Contagion processes on the static and activity driven coupling networks

    OpenAIRE

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

    2015-01-01

    The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and a...

  5. Towards Device-Independent Information Processing on General Quantum Networks

    Science.gov (United States)

    Lee, Ciarán M.; Hoban, Matty J.

    2018-01-01

    The violation of certain Bell inequalities allows for device-independent information processing secure against nonsignaling eavesdroppers. However, this only holds for the Bell network, in which two or more agents perform local measurements on a single shared source of entanglement. To overcome the practical constraints that entangled systems can only be transmitted over relatively short distances, large-scale multisource networks have been employed. Do there exist analogs of Bell inequalities for such networks, whose violation is a resource for device independence? In this Letter, the violation of recently derived polynomial Bell inequalities will be shown to allow for device independence on multisource networks, secure against nonsignaling eavesdroppers.

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

    Science.gov (United States)

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

    1991-01-01

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

  7. Understanding human visual processing with Deep Neural Networks

    OpenAIRE

    Thorat, Sushrut

    2016-01-01

    This presentation has 2 parts:1. An introduction to the vision processing - neuroscience, and machine vision.2. Discussion of one of the first papers relating Deep Networks to the visual ventral stream. (Khaligh-Razavi, 2014)

  8. Parallel Distributed Processing Theory in the Age of Deep Networks.

    Science.gov (United States)

    Bowers, Jeffrey S

    2017-12-01

    Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

  9. Processing horizontal networks measured by integrated terrestrial and GPS technologies

    Directory of Open Access Journals (Sweden)

    Vincent Jakub

    2003-09-01

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

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

    International Nuclear Information System (INIS)

    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

  11. Precision Scaling of Neural Networks for Efficient Audio Processing

    OpenAIRE

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

    2017-01-01

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

  12. Neural PID Control Strategy for Networked Process Control

    Directory of Open Access Journals (Sweden)

    Jianhua Zhang

    2013-01-01

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

  13. Neural network training by Kalman filtering in process system monitoring

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1996-03-01

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

  14. Software/hardware distributed processing network supporting the Ada environment

    Science.gov (United States)

    Wood, Richard J.; Pryk, Zen

    1993-09-01

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

  15. Robust collaborative process interactions under system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2013-01-01

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes its state, it sends messages to the relevant processes to inform about this change. However, server crashes

  16. Social network analysis in software process improvement

    DEFF Research Database (Denmark)

    Nielsen, Peter Axel; Tjørnehøj, Gitte

    2010-01-01

    Software process improvement in small organisation is often problematic and communication and knowledge sharing is more informal. To improve software processes we need to understand how they communicate and share knowledge. In this article have studied the company SmallSoft through action research...

  17. Process efficiency. Redesigning social networks to improve surgery patient flow.

    Science.gov (United States)

    Samarth, Chandrika N; Gloor, Peter A

    2009-01-01

    We propose a novel approach to improve throughput of the surgery patient flow process of a Boston area teaching hospital. A social network analysis was conducted in an effort to demonstrate that process efficiency gains could be achieved through redesign of social network patterns at the workplace; in conjunction with redesign of organization structure and the implementation of workflow over an integrated information technology system. Key knowledge experts and coordinators in times of crisis were identified and a new communication structure more conducive to trust and knowledge sharing was suggested. The new communication structure is scalable without compromising on coordination required among key roles in the network for achieving efficiency gains.

  18. Engineering processes for the African VLBI network

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Crosetto, Dario B.

    1996-01-01

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

  20. Scalable Networked Information Processing Environment (SNIPE)

    Energy Technology Data Exchange (ETDEWEB)

    Fagg, G.E.; Moore, K. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science; Dongarra, J.J. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science]|[Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Geist, A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.

    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.

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

    Science.gov (United States)

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

    2010-01-19

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

  2. High temperature radioisotope capsule

    International Nuclear Information System (INIS)

    Bradshaw, G.B.

    1976-01-01

    A high temperature radioisotope capsule made up of three concentric cylinders, with the isotope fuel located within the innermost cylinder is described. The innermost cylinder has hemispherical ends and is constructed of a tantalum alloy. The intermediate cylinder is made of a molybdenum alloy and is capable of withstanding the pressure generated by the alpha particle decay of the fuel. The outer cylinder is made of a platinum alloy of high resistance to corrosion. A gas separates the innermost cylinder from the intermediate cylinder and the intermediate cylinder from the outer cylinder

  3. Competing Contact Processes on Homogeneous Networks with Tunable Clusterization

    Science.gov (United States)

    Rybak, Marcin; Kułakowski, Krzysztof

    2013-03-01

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

  4. Design of common heat exchanger network for batch processes

    International Nuclear Information System (INIS)

    Anastasovski, Aleksandar

    2014-01-01

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

  5. Towards the understanding of network information processing in biology

    Science.gov (United States)

    Singh, Vijay

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

  6. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  7. Renal fascial network in retroperitoneal extension of pathologic processes

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  8. A fuzzy art neural network based color image processing and ...

    African Journals Online (AJOL)

    To improve the learning process from the input data, a new learning rule was suggested. In this paper, a new method is proposed to deal with the RGB color image pixels, which enables a Fuzzy ART neural network to process the RGB color images. The application of the algorithm was implemented and tested on a set of ...

  9. All-optical signal processing for optical packet switching networks

    NARCIS (Netherlands)

    Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

    2005-01-01

    We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

  10. Optimization of blanking process using neural network simulation

    International Nuclear Information System (INIS)

    Hambli, R.

    2005-01-01

    The present work describes a methodology using the finite element method and neural network simulation in order to predict the optimum punch-die clearance during sheet metal blanking processes. A damage model is used in order to describe crack initiation and propagation into the sheet. The proposed approach combines predictive finite element and neural network modeling of the leading blanking parameters. Numerical results obtained by finite element computation including damage and fracture modeling were utilized to train the developed simulation environment based on back propagation neural network modeling. The comparative study between the numerical results and the experimental ones shows the good agreement. (author)

  11. Bayesian network modeling of operator's state recognition process

    International Nuclear Information System (INIS)

    Hatakeyama, Naoki; Furuta, Kazuo

    2000-01-01

    Nowadays we are facing a difficult problem of establishing a good relation between humans and machines. To solve this problem, we suppose that machine system need to have a model of human behavior. In this study we model the state cognition process of a PWR plant operator as an example. We use a Bayesian network as an inference engine. We incorporate the knowledge hierarchy in the Bayesian network and confirm its validity using the example of PWR plant operator. (author)

  12. Natural Language Processing with Small Feed-Forward Networks

    OpenAIRE

    Botha, Jan A.; Pitler, Emily; Ma, Ji; Bakalov, Anton; Salcianu, Alex; Weiss, David; McDonald, Ryan; Petrov, Slav

    2017-01-01

    We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper in memory and computational requirements than deep recurrent models. Motivated by resource-constrained environments like mobile phones, we showcase simple techniques for obtaining such small neural network models, and investigate different tradeoffs when deciding how to allocate a small memory...

  13. Improving Earth/Prediction Models to Improve Network Processing

    Science.gov (United States)

    Wagner, G. S.

    2017-12-01

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

  14. Capsule endoscopy: Beyond small bowel

    Directory of Open Access Journals (Sweden)

    Samuel N Adler

    2012-01-01

    Full Text Available In this article the brief and dramatic history of capsule endoscopy of the digestive tract is reviewed. Capsule endoscopy offers a non invasive method to diagnose diseases that affect the esophagus, small bowel and colon. Technological improvements relating to optics, software, data recorders with two way communication have revolutionized this field. These advancements have produced better diagnostic performance.

  15. High-speed precision weighing of pharmaceutical capsules

    International Nuclear Information System (INIS)

    Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

    2009-01-01

    In this paper, we present a cost-effective method for fast and accurate in-line weighing of hard gelatin capsules based on the optimized capacitance sensor and real-time processing of the capsule capacitance profile resulting from 5000 capacitance measurements per second. First, the effect of the shape and size of the capacitive sensor on the sensitivity and stability of the measurements was investigated in order to optimize the performance of the system. The method was tested on two types of hard gelatin capsules weighing from 50 mg to 650 mg. The results showed that the capacitance profile was exceptionally well correlated with the capsule weight with the correlation coefficient exceeding 0.999. The mean precision of the measurements was in the range from 1 mg to 3 mg, depending on the size of the capsule and was significantly lower than the 5% weight tolerances usually used by the pharmaceutical industry. Therefore, the method was found feasible for weighing pharmaceutical hard gelatin capsules as long as certain conditions are met regarding the capsule fill properties and environment stability. The proposed measurement system can be calibrated by using only two or three sets of capsules with known weight. However, for most applications it is sufficient to use only empty and nominally filled capsules for calibration. Finally, a practical application of the proposed method showed that a single system is capable of weighing around 75 000 capsules per hour, while using multiple systems could easily increase the inspection rate to meet almost any requirements

  16. Sustainable Process Networks for CO2 Conversion

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Kongpanna, P.; Pavarajam, V.

    According to various organizations, especially the Intergovernmental Panel on Climate Change, global warming is an ever-increasing threat to the environment and poses a problem if not addressed. As a result, efforts are being made across academic and industrial fields to find methods of reducing...... drawbacks to this geologic storage system: the CO2 is not eliminated, the implementation is limited due to natural phenomena, and the capturing methods are often expensive. Thus, it is desirable to develop an alternative strategy for reducing the CO2 emissions [2]. An additional process that reduces...... that are thermodynamically feasible, including the co-reactants, catalysts, operating conditions and reactions. Research has revealed that there are a variety of reactions that fulfill the aforementioned criteria. The products that are formed fall into categories: fuels, bulk chemicals and specialty chemicals. While fuels...

  17. Multimodal processes scheduling in mesh-like network environment

    Directory of Open Access Journals (Sweden)

    Bocewicz Grzegorz

    2015-06-01

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

  18. A Study on the Manufacturing Properties of Crack Self-Healing Capsules Using Cement Powder for Addition to Cement Composites

    OpenAIRE

    Choi, Yun-Wang; Oh, Sung-Rok; Choi, Byung-Keol

    2017-01-01

    We fabricated crack self-healing capsules using cement powder for mixing into cement composites and evaluated the properties of the capsule manufacturing process in this study. The manufacture of the self-healing capsules is divided into core production processing of granulating cement in powder form and a coating process for creating a wall on the surfaces of the granulated cement particles. The produced capsules contain unhardened cement and can be mixed directly with the cement composite m...

  19. pn: A Tool for Improved Derivation of Process Networks

    Directory of Open Access Journals (Sweden)

    Sven Verdoolaege

    2007-04-01

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

  20. A Generic Methodology for Superstructure Optimization of Different Processing Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Frauzem, Rebecca; Zhang, Lei

    2016-01-01

    In this paper, we propose a generic computer-aided methodology for synthesis of different processing networks using superstructure optimization. The methodology can handle different network optimization problems of various application fields. It integrates databases with a common data architecture......, a generic model to represent the processing steps, and appropriate optimization tools. A special software interface has been created to automate the steps in the methodology workflow, allow the transfer of data between tools and obtain the mathematical representation of the problem as required...

  1. Possibilistic networks for uncertainty knowledge processing in student diagnosis

    Directory of Open Access Journals (Sweden)

    Adina COCU

    2006-12-01

    Full Text Available In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.

  2. Nonlinear identification of process dynamics using neural networks

    International Nuclear Information System (INIS)

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

    1992-01-01

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

  3. Social networks in nursing work processes: an integrative literature review

    Directory of Open Access Journals (Sweden)

    Ana Cláudia Mesquita

    Full Text Available Abstract OBJECTIVE To identify and analyze the available evidence in the literature on the use of social networks in nursing work processes. METHOD An integrative review of the literature conducted in PubMed, CINAHL, EMBASE and LILACS databases in January 2016, using the descriptors social media, social networking, nursing, enfermagem, redes sociais, mídias sociais, and the keyword nursing practice, without year restriction. RESULTS The sample consisted of 27 international articles which were published between 2011 and 2016. The social networks used were Facebook (66.5%, Twitter (30% and WhatsApp (3.5%. In 70.5% of the studies, social networks were used for research purposes, in 18.5% they were used as a tool aimed to assist students in academic activities, and in 11% for executing interventions via the internet. CONCLUSION Nurses have used social networks in their work processes such as Facebook, Twitter and WhatsApp to research, teach and watch. The articles show several benefits in using such tools in the nursing profession; however, ethical considerations regarding the use of social networks deserve further discussion.

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

    Science.gov (United States)

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

    2014-12-01

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

  5. Processing of seismic signals from a seismometer network

    International Nuclear Information System (INIS)

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

    1983-08-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Collaborative In-Network Processing for Target Tracking

    Directory of Open Access Journals (Sweden)

    Juan Liu

    2003-03-01

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

  9. Multiple k Nearest Neighbor Query Processing in Spatial Network Databases

    DEFF Research Database (Denmark)

    Xuegang, Huang; Jensen, Christian Søndergaard; Saltenis, Simonas

    2006-01-01

    This paper concerns the efficient processing of multiple k nearest neighbor queries in a road-network setting. The assumed setting covers a range of scenarios such as the one where a large population of mobile service users that are constrained to a road network issue nearest-neighbor queries...... for points of interest that are accessible via the road network. Given multiple k nearest neighbor queries, the paper proposes progressive techniques that selectively cache query results in main memory and subsequently reuse these for query processing. The paper initially proposes techniques for the case...... where an upper bound on k is known a priori and then extends the techniques to the case where this is not so. Based on empirical studies with real-world data, the paper offers insight into the circumstances under which the different proposed techniques can be used with advantage for multiple k nearest...

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  11. Learning to Diagnose Cirrhosis with Liver Capsule Guided Ultrasound Image Classification

    Directory of Open Access Journals (Sweden)

    Xiang Liu

    2017-01-01

    Full Text Available This paper proposes a computer-aided cirrhosis diagnosis system to diagnose cirrhosis based on ultrasound images. We first propose a method to extract a liver capsule on an ultrasound image, then, based on the extracted liver capsule, we fine-tune a deep convolutional neural network (CNN model to extract features from the image patches cropped around the liver capsules. Finally, a trained support vector machine (SVM classifier is applied to classify the sample into normal or abnormal cases. Experimental results show that the proposed method can effectively extract the liver capsules and accurately classify the ultrasound images.

  12. An application of neural networks to process and materials control

    International Nuclear Information System (INIS)

    Howell, J.A.; Whiteson, R.

    1991-01-01

    Process control consists of two basic elements: a model of the process and knowledge of the desired control algorithm. In some cases the level of the control algorithm is merely supervisory, as in an alarm-reporting or anomaly-detection system. If the model of the process is known, then a set of equations may often be solved explicitly to provide the control algorithm. Otherwise, the model has to be discovered through empirical studies. Neural networks have properties that make them useful in this application. They can learn (make internal models from experience or observations). The problem of anomaly detection in materials control systems fits well into this general control framework. To successfully model a process with a neutral network, a good set of observables must be chosen. These observables must in some sense adequately span the space of representable events, so that a signature metric can be built for normal operation. In this way, a non-normal event, one that does not fit within the signature, can be detected. In this paper, we discuss the issues involved in applying a neural network model to anomaly detection in materials control systems. These issues include data selection and representation, network architecture, prediction of events, the use of simulated data, and software tools. 10 refs., 4 figs., 1 tab

  13. MODEL ANALYTICAL NETWORK PROCESS (ANP DALAM PENGEMBANGAN PARIWISATA DI JEMBER

    Directory of Open Access Journals (Sweden)

    Sukidin Sukidin

    2015-04-01

    Full Text Available Abstrak    : Model Analytical Network Process (ANP dalam Pengembangan Pariwisata di Jember. Penelitian ini mengkaji kebijakan pengembangan pariwisata di Jember, terutama kebijakan pengembangan agrowisata perkebunan kopi dengan menggunakan Jember Fashion Carnival (JFC sebagai event marketing. Metode yang digunakan adalah soft system methodology dengan menggunakan metode analitis jaringan (Analytical Network Process. Penelitian ini menemukan bahwa pengembangan pariwisata di Jember masih dilakukan dengan menggunakan pendekatan konvensional, belum terkoordinasi dengan baik, dan lebih mengandalkan satu even (atraksi pariwisata, yakni JFC, sebagai lokomotif daya tarik pariwisata Jember. Model pengembangan konvensional ini perlu dirancang kembali untuk memperoleh pariwisata Jember yang berkesinambungan. Kata kunci: pergeseran paradigma, industry pariwisata, even pariwisata, agrowisata Abstract: Analytical Network Process (ANP Model in the Tourism Development in Jember. The purpose of this study is to conduct a review of the policy of tourism development in Jember, especially development policies for coffee plantation agro-tourism by using Jember Fashion Carnival (JFC as event marketing. The research method used is soft system methodology using Analytical Network Process. The result shows that the tourism development in Jember is done using a conventional approach, lack of coordination, and merely focus on a single event tourism, i.e. the JFC, as locomotive tourism attraction in Jember. This conventional development model needs to be redesigned to reach Jember sustainable tourism development. Keywords: paradigm shift, tourism industry, agro-tourism

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

    Science.gov (United States)

    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…

  15. Mapping debris flow susceptibility using analytical network process ...

    Indian Academy of Sciences (India)

    Evangelin Ramani Sujatha

    2017-11-23

    Nov 23, 2017 ... methods known as the analytical network process (ANP) is used to map the ..... ciated in any prospective way, through feedbacks ..... slide susceptibility by means of multivariate statistical .... and bivariate statistics: A case study in southern Italy;. Nat. ... combination applied to Tevankarai Stream Watershed,.

  16. Neural network connectivity and response latency modelled by stochastic processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...

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

    NARCIS (Netherlands)

    Zissulescu-Ianculescu, Claudiu

    2008-01-01

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

  18. Network formation determined by the diffusion process of random walkers

    International Nuclear Information System (INIS)

    Ikeda, Nobutoshi

    2008-01-01

    We studied the diffusion process of random walkers in networks formed by their traces. This model considers the rise and fall of links determined by the frequency of transports of random walkers. In order to examine the relation between the formed network and the diffusion process, a situation in which multiple random walkers start from the same vertex is investigated. The difference in diffusion rate of random walkers according to the difference in dimension of the initial lattice is very important for determining the time evolution of the networks. For example, complete subgraphs can be formed on a one-dimensional lattice while a graph with a power-law vertex degree distribution is formed on a two-dimensional lattice. We derived some formulae for predicting network changes for the 1D case, such as the time evolution of the size of nearly complete subgraphs and conditions for their collapse. The networks formed on the 2D lattice are characterized by the existence of clusters of highly connected vertices and their life time. As the life time of such clusters tends to be small, the exponent of the power-law distribution changes from γ ≅ 1-2 to γ ≅ 3

  19. Competing spreading processes and immunization in multiplex networks

    International Nuclear Information System (INIS)

    Gao, Bo; Deng, Zhenghong; Zhao, Dawei

    2016-01-01

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

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

    Science.gov (United States)

    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.

  1. Qualia could arise from information processing in local cortical networks.

    Science.gov (United States)

    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.

  2. Applying Trusted Network Technology To Process Control Systems

    Science.gov (United States)

    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.

  3. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

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

    2017-05-01

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

  4. Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Caiyun Huang

    2014-07-01

    Full Text Available As a newly proposed theory, compressive sensing (CS is commonly used in signal processing area. This paper investigates the applications of compressed sensing (CS in wireless sensor networks (WSNs. First, the development and research status of compressed sensing technology and wireless sensor networks are described, then a detailed investigation of WSNs research based on CS are conducted from aspects of data fusion, signal acquisition, signal routing transmission, and signal reconstruction. At the end of the paper, we conclude our survey and point out the possible future research directions.

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

    Science.gov (United States)

    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.

  6. Status of irradiation capsule design

    International Nuclear Information System (INIS)

    Nagata, Hiroshi; Yamaura, Takayuki; Nagao, Yoshiharu

    2013-01-01

    For the irradiation test after the restart of JMTR, further precise temperature control and temperature prediction are required. In the design of irradiation capsule, particularly sophisticated irradiation temperature prediction and evaluation are urged. Under such circumstance, among the conventional design techniques of irradiation capsule, the authors reviewed the evaluation method of irradiation temperature. In addition, for the improvement of use convenience, this study examined and improved FINAS/STAR code in order to adopt the new calculation code that enables a variety of analyses. In addition, the study on the common use of the components for radiation capsule enabled the shortening of design period. After the restart, the authors will apply this improved calculation code to the design of irradiation capsule. (A.O.)

  7. Uncertainty Reduction for Stochastic Processes on Complex Networks

    Science.gov (United States)

    Radicchi, Filippo; Castellano, Claudio

    2018-05-01

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

  8. Promoting information diffusion through interlayer recovery processes in multiplex networks

    Science.gov (United States)

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

    2017-09-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

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

  10. Modeling of an industrial drying process by artificial neural networks

    Directory of Open Access Journals (Sweden)

    E. Assidjo

    2008-09-01

    Full Text Available A suitable method is needed to solve the nonquality problem in the grated coconut industry due to the poor control of product humidity during the process. In this study the possibility of using an artificial neural network (ANN, precisely a Multilayer Perceptron, for modeling the drying step of the production of grated coconut process is highlighted. Drying must confer to the product a final moisture of 3%. Unfortunately, under industrial conditions, this moisture varies from 1.9 to 4.8 %. In order to control this parameter and consequently reduce the proportion of the product that does not meet the humidity specification, a 9-4-1 neural network architecture was established using data gathered from an industrial plant. This Multilayer Perceptron can satisfactorily model the process with less bias, ranging from -0.35 to 0.34%, and can reduce the rate of rejected products from 92% to 3% during the first cycle of drying.

  11. Generation of colloidal granules and capsules from double emulsion drops

    Science.gov (United States)

    Hess, Kathryn S.

    Assemblies of colloidal particles are extensively used in ceramic processing, pharmaceuticals, inks and coatings. In this project, the aim was to develop a new technique to fabricate monodispersed colloidal assemblies. The use of microfluidic devices and emulsion processing allows for the fabrication of complex materials that can be used in a variety of applications. A microfluidic device is used to create monodispersed water/oil/water (w/o/w) double emulsions with interior droplets of colloidal silica suspension ranging in size from tens to hundreds of microns. By tailoring the osmotic pressure using glycerol as a solute in the continuous and inner phases of the emulsion, we can control the final volume size of the monodispersed silica colloidal crystals that form in the inner droplets of the double emulsion. Modifying the ionic strength in the colloidal dispersion can be used to affect the particle-particle interactions and crystal formation of the final colloidal particle. This w/o/w technique has been used with other systems of metal oxide colloids and cellulose nanocrystals. Encapsulation of the colloidal suspension in a polymer shell for the generation of ceramic-polymer core-shell particles has also been developed. These core-shell particles have spawned new research in the field of locally resonant acoustic metamaterials. Systems and chemistries for creating cellulose hydrogels within the double emulsions have also been researched. Water in oil single emulsions and double emulsions have been used to create cellulose hydrogel spheres in the sub-100 micron diameter range. Oil/water/oil double emulsions allow us to create stable cellulose capsules. The addition of a second hydrogel polymer, such as acrylate or alginate, further strengthens the cellulose gel network and can also be processed into capsules and particles using the microfluidic device. This work could have promising applications in acoustic metamaterials, personal care products, pharmaceuticals

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

    Science.gov (United States)

    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.

  13. Analytical network process based optimum cluster head selection in wireless sensor network.

    Science.gov (United States)

    Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

    2017-01-01

    Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of

  14. Versatile Loading of Diverse Cargo into Functional Polymer Capsules.

    Science.gov (United States)

    Richardson, Joseph J; Maina, James W; Ejima, Hirotaka; Hu, Ming; Guo, Junling; Choy, Mei Y; Gunawan, Sylvia T; Lybaert, Lien; Hagemeyer, Christoph E; De Geest, Bruno G; Caruso, Frank

    2015-02-01

    Polymer microcapsules are of particular interest for applications including self-healing coatings, catalysis, bioreactions, sensing, and drug delivery. The primary way that polymer capsules can exhibit functionality relevant to these diverse fields is through the incorporation of functional cargo in the capsule cavity or wall. Diverse functional and therapeutic cargo can be loaded into polymer capsules with ease using polymer-stabilized calcium carbonate (CaCO 3 ) particles. A variety of examples are demonstrated, including 15 types of cargo, yielding a toolbox with effectively 500+ variations. This process uses no harsh reagents and can take less than 30 min to prepare, load, coat, and form the hollow capsules. For these reasons, it is expected that the technique will play a crucial role across scientific studies in numerous fields.

  15. A Fuzzy analytical hierarchy process approach in irrigation networks maintenance

    Science.gov (United States)

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

    2017-11-01

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

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

    Science.gov (United States)

    Dudziak, Martin Joseph

    Quantum theory since its earliest formulations in the Copenhagen Interpretation has been difficult to integrate with general relativity and with classical Newtonian physics. There has been traditionally a regard for quantum phenomena as being a limiting case for a natural order that is fundamentally classical except for microscopic extrema where quantum mechanics must be applied, more as a mathematical reconciliation rather than as a description and explanation. Macroscopic sciences including the study of biological neural networks, cellular energy transports and the broad field of non-linear and chaotic systems point to a quantum dimension extending across all scales of measurement and encompassing all of Nature as a fundamentally quantum universe. Theory and observation lead to a number of hypotheses all of which point to dynamic, evolving networks of fundamental or elementary processes as the underlying logico-physical structure (manifestation) in Nature and a strongly quantized dimension to macroscalar processes such as are found in biological, ecological and social systems. The fundamental thesis advanced and presented herein is that quantum phenomena may be the direct consequence of a universe built not from objects and substance but from interacting, interdependent processes collectively operating as sets and networks, giving rise to systems that on microcosmic or macroscopic scales function wholistically and organically, exhibiting non-locality and other non -classical phenomena. The argument is made that such effects as non-locality are not aberrations or departures from the norm but ordinary consequences of the process-network dynamics of Nature. Quantum processes are taken to be the fundamental action-events within Nature; rather than being the exception quantum theory is the rule. The argument is also presented that the study of quantum physics could benefit from the study of selective higher-scale complex systems, such as neural processes in the brain

  17. Signal Processing Device (SPD) for networked radiation monitoring system

    International Nuclear Information System (INIS)

    Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

    2010-01-01

    A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

  18. Supply Chain Management: from Linear Interactions to Networked Processes

    Directory of Open Access Journals (Sweden)

    Doina FOTACHE

    2006-01-01

    Full Text Available Supply Chain Management is a distinctive product, with a tremendous impact on the software applications market. SCM applications are back-end solutions intended to link suppliers, manufacturers, distributors and resellers in a production and distribution network, which allows the enterprise to track and consolidate the flows of materials and data trough the process of manufacturing and distribution of goods/services. The advent of the Web as a major means of conducting business transactions and business-tobusiness communications, coupled with evolving web-based supply chain management (SCM technology, has resulted in a transition period from “linear” supply chain models to "networked" supply chain models. The technologies to enable dynamic process changes and real time interactions between extended supply chain partners are emerging and being deployed at an accelerated pace.

  19. A Networked Perspective on the Engineering Design Process: At the Intersection of Process and Organisation Architectures

    DEFF Research Database (Denmark)

    Parraguez, Pedro

    projects often fail to be on time, on budget, and meeting specifications. Despite the wealth of process models available, previous approaches have been insufficient to provide a networked perspective that allows the challenging combination of organisational and process complexity to unfold. The lack...

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

    Science.gov (United States)

    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.

  1. Mashup Model and Verification Using Mashup Processing Network

    Science.gov (United States)

    Zahoor, Ehtesham; Perrin, Olivier; Godart, Claude

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

  2. Information processing and routing in wireless sensor networks

    CERN Document Server

    Yu, Yang; Krishnamachari, Bhaskar

    2006-01-01

    This book presents state-of-the-art cross-layer optimization techniques for energy-efficient information processing and routing in wireless sensor networks. Besides providing a survey on this important research area, three specific topics are discussed in detail - information processing in a collocated cluster, information transport over a tree substrate, and information routing for computationally intensive applications. The book covers several important system knobs for cross-layer optimization, including voltage scaling, rate adaptation, and tunable compression. By exploring tradeoffs of en

  3. Social networks in nursing work processes: an integrative literature review.

    Science.gov (United States)

    Mesquita, Ana Cláudia; Zamarioli, Cristina Mara; Fulquini, Francine Lima; Carvalho, Emilia Campos de; Angerami, Emilia Luigia Saporiti

    2017-03-20

    To identify and analyze the available evidence in the literature on the use of social networks in nursing work processes. An integrative review of the literature conducted in PubMed, CINAHL, EMBASE and LILACS databases in January 2016, using the descriptors social media, social networking, nursing, enfermagem, redes sociais, mídias sociais, and the keyword nursing practice, without year restriction. The sample consisted of 27 international articles which were published between 2011 and 2016. The social networks used were Facebook (66.5%), Twitter (30%) and WhatsApp (3.5%). In 70.5% of the studies, social networks were used for research purposes, in 18.5% they were used as a tool aimed to assist students in academic activities, and in 11% for executing interventions via the internet. Nurses have used social networks in their work processes such as Facebook, Twitter and WhatsApp to research, teach and watch. The articles show several benefits in using such tools in the nursing profession; however, ethical considerations regarding the use of social networks deserve further discussion. Identificar e analisar as evidências disponíveis na literatura sobre a utilização de redes sociais nos processos de trabalho em enfermagem. Revisão integrativa da literatura realizada em janeiro de 2016, nas bases de dados PubMed, CINAHL, EMBASE e LILACS, com os descritores social media, social networking, nursing, enfermagem, redes sociais, mídias sociais e a palavra-chave nursing practice, sem restrição de ano. A amostra foi composta por 27 artigos, os quais foram publicados entre 2011 e 2016, todos internacionais. As redes sociais utilizadas foram o Facebook (66,5%), o Twitter (30%) e o WhatsApp (3,5%). Em 70,5% dos estudos as redes sociais foram utilizadas para fins de pesquisa, em 18,5% como ferramenta para auxiliar estudantes nas atividades acadêmicas, e em 11% para a realização de intervenções via internet. Em seus processos de trabalho, os enfermeiros têm utilizado

  4. Processing of chromatic information in a deep convolutional neural network.

    Science.gov (United States)

    Flachot, Alban; Gegenfurtner, Karl R

    2018-04-01

    Deep convolutional neural networks are a class of machine-learning algorithms capable of solving non-trivial tasks, such as object recognition, with human-like performance. Little is known about the exact computations that deep neural networks learn, and to what extent these computations are similar to the ones performed by the primate brain. Here, we investigate how color information is processed in the different layers of the AlexNet deep neural network, originally trained on object classification of over 1.2M images of objects in their natural contexts. We found that the color-responsive units in the first layer of AlexNet learned linear features and were broadly tuned to two directions in color space, analogously to what is known of color responsive cells in the primate thalamus. Moreover, these directions are decorrelated and lead to statistically efficient representations, similar to the cardinal directions of the second-stage color mechanisms in primates. We also found, in analogy to the early stages of the primate visual system, that chromatic and achromatic information were segregated in the early layers of the network. Units in the higher layers of AlexNet exhibit on average a lower responsivity for color than units at earlier stages.

  5. Processes linked to contact changes in adoptive kinship networks.

    Science.gov (United States)

    Dunbar, Nora; van Dulmen, Manfred H M; Ayers-Lopez, Susan; Berge, Jerica M; Christian, Cinda; Gossman, Ginger; Henney, M Susan M; Mendenhall, Tai J; Grotevant, Harold D; McRoy, Ruth G

    2006-12-01

    The purpose of this study was to reveal underlying processes in adoptive kinship networks that experienced increases or decreases in levels of openness during the child's adolescent years. Intensive case study analyses were conducted for 8 adoptive kinship networks (each including an adoptive mother, adoptive father, adopted adolescent, and birth mother), half of whom had experienced an increase in openness from indirect (mediated) to direct (fully disclosed) contact and half of whom had ceased indirect contact between Waves 1 and 2 of a longitudinal study. Adoptive mothers tended to be more involved in contact with the birth mother than were adoptive fathers or adopted adolescents. Members of adoptive kinship networks in which a decrease in level of contact took place had incongruent perspectives about who initiated the stop in contact and why the stop took place. Birth mothers were less satisfied with their degree of contact than were adoptive parents. Adults' satisfaction with contact was related to feelings of control over type and amount of interactions and permeability of family boundaries. In all adoptive kinship networks, responsibility for contact had shifted toward the adopted adolescent regardless of whether the adolescent was aware of this change in responsibility.

  6. Summary Report for Capsule Dry Storage Project

    Energy Technology Data Exchange (ETDEWEB)

    JOSEPHSON, W S

    2003-09-04

    There are 1.936 cesium (Cs) and strontium (Sr) capsules stored in pools at the Waste Encapsulation and Storage Facility (WESF). These capsules will be moved to dry storage on the Hanford Site as an interim measure to reduce risk. The Cs/Sr Capsule Dry Storage Project (CDSP) is conducted under the assumption the capsules will eventually be moved to the repository at Yucca Mountain, and the design criteria include requirements that will facilitate acceptance at the repository. The storage system must also permit retrieval of capsules in the event vitrification of the capsule contents is pursued. A cut away drawing of a typical cesium chloride (CsCI) capsule and the capsule property and geometry information are provided in Figure 1.1. Strontium fluoride (SrF{sub 2}) capsules are similar in design to CsCl capsules. Further details of capsule design, current state, and reference information are given later in this report and its references. Capsule production and life history is covered in WMP-16938, Capsule Characterization Report for Capsule Dry Storage Project, and is briefly summarized in Section 5.2 of this report.

  7. Proceedings: Distributed digital systems, plant process computers, and networks

    International Nuclear Information System (INIS)

    1995-03-01

    These are the proceedings of a workshop on Distributed Digital Systems, Plant Process Computers, and Networks held in Charlotte, North Carolina on August 16--18, 1994. The purpose of the workshop was to provide a forum for technology transfer, technical information exchange, and education. The workshop was attended by more than 100 representatives of electric utilities, equipment manufacturers, engineering service organizations, and government agencies. The workshop consisted of three days of presentations, exhibitions, a panel discussion and attendee interactions. Original plant process computers at the nuclear power plants are becoming obsolete resulting in increasing difficulties in their effectiveness to support plant operations and maintenance. Some utilities have already replaced their plant process computers by more powerful modern computers while many other utilities intend to replace their aging plant process computers in the future. Information on recent and planned implementations are presented. Choosing an appropriate communications and computing network architecture facilitates integrating new systems and provides functional modularity for both hardware and software. Control room improvements such as CRT-based distributed monitoring and control, as well as digital decision and diagnostic aids, can improve plant operations. Commercially available digital products connected to the plant communications system are now readily available to provide distributed processing where needed. Plant operations, maintenance activities, and engineering analyses can be supported in a cost-effective manner. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database

  8. Design and fabrication of non-instrumented capsule

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yong Sung; Lee, Jeong Young; Kim, Joon Yeon; Lee, Sung Ho; Ji, Dae Young; Kim, Suk Hoon; Ahn, Sung Ho [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1995-04-01

    The use of non-instrumented capsule designed and fabricated in this time is for the evaluation of material irradiation performance, it is to be installed in the inner core of HANARO. The design process of non-instrumented capsule was accomplished by the decision of the quality of material and the shape, thermal analysis, structural analysis. The temperature of the specimen and the stress in capsule during irradiation test was calculated by the thermal analysis and the structural analysis. GGENGTC code and ABAQUS code were used for the calculation of non-instrumented capsule. In case of installing the capsule in irradiation hole, the coolant flow rate and the pressure drop in the hole is changed, which will affect the coolant flow rate of the fuel region. Eventually the coolant flow rate outside capsule have to be restricted to the allowable range. In order to obtain the required pressure drop, the flow rate control mechanism, end plate and orifice ring were used in this test. The test results are compared with 36-element fuel pressure drop data which AECL performed by the SCTR facility.

  9. Failure of the capsule for coated particles irradiation

    International Nuclear Information System (INIS)

    Yamaki, Jikei; Nomura, Yasushi; Nagamatsuya, Takaaki; Yamahara, Takeshi; Sakai, Haruyuki

    1975-10-01

    During operation cycle No. 27 of the JMTR (Japan Material Testing Reactor) on May 20, 1974, leakage of the fission product gas occurred from the capsule 72F-7A, which contained coated particles for the irradiation; the coated particles are for the development of a multi-purpose high temperature gas cooled reactor. The capsule was designed for heat 1600 0 C. Three nickel plates as the heat reflector were sandwiched in between the plates of titanium and zirconium, which were adsorbents for the impurity gases in the cladding tube (Nb-1%Zr). Temperatures of the plates were about 1000 0 C under the irradiation, so one metal diffused into the other metal through interfaces, resulting in the formation of an alloy. Its melting point was lower than those of metals in the capsule. The cladding material Nb-1%Zr was melted by the alloy and finally a pin hole developed through the cladding. The process of failure, design of the capsule, post-irradiation test of the capsule and the failure-reproducing experiment with a mock-up capsule are described. (auth.)

  10. Design and fabrication of non-instrumented capsule

    International Nuclear Information System (INIS)

    Kim, Yong Sung; Lee, Jeong Young; Kim, Joon Yeon; Lee, Sung Ho; Ji, Dae Young; Kim, Suk Hoon; Ahn, Sung Ho

    1995-04-01

    The use of non-instrumented capsule designed and fabricated in this time is for the evaluation of material irradiation performance, it is to be installed in the inner core of HANARO. The design process of non-instrumented capsule was accomplished by the decision of the quality of material and the shape, thermal analysis, structural analysis. The temperature of the specimen and the stress in capsule during irradiation test was calculated by the thermal analysis and the structural analysis. GGENGTC code and ABAQUS code were used for the calculation of non-instrumented capsule. In case of installing the capsule in irradiation hole, the coolant flow rate and the pressure drop in the hole is changed, which will affect the coolant flow rate of the fuel region. Eventually the coolant flow rate outside capsule have to be restricted to the allowable range. In order to obtain the required pressure drop, the flow rate control mechanism, end plate and orifice ring were used in this test. The test results are compared with 36-element fuel pressure drop data which AECL performed by the SCTR facility

  11. [Exploring the clinical characters of Shugan Jieyu capsule through text mining].

    Science.gov (United States)

    Pu, Zheng-Ping; Xia, Jiang-Ming; Xie, Wei; He, Jin-Cai

    2017-09-01

    The study was main to explore the clinical characters of Shugan Jieyu capsule through text mining. The data sets of Shugan Jieyu capsule were downloaded from CMCC database by the method of literature retrieved from May 2009 to Jan 2016. Rules of Chinese medical patterns, diseases, symptoms and combination treatment were mined out by data slicing algorithm, and they were demonstrated in frequency tables and two dimension based network. Then totally 190 literature were recruited. The outcomess suggested that SC was most frequently correlated with liver Qi stagnation. Primary depression, depression due to brain disease, concomitant depression followed by physical diseases, concomitant depression followed by schizophrenia and functional dyspepsia were main diseases treated by Shugan Jieyu capsule. Symptoms like low mood, psychic anxiety, somatic anxiety and dysfunction of automatic nerve were mainy relieved bv Shugan Jieyu capsule.For combination treatment. Shugan Jieyu capsule was most commonly used with paroxetine, sertraline and fluoxetine. The research suggested that syndrome types and mining results of Shugan Jieyu capsule were almost the same as its instructions. Syndrome of malnutrition of heart spirit was the potential Chinese medical pattern of Shugan Jieyu capsule. Primary comorbid anxiety and depression, concomitant comorbid anxiety and depression followed by physical diseases, and postpartum depression were potential diseases treated by Shugan Jieyu capsule.For combination treatment, Shugan Jieyu capsule was most commonly used with paroxetine, sertraline and fluoxetine. Copyright© by the Chinese Pharmaceutical Association.

  12. A Study of Rank Defect and Network Effect in Processing the CMONOC Network on Bernese

    Directory of Open Access Journals (Sweden)

    Weiwei Wu

    2018-02-01

    Full Text Available High-precision GPS data processing on Bernese has been employed to routinely resolve daily position solutions of GPS stations in the Crustal Movement Observation Network of China (CMONOC. The rank-deficient problems of the normal equation (NEQ system and the network effect on the frame alignment of NEQs in the processing of CMONOC data on Bernese still present difficulties. In this study, we diagnose the rank-deficient problems of the original NEQ, review the efficiency of the controlled datum removal (CDR method in filtering out the three frame-origin-related datum contents, investigate the reliabilities of the inherited frame orientation and scale information from the fixation of the GPS satellite orbits and the Earth rotation parameters in establishing the NEQ of the CMONOC network on Bernese, and analyze the impact of the network effect on the position time series of GPS stations. Our results confirm the nonsingularity of the original NEQ and the efficiency of the CDR filtering in resolving the rank-deficient problems; show that the frame origin parameters are weakly defined and should be stripped off, while the frame orientation and scale parameters should be retained due to their insufficient redefinition from the minimal constraint (MC implementation through inhomogeneous and asymmetrical fiducial networks; and reveal the superiority of a globally distributed fiducial network for frame alignment of the reconstructed NEQs via No-Net-Translation (NNT MC conditions. Finally, we attribute the two apparent discontinuities in the position time series to the terrestrial reference frame (TRF conversions of the GPS satellite orbits, and identify it as the orbit TRF effect.

  13. Cellular Neural Network for Real Time Image Processing

    International Nuclear Information System (INIS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-01-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  14. Neural networks in front-end processing and control

    International Nuclear Information System (INIS)

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M.

    1992-01-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper the authors illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. The authors also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. The authors outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. The authors also present some of the difficulties encountered in applying these networks

  15. Neural networks in front-end processing and control

    International Nuclear Information System (INIS)

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M.

    1991-07-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper we illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. We also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. We outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. We also present some of the difficulties encountered in applying these networks. (author) 13 figs., 9 refs

  16. Equilibrium ignition for ICF capsules

    International Nuclear Information System (INIS)

    Lackner, K.S.; Colgate, S.A.; Johnson, N.L.; Kirkpatrick, R.C.; Menikoff, R.; Petschek, A.G.

    1993-01-01

    There are two fundamentally different approaches to igniting DT fuel in an ICF capsule which can be described as equilibrium and hot spot ignition. In both cases, a capsule which can be thought of as a pusher containing the DT fuel is imploded until the fuel reaches ignition conditions. In comparing high-gain ICF targets using cryogenic DT for a pusher with equilibrium ignition targets using high-Z pushers which contain the radiation. The authors point to the intrinsic advantages of the latter. Equilibrium or volume ignition sacrifices high gain for lower losses, lower ignition temperature, lower implosion velocity and lower sensitivity of the more robust capsule to small fluctuations and asymmetries in the drive system. The reduction in gain is about a factor of 2.5, which is small enough to make the more robust equilibrium ignition an attractive alternative

  17. Endurance test for DUPIC capsule

    International Nuclear Information System (INIS)

    Chung, Heung June; Bae, K. K.; Lee, C. Y.; Park, J. M.; Ryu, J. S.

    1999-07-01

    This report presents the pressure drop, vibration and endurance test results for mini-plate fuel rig which were designed fabricately by KAERI. From the pressure drop test results, it is noted that the flow rate across the capsule corresponding to the pressure drop of 200 kPa is measured to be about 9.632 kg/sec. Vibration frequency for the capsule ranges from 14 to 18.5 Hz. RMS (Root Mean Square) displacement for the fuel rig is less than 14 μm, and the maximum displacement is less than 54 μm. Based on the endurance test results, the appreciable fretting wear for the DUPIC capsule was not detected. Oxidation on the support tube is observed, also tiny trace of wear between contact points observed. (author). 4 refs., 10 tabs., 45 figs

  18. Competing contact processes in the Watts-Strogatz network

    Science.gov (United States)

    Rybak, Marcin; Malarz, Krzysztof; Kułakowski, Krzysztof

    2016-06-01

    We investigate two competing contact processes on a set of Watts-Strogatz networks with the clustering coefficient tuned by rewiring. The base for network construction is one-dimensional chain of N sites, where each site i is directly linked to nodes labelled as i ± 1 and i ± 2. So initially, each node has the same degree k i = 4. The periodic boundary conditions are assumed as well. For each node i the links to sites i + 1 and i + 2 are rewired to two randomly selected nodes so far not-connected to node i. An increase of the rewiring probability q influences the nodes degree distribution and the network clusterization coefficient 𝓒. For given values of rewiring probability q the set 𝓝(q)={𝓝1,𝓝2,...,𝓝 M } of M networks is generated. The network's nodes are decorated with spin-like variables s i ∈ { S,D }. During simulation each S node having a D-site in its neighbourhood converts this neighbour from D to S state. Conversely, a node in D state having at least one neighbour also in state D-state converts all nearest-neighbours of this pair into D-state. The latter is realized with probability p. We plot the dependence of the nodes S final density n S T on initial nodes S fraction n S 0. Then, we construct the surface of the unstable fixed points in (𝓒, p, n S 0) space. The system evolves more often toward n S T for (𝓒, p, n S 0) points situated above this surface while starting simulation with (𝓒, p, n S 0) parameters situated below this surface leads system to n S T =0. The points on this surface correspond to such value of initial fraction n S * of S nodes (for fixed values 𝓒 and p) for which their final density is n S T=1/2.

  19. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    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.

  20. Distributed Sensing and Processing for Multi-Camera Networks

    Science.gov (United States)

    Sankaranarayanan, Aswin C.; Chellappa, Rama; Baraniuk, Richard G.

    Sensor networks with large numbers of cameras are becoming increasingly prevalent in a wide range of applications, including video conferencing, motion capture, surveillance, and clinical diagnostics. In this chapter, we identify some of the fundamental challenges in designing such systems: robust statistical inference, computationally efficiency, and opportunistic and parsimonious sensing. We show that the geometric constraints induced by the imaging process are extremely useful for identifying and designing optimal estimators for object detection and tracking tasks. We also derive pipelined and parallelized implementations of popular tools used for statistical inference in non-linear systems, of which multi-camera systems are examples. Finally, we highlight the use of the emerging theory of compressive sensing in reducing the amount of data sensed and communicated by a camera network.

  1. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P J; Gu, F; Ball, A D [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1998-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  2. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P.J.; Gu, F.; Ball, A.D. [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1997-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  3. Forecasting financial asset processes: stochastic dynamics via learning neural networks.

    Science.gov (United States)

    Giebel, S; Rainer, M

    2010-01-01

    Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

  4. Competing spreading processes on multiplex networks: awareness and epidemics.

    Science.gov (United States)

    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).] 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.

  5. Altered organization of face processing networks in temporal lobe epilepsy

    Science.gov (United States)

    Riley, Jeffrey D.; Fling, Brett W.; Cramer, Steven C.; Lin, Jack J.

    2015-01-01

    SUMMARY Objective Deficits in social cognition are common and significant in people with temporal lobe epilepsy (TLE), but the functional and structural underpinnings remain unclear. The present study investigated how the side of seizure focus impacts face processing networks in temporal lobe epilepsy. Methods We used functional magnetic resonance imaging (fMRI) of a face processing paradigm to identify face responsive regions in 24 individuals with unilateral temporal lobe epilepsy (Left = 15; Right = 9) and 19 healthy controls. fMRI signals of face responsive regions ispilateral and contralateral to the side of seizure onset were delineated in TLE and compared to the healthy controls with right and left side combined. Diffusion tensor images were acquired to investigate structural connectivity between face regions that differed in fMRI signals between the two groups. Results In temporal lobe epilepsy, activation of the cortical face processing networks varied according to side of seizure onset. In temporal lobe epilepsy, the laterality of amygdala activation was shifted to the side contralateral to the seizure focus while controls showed no significant asymmetry. Furthermore, compared to controls, patients with TLE showed decreased activation of the occipital face responsive region in the ipsilateral side and an increased activity of the anterior temporal lobe in the contralateral side to the seizure focus. Probabilistic tractography revealed that the occipital face area and anterior temporal lobe are connected via the inferior longitudinal fasciculus, which in individuals with temporal lobe epilepsy showed reduced integrity. Significance Taken together, these findings suggest that brain function and white matter integrity of networks subserving face processing are impaired on the side of seizure onset, accompanied by altered responses on the side contralateral to the seizure. PMID:25823855

  6. Bayesian networks applied to process diagnostics. Applications in energy industry

    Energy Technology Data Exchange (ETDEWEB)

    Widarsson, Bjoern (ed.); Karlsson, Christer; Dahlquist, Erik [Maelardalen Univ., Vaesteraas (Sweden); Nielsen, Thomas D.; Jensen, Finn V. [Aalborg Univ. (Denmark)

    2004-10-01

    Uncertainty in process operation occurs frequently in heat and power industry. This makes it hard to find the occurrence of an abnormal process state from a number of process signals (measurements) or find the correct cause to an abnormality. Among several other methods, Bayesian Networks (BN) is a method to build a model which can handle uncertainty in both process signals and the process itself. The purpose of this project is to investigate the possibilities to use BN for fault detection and diagnostics in combined heat and power industries through execution of two different applications. Participants from Aalborg University represent the knowledge of BN and participants from Maelardalen University have the experience from modelling heat and power applications. The co-operation also includes two energy companies; Elsam A/S (Nordjyllandsverket) and Maelarenergi AB (Vaesteraas CHP-plant), where the two applications are made with support from the plant personnel. The project ended out in two quite different applications. At Nordjyllandsverket, an application based (due to the lack of process knowledge) on pure operation data is build with capability to detect an abnormal process state in a coal mill. Detection is made through a conflict analysis when entering process signals into a model built by analysing the operation database. The application at Maelarenergi is built with a combination of process knowledge and operation data and can detect various faults caused by the fuel. The process knowledge is used to build a causal network structure and the structure is then trained by data from the operation database. Both applications are made as off-online applications, but they are ready for being run on-line. The performance of fault detection and diagnostics are good, but a lack of abnormal process states with known cause reduces the evaluation possibilities. Advantages with combining expert knowledge of the process with operation data are the possibility to represent

  7. Triggered Release from Polymer Capsules

    Energy Technology Data Exchange (ETDEWEB)

    Esser-Kahn, Aaron P. [Univ. of Illinois, Urbana, IL (United States). Beckman Inst. for Advanced Science and Technology and Dept. of Chemistry; Odom, Susan A. [Univ. of Illinois, Urbana, IL (United States). Beckman Inst. for Advanced Science and Technology and Dept. of Chemistry; Sottos, Nancy R. [Univ. of Illinois, Urbana, IL (United States). Beckman Inst. for Advanced Science and Technology and Dept. of Materials Science and Engineering; White, Scott R. [Univ. of Illinois, Urbana, IL (United States). Beckman Inst. for Advanced Science and Technology and Dept. of Aerospace Engineering; Moore, Jeffrey S. [Univ. of Illinois, Urbana, IL (United States). Beckman Inst. for Advanced Science and Technology and Dept. of Chemistry

    2011-07-06

    Stimuli-responsive capsules are of interest in drug delivery, fragrance release, food preservation, and self-healing materials. Many methods are used to trigger the release of encapsulated contents. Here we highlight mechanisms for the controlled release of encapsulated cargo that utilize chemical reactions occurring in solid polymeric shell walls. Triggering mechanisms responsible for covalent bond cleavage that result in the release of capsule contents include chemical, biological, light, thermal, magnetic, and electrical stimuli. We present methods for encapsulation and release, triggering methods, and mechanisms and conclude with our opinions on interesting obstacles for chemically induced activation with relevance for controlled release.

  8. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol

    2011-01-01

    of a computer aided multilevel modeling network consisting a collection of new and adopted models, methods and tools for the systematic design and analysis of processes employing lipid technology. This is achieved by decomposing the problem into four levels of modeling: 1. pure component properties; 2. mixtures...... and phase behavior; 3. unit operations; and 4. process synthesis and design. The methods and tools in each level include: For the first level, a lipid‐database of collected experimental data from the open literature, confidential data from industry and generated data from validated predictive property...... of these unit operations with respect to performance parameters such as minimum total cost, product yield improvement, operability etc., and process intensification for the retrofit of existing biofuel plants. In the fourth level the information and models developed are used as building blocks...

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

    Science.gov (United States)

    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. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  10. A brain network processing the age of faces.

    Directory of Open Access Journals (Sweden)

    György A Homola

    Full Text Available Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships.

  11. Welding of iridium heat source capsule components

    International Nuclear Information System (INIS)

    Mustaleski, T.M.; Yearwood, J.C.; Burgan, C.E.; Green, L.A.

    1991-01-01

    Interplanetary spacecraft have long used radioisotope thermoelectric generators (RTG) to produce power for instrumentation. These RTG produce electrical energy from the heat generated through the radioactive decay of plutonium-238. The plutonium is present as a ceramic pellet of plutonium oxide. The pellet is encapsulated in a containment shell of iridium. Iridium is the material of choice for these capsules because of its compatibility with the plutonium dioxide. The high-energy beam welding (electron beam and laser) processes used in the fabrication of the capsules has not been published. These welding procedures were originally developed at the Mound Laboratories and have been adapted for use at the Oak Ridge Y-12 Plant. The work involves joining of thin material in small sizes to exacting tolerances. There are four different electron beam welds on each capsule, with one procedure being used in three locations. There is also a laser weld used to seal the edges of a sintered frit assembly. An additional electron beam weld is also performed to seal each of the iridium blanks in a stainless steel waster sheet prior to forming. In the transfer of these welding procedures from one facility to another, a number of modifications were necessary. These modifications are discussed in detail, as well as the inherent problems in making welds in material which is only 0.005 in. thick. In summary, the paper discusses the welding of thin components of iridium using the high energy beam processes. While the peculiarities of iridium are pertinent to the discussion, much of the information is of general interest to the users of these processes. This is especially true of applications involving thin materials and high-precision assemblies

  12. Integration of social networks in the teaching and learning process

    Directory of Open Access Journals (Sweden)

    Cynthia Dedós Reyes

    2015-09-01

    Full Text Available In this research we explored the integration of social media in the process of learning and teaching, in a private higher education institution, in Puerto Rico. Attention was given to the perspectives of teachers and students. The participants —9 part-time teachers and 118 students— were selected based on availability. The results showed that teachers and students alike use social the network You Tube for academic purposes; and use Facebook, Twitter, and blogs for social purposes and entertainment. Results also revealed that there is no significant contrast between the perspectives of teachers and students digital immigrants.

  13. Use of neural networks in process engineering. Thermodynamics, diffusion, and process control and simulation applications

    International Nuclear Information System (INIS)

    Otero, F

    1998-01-01

    This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant operating data. Three examples of the use of ANNs in typical process engineering applications such as prediction of activity in solvent-polymer binary systems, prediction of a surfactant self-diffusion coefficient of micellar systems, and process control and simulation are shown. These examples are important for polymerization applications, enhanced-oil recovery, and automatic process control

  14. A method of network topology optimization design considering application process characteristic

    Science.gov (United States)

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

    2018-03-01

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

  15. Information processing by networks of quantum decision makers

    Science.gov (United States)

    Yukalov, V. I.; Yukalova, E. P.; Sornette, D.

    2018-02-01

    We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the generalization of quantum decision theory, developed earlier for single decision makers realizing one-step decisions, in two principal aspects. First, several decision makers are considered simultaneously, who interact with each other through information exchange. Second, a multistep procedure is treated, when the agents exchange information many times. Several decision makers exchanging information and forming their judgment, using quantum rules, form a kind of a quantum information network, where collective decisions develop in time as a result of information exchange. In addition to characterizing collective decisions that arise in human societies, such networks can describe dynamical processes occurring in artificial quantum intelligence composed of several parts or in a cluster of quantum computers. The practical usage of the theory is illustrated on the dynamic disjunction effect for which three quantitative predictions are made: (i) the probabilistic behavior of decision makers at the initial stage of the process is described; (ii) the decrease of the difference between the initial prospect probabilities and the related utility factors is proved; (iii) the existence of a common consensus after multiple exchange of information is predicted. The predicted numerical values are in very good agreement with empirical data.

  16. USC orthogonal multiprocessor for image processing with neural networks

    Science.gov (United States)

    Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

    1990-07-01

    This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

  17. Genetic Algorithms vs. Artificial Neural Networks in Economic Forecasting Process

    Directory of Open Access Journals (Sweden)

    Nicolae Morariu

    2008-01-01

    Full Text Available This paper aims to describe the implementa-tion of a neural network and a genetic algorithm system in order to forecast certain economic indicators of a free market economy. In a free market economy forecasting process precedes the economic planning (a management function, providing important information for the result of the last process. Forecasting represents a starting point in setting of target for a firm, an organization or even a branch of the economy. Thus, the forecasting method used can influence in a significant mode the evolution of an entity. In the following we will describe the forecasting of an economic indicator using two intelligent systems. The difference between the results obtained by this two systems are described in chapter IV.

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

    Science.gov (United States)

    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.

  19. Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks

    Directory of Open Access Journals (Sweden)

    Cosimo Lacava

    2017-01-01

    Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.

  20. Deformation of ovalbumin-alginate capsules in a T-Junction

    Science.gov (United States)

    Häner, Edgar; Juel, Anne

    2015-11-01

    We study experimentally the flow-induced deformation of liquid-filled ovalbumin-alginate capsules in a T-junction. In applications, capsules/cells often negotiate branched networks with junctions thus experiencing large deformations. We investigate the constant volume-flux viscous flow of buoyancy-neutral thin-walled capsules close to the centreline of rectangular channels, by comparison to near-rigid gelled beads. The motion of the capsules in straight channels scales with the capillary number - the ration of viscous to elastic forces. However, the effect of elastic deformation on the motion is sufficiently weak that a rigid sphere model predicts the velocity of capsules with diameters of up to 70% of that of the channel to within 5%. In the T-junction, systematic selection of daughter channel (right-left) occurs outside a finite region around the channel centreline, by contrast with near-rigid gelled beads, where the actual centreline is the separator. We quantify the behaviour of capsules in terms of their longitudinal stretching (up to a factor of three without rupture). We show the large range of deformations encountered can be applied to the measurement of the elastic properties of capsules as well as to the geometric-induced sorting and manipulation of capsules.

  1. Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches

    Directory of Open Access Journals (Sweden)

    Manjunath Patel Gowdru Chandrashekarappa

    2014-01-01

    Full Text Available The present research work is focussed to develop an intelligent system to establish the input-output relationship utilizing forward and reverse mappings of artificial neural networks. Forward mapping aims at predicting the density and secondary dendrite arm spacing (SDAS from the known set of squeeze cast process parameters such as time delay, pressure duration, squeezes pressure, pouring temperature, and die temperature. An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN and genetic algorithm neural network (GA-NN. The batch mode of training is employed for both supervised learning networks and requires huge training data. The requirement of huge training data is generated artificially at random using regression equation derived through real experiments carried out earlier by the same authors. The performances of BPNN and GA-NN models are compared among themselves with those of regression for ten test cases. The results show that both models are capable of making better predictions and the models can be effectively used in shop floor in selection of most influential parameters for the desired outputs.

  2. Network and Database Security: Regulatory Compliance, Network, and Database Security - A Unified Process and Goal

    Directory of Open Access Journals (Sweden)

    Errol A. Blake

    2007-12-01

    Full Text Available Database security has evolved; data security professionals have developed numerous techniques and approaches to assure data confidentiality, integrity, and availability. This paper will show that the Traditional Database Security, which has focused primarily on creating user accounts and managing user privileges to database objects are not enough to protect data confidentiality, integrity, and availability. This paper is a compilation of different journals, articles and classroom discussions will focus on unifying the process of securing data or information whether it is in use, in storage or being transmitted. Promoting a change in Database Curriculum Development trends may also play a role in helping secure databases. This paper will take the approach that if one make a conscientious effort to unifying the Database Security process, which includes Database Management System (DBMS selection process, following regulatory compliances, analyzing and learning from the mistakes of others, Implementing Networking Security Technologies, and Securing the Database, may prevent database breach.

  3. Capsule safety analysis of PRTF irradiation facility

    International Nuclear Information System (INIS)

    Suwarto

    2013-01-01

    Power Ramp Test Facility (PRTF) is an irradiation facility used for fuel testing of power reactor. PRTF has a capsule which is a test fuel rod container. During operation, pressurized water of 160 bars flows through in the capsule. Due to the high pressure it should be analyzed the impact of the capsule on reactor core safety. This analysis has purpose to calculate the ability of capsule pressure capacity. The analysis was carried out by calculating pressure capacity. From the calculating results it can be concluded that the capsule with pressure capacity of 438 bars will be safe to prevent the operation pressure of PRTF. (author)

  4. Probing cell internalisation mechanics with polymer capsules.

    Science.gov (United States)

    Chen, Xi; Cui, Jiwei; Ping, Yuan; Suma, Tomoya; Cavalieri, Francesca; Besford, Quinn A; Chen, George; Braunger, Julia A; Caruso, Frank

    2016-10-06

    We report polymer capsule-based probes for quantifying the pressure exerted by cells during capsule internalisation (P in ). Poly(methacrylic acid) (PMA) capsules with tuneable mechanical properties were fabricated through layer-by-layer assembly. The P in was quantified by correlating the cell-induced deformation with the ex situ osmotically induced deformation of the polymer capsules. Ultimately, we found that human monocyte-derived macrophage THP-1 cells exerted up to approximately 360 kPa on the capsules during internalisation.

  5. Eigenanalysis of a neural network for optic flow processing

    International Nuclear Information System (INIS)

    Weber, F; Eichner, H; Borst, A; Cuntz, H

    2008-01-01

    Flies gain information about self-motion during free flight by processing images of the environment moving across their retina. The visual course control center in the brain of the blowfly contains, among others, a population of ten neurons, the so-called vertical system (VS) cells that are mainly sensitive to downward motion. VS cells are assumed to encode information about rotational optic flow induced by self-motion (Krapp and Hengstenberg 1996 Nature 384 463-6). Recent evidence supports a connectivity scheme between the VS cells where neurons with neighboring receptive fields are connected to each other by electrical synapses at the axonal terminals, whereas the boundary neurons in the network are reciprocally coupled via inhibitory synapses (Haag and Borst 2004 Nat. Neurosci. 7 628-34; Farrow et al 2005 J. Neurosci. 25 3985-93; Cuntz et al 2007 Proc. Natl Acad. Sci. USA). Here, we investigate the functional properties of the VS network and its connectivity scheme by reducing a biophysically realistic network to a simplified model, where each cell is represented by a dendritic and axonal compartment only. Eigenanalysis of this model reveals that the whole population of VS cells projects the synaptic input provided from local motion detectors on to its behaviorally relevant components. The two major eigenvectors consist of a horizontal and a slanted line representing the distribution of vertical motion components across the fly's azimuth. They are, thus, ideally suited for reliably encoding translational and rotational whole-field optic flow induced by respective flight maneuvers. The dimensionality reduction compensates for the contrast and texture dependence of the local motion detectors of the correlation-type, which becomes particularly pronounced when confronted with natural images and their highly inhomogeneous contrast distribution

  6. Introduction to the physics of ICF capsules

    International Nuclear Information System (INIS)

    Lindl, J.D.

    1989-01-01

    Inertial Confinement Fusion is an approach to fusion which relies on the inertia of the fuel mass to provide confinement. To achieve conditions under which this confinement is sufficient for efficient thermonuclear burn, high gain ICF targets designed to be imploded directly by laser light. These capsules are generally a spherical shell which is filled with low density DT gas. The shell is composed of an outer region which forms the ablator and an inner region of frozen or liquid DT which forms the main fuel. Energy from the driver is delivered to the ablator which heats up and expands. As the ablator expands and blows outward, the rest of the shell is forced inward to conserve momentum. In this implosion process, several features are important. We define the in-flight-aspect-ratio (IFAR) as the ratio of the shell radius R as it implodes to its thickness ΔR. Hydrodynamic instabilities during the implosion impose limits on this ratio which results in a minimum pressure requirement of about 100 Mbar. The convergence ratio is defined as the ratio of the initial outer radius of the ablator to the final compressed radius of the hot spot. This hot spot is the central region of the compressed fuel which is required to ignite the main fuel in high gain designs. Typical convergence ratios are 30--40. To maintain a nearly spherical shape during the implosion, when convergence ratios are this large, the flux delivered to the capsule must be uniform to a few percent. The remainder of this paper discusses the conditions necessary to achieve thermonuclear ignition in these ICF capsules

  7. A modular and programmable development platform for capsule endoscopy system.

    Science.gov (United States)

    Khan, Tareq Hasan; Shrestha, Ravi; Wahid, Khan A

    2014-06-01

    The state-of-the-art capsule endoscopy (CE) technology offers painless examination for the patients and the ability to examine the interior of the gastrointestinal tract by a noninvasive procedure for the gastroenterologists. In this work, a modular and flexible CE development system platform consisting of a miniature field programmable gate array (FPGA) based electronic capsule, a microcontroller based portable data recorder unit and computer software is designed and developed. Due to the flexible and reprogrammable nature of the system, various image processing and compression algorithms can be tested in the design without requiring any hardware change. The designed capsule prototype supports various imaging modes including white light imaging (WLI) and narrow band imaging (NBI), and communicates with the data recorder in full duplex fashion, which enables configuring the image size and imaging mode in real time during examination. A low complexity image compressor based on a novel color-space is implemented inside the capsule to reduce the amount of RF transmission data. The data recorder contains graphical LCD for real time image viewing and SD cards for storing image data. Data can be uploaded to a computer or Smartphone by SD card, USB interface or by wireless Bluetooth link. Computer software is developed that decompresses and reconstructs images. The fabricated capsule PCBs have a diameter of 16 mm. An ex-vivo animal testing has also been conducted to validate the results.

  8. PHANTOMS: Nanotechnology network for information processing and storage*

    Science.gov (United States)

    Correia, Antonio

    2001-06-01

    It is now accepted that nanotechnology is one of the key enabling technologies for sustainable and competitive growth in Europe. Nanoelectronics is certainly the branch with the most significant commercial impact and covers a huge range of interdisciplinary areas of research and development such as molecular electronics, bioelectronics, spintronics, nanoimprint, nanoscale optics, lithography, architecture and nanoprobes. It is also accepted that a significant investment will be required to ensure Europe's competitiveness in nanotechnology. At this stage it is impossible to predict the exact course that the nanoelectronics revolution will take and, therefore, its effect on our daily lives. We can, however, be resonably sure that nanotechnology will have a profound impact on the future development of many commercial sectors. The greatest impact is likely to be in the electronics sector, where the demand for technologies permitting faster processing of data at lower costs will remain undiminished. In order to avoid European industry and R & D being left behind the United States and Japan in this fast emerging nanoelectronics field, the PHANTOMS Network Scheme will promote European science and research through a pluri-national networking action, put together research capacities present in the various European regions and stimulate commercial nanoelectronic applications.

  9. Applying fuzzy analytic network process in quality function deployment model

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Afsharkazemi

    2012-08-01

    Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.

  10. Developmental process emerges from extended brain-body-behavior networks

    Science.gov (United States)

    Byrge, Lisa; Sporns, Olaf; Smith, Linda B.

    2014-01-01

    Studies of brain connectivity have focused on two modes of networks: structural networks describing neuroanatomy and the intrinsic and evoked dependencies of functional networks at rest and during tasks. Each mode constrains and shapes the other across multiple time scales, and each also shows age-related changes. Here we argue that understanding how brains change across development requires understanding the interplay between behavior and brain networks: changing bodies and activities modify the statistics of inputs to the brain; these changing inputs mold brain networks; these networks, in turn, promote further change in behavior and input. PMID:24862251

  11. Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

    Science.gov (United States)

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

    2018-04-01

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

  12. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    Science.gov (United States)

    Orbán, Levente L; Chartier, Sylvain

    2015-01-01

    Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

  13. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    Science.gov (United States)

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high. Copyright © 2015 Elsevier

  14. Contraindications for video capsule endoscopy

    OpenAIRE

    Bandorski, Dirk; Kurniawan, Niehls; Baltes, Peter; Hoeltgen, Reinhard; Hecker, Matthias; Stunder, Dominik; Keuchel, Martin

    2016-01-01

    Video capsule endoscopy (VCE) has been applied in the last 15 years in an increasing field of applications. Although many contraindications have been put into perspective, some precautions still have to be considered. Known stenosis of the gastrointestinal tract is a clear contraindication for VCE unless surgery is already scheduled or at least has been considered as an optional treatment modality. In patients with a higher incidence of stenosis, as in an established diagnosis of Crohn?s dise...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Mauricio Herrera

    Full Text Available 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.

  17. Measurement of company effectiveness using analytic network process method

    Directory of Open Access Journals (Sweden)

    Goran Janjić

    2017-07-01

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

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

    Science.gov (United States)

    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. Measurement of company effectiveness using analytic network process method

    Science.gov (United States)

    Goran, Janjić; Zorana, Tanasić; Borut, Kosec

    2017-07-01

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

  20. Managing logistical processes in franchise retail trade networks

    OpenAIRE

    Grigorenko Tatyana N.; Kochubey Dmitriy V.

    2013-01-01

    The article analyses approaches to organisation of internal logistics of franchise trade networks and methodical provision of assessment of results of logistical activity at companies of franchise networks. The article justifies urgency of application of referent models of management of supply chains in construction of a system of management of logistical activity of franchise networks. It offers classification of models of management of internal logistics of franchise retail trade networks. ...

  1. Coarse-grained simulation of a real-time process control network under peak load

    International Nuclear Information System (INIS)

    George, A.D.; Clapp, N.E. Jr.

    1992-01-01

    This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks

  2. High level cognitive information processing in neural networks

    Science.gov (United States)

    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.

  3. Photophysics Applied to Cavitands and Capsules.

    Science.gov (United States)

    Berryman, Orion B; Dube, Henry; Rebek, Julius

    2011-07-01

    The use of light as a stimulus to control functional materials or nano-devices is appealing as it provides convenient control of triggering events where and when they are desired without introducing extra components to the system. Many photophysical and photochemical processes are extremely fast, giving rise to nearly instantaneous onset of events. However, these fast processes can be challenging to engineer into chemical systems. Supramolecular chemistry offers a convenient way to study and control photoprocesses. Given the reversible and self-programmed nature of modern host-guest systems, a modular approach can be considered in which different photoprocesses are coupled to obtain complex functions that emerge and are controlled solely by light inputs. In this review, we highlight recent examples of photoswitching and photophysics applied in the context of supramolecular host-guest systems, with a particular emphasis on resorcinarene based cavitands and hydrogen bonded capsules.

  4. Exploiting global information in complex network repair processes

    Institute of Scientific and Technical Information of China (English)

    Tianyu WANG; Jun ZHANG; Sebastian WANDELT

    2017-01-01

    Robustness of complex networks has been studied for decades,with a particular focus on network attack.Research on network repair,on the other hand,has been conducted only very lately,given the even higher complexity and absence of an effective evaluation metric.A recently proposed network repair strategy is self-healing,which aims to repair networks for larger compo nents at a low cost only with local information.In this paper,we discuss the effectiveness and effi ciency of self-healing,which limits network repair to be a multi-objective optimization problem and makes it difficult to measure its optimality.This leads us to a new network repair evaluation metric.Since the time complexity of the computation is very high,we devise a greedy ranking strategy.Evaluations on both real-world and random networks show the effectiveness of our new metric and repair strategy.Our study contributes to optimal network repair algorithms and provides a gold standard for future studies on network repair.

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

    Science.gov (United States)

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

    2009-02-21

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

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

    Directory of Open Access Journals (Sweden)

    Hamidreza Kermajani

    2014-07-01

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

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

    Science.gov (United States)

    Kermajani, Hamidreza; Gomez, Carles

    2014-07-07

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

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

    Directory of Open Access Journals (Sweden)

    Francisco eAboitiz

    2014-03-01

    Full Text Available A cardinal symptom of Attenion 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 produce 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.

  9. Financial risk analysis in the synthesis and design of processing networks: Balancing risk and return

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sin, Gürkan; Gani, Rafiqul

    2014-01-01

    The construction of a processing network is a corporate investment, that processing companies make with the goal of creating the conditions to increase their value. In a previous work, a computer-aided framework supporting the design of processing network under uncertainty has been presented (Qua...... and financial risk models. Through the solution of a small benchmark problem, the impact of financial factors on the optimal network configuration is presented and discussed....

  10. Status of the material capsule irradiation and the development of the new capsule technology in HANARO

    International Nuclear Information System (INIS)

    Choo, Kee-Nam; Kang, Young-Hwan; Choi, Myoung-Hwan; Cho, Man-Soon; Kim, Bong-Goo

    2006-01-01

    A material capsule system including a main capsule, fixing, control, cutting, and transport systems was developed for an irradiation test of non-fissile materials in HANARO. 14 irradiation capsules (12 instrumented and 2 non-instrumented capsules) have been designed, fabricated and successfully irradiated in the HANARO CT and IR test holes since 1995. The capsules were mainly designed for an irradiation of the RPV (Reactor Pressure Vessel), reactor core materials, and Zr-based alloys. Most capsules were made for KAERI material research projects, but 5 capsules were made as a part of national projects for the promotion of the HANARO utilization for universities. Based on the accumulated irradiation experience and the user's sophisticated requirements, development of new instrumented capsule technologies for a more precise control of the irradiation temperature and fluence of a specimen irrespective of the reactor operation has been performed in HANARO. (author)

  11. NASPGHAN Capsule Endoscopy Clinical Report.

    Science.gov (United States)

    Friedlander, Joel A; Liu, Quin Y; Sahn, Benjamin; Kooros, Koorosh; Walsh, Catharine M; Kramer, Robert E; Lightdale, Jenifer R; Khlevner, Julie; McOmber, Mark; Kurowski, Jacob; Giefer, Matthew J; Pall, Harpreet; Troendle, David M; Utterson, Elizabeth C; Brill, Herbert; Zacur, George M; Lirio, Richard A; Lerner, Diana G; Reynolds, Carrie; Gibbons, Troy E; Wilsey, Michael; Liacouras, Chris A; Fishman, Douglas S

    2017-03-01

    Wireless capsule endoscopy (CE) was introduced in 2000 as a less invasive method to visualize the distal small bowel in adults. Because this technology has advanced it has been adapted for use in pediatric gastroenterology. Several studies have described its clinical use, utility, and various training methods but pediatric literature regarding CE is limited. This clinical report developed by the Endoscopic and Procedures Committee of the North American Society of Pediatric Gastroenterology, Hepatology and Nutrition outlines the current literature, and describes the recommended current role, use, training, and future areas of research for CE in pediatrics.

  12. State diagram for adhesion dynamics of deformable capsules under shear flow.

    Science.gov (United States)

    Luo, Zheng Yuan; Bai, Bo Feng

    2016-08-17

    Due to the significance of understanding the underlying mechanisms of cell adhesion in biological processes and cell capture in biomedical applications, we numerically investigate the adhesion dynamics of deformable capsules under shear flow by using a three-dimensional computational fluid dynamic model. This model is based on the coupling of the front tracking-finite element method for elastic mechanics of the capsule membrane and the adhesion kinetics simulation for adhesive interactions between capsules and functionalized surfaces. Using this model, three distinct adhesion dynamic states are predicted, such as detachment, rolling and firm-adhesion. Specifically, the effects of capsule deformability quantified by the capillary number on the transitions of these three dynamic states are investigated by developing an adhesion dynamic state diagram for the first time. At low capillary numbers (e.g. Ca state no longer appears, since capsules exhibit large deviation from the spherical shape.

  13. Herniation of the anterior lens capsule

    Directory of Open Access Journals (Sweden)

    Pereira Nolette

    2007-01-01

    Full Text Available Herniation of the anterior lens capsule is a rare abnormality in which the capsule bulges forward in the pupillary area. This herniation can be mistaken for an anterior lenticonus where both the capsule and the cortex bulge forward. The exact pathology behind this finding is still unclear. We report the clinical, ultrasound biomicroscopy (UBM and histopathological findings of a case of herniation of the anterior lens capsule. UBM helped to differentiate this entity from anterior lenticonus. Light microscopy revealed capsular splitting suggestive of capsular delamination and collection of fluid (aqueous in the area of herniation giving it a characteristic appearance.

  14. Diagnostic and therapeutic radio pharmaceutical capsules

    International Nuclear Information System (INIS)

    Haney, T.A.; Wedeking, P.W.; Morcos, N.A.

    1981-01-01

    An improved pharmaceutical radioactive capsule consisting of a non-toxic, water soluble material adapted to being ingested and rapidly disintegrating on contact with fluids of the gastro-intestinal tract is described. Each capsule is provided with filler material supporting a pharmaceutically useful radioactive compound absorbable from the gastro-intestinal tract. The capsule is preferably of gelatin, methyl cellulose or polyvinyl alcohol and the filler is a polyethylene glycol. The radioactive compound may be iodine e.g. sodium radioiodide I-131 or 123. The capsule may also contain a reducing agent e.g. sodium thiosulphate, sulphite, or bisulphite. (author)

  15. Gaussian process regression for sensor networks under localization uncertainty

    Science.gov (United States)

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

    2013-01-01

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

  16. Supercritical boiler material selection using fuzzy analytic network process

    Directory of Open Access Journals (Sweden)

    Saikat Ranjan Maity

    2012-08-01

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

  17. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    Directory of Open Access Journals (Sweden)

    Levente L Orbán

    Full Text Available Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

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

    Science.gov (United States)

    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…

  19. Alginate/sodium caseinate aqueous-core capsules: a pH-responsive matrix.

    Science.gov (United States)

    Ben Messaoud, Ghazi; Sánchez-González, Laura; Jacquot, Adrien; Probst, Laurent; Desobry, Stéphane

    2015-02-15

    Alginate capsules have several applications. Their functionality depends considerably on their permeability, chemical and mechanical stability. Consequently, the creation of composite system by addition of further components is expected to control mechanical and release properties of alginate capsules. Alginate and alginate-sodium caseinate composite liquid-core capsules were prepared by a simple extrusion. The influence of the preparation pH and sodium caseinate concentration on capsules physico-chemical properties was investigated. Results showed that sodium caseinate influenced significantly capsules properties. As regards to the membrane mechanical stability, composite capsules prepared at pH below the isoelectric point of sodium caseinate exhibited the highest surface Young's modulus, increasing with protein content, explained by potential electrostatic interactions between sodium caseinate amino-groups and alginate carboxylic group. The kinetic of cochineal red A release changed significantly for composite capsules and showed a pH-responsive release. Sodium caseinate-dye mixture studied by absorbance and fluorescence spectroscopy confirmed complex formation at pH 2 by electrostatic interactions between sodium caseinate tryptophan residues and cochineal red sulfonate-groups. Consequently, the release mechanism was explained by membrane adsorption process. This global approach is useful to control release mechanism from macro and micro-capsules by incorporating guest molecules which can interact with the entrapped molecule under specific conditions. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. The redesign of a warranty distribution network with recovery processes

    NARCIS (Netherlands)

    Ashayeri, J.; Ma, N.; Sotirov, R.

    A warranty distribution network provides aftersales warranty services to customers and resembles a closed-loop supply chain network with specific challenges for reverse flows management like recovery, repair, and reflow of refurbished products. We present here a nonlinear and nonconvex mixed integer

  1. Collaborative Wireless Sensor Networks in Industrial and Business Processes

    NARCIS (Netherlands)

    Marin Perianu, Mihai

    2008-01-01

    Personal computers, mobile telephony and the Internet made the vision of everyone being networked real, at such a level of quality and speed that people could only dream of, one hundred years ago. Nowadays, another dream starts to become reality: the dream of networking everything. The limits of

  2. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as perception, back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally the application of artificial neural network for Chinese character recognition is also given. (author)

  3. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as Perceptron, Back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally, the application of artificial neural network for Chinese Character Recognition is also given. (author)

  4. Dense distributed processing in a hindlimb scratch motor network

    DEFF Research Database (Denmark)

    Guzulaitis, Robertas; Hounsgaard, Jørn Dybkjær

    2014-01-01

    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...

  5. Performance in wireless networks and industrial wireless networks on control processes in real time under industrial environments

    Directory of Open Access Journals (Sweden)

    Juan F. Monsalve-Posada

    2015-01-01

    Full Text Available The growing use of Ethernet networks on the industrial automation pyramid has led many companies to develop new devices to operate in requirements of this level, nowadays it is called Industrial Ethernet network, on the market there are various sensors and actuators to industrial scale equipped with this technology, many of these devices are very expensive. In this paper, the performance of two wireless networks is evaluated, the first network has conventional Ethernet devices, and the second network has Industrial Ethernet devices. For the process we vary four parameters such as distance, number of bytes, the signal to noise ratio, and the packet error rate, and then we measure delays and compare with metric statistics results, Box Plot graphs were used for the analysis. Finally, we conclude that under the parameters and conditions tested, wireless networks can serve as a communication system in control applications with allowable delays of up to 50 ms, in addition, the results show a better performance of Industrial Ethernet networks over conventional networks, with differences in the RTT of milliseconds. Therefore, it is recommended to establish what risk is for the process to control these delays to determine if the equipment conventional applies, since under certain features like humidity and temperature can operate properly for a considerable time and at lower cost than devices to Industrial Ethernet.

  6. Application of Bio-digestion for Capsule Gelatin-- From the Pharmaceutical Wastes to the Manure

    Science.gov (United States)

    Pan, C.; Huang, S.; Chang, Y.; Wen, J.

    2013-12-01

    The purpose of this study was to bio-digest the capsule gelatin from the waste of pharmaceutical processes such as cutting and stamping for capsule shells producing. We screened soil bacterial flora for capsule gelatin biolysis, and found the most competent one named Yuntech-7. A 15% (w/w) of capsule gelatin could fully digested by Yuntech-7 for 3 days growth with an N-limited medium in a 37°C incubator. In order to recycle and reuse the gelatin waste, the different percentages of capsule gelatin were co-composted with the vegetable residues to produce manure in an anaerobic fermentation by an extra Yuntech-7 inoculation. After 14 days incubation, we collected the filtrate to examine the contents of N, P, and K. The data shows that the P and K keep the same value by roughly between the blank and the control sets, but the total N values were approximately a 5-fold increase in 20% and a 10-fold increase in 40% of capsule gelatin integrated. We suggested that the capsule gelatin was majorly decomposed by Yuntech-7, because the total N value was no observable change in the capsule gelatin and vegetable residues co-compost with a Yuntech-7-free condition. We also performed some field tests using the capsule gelatin generated liquid manure, and the preliminary test shows the plants got great benefits on culture size and in environmental resistance. In conclusion, the process in bio-digestion of waste capsule gelatin by soil bacteria, Yuntech-7, was produced a valuable manure not only aliment the plants but also complement the soil bacterial populations.

  7. On common noise-induced synchronization in complex networks with state-dependent noise diffusion processes

    Science.gov (United States)

    Russo, Giovanni; Shorten, Robert

    2018-04-01

    This paper is concerned with the study of common noise-induced synchronization phenomena in complex networks of diffusively coupled nonlinear systems. We consider the case where common noise propagation depends on the network state and, as a result, the noise diffusion process at the nodes depends on the state of the network. For such networks, we present an algebraic sufficient condition for the onset of synchronization, which depends on the network topology, the dynamics at the nodes, the coupling strength and the noise diffusion. Our result explicitly shows that certain noise diffusion processes can drive an unsynchronized network towards synchronization. In order to illustrate the effectiveness of our result, we consider two applications: collective decision processes and synchronization of chaotic systems. We explicitly show that, in the former application, a sufficiently large noise can drive a population towards a common decision, while, in the latter, we show how common noise can synchronize a network of Lorentz chaotic systems.

  8. An exploratory study on the potential value add of social networking to the Entrepreneurial process

    Directory of Open Access Journals (Sweden)

    Alex Antonites

    2011-12-01

    Full Text Available It is widely established in scientific literature that entrepreneurship directly contributes to both employment generation and economic growth. Entrepreneurship is said to be subject to a very specific process which includes opportunity recognition, resource allocation, innovation and networking. Networking specifically, is an essential part of the entrepreneurial process as it is employed to assist entrepreneurs to capitalise on opportunities, allocate resources, find ways to innovate and contest ambiguity. With the advent of Web 2.0 and online social networking platforms the way in which people exchange information and network has changed significantly and has spawned a new social culture on a global level. The purpose of this study is to examine the value that online social networking adds to the entrepreneurial process, specifically focussing on the South African landscape. Keywords and phrases: Entrepreneurship; Networking; Social capital; Social networking; Social media

  9. Stochastic Capsule Endoscopy Image Enhancement

    Directory of Open Access Journals (Sweden)

    Ahmed Mohammed

    2018-06-01

    Full Text Available Capsule endoscopy, which uses a wireless camera to take images of the digestive tract, is emerging as an alternative to traditional colonoscopy. The diagnostic values of these images depend on the quality of revealed underlying tissue surfaces. In this paper, we consider the problem of enhancing the visibility of detail and shadowed tissue surfaces for capsule endoscopy images. Using concentric circles at each pixel for random walks combined with stochastic sampling, the proposed method enhances the details of vessel and tissue surfaces. The framework decomposes the image into two detailed layers that contain shadowed tissue surfaces and detail features. The target pixel value is recalculated for the smooth layer using similarity of the target pixel to neighboring pixels by weighting against the total gradient variation and intensity differences. In order to evaluate the diagnostic image quality of the proposed method, we used clinical subjective evaluation with a rank order on selected KID image database and compared it to state-of-the-art enhancement methods. The result showed that the proposed method provides a better result in terms of diagnostic image quality and objective quality contrast metrics and structural similarity index.

  10. A New Family of Capsule Polymerases Generates Teichoic Acid-Like Capsule Polymers in Gram-Negative Pathogens.

    Science.gov (United States)

    Litschko, Christa; Oldrini, Davide; Budde, Insa; Berger, Monika; Meens, Jochen; Gerardy-Schahn, Rita; Berti, Francesco; Schubert, Mario; Fiebig, Timm

    2018-05-29

    Group 2 capsule polymers represent crucial virulence factors of Gram-negative pathogenic bacteria. They are synthesized by enzymes called capsule polymerases. In this report, we describe a new family of polymerases that combine glycosyltransferase and hexose- and polyol-phosphate transferase activity to generate complex poly(oligosaccharide phosphate) and poly(glycosylpolyol phosphate) polymers, the latter of which display similarity to wall teichoic acid (WTA), a cell wall component of Gram-positive bacteria. Using modeling and multiple-sequence alignment, we showed homology between the predicted polymerase domains and WTA type I biosynthesis enzymes, creating a link between Gram-negative and Gram-positive cell wall biosynthesis processes. The polymerases of the new family are highly abundant and found in a variety of capsule-expressing pathogens such as Neisseria meningitidis , Actinobacillus pleuropneumoniae , Haemophilus influenzae , Bibersteinia trehalosi , and Escherichia coli with both human and animal hosts. Five representative candidates were purified, their activities were confirmed using nuclear magnetic resonance (NMR) spectroscopy, and their predicted folds were validated by site-directed mutagenesis. IMPORTANCE Bacterial capsules play an important role in the interaction between a pathogen and the immune system of its host. During the last decade, capsule polymerases have become attractive tools for the production of capsule polymers applied as antigens in glycoconjugate vaccine formulations. Conventional production of glycoconjugate vaccines requires the cultivation of the pathogen and thus the highest biosafety standards, leading to tremendous costs. With regard to animal husbandry, where vaccines could avoid the extensive use of antibiotics, conventional production is not sufficiently cost-effective. In contrast, enzymatic synthesis of capsule polymers is pathogen-free and fast, offers high stereo- and regioselectivity, and works with high efficacy

  11. Network design in a process of transition; Netzberechnung im Wandel

    Energy Technology Data Exchange (ETDEWEB)

    Schmieg, M. [Digsilent GmbH, Gomaringen (Germany)

    1998-08-01

    In the wake of liberalisation of the energy markets, new problems are encountered in connection with transmission network planning and operation, including a shift in aspects in network design, and new requirements are to be considered. The PowerFactory software warrants to network owners reliable performance of the necessary calculation and monitoring functions along with features allowing easy adaptation to individual operating concepts. (orig./CB) [Deutsch] Die Liberalisierung der Energiemaerkte wirft in puncto Netzplanung und Netzbetrieb neue Fragen auf, verschiebt die Schwerpunkte der Netzberechnung und stellt veraenderte Anforderungen. Die PowerFactory-Software verspricht dem Anwender die langfristig notwendigen Berechungs- und Ueberwachungsfunktionen und laesst sich einfach an individuelle Betriebskonzepte anpassen. (orig.)

  12. Information quality in dynamic networked business process management

    NARCIS (Netherlands)

    Rasouli, M.; Eshuis, H.; Trienekens, J.J.M.; Kusters, R.J.; Grefen, P.W.P.J.; Devruyne, C.; Panetto, H.; Meersman, R.; Dillon, T.; Weichhart, G.; An, Y.; Ardagna, C.A.

    2015-01-01

    The competition in globalized markets forces organizations to provide mass-customized integrated solutions for customers. Mass-customization of integrated solutions by business network requires adaptive interactions between parties to address emerging requirements of customers. These adaptive

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

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    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.

  14. Neural Networks as a Tool for Georadar Data Processing

    Directory of Open Access Journals (Sweden)

    Szymczyk Piotr

    2015-12-01

    Full Text Available In this article a new neural network based method for automatic classification of ground penetrating radar (GPR traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

  15. Initial process of updating the core of a network

    OpenAIRE

    TORTAJADA RODRÍGUEZ, MARCOS

    2013-01-01

    This report concerns my internship in the MI2S between the months of March and July of 2013, being employed by the Centre National de Recherche Scientifique. The CNRS is the most important public organization for scientific research, its aim is to coordinate the activities of the laboratories to make the scientific research more efficient. As a part of my course of Computer Networks and Telecommunications specializing in Wireless Networks and Security (a French professional bac...

  16. Neural network post-processing of grayscale optical correlator

    Science.gov (United States)

    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.

  17. Social Networking: Product or Process and What Shade of Grey?

    OpenAIRE

    Gelfand, Julia (UCI); Lin, Anthony (UCI); GreyNet, Grey Literature Network Service

    2011-01-01

    Social networking which debuted in 1997 is now an established and common method of communication with much variation and is increasingly related to and supportive of academic publishing, scholarship and generating new information. Some of the most mature and popular sites are Facebook, Bebo, Twitter, Linked-In and Plaxo plus many more specialized examples. As many professional societies and individuals choose to develop a presence on social networking sites (SNSs), the utility of them has b...

  18. Passive sorting of capsules by deformability

    Science.gov (United States)

    Haener, Edgar; Juel, Anne

    We study passive sorting according to deformability of liquid-filled ovalbumin-alginate capsules. We present results for two sorting geometries: a straight channel with a half-cylindrical obstruction and a pinched flow fractioning device (PFF) adapted for use with capsules. In the half-cylinder device, the capsules deform as they encounter the obstruction, and travel around the half-cylinder. The distance from the capsule's centre of mass to the surface of the half-cylinder depends on deformability, and separation between capsules of different deformability is amplified by diverging streamlines in the channel expansion downstream of the obstruction. We show experimentally that capsules can be sorted according to deformability with their downstream position depending on capillary number only, and we establish the sensitivity of the device to experimental variability. In the PFF device, particles are compressed against a wall using a strong pinching flow. We show that capsule deformation increases with the intensity of the pinching flow, but that the downstream capsule position is not set by deformation in the device. However, when using the PFF device like a T-Junction, we achieve improved sorting resolution compared to the half-cylinder device.

  19. Third Party Referrals in the Venture Capital Financing Process: Do Network Ties Matter?

    NARCIS (Netherlands)

    Heuven, J.M.J.

    2008-01-01

    In this paper we focus on the role of third party referrals in the venture capital funding process. Taking network theory as our theoretical perspective we explore if and how third parties play a role in the funding process. Hereby we focus on both the network ties between new venture teams and

  20. On the Modeling and Analysis of Heterogeneous Radio Access Networks using a Poisson Cluster Process

    DEFF Research Database (Denmark)

    Suryaprakash, Vinay; Møller, Jesper; Fettweis, Gerhard P.

    processes, some of which are alluded to (later) in this paper. We model a heterogeneous network consisting of two types of base stations by using a particular Poisson cluster process model. The main contributions are two-fold. First, a complete description of the interference in heterogeneous networks...

  1. The Interaction between Personality, Social Network Position and Involvement in Innovation Process

    NARCIS (Netherlands)

    E. Dolgova (Evgenia); W. van Olffen (Woody); F.A.J. van den Bosch (Frans); H.W. Volberda (Henk)

    2010-01-01

    textabstractAbstract This dissertation proposal investigates how personality and individuals’ social network position affect individuals’ involvement into the innovation process. It posits that people would feel inclined to become involved into the different phases of the innovation process

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

    Science.gov (United States)

    Harling, Guy; Onnela, Jukka-Pekka

    2018-03-01

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

  3. Intrauterine fertilization capsules--a clinical trial

    DEFF Research Database (Denmark)

    Lenz, S; Lindenberg, S; Sundberg, K

    1991-01-01

    Treatment of 26 women with tubal infertility was attempted using intrauterine capsules loaded with oocytes and spermatozoa. The stimulation protocol was as used for in vitro fertilization and embryo transfer and consisted of short-term use of Buserelin, human menopausal gonadotropin, and human...... and piston from an intrauterine device. Six complete capsules and parts of two other capsules were expelled. None of the women became pregnant, compared with a pregnancy rate of 21% per aspiration following in vitro fertilization and embryo transfer during the same period....... chorionic gonadotropin. Oocytes were collected by ultrasonically guided transvaginal aspiration, and spermatozoa were prepared by swim-up technique. The gametes were placed in agar capsules 4 hr after oocyte collection, and the capsules were introduced to the uterine fundus using an insertion tube...

  4. Finding the Sweet Spot: Network Structures and Processes for Increased Knowledge Mobilization

    Directory of Open Access Journals (Sweden)

    Patricia Briscoe

    2016-06-01

    Full Text Available The use of networks in public education is one of a number of knowledge mobilization (KMb strategies utilized to promote evidence-based research into practice. However, challenges exist in the ability to effectively mobilizing knowledge through external partnership networks. The purpose of this paper is to further explore how networks work. Data was collected from virtual discussions for an interim report for a province-wide government initiative. A secondary analysis of the data was performed. The findings present network structures and processes that partners were engaged in when building a network within education. The implications of this study show that building a network for successful outcomes is complex and metaphorically similar to finding the “sweet spot.” It is challenging but networks that used strategies to align structures and processes proved to achieve more success in mobilizing research to practice.

  5. Adhesive capsulitis of the shoulder: MR arthrography

    International Nuclear Information System (INIS)

    Kim, Hyun Jeong; Han, Tae Il; Lee, Kwang Won; Choi, Youn Seon; Kim, Dae Hong; Han, Hyun Young; Song, Mun Kab; Kwon, Soon Tae

    2001-01-01

    Adhesive capsulitis is a clinical syndrome involving pain and decreased joint motion caused by thickening and contraction of the joint capsule. The purpose of this study is to describe the MR arthrographic findings of this syndrome. Twenty-nine sets of MR arthrographic images were included in the study. Fourteen patients had adhesive capsulitis diagnosed by physical examination and arthrography, and their MR arthrographic findings were compared with those of 15 subjects in the control group. The images were retrospectively reviewed with specific attention to the thickness of the joint capsule, volume of the axillary pouch (length, width, height(depth)), thinkness of the coracohumeral ligament, presence of extra-articular contrast extravasation, and contrst filling of the subcoracoid bursa. Mean capsular thickness measured at the inferior portion of the axillary pouch was 4.1 mm in patients with adhesive capsulitis and 1.5 mm in the control group. The mean width of the axillary pouch was 2.5 mm in patients and 9.5 mm in controls. In patients, the capsule was significantly thicker and the axillary pouch significantly narrower than in controls (p<0.05). Capsule thickness greater than 2.5 mm at the inferior portion of the axillary pouch (sensitivity 93%, specificity 80%) and a pouch narrower than 3.5 mm (sensitivity 93%, specificity 100%) were useful criteria for the diagnosis of adhesive capsulitis. In patients with this condition, extra-articular contrast extravasation was noted in six patients (43%) and contrast filling of the subcoracoid bursa in three (21%). The MR arthrographic findings of adhesive capsulitis are capsular thickening, a low-volume axillary pouch, extra-articular contrast extravasation, and contrast filling of the subcoracoid bursa. Capsule thickness greater than 2.5 mm at the inferior portion of the axillary pouch and a pouch width of less than 3.5 mm are useful diagnostic imaging characteristics

  6. Thermoregulation of Capsule Production by Streptococcus pyogenes

    Science.gov (United States)

    Kang, Song Ok; Wright, Jordan O.; Tesorero, Rafael A.; Lee, Hyunwoo; Beall, Bernard; Cho, Kyu Hong

    2012-01-01

    The capsule of Streptococcus pyogenes serves as an adhesin as well as an anti-phagocytic factor by binding to CD44 on keratinocytes of the pharyngeal mucosa and the skin, the main entry sites of the pathogen. We discovered that S. pyogenes HSC5 and MGAS315 strains are further thermoregulated for capsule production at a post-transcriptional level in addition to the transcriptional regulation by the CovRS two-component regulatory system. When the transcription of the hasABC capsular biosynthetic locus was de-repressed through mutation of the covRS system, the two strains, which have been used for pathogenesis studies in the laboratory, exhibited markedly increased capsule production at sub-body temperature. Employing transposon mutagenesis, we found that CvfA, a previously identified membrane-associated endoribonuclease, is required for the thermoregulation of capsule synthesis. The mutation of the cvfA gene conferred increased capsule production regardless of temperature. However, the amount of the capsule transcript was not changed by the mutation, indicating that a post-transcriptional regulator mediates between CvfA and thermoregulated capsule production. When we tested naturally occurring invasive mucoid strains, a high percentage (11/53, 21%) of the strains exhibited thermoregulated capsule production. As expected, the mucoid phenotype of these strains at sub-body temperature was due to mutations within the chromosomal covRS genes. Capsule thermoregulation that exhibits high capsule production at lower temperatures that occur on the skin or mucosal surface potentially confers better capability of adhesion and invasion when S. pyogenes penetrates the epithelial surface. PMID:22615992

  7. Hydrodynamick instabilities on ICF capsules

    International Nuclear Information System (INIS)

    Haan, S.W.

    1991-01-01

    This article summarizes our current understanding of hydrodynamic instabilities as relevant to ICF. First we discuss classical, single mode Rayleigh-Taylor instability, and nonlinear effects in the evolution of a single mode. Then we discuss multimode systems, considering: (1) the onset of nonlinearity; (2) a second order mode coupling theory for weakly nonlinear effects, and (3) the fully nonlinear regime. Two stabilization mechanisms relevant to ICF are described next: gradient scale length and convective stabilization. Then we describe a model which is meant to estimate the weakly nonlinear evolution of multi-mode systems as relevant to ICF, given the short-wavelength stabilization. Finally, we discuss the relevant code simulation capability, and experiments. At this time we are quite optimistic about our ability to estimate instability growth on ICF capsules, but further experiments and simulations are needed to verify the modeling. 52 refs

  8. SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

    Science.gov (United States)

    Zhang, Wenhao; Li, Hanyu; Yang, Minda; Mesgarani, Nima

    2016-03-01

    A characteristic property of biological neurons is their ability to dynamically change the synaptic efficacy in response to variable input conditions. This mechanism, known as synaptic depression, significantly contributes to the formation of normalized representation of speech features. Synaptic depression also contributes to the robust performance of biological systems. In this paper, we describe how synaptic depression can be modeled and incorporated into deep neural network architectures to improve their generalization ability. We observed that when synaptic depression is added to the hidden layers of a neural network, it reduces the effect of changing background activity in the node activations. In addition, we show that when synaptic depression is included in a deep neural network trained for phoneme classification, the performance of the network improves under noisy conditions not included in the training phase. Our results suggest that more complete neuron models may further reduce the gap between the biological performance and artificial computing, resulting in networks that better generalize to novel signal conditions.

  9. Traffic analysis and signal processing in optical packet switched networks

    DEFF Research Database (Denmark)

    Fjelde, Tina

    2002-01-01

    /s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

  10. Social networks in the R&D process

    DEFF Research Database (Denmark)

    Dahl, Michael S.; Østergaard, Christian Richter

    2005-01-01

    Whether social networks diffuse knowledge across firm boundaries has been the topic of much debate. To inform these theories, this article considers two questions. First, who has contacts across firm boundaries? And second, when do these relations diffuse knowledge? Our empirical evidence comes...... valuable knowledge from their networks. These findings show that the long-term relationships, which are more likely based on trust and reputation, are also more likely to be a channel valuable knowledge. (c) 2004 Elsevier B.V. All rights reserved....

  11. Modeling Wireless Sensor Networks for Monitoring in Biological Processes

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil

    parameters, as the use of wired sensors is impractical. In this thesis, a ZigBee based wireless sensor network was employed and only a part of the herd was monitored, as monitoring each individual animal in a large herd under practical conditions is inefficient. Investigations to show that the monitored...... (MMAE) approach to the data resulted in the highest classification success rate, due to the use of precise forth-order mathematical models which relate the feed offer to the pitch angle of the neck. This thesis shows that wireless sensor networks can be successfully employed to monitor the behavior...

  12. Adaptive Smoothing in fMRI Data Processing Neural Networks

    DEFF Research Database (Denmark)

    Vilamala, Albert; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

    2017-01-01

    in isolation. With the advent of new tools for deep learning, recent work has proposed to turn these pipelines into end-to-end learning networks. This change of paradigm offers new avenues to improvement as it allows for a global optimisation. The current work aims at benefitting from this paradigm shift...... by defining a smoothing step as a layer in these networks able to adaptively modulate the degree of smoothing required by each brain volume to better accomplish a given data analysis task. The viability is evaluated on real fMRI data where subjects did alternate between left and right finger tapping tasks....

  13. Virtual optical network provisioning with unified service logic processing model for software-defined multidomain optical networks

    Science.gov (United States)

    Zhao, Yongli; Li, Shikun; Song, Yinan; Sun, Ji; Zhang, Jie

    2015-12-01

    Hierarchical control architecture is designed for software-defined multidomain optical networks (SD-MDONs), and a unified service logic processing model (USLPM) is first proposed for various applications. USLPM-based virtual optical network (VON) provisioning process is designed, and two VON mapping algorithms are proposed: random node selection and per controller computation (RNS&PCC) and balanced node selection and hierarchical controller computation (BNS&HCC). Then an SD-MDON testbed is built with OpenFlow extension in order to support optical transport equipment. Finally, VON provisioning service is experimentally demonstrated on the testbed along with performance verification.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-01

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

  15. Probabilistic Models and Process Calculi for Mobile Ad Hoc Networks

    DEFF Research Database (Denmark)

    Song, Lei

    , thus the network topology may undergo constant changes. Moreover the devices in an MANET are loosely connected not depending on pre-installed infrastructure or central control components, they exchange messages via wireless connections which are less reliable compared to wired connections. Therefore...

  16. Social Networks as Information Source for the Purchase Decision Process

    Directory of Open Access Journals (Sweden)

    Camila Leoni Nascimento

    2014-12-01

    Full Text Available The social networks have caused changes in the consumption habits and in the ways of relationship among companies and consumers, emerging a more demanding and informed consumer. In this paper it is aimed to assess the social networks as a source of information for the purchase of goods or services. In the study it was applied a research of exploratory nature through the survey method, conducted through personal interviews using a questionnaire with closed-ended questions. The sample of non-probabilistic type was comprised of 200 individuals from a higher education institution of São Paulo State hinterland. The survey data were analyzed descriptively. Overall, the results showed the use of social networks as a source of information search, in which the main motive is the practicality. The results corroborate the studies of Kotler and Keller (2006 when they state that the consumer seeks information on social networks to help him in the purchase, as Edelman and Hirshberg (2006 when approaching the user confidence in their friends’ opinion. For future works it is recommended to check what strategies and in what ways the companies could work in order to provide more detailed data to Internet users, aiming to support them in the decision

  17. [Evaluation of nopal capsules in diabetes mellitus].

    Science.gov (United States)

    Frati Munari, A C; Vera Lastra, O; Ariza Andraca, C R

    1992-01-01

    To find out if commercial capsules with dried nopal (prickle-pear cactus, Opuntia ficus indica may have a role in the management of diabetes mellitus, three experiments were performed: 30 capsules where given in fasting condition to 10 diabetic subjects and serum glucose was measured through out 3 hours; a control test was performed with 30 placebo capsules. OGTT with previous intake of 30 nopal or placebo capsules was performed in ten healthy individuals. In a crossover and single blinded study 14 diabetic patients withdrew the oral hypoglycemic treatment and received 10 nopal or placebo capsules t.i.d. during one week; serum glucose, cholesterol and tryglycerides levels were measured before and after each one-week period. Five healthy subjects were also studied in the same fashion. Opuntia capsules did not show acute hypoglycemic effect and did not influence OGTT. In diabetic patients serum glucose, cholesterol and tryglycerides levels did not change with Opuntia, but they increased with placebo (P nopal, while cholesterol and triglycerides decreased (P < 0.01 vs. placebo). The intake of 30 Opuntia capsules daily in patients with diabetes mellitus had a discrete beneficial effect on glucose and cholesterol. However this dose is unpractical and at present it is not recommended in the management of diabetes mellitus.

  18. Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

    Directory of Open Access Journals (Sweden)

    V. B. Surya Prasath

    2016-12-01

    Full Text Available Video capsule endoscopy (VCE is used widely nowadays for visualizing the gastrointestinal (GI tract. Capsule endoscopy exams are prescribed usually as an additional monitoring mechanism and can help in identifying polyps, bleeding, etc. To analyze the large scale video data produced by VCE exams, automatic image processing, computer vision, and learning algorithms are required. Recently, automatic polyp detection algorithms have been proposed with various degrees of success. Though polyp detection in colonoscopy and other traditional endoscopy procedure based images is becoming a mature field, due to its unique imaging characteristics, detecting polyps automatically in VCE is a hard problem. We review different polyp detection approaches for VCE imagery and provide systematic analysis with challenges faced by standard image processing and computer vision methods.

  19. Oxygen fugacity and piston cylinder capsule assemblies

    Science.gov (United States)

    Jakobsson, S.

    2011-12-01

    A double capsule assembly designed to control oxygen fugacity in piston cylinder experiments has been tested at 1200 °C and 10 kbar. The assembly consists of an outer Pt-capsule containing a solid buffer (Ni-NiO or Co-CoO plus H2O) and an inner AuPd-capsule containing the sample, H2O and a Pt-wire. To prevent direct contact with the buffer phases the AuPd-capsule is embedded in finely ground Al2O3 along with some coarser, fractured Al2O3 facilitating fluid inclusion formation. No water loss is observed in the sample even after 48 hrs but a slight increase in water content is observed in longer duration runs due to oxygen and hydrogen diffusion into the AuPd-capsule. Carbon from the furnace also diffuses through the outer Pt-capsule but reacts with H2O in the outer capsule to form CO2 and never reaches the inner capsule. Oxygen fugacity of runs in equilibrium with the Ni-NiO and Co-CoO buffers was measured by analyzing the Fe content of the Pt-wire in the sample1 and by analyzing Fe dissolved in the AuPd capsule2. The second method gives values that are in good agreement with established buffer whereas results from the first method are one half to one log units higher than the established values. References 1. E. Medard, C. A. McCammon, J. A. Barr, T. L. Grove, Am. Mineral. 93, 1838 (2008). 2. J. Barr, T. Grove, Contrib. Mineral. Petrol. 160, 631 (2010)

  20. WESF cesium capsule behavior at high temperature or during thermal cycling

    International Nuclear Information System (INIS)

    Tingey, G.L.; Gray, W.J.; Shippell, R.J.; Katayama, Y.B.

    1985-06-01

    Double-walled stainless steel (SS) capsules prepared for storage of radioactive 137 Cs from defense waste are now being considered for use as sources for commercial irradiation. Cesium was recovered at B-plant from the high-level radioactive waste generated during processing of defense nuclear fuel. It was then purified, converted to the chloride form, and encapsulated at the Hanford Waste Encapsulation and Storage Facility (WESF). The molten cesium chloride salt was encapsulated by pouring it into the inner of two concentric SS cylinders. Each cylinder was fitted with a SS end cap that was welded in place by inert gas-tungsten arc welding. The capsule configuration and dimensions are shown in Figure 1. In a recent review of the safety of these capsules, Tingey, Wheelwright, and Lytle (1984) indicated that experimental studies were continuing to produce long-term corrosion data, to reaffirm capsule integrity during a 90-min fire where capsule temperatures reached 800 0 C, to monitor mechanical properties as a function of time, and to assess the effects of thermal cycling due to periodic transfer of the capsules from a water storage pool to the air environment of an irradiator facility. This report covers results from tests that simulated the effects of the 90-min fire and from thermal cycling actual WESF cesium capsules for 3845 cycles over a period of six months. 11 refs., 39 figs., 9 tabs

  1. Preparation of sustained release capsules by electrostatic dry powder coating, using traditional dip coating as reference.

    Science.gov (United States)

    Yang, Yan; Shen, Lian; Yuan, Feng; Fu, Hui; Shan, Weiguang

    2018-05-30

    Lately, a great deal of attention is being paid to capsule coating, since the coat protects active pharmaceutical ingredients (APIs) from damage, as is in the case of tablet and pellet. However, moisture and heat sensitivity of gelatin shells make it challenging to coat capsules using the conventional aqueous coating techniques. In an effort to overcome this challenge, the present study aims to coat capsules using two different coating techniques: electrostatic dry powder coating (EDPC) and dip coating (DC). Both capsule coatings and free films were prepared by these two coating techniques, and the effects of coating formulations and processing conditions on the film quality were investigated. The corresponding drug in vitro release and mechanisms were characterized and compared. The results of dissolution tests demonstrated that the drug release behavior of both EDPC and DC coated capsules could be optimized to a sustained release of 24 h, following the Fick's diffusion law. The results of this study suggest that EDPC method is better than DC method for coating capsules, with respect to the higher production efficiency and better stability, indicating that this dry coating technology has promised in gelatin capsule coating applications. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. A disposable and multifunctional capsule for easy operation of microfluidic elastomer systems

    International Nuclear Information System (INIS)

    Thorslund, Sara; Läräng, Thomas; Kreuger, Johan; Nguyen, Hugo; Barkefors, Irmeli

    2011-01-01

    The global lab-on-chip and microfluidic markets for cell-based assays have been predicted to grow considerably, as novel microfluidic systems enable cell biologists to perform in vitro experiments at an unprecedented level of experimental control. Nevertheless, microfluidic assays must, in order to compete with conventional assays, be made available at easily affordable costs, and in addition be made simple to operate for users having no previous experience with microfluidics. We have to this end developed a multifunctional microfluidic capsule that can be mass-produced at low cost in thermoplastic material. The capsule enables straightforward operation of elastomer inserts of optional design, here exemplified with insert designs for molecular gradient formation in microfluidic cell culture systems. The integrated macro–micro interface of the capsule ensures reliable connection of the elastomer fluidic structures to an external perfusion system. A separate compartment in the capsule filled with superabsorbent material is used for internal waste absorption. The capsule assembly process is made easy by integrated snap-fits, and samples within the closed capsule can be analyzed using both inverted and upright microscopes. Taken together, the capsule concept presented here could help accelerate the use of microfluidic-based biological assays in the life science sector. (technical note)

  3. The default network and self-generated thought: component processes, dynamic control, and clinical relevance

    Science.gov (United States)

    Andrews-Hanna, Jessica R.; Smallwood, Jonathan; Spreng, R. Nathan

    2014-01-01

    Though only a decade has elapsed since the default network was first emphasized as being a large-scale brain system, recent years have brought great insight into the network’s adaptive functions. A growing theme highlights the default network as playing a key role in internally-directed—or self-generated—thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the default network. First, we present evidence that self-generated thought is a multi-faceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the default network, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced. PMID:24502540

  4. An integrated knowledge-based framework for synthesis and design of enterprise-wide processing networks

    DEFF Research Database (Denmark)

    Sin, Gürkan

    material, product portfolio and process technology selection for a given market scenario, their sustainability metrics and risk of investment under market uncertainties enabling risk-aware decision making. The framework is highlighted with successful applications for soybean oil processing (food technology......, the synthesis and design of processing networks is a complex and multidisciplinary problem, which involves many strategic and tactical decisions at business (considering financial criteria, market competition, supply chain network, etc) and engineering levels (considering synthesis, design and optimization...

  5. Ethanol production from steam exploded rapeseed straw and the process simulation using artificial neural networks

    DEFF Research Database (Denmark)

    Talebnia, Farid; Mighani, Moein; Rahimnejad, Mostafa

    2015-01-01

    and 67% of maximum theoretical value. Next, data of the experimental runs were exploited for modeling the processes by artificial neural networks (ANNs) and performance of the developed models was evaluated. The ANN-based models showed a great potential for time-course prediction of the studied processes....... Efficiency of the joint network for simulating the whole process was also determined and promising results were obtained....

  6. A study of the discovery process in 802.11 networks

    OpenAIRE

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  8. Statistical tools and control of internal lubricant content of inhalation grade HPMC capsules during manufacture.

    Science.gov (United States)

    Ayala, Guillermo; Díez, Fernando; Gassó, María T; Jones, Brian E; Martín-Portugués, Rafael; Ramiro-Aparicio, Juan

    2016-04-30

    The internal lubricant content (ILC) of inhalation grade HPMC capsules is a key factor to ensure good powder release when the patient inhales a medicine from a dry powder inhaler (DPI). Powder release from capsules has been shown to be influenced by the ILC. The characteristics used to measure this are the emitted dose, fine particle fraction and mass median aerodynamic diameter. In addition the ILC level is critical for capsule shell manufacture because it is an essential part of the process that cannot work without it. An experiment has been applied to the manufacture of inhalation capsules with the required ILC. A full factorial model was used to identify the controlling factors and from this a linear model has been proposed to improve control of the process. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Distributed collaborative processing in wireless sensor networks with application to target localization and beamforming

    OpenAIRE

    Béjar Haro, Benjamín

    2013-01-01

    Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of es...

  10. Culture, agency and power: Theoretical reflections on informal economic networks and political process

    OpenAIRE

    Meagher, Kate

    2009-01-01

    Do network theory really offer a suitable concept for the theorization of informal processes of economic regulation and institutional change? This working paper challenges both essentialist and skeptical attitudes to networks through an examination of the positive and negative effects of network governance in contemporary societies in a range of regional contexts. The analysis focuses on three broad principles of non-state organization - culture, agency and power - and their role in shaping p...

  11. Digital Signal Processing and Control for the Study of Gene Networks

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-01

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  12. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Science.gov (United States)

    Kwak, Doyeon; Kim, Wonjoon

    2017-01-01

    It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  13. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Directory of Open Access Journals (Sweden)

    Doyeon Kwak

    Full Text Available It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  14. Study on algorithm of process neural network for soft sensing in sewage disposal system

    Science.gov (United States)

    Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

    2006-11-01

    A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

  15. Facile and Scalable Synthesis of Monodispersed Spherical Capsules with a Mesoporous Shell

    KAUST Repository

    Qi, Genggeng

    2010-05-11

    Monodispersed HMSs with tunable particle size and shell thickness were successfully synthesized using relatively concentrated polystyrene latex templates and a silica precursor in a weakly basic ethanol/water mixture. The particle size of the capsules can vary from 100 nm to micrometers. These highly engineered monodispersed capsules synthesized by a facile and scalable process may find applications in drug delivery, catalysis, separationm or as biological and chemical microreactors. © 2010 American Chemical Society.

  16. Neuro-fuzzy Classification System for Wireless-Capsule Endoscopic Images

    OpenAIRE

    Vassilis S. Kodogiannis; John N. Lygouras

    2008-01-01

    In this research study, an intelligent detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the M2A Swallowable Imaging Capsule - a patented, video color-imaging disposable capsule. Schemes have been developed to extract texture features from the fuzzy texture spectra in the chromatic and achromatic domains for a selected region of interest from ...

  17. Class A Network Dataring gauges - 1991 data processing and analysis

    OpenAIRE

    Shaw, S.M.

    1992-01-01

    This report presents a summary of still water level data processing for 1991 from 34 modernised dataring sites around the UK coast. Details of geographic position, reference levels, processing, statistics and analyses are included.

  18. Process identification through modular neural networks and rule extraction (extended abstract)

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.; Blockeel, Hendrik; Denecker, Marc

    2002-01-01

    Monolithic neural networks may be trained from measured data to establish knowledge about the process. Unfortunately, this knowledge is not guaranteed to be found and – if at all – hard to extract. Modular neural networks are better suited for this purpose. Domain-ordered by topology, rule

  19. A Recommended Framework for the Network-Centric Acquisition Process

    Science.gov (United States)

    2009-09-01

    ISO /IEC 12207 , Systems and Software Engineering-Software Life-Cycle Processes  ANSI/EIA 632, Processes for Engineering a System. There are...engineering [46]. Some of the process models presented in the DAG are:  ISO /IEC 15288, Systems and Software Engineering-System Life-Cycle Processes...e.g., ISO , IA, Security, etc.). Vetting developers helps ensure that they are using industry best industry practices and maximize the IA compliance

  20. Capsule production by Pseudomonas aeruginosa

    Energy Technology Data Exchange (ETDEWEB)

    Lynn, A.R.

    1984-01-01

    Mucoid strains of Pseudomonas aeruginosa, associated almost exclusively with chronic respiratory infections in patients with cystic fibrosis, possess a capsule composed of alginic acid similar to one produced by Azotobacter vinelandii. Recent reports have provided evidence that the biosynthetic pathway for alginate in P. aeruginosa may differ from the pathway proposed for A. vinelandii in that synthesis in P. aeruginosa may occur by way of the Entner-Doudoroff pathway. Incorporation of isotope from (6-/sup 14/C)glucose into alginate by both P. aueroginosa and A. vinelandii was 10-fold greater than that from either (1-/sup 14/C)/sup -/ or (2-/sup 14/C)glucose, indicating preferential utilization of the bottom half of the glucose molecule for alginate biosynthesis. These data strongly suggest that the Entner-Doudoroff pathway plays a major role in alginate synthesis in both P. aeruginosa and A. vinelandii. The enzymes of carbohydrate metabolism in mucoid strains of P. aeruginosa appear to be unchanged whether alignate is actively produced or not and activities do not differ significantly from nonmucoid strain PAO.

  1. Vortex rings from Sphagnum moss capsules

    Science.gov (United States)

    Whitaker, Dwight; Strassman, Sam; Cha, Jung; Chang, Emily; Guo, Xinyi; Edwards, Joan

    2010-11-01

    The capsules of Sphagnum moss use vortex rings to disperse spores to suitable habitats many kilometers away. Vortex rings are created by the sudden release of pressurized air when the capsule ruptures, and are an efficient way to carry the small spores with low terminal velocities to heights where they can be carried by turbulent wind currents. We will present our computational model of these explosions, which are carried out using a 2-D large eddy simulation (LES) on FLUENT. Our simulations can reproduce the observed motion of the spore clouds observed from moss capsules with high-speed videos, and we will discuss the roles of bursting pressure, cap mass, and capsule morphology on the formation and quality of vortex rings created by this plant.

  2. 21 CFR 520.1660b - Oxytetracycline hydrochloride capsules.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 6 2010-04-01 2010-04-01 false Oxytetracycline hydrochloride capsules. 520.1660b... Oxytetracycline hydrochloride capsules. (a) Specifications. The drug is in capsule form with each capsule containing 125 or 250 milligrams of oxytetracycline hydrochloride. Oxytetracycline is the antibiotic...

  3. Functional network connectivity underlying food processing: disturbed salience and visual processing in overweight and obese adults.

    Science.gov (United States)

    Kullmann, Stephanie; Pape, Anna-Antonia; Heni, Martin; Ketterer, Caroline; Schick, Fritz; Häring, Hans-Ulrich; Fritsche, Andreas; Preissl, Hubert; Veit, Ralf

    2013-05-01

    In order to adequately explore the neurobiological basis of eating behavior of humans and their changes with body weight, interactions between brain areas or networks need to be investigated. In the current functional magnetic resonance imaging study, we examined the modulating effects of stimulus category (food vs. nonfood), caloric content of food, and body weight on the time course and functional connectivity of 5 brain networks by means of independent component analysis in healthy lean and overweight/obese adults. These functional networks included motor sensory, default-mode, extrastriate visual, temporal visual association, and salience networks. We found an extensive modulation elicited by food stimuli in the 2 visual and salience networks, with a dissociable pattern in the time course and functional connectivity between lean and overweight/obese subjects. Specifically, only in lean subjects, the temporal visual association network was modulated by the stimulus category and the salience network by caloric content, whereas overweight and obese subjects showed a generalized augmented response in the salience network. Furthermore, overweight/obese subjects showed changes in functional connectivity in networks important for object recognition, motivational salience, and executive control. These alterations could potentially lead to top-down deficiencies driving the overconsumption of food in the obese population.

  4. Adhesive capsulitis: review of imaging and treatment

    International Nuclear Information System (INIS)

    Harris, Guy; Bou-Haider, Pascal; Harris, Craig

    2013-01-01

    Adhesive capsulitis is one of the most common conditions affecting the shoulder; however, early clinical diagnosis can be challenging. Treatment is most effective when commenced prior to the onset of capsular thickening and contracture; consequently, the role of imaging is increasing. The aim of this review is to demonstrate the typical imaging appearances of adhesive capsulitis and to examine some of the evidence regarding each of these imaging modalities. An evaluation of the various management options available to the clinician is also presented.

  5. Radioactive gas-containing polymeric capsule

    International Nuclear Information System (INIS)

    Winchell, H.S.; Lewis, R.E.

    1975-01-01

    A disposable ventilation study system for dispensing a single patient dosage of gaseous radioisotopes to patients for pulmonary function studies is disclosed. A gas impermeable capsule encloses the gaseous radioisotope and is stored within a radioactivity shielding body of valve means which shears the capsule to dispense the radioisotope to the patient. A breathing bag receives the patient's exhalation of the radioisotope and permits rebreathing of the radioisotope by the patient. 18 claims, 7 drawing figures

  6. Social multimedia signals a signal processing approach to social network phenomena

    CERN Document Server

    Roy, Suman Deb

    2014-01-01

    This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

  7. Features of Joint Capsule Formation After Antenatal Action of Antigen

    Directory of Open Access Journals (Sweden)

    A.V. Fedotchenko

    2014-10-01

    Full Text Available In this paper using morphometric, histological, histochemical and statistical methods, we have investigated the dynamics of hip joint capsule formation in white laboratory rats during the postnatal period after intrefetal introduction of antigen. It is found that antenatal effect of antigen leads to an increase in the number of lymphocytes, in particular PNA+, in joint capsule. Against this background, we observed an increase in the proportion of cells, the basic substance and elastic fibers, while reducing the content of collagen fibers, violations in polysaccharides and fibroblasts distribution that indicates the development of dysplastic processes in the hip joint and can be regarded as the leading factor of coxarthrosis development. Experimentally, we have detected arachnodactylia as a visual clinical manifestation of dysplasia.

  8. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  9. Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

    KAUST Repository

    Alsibyani, Hassan M.

    2018-01-01

    . For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing

  10. Fault detection and diagnosis for complex multivariable processes using neural networks

    International Nuclear Information System (INIS)

    Weerasinghe, M.

    1998-06-01

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

  11. Multisensor Network System for Wildfire Detection Using Infrared Image Processing

    Directory of Open Access Journals (Sweden)

    I. Bosch

    2013-01-01

    Full Text Available This paper presents the next step in the evolution of multi-sensor wireless network systems in the early automatic detection of forest fires. This network allows remote monitoring of each of the locations as well as communication between each of the sensors and with the control stations. The result is an increased coverage area, with quicker and safer responses. To determine the presence of a forest wildfire, the system employs decision fusion in thermal imaging, which can exploit various expected characteristics of a real fire, including short-term persistence and long-term increases over time. Results from testing in the laboratory and in a real environment are presented to authenticate and verify the accuracy of the operation of the proposed system. The system performance is gauged by the number of alarms and the time to the first alarm (corresponding to a real fire, for different probability of false alarm (PFA. The necessity of including decision fusion is thereby demonstrated.

  12. Critical behavior of the contact process on small-world networks

    Science.gov (United States)

    Ferreira, Ronan S.; Ferreira, Silvio C.

    2013-11-01

    We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

  13. Analysing the Outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center

    OpenAIRE

    Marjeta, Katri

    2011-01-01

    Marjeta, Katri. 2011. Analysing the outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center. Master´s thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 57. Due to confidentiality issues, this work has been modified from its original form. The aim of this Master Thesis work is to describe and analyze the outbound logistics process enhancement projects executed in Nokia-Siemens Networks Global Distribution Center after the N...

  14. The governance of regional networks in the process of European integration

    OpenAIRE

    Cappellin, Riccardo

    2001-01-01

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

  15. Management of the Cs/Sr Capsule Project at the Hanford Site. Technology Readiness Assessment Report

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    2018-01-01

    The Federal Project Director (FPD) for the U.S. Department of Energy (DOE), Richland Operations Office (RL) Waste Management and D&D Division (WMD) requested a Technology Readiness Assessment (TRA) for the Management of the Cesium/Strontium Capsule Storage Project (MCSCP) at the Waste Encapsulation and Storage Facility (WESF) on the Hanford Site in Washington State. The MCSCP CD-1 TRA was performed by a team selected in collaboration between the Office of Environmental Management (EM) Chief Engineer (EM-3.3) and RL, WMD FPD. The TRA Team included subject matter and technical experts having experience in cask storage, process engineering, and system design who were independent of the MCSCP, and the team was led by the Director of Operations and Processes from the EM Chief Engineer's Office (EM-3.32). Movement of the Cs/Sr capsules to dry storage, based on information from the conceptual design, involves (1) capsule packaging, (2) capsule transfer, and (3) capsule storage. The project has developed a conceptual process, described in 30059-R-02, "NAC Conceptual Design Report for the Management of the Cesium and Strontium Capsules Project", which identifies the five major activities in the process to complete the transfer from storage pool to pad-mounted cask storage. The process, shown schematically in Figure 1, is comprised of the following process steps: (1) loading capsules into the UCS; (2) UCS processing; (3) UCS insertion into the TSC Basket; (4) cask transport from WESF to CSA and (5) extended storage at the CSA.

  16. Filtering and spectral processing of 1-D signals using cellular neural networks

    NARCIS (Netherlands)

    Moreira-Tamayo, O.; Pineda de Gyvez, J.

    1996-01-01

    This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

  17. A collaborative processes synchronization method with regard to system crashes and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2014-01-01

    Processes can synchronize their states by exchanging messages. System crashes and network failures may cause message loss, so that state changes of a process may remain unnoticed by its partner processes, resulting in state inconsistency or deadlocks. In this paper we define a method to transform a

  18. Robust client/server shared state interactions of collaborative process with system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes state, it sends messages to relevant processes to inform about this change. However, server crashes and

  19. Predictive business process monitoring with LSTM neural networks

    NARCIS (Netherlands)

    Tax, N.; Verenich, I.; La Rosa, M.; Dumas, M.; Pohl, Klaus; Dubois, Eric

    2017-01-01

    Predictive business process monitoring methods exploit logs of completed cases of a process in order to make predictions about running cases thereof. Existing methods in this space are tailor-made for specific prediction tasks. Moreover, their relative accuracy is highly sensitive to the dataset at

  20. Building a multilevel modeling network for lipid processing systems

    DEFF Research Database (Denmark)

    Mustaffa, Azizul Azri; Díaz Tovar, Carlos Axel; Hukkerikar, Amol

    2011-01-01

    ). The applicability of this methodology is highlighted in each level of modeling through the analysis of a lipid process that has significant relevance in the edible oil and biodiesel industries since it determines the quality of the final oil product, the physical refining process of oils and fats....

  1. Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers

    International Nuclear Information System (INIS)

    Mikulandrić, Robert; Lončar, Dražen; Böhning, Dorith; Böhme, Rene; Beckmann, Michael

    2014-01-01

    Highlights: • 2 Different equilibrium models are developed and their performance is analysed. • Neural network prediction models for 2 different fixed bed gasifier types are developed. • The influence of different input parameters on neural network model performance is analysed. • Methodology for neural network model development for different gasifier types is described. • Neural network models are verified for various operating conditions based on measured data. - Abstract: The number of the small and middle-scale biomass gasification combined heat and power plants as well as syngas production plants has been significantly increased in the last decade mostly due to extensive incentives. However, existing issues regarding syngas quality, process efficiency, emissions and environmental standards are preventing biomass gasification technology to become more economically viable. To encounter these issues, special attention is given to the development of mathematical models which can be used for a process analysis or plant control purposes. The presented paper analyses possibilities of neural networks to predict process parameters with high speed and accuracy. After a related literature review and measurement data analysis, different modelling approaches for the process parameter prediction that can be used for an on-line process control were developed and their performance were analysed. Neural network models showed good capability to predict biomass gasification process parameters with reasonable accuracy and speed. Measurement data for the model development, verification and performance analysis were derived from biomass gasification plant operated by Technical University Dresden

  2. Capsule endoscopy in neoplastic diseases

    Science.gov (United States)

    Pennazio, Marco; Rondonotti, Emanuele; de Franchis, Roberto

    2008-01-01

    Until recently, diagnosis and management of small-bowel tumors were delayed by the difficulty of access to the small bowel and the poor diagnostic capabilities of the available diagnostic techniques. An array of new methods has recently been developed, increasing the possibility of detecting these tumors at an earlier stage. Capsule endoscopy (CE) appears to be an ideal tool to recognize the presence of neoplastic lesions along this organ, since it is non-invasive and enables the entire small bowel to be visualized. High-quality images of the small-bowel mucosa may be captured and small and flat lesions recognized, without exposure to radiation. Recent studies on a large population of patients undergoing CE have reported small-bowel tumor frequency only slightly above that reported in previous surgical series (range, 1.6%-2.4%) and have also confirmed that the main clinical indication to CE in patients with small-bowel tumors is obscure gastrointestinal (GI) bleeding. The majority of tumors identified by CE are malignant; many were unsuspected and not found by other methods. However, it remains difficult to identify pathology and tumor type based on the lesion’s endoscopic appearance. Despite its limitations, CE provides crucial information leading in most cases to changes in subsequent patient management. Whether the use of CE in combination with other new diagnostic (MRI or multidetector CT enterography) and therapeutic (Push-and-pull enteroscopy) techniques will lead to earlier diagnosis and treatment of these neoplasms, ultimately resulting in a survival advantage and in cost savings, remains to be determined through carefully-designed studies. PMID:18785274

  3. Rendezvous effects in the diffusion process on bipartite metapopulation networks.

    Science.gov (United States)

    Cao, Lang; Li, Xun; Wang, Bing; Aihara, Kazuyuki

    2011-10-01

    Epidemic outbreaks have been shown to be closely related to the rendezvous-induced transmission of infection, which is caused by casual contact with infected individuals in public gatherings. To investigate rendezvous effects in the spread of infectious diseases, we propose an epidemic model on metapopulation networks bipartite-divided into two sets of location and rendezvous nodes. At a given transition rate γ(kk')(p), each individual transfers from location k to rendezvous p (where rendezvous-induced disease incidence occurs) and thereafter moves to location k'. We find that the eigenstructure of a transition-rate-dependent matrix determines the epidemic threshold condition. Both analytical and numerical results show that rendezvous-induced transmission accelerates the progress of infectious diseases, implying the significance of outbreak control measures including prevention of public gatherings or decentralization of a large-scale rendezvous into downsized ones.

  4. An x-ray-based capsule for colorectal cancer screening incorporating single photon counting technology

    Science.gov (United States)

    Lifshitz, Ronen; Kimchy, Yoav; Gelbard, Nir; Leibushor, Avi; Golan, Oleg; Elgali, Avner; Hassoon, Salah; Kaplan, Max; Smirnov, Michael; Shpigelman, Boaz; Bar-Ilan, Omer; Rubin, Daniel; Ovadia, Alex

    2017-03-01

    An ingestible capsule for colorectal cancer screening, based on ionizing-radiation imaging, has been developed and is in advanced stages of system stabilization and clinical evaluation. The imaging principle allows future patients using this technology to avoid bowel cleansing, and to continue the normal life routine during procedure. The Check-Cap capsule, or C-Scan ® Cap, imaging principle is essentially based on reconstructing scattered radiation, while both radiation source and radiation detectors reside within the capsule. The radiation source is a custom-made radioisotope encased in a small canister, collimated into rotating beams. While traveling along the human colon, irradiation occurs from within the capsule towards the colon wall. Scattering of radiation occurs both inside and outside the colon segment; some of this radiation is scattered back and detected by sensors onboard the capsule. During procedure, the patient receives small amounts of contrast agent as an addition to his/her normal diet. The presence of contrast agent inside the colon dictates the dominant physical processes to become Compton Scattering and X-Ray Fluorescence (XRF), which differ mainly by the energy of scattered photons. The detector readout electronics incorporates low-noise Single Photon Counting channels, allowing separation between the products of these different physical processes. Separating between radiation energies essentially allows estimation of the distance from the capsule to the colon wall, hence structural imaging of the intraluminal surface. This allows imaging of structural protrusions into the colon volume, especially focusing on adenomas that may develop into colorectal cancer.

  5. Array signal processing in the NASA Deep Space Network

    Science.gov (United States)

    Pham, Timothy T.; Jongeling, Andre P.

    2004-01-01

    In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

  6. Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

    2015-08-01

    With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

  7. GPS data processing of networks with mixed single- and dual-frequency receivers for deformation monitoring

    Science.gov (United States)

    Zou, X.; Deng, Z.; Ge, M.; Dick, G.; Jiang, W.; Liu, J.

    2010-07-01

    In order to obtain crustal deformations of higher spatial resolution, existing GPS networks must be densified. This densification can be carried out using single-frequency receivers at moderate costs. However, ionospheric delay handling is required in the data processing. We adapt the Satellite-specific Epoch-differenced Ionospheric Delay model (SEID) for GPS networks with mixed single- and dual-frequency receivers. The SEID model is modified to utilize the observations from the three nearest dual-frequency reference stations in order to avoid contaminations from more remote stations. As data of only three stations are used, an efficient missing data constructing approach with polynomial fitting is implemented to minimize data losses. Data from large scale reference networks extended with single-frequency receivers can now be processed, based on the adapted SEID model. A new data processing scheme is developed in order to make use of existing GPS data processing software packages without any modifications. This processing scheme is evaluated using a sub-network of the German SAPOS network. The results verify that the new scheme provides an efficient way to densify existing GPS networks with single-frequency receivers.

  8. Apresentação do processo de confecção da cápsula do aparelho de amplificação sonora individual intra-aural por meio de digitalização Presenting the process of making the capsule of intra-aural hearing aid through digitization

    Directory of Open Access Journals (Sweden)

    Jerusa Roberta Massola de Oliveira

    2013-02-01

    Full Text Available OBJETIVO: o objetivo deste estudo é apresentar as etapas do processo de confecção da cápsula do aparelho de amplificação sonora individual intra-aural por meio da digitalização. MÉTODO: foram utilizadas otoplásticas e os equipamentos Legato para realizar o escaneamento e Envisiontec para sinterização, ambos disponibilizados pela empresa Phonak. RESULTADOS: os resultados sinalizam para cápsula de aparelho de amplificação sonora individual intra-aurais, plenamente satisfatórias, sendo constatada todas as vantagens documentadas pelo fabricante. CONCLUSÃO: a nova técnica de confecção de cápsula por meio de processo de digitalização demonstrou ser eficaz com alta qualidade e mantendo a impressão fiel da orelha, além de durabilidade significativa.PURPOSE: the objective of this study is to present the steps involved in making the capsule of intra-aural hearing aids through scanning. METHOD: we used the Legato otoplasty equipment in order to perform scanning and Enisiontec for sintering, both provided by the company Phonak. RESULTS: the results point out to capsule-ear hearing aid, as being fully satisfying and with all the benefits documented by the manufacturer. CONCLUSION: a new technique in order to make the capsule through the scanning process has been proven effective and with high quality and keeping the faithful imprint of the ear, in addition to significant durability.

  9. Using an Artificial Neural Network Approach for Supplier Evaluation Process and a Sectoral Application

    Directory of Open Access Journals (Sweden)

    A. Yeşim Yayla

    2011-02-01

    Full Text Available In this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network's independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network's input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network's inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network's outputs. The data set of the network's are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.

  10. Benchmarking uranyl peroxide capsule chemistry in organic media

    Energy Technology Data Exchange (ETDEWEB)

    Neal, Harrison A.; Nyman, May [Department of Chemistry, Oregon State University, Corvallis, OR (United States); Szymanowski, Jennifer; Fein, Jeremy B.; Burns, Peter C. [Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN (United States)

    2017-01-03

    Uranyl peroxide capsules are a recent addition to polyoxometalate (POM) chemistry. Ten years of development has ensued only in water, while transition metal POMs are commonly exploited in aqueous and organic media, controlled by counterions or ligation to render the clusters hydrophilic or hydrophobic. Here, new uranyl POM behavior is recognized in organic media, including (1) stabilization and immobilization of encapsulated hydrophilic countercations, identified by Li nuclear magnetic resonance (NMR) spectroscopy, (2) formation of new cluster species upon phase transfer, (3) extraction of uranyl clusters from different starting materials including simulated spent nuclear fuel, (4) selective phase transfer of one cluster type from a mixture, and (5) phase transfer of clusters from both acidic and alkaline media. The capsule morphology of the uranyl POMs renders accurate characterization by X-ray scattering, including the distinction of geometrically similar clusters. Compositional analysis of the aqueous phase post-extraction provided a quantitative determination of the ion exchange process that enables transfer of the clusters into the organic phase. Preferential partitioning of uranyl POMs into organic media presents new frontiers in metal ion behavior and chemical reactions in the confined space of the cluster capsules in hydrophobic media, as well as the reactivity of clusters at the organic/aqueous interface. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  11. Benchmarking uranyl peroxide capsule chemistry in organic media

    International Nuclear Information System (INIS)

    Neal, Harrison A.; Nyman, May; Szymanowski, Jennifer; Fein, Jeremy B.; Burns, Peter C.

    2017-01-01

    Uranyl peroxide capsules are a recent addition to polyoxometalate (POM) chemistry. Ten years of development has ensued only in water, while transition metal POMs are commonly exploited in aqueous and organic media, controlled by counterions or ligation to render the clusters hydrophilic or hydrophobic. Here, new uranyl POM behavior is recognized in organic media, including (1) stabilization and immobilization of encapsulated hydrophilic countercations, identified by Li nuclear magnetic resonance (NMR) spectroscopy, (2) formation of new cluster species upon phase transfer, (3) extraction of uranyl clusters from different starting materials including simulated spent nuclear fuel, (4) selective phase transfer of one cluster type from a mixture, and (5) phase transfer of clusters from both acidic and alkaline media. The capsule morphology of the uranyl POMs renders accurate characterization by X-ray scattering, including the distinction of geometrically similar clusters. Compositional analysis of the aqueous phase post-extraction provided a quantitative determination of the ion exchange process that enables transfer of the clusters into the organic phase. Preferential partitioning of uranyl POMs into organic media presents new frontiers in metal ion behavior and chemical reactions in the confined space of the cluster capsules in hydrophobic media, as well as the reactivity of clusters at the organic/aqueous interface. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  12. Technology Insight: current status of video capsule endoscopy.

    Science.gov (United States)

    Cave, David R

    2006-03-01

    Video capsule endoscopy (VCE) is the most recent major practical and conceptual development in the field of endoscopy. The video capsule endoscope-a small, pill-sized, passive imaging device-has been demonstrated to be the pre-eminent imaging device for disorders of the small intestine. The initial use for VCE was to detect the origin of obscure gastrointestinal bleeding. Several other indications have now been justified, or are in the process of evaluation. More than 200,000 of these disposable devices have been used worldwide, with an extraordinarily good safety record: indeed, the device has been approved for use in children as young as 10 years of age. In addition, a double-ended capsule has now been approved for the evaluation of mucosal disease in the esophagus. The now-widespread deployment of the device into gastrointestinal practice in the US and many other countries suggests that VCE has achieved mainstream utility. The development of similar competitor devices, and devices whose movement can be controlled, is in progress.

  13. Information processing speed and attention in multiple sclerosis: Reconsidering the Attention Network Test (ANT).

    Science.gov (United States)

    Roth, Alexandra K; Denney, Douglas R; Lynch, Sharon G

    2015-01-01

    The Attention Network Test (ANT) assesses attention in terms of discrepancies between response times to items that differ in the burden they place on some facet of attention. However, simple arithmetic difference scores commonly used to capture these discrepancies fail to provide adequate control for information processing speed, leading to distorted findings when patient and control groups differ markedly in the speed with which they process and respond to stimulus information. This study examined attention networks in patients with multiple sclerosis (MS) using simple difference scores, proportional scores, and residualized scores that control for processing speed through statistical regression. Patients with relapsing-remitting (N = 20) or secondary progressive (N = 20) MS and healthy controls (N = 40) of similar age, education, and gender completed the ANT. Substantial differences between patients and controls were found on all measures of processing speed. Patients exhibited difficulties in the executive control network, but only when difference scores were considered. When deficits in information processing speed were adequately controlled using proportional or residualized score, deficits in the alerting network emerged. The effect sizes for these deficits were notably smaller than those for overall information processing speed and were also limited to patients with secondary progressive MS. Deficits in processing speed are more prominent in MS than those involving attention, and when the former are properly accounted for, differences in the latter are confined to the alerting network.

  14. Managing Distributed Innovation Processes in Virtual Organizations by Applying the Collaborative Network Relationship Analysis

    Science.gov (United States)

    Eschenbächer, Jens; Seifert, Marcus; Thoben, Klaus-Dieter

    Distributed innovation processes are considered as a new option to handle both the complexity and the speed in which new products and services need to be prepared. Indeed most research on innovation processes was focused on multinational companies with an intra-organisational perspective. The phenomena of innovation processes in networks - with an inter-organisational perspective - have been almost neglected. Collaborative networks present a perfect playground for such distributed innovation processes whereas the authors highlight in specific Virtual Organisation because of their dynamic behaviour. Research activities supporting distributed innovation processes in VO are rather new so that little knowledge about the management of such research is available. With the presentation of the collaborative network relationship analysis this gap will be addressed. It will be shown that a qualitative planning of collaboration intensities can support real business cases by proving knowledge and planning data.

  15. Evaluasi Kinerja Organisasi Publik Dengan Menggunakan Pendekatan Balanced Scorecard dan Analytic Network Process

    Directory of Open Access Journals (Sweden)

    Adi Mora Tunggul

    2016-12-01

    Full Text Available Balanced scorecard is a strategic business management method that links performance evaluation to vision and strategies using a multidimensional set of financial and nonfinancial performance metrics. This study examined both quantitative data for the proposed Analytic Network Process method. The purpose of this research is to build a model that combines the Balanced Scorecard approach and Analytical Network Process to assist in the performance evaluation of public organizations tax services. Balanced Scorecard concept is applied to determine the hierarchy of the financial perspective, customer perspective, internal business processes, and learning and growth perspective as well as their respective performance indicators of public organizations and then Analytical Network Process used to tolerate vagueness and ambiguity of information and built an information system that is applied to facilitate the performance evaluation process. The study provides recommendations to the management of public organizations regarding the tax service strategy to improve the performance of public organizations.

  16. D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process

    Directory of Open Access Journals (Sweden)

    Shu-zhi Gao

    2014-01-01

    Full Text Available PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming at the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic fuzzy neural network (D-FNN is adopted to establish the PVC stripping process model based on the actual process operation datum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two single-input-single-output (SISO subsystems (slurry flow to top tower temperature and steam flow to bottom tower temperature. Finally, the PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the effectiveness of the proposed integrated intelligent control method.

  17. Arthroscopic treatment of refractory adhesive capsulitis of the shoulder

    Directory of Open Access Journals (Sweden)

    Marcos Rassi Fernandes

    Full Text Available OBJECTIVE: to evaluate the results of arthroscopic treatment of refractory adhesive capsulitis of the shoulder associated as for improved range of motion after a minimum follow up of six years. METHODS: from August 2002 to December 2004, ten patients with adhesive capsulitis of the shoulder resistant to conservative treatment underwent arthroscopic surgery. One interscalene catheter was placed for postoperative analgesia before the procedure. All were in Phase II, with a minimum follow up of two years. The mean age was 52.9 years (39-66, predominantly female (90%, six on the left shoulder. The time between onset of symptoms and surgical treatment ranged from six to 20 months. Four adhesive capsulitis were found to be primary (40% and six secondary (60%. RESULTS: the preoperative mean of active anterior elevation was 92°, of external rotation was 10.5° of the L5 level internal rotation; the postoperative ones were 149°, 40° and T12 level, respectively. Therefore, the average gain was 57° for the anterior elevation, 29.5° for external rotation in six spinous processes. There was a significant difference in movements' gains between the pre and post-operative periods (p<0.001. By the Constant Score (range of motion, there was an increase of 13.8 (average pre to 32 points (average post. CONCLUSION: the arthroscopic treatment proved effective in refractory adhesive capsulitis of the shoulder resistant to conservative treatment, improving the range of joint movements of patients evaluated after a minimum follow up of six years.

  18. Living in the branches: population dynamics and ecological processes in dendritic networks

    Science.gov (United States)

    Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

    2007-01-01

    Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

  19. Urbanisation processes in Slovenia and their effects on urban networks

    Directory of Open Access Journals (Sweden)

    Kaliopa Dimitrovska Andrews

    2000-01-01

    Full Text Available The article presents processes of changes in the structure of settlement systems in Europe and Slovenia. Hypotheses that have to be given adequate respect as starting points in the development of the urban system follow particular levels of discourse, from the European and national, regional level to the local level. Thus directing urbanisation is different on different levels. Two examples of directing urbanisation processes on the local level are presented, for the functional urban region of Ljubljana and the municipality of Domžale. In conclusion ideas about measures and instruments for achieving urban development policies are shown.

  20. Epidemic Processes on Complex Networks : Modelling, Simulation and Algorithms

    NARCIS (Netherlands)

    Van de Bovenkamp, R.

    2015-01-01

    Local interactions on a graph will lead to global dynamic behaviour. In this thesis we focus on two types of dynamic processes on graphs: the Susceptible-Infected-Susceptilbe (SIS) virus spreading model, and gossip style epidemic algorithms. The largest part of this thesis is devoted to the SIS

  1. Affective and executive network processing associated with persuasive antidrug messages.

    Science.gov (United States)

    Ramsay, Ian S; Yzer, Marco C; Luciana, Monica; Vohs, Kathleen D; MacDonald, Angus W

    2013-07-01

    Previous research has highlighted brain regions associated with socioemotional processes in persuasive message encoding, whereas cognitive models of persuasion suggest that executive brain areas may also be important. The current study aimed to identify lateral prefrontal brain areas associated with persuasive message viewing and understand how activity in these executive regions might interact with activity in the amygdala and medial pFC. Seventy adolescents were scanned using fMRI while they watched 10 strongly convincing antidrug public service announcements (PSAs), 10 weakly convincing antidrug PSAs, and 10 advertisements (ads) unrelated to drugs. Antidrug PSAs compared with nondrug ads more strongly elicited arousal-related activity in the amygdala and medial pFC. Within antidrug PSAs, those that were prerated as strongly persuasive versus weakly persuasive showed significant differences in arousal-related activity in executive processing areas of the lateral pFC. In support of the notion that persuasiveness involves both affective and executive processes, functional connectivity analyses showed greater coactivation between the lateral pFC and amygdala during PSAs known to be strongly (vs. weakly) convincing. These findings demonstrate that persuasive messages elicit activation in brain regions responsible for both emotional arousal and executive control and represent a crucial step toward a better understanding of the neural processes responsible for persuasion and subsequent behavior change.

  2. The gamma model : a new neural network for temporal processing

    NARCIS (Netherlands)

    Vries, de B.

    1992-01-01

    In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.

  3. Development of Multiple Capsule Robots in Pipe

    Directory of Open Access Journals (Sweden)

    Shuxiang Guo

    2018-05-01

    Full Text Available Swallowable capsule robots which travel in body cavities to implement drug delivery, minimally invasive surgery, and diagnosis have provided great potential for medical applications. However, the space constraints of the internal environment and the size limitations of the robots are great challenges to practical application. To address the fundamental challenges of narrow body cavities, a different-frequency driven approach for multiple capsule robots with screw structure manipulated by external electromagnetic field is proposed in this paper. The multiple capsule robots are composed of driven permanent magnets, joint permanent magnets, and a screw body. The screw body generates a propulsive force in a fluidic environment. Moreover, robots can form new constructions via mutual docking and release. To provide manipulation guidelines for active locomotion, a dynamic model of axial propulsion and circumferential torque is established. The multiple start and step-out frequencies for multiple robots are defined theoretically. Moreover, the different-frequency driven approach based on geometrical parameters of screw structure and the overlap angles of magnetic polarities is proposed to drive multiple robots in an identical electromagnetic field. Finally, two capsule robots were prototyped and experiments in a narrow pipe were conducted to verify the different motions such as docking, release, and cooperative locomotion. The experimental results demonstrated the validity of the driven approach for multiple capsule robots in narrow body cavities.

  4. Scaling effects in spiral capsule robots.

    Science.gov (United States)

    Liang, Liang; Hu, Rong; Chen, Bai; Tang, Yong; Xu, Yan

    2017-04-01

    Spiral capsule robots can be applied to human gastrointestinal tracts and blood vessels. Because of significant variations in the sizes of the inner diameters of the intestines as well as blood vessels, this research has been unable to meet the requirements for medical applications. By applying the fluid dynamic equations, using the computational fluid dynamics method, to a robot axial length ranging from 10 -5 to 10 -2  m, the operational performance indicators (axial driving force, load torque, and maximum fluid pressure on the pipe wall) of the spiral capsule robot and the fluid turbulent intensity around the robot spiral surfaces was numerically calculated in a straight rigid pipe filled with fluid. The reasonableness and validity of the calculation method adopted in this study were verified by the consistency of the calculated values by the computational fluid dynamics method and the experimental values from a relevant literature. The results show that the greater the fluid turbulent intensity, the greater the impact of the fluid turbulence on the driving performance of the spiral capsule robot and the higher the energy consumption of the robot. For the same level of size of the robot, the axial driving force, the load torque, and the maximum fluid pressure on the pipe wall of the outer spiral robot were larger than those of the inner spiral robot. For different requirements of the operating environment, we can choose a certain kind of spiral capsule robot. This study provides a theoretical foundation for spiral capsule robots.

  5. Modeling Aggregation Processes of Lennard-Jones particles Via Stochastic Networks

    Science.gov (United States)

    Forman, Yakir; Cameron, Maria

    2017-07-01

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

  6. Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

    1992-01-01

    This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

  7. Epidemic spreading in annealed directed networks: susceptible-infected-susceptible model and contact process.

    Science.gov (United States)

    Kwon, Sungchul; Kim, Yup

    2013-01-01

    We investigate epidemic spreading in annealed directed scale-free networks with the in-degree (k) distribution P(in)(k)~k(-γ(in)) and the out-degree (ℓ) distribution, P(out)(ℓ)~ℓ(-γ(out)). The correlation of each node on the networks is controlled by the probability r(0≤r≤1) in two different algorithms, the so-called k and ℓ algorithms. For r=1, the k algorithm gives =, whereas the ℓ algorithm gives =. For r=0, = for both algorithms. As the prototype of epidemic spreading, the susceptible-infected-susceptible model and contact process on the networks are analyzed using the heterogeneous mean-field theory and Monte Carlo simulations. The directedness of links and the correlation of the network are found to play important roles in the spreading, so that critical behaviors of both models are distinct from those on undirected scale-free networks.

  8. Interventional microadhesiolysis: A new nonsurgical release technique for adhesive capsulitis of the shoulder

    Directory of Open Access Journals (Sweden)

    Lim Tae-Kyun

    2008-01-01

    Full Text Available Abstract Background A nonsurgical intervention, interventional microadhesiolysis, was developed to release adhesions in joints and soft tissues. This paper introduces the procedure and evaluates the efficacy of the intervention for adhesive capsulitis of the shoulder. Methods Ten patients (five men and five women with primary adhesive capsulitis of the shoulder were treated at a chronic pain management center in Korea. Three specially made needles are used in interventional microadhesiolysis: the Round, Flexed Round, and Ahn's needles. A Round Needle is inserted on the skin over middle of supraspinatus and advanced under the acromion and acromioclavicular joint (subacromial release. A Flexed Round Needle is inserted two-fingers caudal to the inferior border of the scapular spine and advanced over the capsule sliding on the surface of infraspinatus muscle-tendon fascia. The capsule is released while an assistant simultaneously passively abducts the shoulder to full abduction (posteroinferior capsule release. An Ahn's Needle is inserted on the skin over the lesser tubercle and advanced under the coracoid process sliding on the surface of the subscapularis muscle (subcoracoid release. Results After the patients underwent interventional microadhesiolysis, the self-rated pain score or severity declined significantly (p p Conclusion Our findings suggest that interventional microadhesiolysis is effective for managing adhesive capsulitis of the shoulder.

  9. An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

    Science.gov (United States)

    Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

    2017-08-01

    Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

  10. Lipid Processing Technology: Building a Multilevel Modeling Network

    OpenAIRE

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol; Quaglia, Alberto; Sin, Gürkan; Kontogeorgis, Georgios; Sarup, Bent; Gani, Rafiqul

    2011-01-01

    Over the past few decades, the world’s fats and oils production has been growing rapidly, far beyond the need for human nutrition. This overproduction combined with the growing consumer preferences for healthier food products and the interest in bio‐fuels, has led the oleo chemical industry to face in the upcoming years major challenges in terms of design and development of better products and more sustainable processes. Although the oleo chemical industry is mature and based on well establis...

  11. Quantifying structural uncertainty on fault networks using a marked point process within a Bayesian framework

    Science.gov (United States)

    Aydin, Orhun; Caers, Jef Karel

    2017-08-01

    Faults are one of the building-blocks for subsurface modeling studies. Incomplete observations of subsurface fault networks lead to uncertainty pertaining to location, geometry and existence of faults. In practice, gaps in incomplete fault network observations are filled based on tectonic knowledge and interpreter's intuition pertaining to fault relationships. Modeling fault network uncertainty with realistic models that represent tectonic knowledge is still a challenge. Although methods that address specific sources of fault network uncertainty and complexities of fault modeling exists, a unifying framework is still lacking. In this paper, we propose a rigorous approach to quantify fault network uncertainty. Fault pattern and intensity information are expressed by means of a marked point process, marked Strauss point process. Fault network information is constrained to fault surface observations (complete or partial) within a Bayesian framework. A structural prior model is defined to quantitatively express fault patterns, geometries and relationships within the Bayesian framework. Structural relationships between faults, in particular fault abutting relations, are represented with a level-set based approach. A Markov Chain Monte Carlo sampler is used to sample posterior fault network realizations that reflect tectonic knowledge and honor fault observations. We apply the methodology to a field study from Nankai Trough & Kumano Basin. The target for uncertainty quantification is a deep site with attenuated seismic data with only partially visible faults and many faults missing from the survey or interpretation. A structural prior model is built from shallow analog sites that are believed to have undergone similar tectonics compared to the site of study. Fault network uncertainty for the field is quantified with fault network realizations that are conditioned to structural rules, tectonic information and partially observed fault surfaces. We show the proposed

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

    Directory of Open Access Journals (Sweden)

    Chun Meng Tang

    2015-12-01

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

  13. Integrated Business and Engineering Framework for Synthesis and Design of Enterprise-Wide Processing Networks

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2012-01-01

    The synthesis and design of processing networks is a complex and multidisciplinary problem, which involves many strategic and tactical decisions at business (considering financial criteria, market competition, supply chain network, etc) and engineering levels (considering synthesis, design...... and optimisation of production technology, R&D, etc), all of which have a deep impact on the profitability of processing industries. In this study, an integrated business and engineering framework for synthesis and design of processing networks is presented. The framework employs a systematic approach to manage...... the complexity while solving simultaneously both the business and the engineering aspects of problems, allowing at the same time, comparison of a large number of alternatives at their optimal points. The results identify the optimal raw material, the product portfolio and select the process technology...

  14. From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing

    Directory of Open Access Journals (Sweden)

    Juan Andres Laura

    2018-03-01

    Full Text Available In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in the natural language processing tasks of sentiment analysis and automatic text generation. If this is possible, then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in such tasks. In our journey, a fundamental difference between a Data Compression Algorithm and Recurrent Neural Networks has been discovered.

  15. Synthesis and Design of Biorefinery Processing Networks with Uncertainty and Sustainability analysis

    DEFF Research Database (Denmark)

    Cheali, Peam; Gernaey, Krist; Sin, Gürkan

    combinations of processing networks. The optimization of the network is formulated as a mixed integer nonlinear programming type of problem and solved in GAMS. The methodology was applied for designing optimal biorefinery networks considering biochemical routes. Furthermore, the methodology has also been...... for processing renewable feedstocks, with the aim of bridging the gap for fuel, chemical and material production. This project is focusing on biorefinery network design, in particular for early stage design and development studies. Optimal biorefinery design is a challenging problem. It is a multi......-objective decision-making problem not only with respect to technical and economic feasibility but also with respect to environmental impacts, sustainability constraints and limited availability & uncertainties of input data at the early design stage. It is therefore useful to develop a systematic methodology...

  16. Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

    NARCIS (Netherlands)

    Kroese, D.P.; Scheinhardt, W.R.W.; Taylor, P.G.

    2004-01-01

    Quasi-birth-and-death (QBD) processes with infinite “phase spaces" can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase" giving the state of the first queue and the “level" giving the state of the second

  17. Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

    Directory of Open Access Journals (Sweden)

    Golmohammadi Hassan

    2013-01-01

    Full Text Available A quantitative structure-property relationship (QSPR study based on partial least squares (PLS and artificial neural network (ANN was developed for the prediction of ferric iron precipitation in bioleaching process. The leaching temperature, initial pH, oxidation/reduction potential (ORP, ferrous concentration and particle size of ore were used as inputs to the network. The output of the model was ferric iron precipitation. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. After optimization and training of the network according to back-propagation algorithm, a 5-5-1 neural network was generated for prediction of ferric iron precipitation. The root mean square error for the neural network calculated ferric iron precipitation for training, prediction and validation set are 32.860, 40.739 and 35.890, respectively, which are smaller than those obtained by PLS model (180.972, 165.047 and 149.950, respectively. Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ferric iron precipitation in bioleaching process.

  18. The key network communication technology in large radiation image cooperative process system

    International Nuclear Information System (INIS)

    Li Zheng; Kang Kejun; Gao Wenhuan; Wang Jingjin

    1998-01-01

    Large container inspection system (LCIS) based on radiation imaging technology is a powerful tool for the customs to check the contents inside a large container without opening it. An image distributed network system is composed of operation manager station, image acquisition station, environment control station, inspection processing station, check-in station, check-out station, database station by using advanced network technology. Mass data, such as container image data, container general information, manifest scanning data, commands and status, must be on-line transferred between different stations. Advanced network communication technology is presented

  19. Algorithm-structured computer arrays and networks architectures and processes for images, percepts, models, information

    CERN Document Server

    Uhr, Leonard

    1984-01-01

    Computer Science and Applied Mathematics: Algorithm-Structured Computer Arrays and Networks: Architectures and Processes for Images, Percepts, Models, Information examines the parallel-array, pipeline, and other network multi-computers.This book describes and explores arrays and networks, those built, being designed, or proposed. The problems of developing higher-level languages for systems and designing algorithm, program, data flow, and computer structure are also discussed. This text likewise describes several sequences of successively more general attempts to combine the power of arrays wi

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

    Science.gov (United States)

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

    2016-03-01

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

  1. Mapping industrial systems - a supply network perspective on enabling technologies, processes and actors

    OpenAIRE

    Srai, Jagjit Singh

    2016-01-01

    This is the author accepted manuscript. The final version is available from InderScience Publishers via http://dx.doi.org/10.1504/IJMTM.2017.10002927 This paper develops a multi-layered multi-stage mapping approach to explore the characteristics of emerging industry supply networks (EI SNs), and how enabling production technologies and supply chain processes are supported by institutional, industrial and supply network actors. The mapping methodology involves the systematic capture of mate...

  2. Breakout Prediction Based on BP Neural Network in Continuous Casting Process

    Directory of Open Access Journals (Sweden)

    Zhang Ben-guo

    2016-01-01

    Full Text Available An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that verified the feasibility of the model.

  3. The first capsule implosion experiments on Orion

    International Nuclear Information System (INIS)

    Garbett, W J; Horsfield, C J; Gales, S G; Leatherland, A E; Rubery, M S; Coltman, J E; Meadowcroft, A E; Rice, S J; Simons, A J; Woolhead, V E

    2016-01-01

    Direct drive capsule implosions are being developed on the Orion laser at AWE as a platform for ICF and HED physics experiments. The Orion facility combines both long pulse and short-pulse beams, making it well suited for studying the physics of alternative ignition approaches. Orion implosions also provide the opportunity to study aspects of polar direct drive. Limitations on drive symmetry from the relatively small number of laser beams makes predictive modelling of the implosions challenging, resulting in some uncertainty in the expected capsule performance. Initial experiments have been fielded to evaluate baseline capsule performance and inform future design optimization. Highly promising DD fusion neutron yields in excess of 10 9 have been recorded. Results from the experiments are presented alongside radiation-hydrocode modelling. (paper)

  4. Capsule endoscopy—A mechatronics perspective

    Science.gov (United States)

    Lin, Lin; Rasouli, Mahdi; Kencana, Andy Prima; Tan, Su Lim; Wong, Kai Juan; Ho, Khek Yu; Phee, Soo Jay

    2011-03-01

    The recent advances in integrated circuit technology, wireless communication, and sensor technology have opened the door for development of miniature medical devices that can be used for enhanced monitoring and treatment of medical conditions. Wireless capsule endoscopy is one of such medical devices that has gained significant attention during the past few years. It is envisaged that future wireless capsule endoscopies replace traditional endoscopy procedures by providing advanced functionalities such as active locomotion, body fluid/tissue sampling, and drug delivery. Development of energy-efficient miniaturized actuation mechanisms is a key step toward achieving this goal. Here, we review some of the actuators that could be integrated into future wireless capsules and discuss the existing challenges.

  5. Chord length distribution for a compound capsule

    International Nuclear Information System (INIS)

    Pitřík, Pavel

    2017-01-01

    Chord length distribution is a factor important in the calculation of ionisation chamber responses. This article describes Monte Carlo calculations of the chord length distribution for a non-convex compound capsule. A Monte Carlo code was set up for generation of random chords and calculation of their lengths based on the input number of generations and cavity dimensions. The code was written in JavaScript and can be executed in the majority of HTML viewers. The plot of occurrence of cords of different lengths has 3 peaks. It was found that the compound capsule cavity cannot be simply replaced with a spherical cavity of a triangular design. Furthermore, the compound capsule cavity is directionally dependent, which must be taken into account in calculations involving non-isotropic fields of primary particles in the beam, unless equilibrium of the secondary charged particles is attained. (orig.)

  6. Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks.

    Science.gov (United States)

    Vestergaard, Christian L; Génois, Mathieu

    2015-10-01

    Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling.

  7. Status of Utilizing Social Media Networks in the Teaching-Learning Process at Public Jordanian Universities

    Directory of Open Access Journals (Sweden)

    Muneera Abdalkareem Alshdefait

    2018-03-01

    Full Text Available This study aimed at finding out the status of utilizing social media networks in the teaching-learning process at public Jordanian Universities. To achieve the goal of the study, the descriptive developmental method was used and a questionnaire was developed, consisting of (35 statements. The questionnaire was checked for its validity and reliability. Then it was distributed to a sample of (382 male and female students from the undergraduate and graduate levels. The study results showed that the participants gave a low score to the status of utilizing social media networks in the teaching-learning process at public Jordanian universities. The results also showed that there were statistically significant differences between the participants of the study according to the academic rank attributed to the graduate students, and according to gender attributed to male students at the instrument macro level and on all dimensions of the two variables. In light of these results, the study recommended that public universities should utilize modern technology in the educational process, urge and encourage the teaching staff members to use the social media networks in the teaching-learning process and raise the students' awareness about the benefits of using social media networks. Keywords: Social media networks, Teaching-learning process, Public Jordanian Universities

  8. Complex network models reveal correlations among network metrics, exercise intensity and role of body changes in the fatigue process

    Science.gov (United States)

    Pereira, Vanessa Helena; Gama, Maria Carolina Traina; Sousa, Filipe Antônio Barros; Lewis, Theodore Gyle; Gobatto, Claudio Alexandre; Manchado-Gobatto, Fúlvia Barros

    2015-05-01

    The aims of the present study were analyze the fatigue process at distinct intensity efforts and to investigate its occurrence as interactions at distinct body changes during exercise, using complex network models. For this, participants were submitted to four different running intensities until exhaustion, accomplished in a non-motorized treadmill using a tethered system. The intensities were selected according to critical power model. Mechanical (force, peak power, mean power, velocity and work) and physiological related parameters (heart rate, blood lactate, time until peak blood lactate concentration (lactate time), lean mass, anaerobic and aerobic capacities) and IPAQ score were obtained during exercises and it was used to construction of four complex network models. Such models have both, theoretical and mathematical value, and enables us to perceive new insights that go beyond conventional analysis. From these, we ranked the influences of each node at the fatigue process. Our results shows that nodes, links and network metrics are sensibility according to increase of efforts intensities, been the velocity a key factor to exercise maintenance at models/intensities 1 and 2 (higher time efforts) and force and power at models 3 and 4, highlighting mechanical variables in the exhaustion occurrence and even training prescription applications.

  9. Improving the Quality of Service and Security of Military Networks with a Network Tasking Order Process

    Science.gov (United States)

    2010-09-01

    44 TACFIRE TACtical FIRE direction system 51 TACOPDAT TACtical Operational DATa 20 TBMCS Theater Battle Management...the MAAP process is complete, the ATO data is finally compiled into Theater Battle Management Core System ( TBMCS ), united with any inputs to SPINS...table. 3.1.5 Other NTO Process Considerations The Air Force uses Theater Battle Management Core System ( TBMCS ) to assist in planning and executing

  10. Image processing and analysis using neural networks for optometry area

    Science.gov (United States)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  11. Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

    Science.gov (United States)

    Mori, Shinichiro

    2017-08-01

    To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  12. A quantum theoretical approach to information processing in neural networks

    Science.gov (United States)

    Barahona da Fonseca, José; Barahona da Fonseca, Isabel; Suarez Araujo, Carmen Paz; Simões da Fonseca, José

    2000-05-01

    A reinterpretation of experimental data on learning was used to formulate a law on data acquisition similar to the Hamiltonian of a mechanical system. A matrix of costs in decision making specifies values attributable to a barrier that opposed to hypothesis formation about decision making. The interpretation of the encoding costs as frequencies of oscillatory phenomena leads to a quantum paradigm based in the models of photoelectric effect as well as of a particle against a potential barrier. Cognitive processes are envisaged as complex phenomena represented by structures linked by valence bounds. This metaphor is used to find some prerequisites to certain types of conscious experience as well as to find an explanation for some pathological distortions of cognitive operations as they are represented in the context of the isolobal model. Those quantum phenomena are understood as representing an analogue programming for specific special purpose computations. The formation of complex chemical structures within the context of isolobal theory is understood as an analog quantum paradigm for complex cognitive computations.

  13. THE USE OF SOCIAL NETWORKS IN THE PROCESS OF LEARNING ENGLISH AS A SECOND LANGUAGE

    Directory of Open Access Journals (Sweden)

    Halyna I. Sotska

    2018-02-01

    Full Text Available In the recent decade many changes in the process of education took place because of the development of information and communication technologies. Online social groups tend to be used by teachers and students for formal (study and informal (personal communication purposes. An efficient teacher may turn social networks into an effective tool, encouraging students to communicate in the target language. With the help of social networks the teacher can activate students in the process of learning, create situations for better understanding and perceiving the material. The use of such approaches as blended learning, corporative learning and active learning helps make the classes more attractive and effective. Moreover, social networks can help in the development of students’ creativity, provision of feedback and cooperative learning. The article deals with the question of influence of Massive online open courses on effectiveness of the educational process for students who learn English as a second language.

  14. Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

    Science.gov (United States)

    Gros, Claudius

    2007-02-01

    The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

  15. Construction of a narrative network aimed at implementing inclusive processes

    Directory of Open Access Journals (Sweden)

    Francesca Salis

    2017-01-01

    Full Text Available The concept of inclusion in its complex aspects aimed at overcoming barriers to learning and involvement has led this research in university, in the light of special pedagogy and didactics, on the basis of inclusion index parameters, detecting the levels of integrated planning with the territory. The purpose of this study is not limited to disability and to special education needs but goes further than that encompassing isolation and/or exclusions. As far as the university system is concerned, it becomes significant to enquire about the inclusion process, in this case by means of a narrative approach, bearing in mind that organizational and learning models, together with access modes may give rise to social exclusion.Università e territorio: costruzione di una rete narrativa per l’implementazione dei processi inclusiviIl costrutto di inclusione nelle sue complesse sfaccettature mirate al superamento delle barriere all’apprendimento e alla partecipazione, ha guidato il presente lavoro di ricerca in ambito universitario alla luce della pedagogia e didattica speciale, sulla base dei parametri dell’Index for Inclusion, rilevando i livelli di progettazione integrata con il territorio. Il suo raggio di azione non si limita alla disabilità ma abbraccia tutti i bisogni educativi speciali, e l’isolamento, la marginalizzazione e/o le esclusioni che ne derivano. Rispetto al sistema universitario è rilevante interrogarsi sul processo di inclusione, in questo caso sulla base dell’approccio narrativo, preso atto che il modello organizzativo e le modalità di accesso e formative possono essere causa di esclusione formativa e sociale.

  16. Prediction of deformations of steel plate by artificial neural network in forming process with induction heating

    International Nuclear Information System (INIS)

    Nguyen, Truong Thinh; Yang, Young Soo; Bae, Kang Yul; Choi, Sung Nam

    2009-01-01

    To control a heat source easily in the forming process of steel plate with heating, the electro-magnetic induction process has been used as a substitute of the flame heating process. However, only few studies have analyzed the deformation of a workpiece in the induction heating process by using a mathematical model. This is mainly due to the difficulty of modeling the heat flux from the inductor traveling on the conductive plate during the induction process. In this study, the heat flux distribution over a steel plate during the induction process is first analyzed by a numerical method with the assumption that the process is in a quasi-stationary state around the inductor and also that the heat flux itself greatly depends on the temperature of the workpiece. With the heat flux, heat flow and thermo-mechanical analyses on the plate to obtain deformations during the heating process are then performed with a commercial FEM program for 34 combinations of heating parameters. An artificial neural network is proposed to build a simplified relationship between deformations and heating parameters that can be easily utilized to predict deformations of steel plate with a wide range of heating parameters in the heating process. After its architecture is optimized, the artificial neural network is trained with the deformations obtained from the FEM analyses as outputs and the related heating parameters as inputs. The predicted outputs from the neural network are compared with those of the experiments and the numerical results. They are in good agreement

  17. Hybrid digital signal processing and neural networks for automated diagnostics using NDE methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.

    1993-11-01

    The primary purpose of the current research was to develop an integrated approach by combining information compression methods and artificial neural networks for the monitoring of plant components using nondestructive examination data. Specifically, data from eddy current inspection of heat exchanger tubing were utilized to evaluate this technology. The focus of the research was to develop and test various data compression methods (for eddy current data) and the performance of different neural network paradigms for defect classification and defect parameter estimation. Feedforward, fully-connected neural networks, that use the back-propagation algorithm for network training, were implemented for defect classification and defect parameter estimation using a modular network architecture. A large eddy current tube inspection database was acquired from the Metals and Ceramics Division of ORNL. These data were used to study the performance of artificial neural networks for defect type classification and for estimating defect parameters. A PC-based data preprocessing and display program was also developed as part of an expert system for data management and decision making. The results of the analysis showed that for effective (low-error) defect classification and estimation of parameters, it is necessary to identify proper feature vectors using different data representation methods. The integration of data compression and artificial neural networks for information processing was established as an effective technique for automation of diagnostics using nondestructive examination methods

  18. Information processing in the transcriptional regulatory network of yeast: Functional robustness

    Directory of Open Access Journals (Sweden)

    Dehmer Matthias

    2009-03-01

    Full Text Available Abstract Background Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism. Results In this paper we study the functional robustness of the transcriptional regulatory network of S. cerevisiae. We model the information processing in the network as a first order Markov chain and study the influence of single gene perturbations on the global, asymptotic communication among genes. Modification in the communication is measured by an information theoretic measure allowing to predict genes that are 'fragile' with respect to single gene knockouts. Our results demonstrate that the predicted set of fragile genes contains a statistically significant enrichment of so called essential genes that are experimentally found to be necessary to ensure vital yeast. Further, a structural analysis of the transcriptional regulatory network reveals that there are significant differences between fragile genes, hub genes and genes with a high betweenness centrality value. Conclusion Our study does not only demonstrate that a combination of graph theoretical, information theoretical and statistical methods leads to meaningful biological results but also that such methods allow to study information processing in gene networks instead of just their structural properties.

  19. Passive and motivated perception of emotional faces: qualitative and quantitative changes in the face processing network.

    Directory of Open Access Journals (Sweden)

    Laurie R Skelly

    Full Text Available Emotionally expressive faces are processed by a distributed network of interacting sub-cortical and cortical brain regions. The components of this network have been identified and described in large part by the stimulus properties to which they are sensitive, but as face processing research matures interest has broadened to also probe dynamic interactions between these regions and top-down influences such as task demand and context. While some research has tested the robustness of affective face processing by restricting available attentional resources, it is not known whether face network processing can be augmented by increased motivation to attend to affective face stimuli. Short videos of people expressing emotions were presented to healthy participants during functional magnetic resonance imaging. Motivation to attend to the videos was manipulated by providing an incentive for improved recall performance. During the motivated condition, there was greater coherence among nodes of the face processing network, more widespread correlation between signal intensity and performance, and selective signal increases in a task-relevant subset of face processing regions, including the posterior superior temporal sulcus and right amygdala. In addition, an unexpected task-related laterality effect was seen in the amygdala. These findings provide strong evidence that motivation augments co-activity among nodes of the face processing network and the impact of neural activity on performance. These within-subject effects highlight the necessity to consider motivation when interpreting neural function in special populations, and to further explore the effect of task demands on face processing in healthy brains.

  20. Topological data analysis of contagion maps for examining spreading processes on networks.

    Science.gov (United States)

    Taylor, Dane; Klimm, Florian; Harrington, Heather A; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A; Mucha, Peter J

    2015-07-21

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges-for example, due to airline transportation or communication media-allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct 'contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  1. Topological data analysis of contagion maps for examining spreading processes on networks

    Science.gov (United States)

    Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

    2015-07-01

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges--for example, due to airline transportation or communication media--allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct `contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  2. Topological data analysis of contagion maps for examining spreading processes on networks

    KAUST Repository

    Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramá r, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

    2015-01-01

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges - for example, due to airline transportation or communication media - allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct 'contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  3. Topological data analysis of contagion maps for examining spreading processes on networks

    KAUST Repository

    Taylor, Dane

    2015-07-21

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth\\'s surface; however, in modern contagions long-range edges - for example, due to airline transportation or communication media - allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct \\'contagion maps\\' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  4. Modeling the Process of Color Image Recognition Using ART2 Neural Network

    Directory of Open Access Journals (Sweden)

    Todor Petkov

    2015-09-01

    Full Text Available This paper thoroughly describes the use of unsupervised adaptive resonance theory ART2 neural network for the purposes of image color recognition of x-ray images and images taken by nuclear magnetic resonance. In order to train the network, the pixel values of RGB colors are regarded as learning vectors with three values, one for red, one for green and one for blue were used. At the end the trained network was tested by the values of pictures and determines the design, or how to visualize the converted picture. As a result we had the same pictures with colors according to the network. Here we use the generalized net to prepare a model that describes the process of the color image recognition.

  5. Effectiveness evaluation of double-layered satellite network with laser and microwave hybrid links based on fuzzy analytic hierarchy process

    Science.gov (United States)

    Zhang, Wei; Rao, Qiaomeng

    2018-01-01

    In order to solve the problem of high speed, large capacity and limited spectrum resources of satellite communication network, a double-layered satellite network with global seamless coverage based on laser and microwave hybrid links is proposed in this paper. By analyzing the characteristics of the double-layered satellite network with laser and microwave hybrid links, an effectiveness evaluation index system for the network is established. And then, the fuzzy analytic hierarchy process, which combines the analytic hierarchy process and the fuzzy comprehensive evaluation theory, is used to evaluate the effectiveness of the double-layered satellite network with laser and microwave hybrid links. Furthermore, the evaluation result of the proposed hybrid link network is obtained by simulation. The effectiveness evaluation process of the proposed double-layered satellite network with laser and microwave hybrid links can help to optimize the design of hybrid link double-layered satellite network and improve the operating efficiency of the satellite system.

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

    Science.gov (United States)

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

    2018-04-01

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

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

    Science.gov (United States)

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

    2018-05-01

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

  8. Design of Endoscopic Capsule With Multiple Cameras.

    Science.gov (United States)

    Gu, Yingke; Xie, Xiang; Li, Guolin; Sun, Tianjia; Wang, Dan; Yin, Zheng; Zhang, Pengfei; Wang, Zhihua

    2015-08-01

    In order to reduce the miss rate of the wireless capsule endoscopy, in this paper, we propose a new system of the endoscopic capsule with multiple cameras. A master-slave architecture, including an efficient bus architecture and a four level clock management architecture, is applied for the Multiple Cameras Endoscopic Capsule (MCEC). For covering more area of the gastrointestinal tract wall with low power, multiple cameras with a smart image capture strategy, including movement sensitive control and camera selection, are used in the MCEC. To reduce the data transfer bandwidth and power consumption to prolong the MCEC's working life, a low complexity image compressor with PSNR 40.7 dB and compression rate 86% is implemented. A chipset is designed and implemented for the MCEC and a six cameras endoscopic capsule prototype is implemented by using the chipset. With the smart image capture strategy, the coverage rate of the MCEC prototype can achieve 98% and its power consumption is only about 7.1 mW.

  9. Physics of ignition for ICF capsules

    International Nuclear Information System (INIS)

    Lindl, J.D.

    1989-01-01

    The implosion of an ICF capsule must accomplish both compression of the main fuel to several hundred grams per cubic centimeter and heating and compression of the central region of the fuel to ignition. This report discusses the physics of these conditions

  10. Extended School Year. Information Capsule. Volume 0910

    Science.gov (United States)

    Blazer, Christie

    2010-01-01

    Extended school years are being considered by districts around the country as educators search for new ways to raise student achievement. The addition of time to the school calendar is also supported by President Barack Obama, who recently stated that American students do not spend enough time in school. This Information Capsule addresses research…

  11. Isolation of Capsulate Bacteria from Acute Dentoalveolar Abscesses

    OpenAIRE

    Lewis, M. A. O.; Milligan, S. G.; MacFarlane, T. W.; Carmichael, F. A.

    2011-01-01

    The presence of a capsule was determined for 198 bacterial strains (57 facultative anaerobes, 141 strict anaerobes) isobdted from pus samples aspirated from 40 acute dentoalveolar abscesses. A total of 133 (67 per cent) of the isolates (42 facultative anaerobes, 91 strict anaerobes) were found to have a capsule. Possession ofa capsule may in part explain the apparent pathogenicity of the bacterial species encountered in acute dentoalveolar abscess.Keywords - Bacterial capsule; Acute dentoalve...

  12. Automated analysis of information processing, kinetic independence and modular architecture in biochemical networks using MIDIA.

    Science.gov (United States)

    Bowsher, Clive G

    2011-02-15

    Understanding the encoding and propagation of information by biochemical reaction networks and the relationship of such information processing properties to modular network structure is of fundamental importance in the study of cell signalling and regulation. However, a rigorous, automated approach for general biochemical networks has not been available, and high-throughput analysis has therefore been out of reach. Modularization Identification by Dynamic Independence Algorithms (MIDIA) is a user-friendly, extensible R package that performs automated analysis of how information is processed by biochemical networks. An important component is the algorithm's ability to identify exact network decompositions based on both the mass action kinetics and informational properties of the network. These modularizations are visualized using a tree structure from which important dynamic conditional independence properties can be directly read. Only partial stoichiometric information needs to be used as input to MIDIA, and neither simulations nor knowledge of rate parameters are required. When applied to a signalling network, for example, the method identifies the routes and species involved in the sequential propagation of information between its multiple inputs and outputs. These routes correspond to the relevant paths in the tree structure and may be further visualized using the Input-Output Path Matrix tool. MIDIA remains computationally feasible for the largest network reconstructions currently available and is straightforward to use with models written in Systems Biology Markup Language (SBML). The package is distributed under the GNU General Public License and is available, together with a link to browsable Supplementary Material, at http://code.google.com/p/midia. Further information is at www.maths.bris.ac.uk/~macgb/Software.html.

  13. Dynamical analysis of yeast protein interaction network during the sake brewing process.

    Science.gov (United States)

    Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

    2011-12-01

    Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

  14. CÆLIS: software for assimilation, management and processing data of an atmospheric measurement network

    Science.gov (United States)

    Fuertes, David; Toledano, Carlos; González, Ramiro; Berjón, Alberto; Torres, Benjamín; Cachorro, Victoria E.; de Frutos, Ángel M.

    2018-02-01

    Given the importance of the atmospheric aerosol, the number of instruments and measurement networks which focus on its characterization are growing. Many challenges are derived from standardization of protocols, monitoring of the instrument status to evaluate the network data quality and manipulation and distribution of large volume of data (raw and processed). CÆLIS is a software system which aims at simplifying the management of a network, providing tools by monitoring the instruments, processing the data in real time and offering the scientific community a new tool to work with the data. Since 2008 CÆLIS has been successfully applied to the photometer calibration facility managed by the University of Valladolid, Spain, in the framework of Aerosol Robotic Network (AERONET). Thanks to the use of advanced tools, this facility has been able to analyze a growing number of stations and data in real time, which greatly benefits the network management and data quality control. The present work describes the system architecture of CÆLIS and some examples of applications and data processing.

  15. Laser Processed Silver Nanowire Network Transparent Electrodes for Novel Electronic Devices

    Science.gov (United States)

    Spechler, Joshua Allen

    Silver nanowire network transparent conducting layers are poised to make headway into a space previously dominated by transparent conducting oxides due to the promise of a flexible, scaleable, lab-atmosphere processable alternative. However, there are many challenges standing in the way between research scale use and consumer technology scale adaptation of this technology. In this thesis we will explore many, and overcome a few of these challenges. We will address the poor conductivity at the narrow nanowire-nanowire junction points in the network by developing a laser based process to weld nanowires together on a microscopic scale. We address the need for a comparative metric for transparent conductors in general, by taking a device level rather than a component level view of these layers. We also address the mechanical, physical, and thermal limitations to the silver nanowire networks by making composites from materials including a colorless polyimide and titania sol-gel. Additionally, we verify our findings by integrating these processes into devices. Studying a hybrid organic/inorganic heterojunction photovoltaic device we show the benefits of a laser processed electrode. Green phosphorescent organic light emitting diodes fabricated on a solution phase processed silver nanowire based electrode show favorable device metrics compared to a conductive oxide electrode based control. The work in this thesis is intended to push the adoption of silver nanowire networks to further allow new device architectures, and thereby new device applications.

  16. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  17. Production of 131I capsules. Quality control of the different stages from the physician's order to patient's administration

    International Nuclear Information System (INIS)

    Freud, A.

    2003-01-01

    The Radiochemistry Department of Rotem Industries produces 131 I hard gelatin capsules for the treatment and diagnosis of different thyroid disorders. Each capsule is designated for a specified patient according to the physician's decision that is based on the patient's morbid status. GMP (Good Manufacturing Practices) requirements have been implemented throughout the production process resulting in the accreditation by the Israeli Ministry of Health. A computerized system has been developed and is used as a QC tool throughout the process of 131 I capsule production. The request by the physician for capsules of various activities are introduced into the system and the process from production through packaging and external radiation monitoring is computer-controlled. The system prevents the possibility of double orders, out of specification production and enables documentation of data regardless of production date. (author)

  18. Automated processing of measuring information and control processes of eutrophication in water for household purpose, based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    О.М. Безвесільна

    2006-04-01

    Full Text Available  The possibilities of application  informational-computer technologies for automated handling of a measuring information about development of seaweed (evtrofication in household reservoirs are considered. The input data’s for a research of processes evtrofication are videoimages of tests of water, which are used for the definition of geometric characteristics, number and biomass of seaweed. For handling a measuring information the methods of digital handling videoimages and mathematical means of artificial neural networks are offered.

  19. Ingestible capsule for remote controlled release of a substance

    DEFF Research Database (Denmark)

    2014-01-01

    The application relates to an ingestible capsule (102) for delivery of a substance e.g. a pharmaceutical drug, to a human or animal. The ingestible capsule comprises a capsule wall structure (202) forming a substantially sealed reservoir or lumen holding the substance (204). An electrical resonance...

  20. The capsule biosynthesis locus of Haemophilus influenzae show conspicuous similarity to the corresponding locus in Haemophilus sputorum and may have been recruited from this species by horizontal gene transfer

    DEFF Research Database (Denmark)

    Nielsen, Signe Maria; de Gier, Camilla; Dimopoulou, Chrysoula

    2015-01-01

    in export and processing of the capsular material, show high similarity to the corresponding genes in capsulate lineages of the pathogenic species Haemophilus influenzae; indeed, standard bexA and bexB PCRs for detection of capsulated strains of H. influenzae give positive results with strains of H....... sputorum was only distantly related to H. influenzae. In contrast to H. influenzae, the capsule locus in H. sputorum is not associated with transposases or other transposable elements. Our data suggest that the capsule locus of capsulate lineages of H. influenzae may relatively recently have been recruited...

  1. Glomerular parietal epithelial cell activation induces collagen secretion and thickening of Bowman's capsule in diabetes.

    Science.gov (United States)

    Holderied, Alexander; Romoli, Simone; Eberhard, Jonathan; Konrad, Lukas A; Devarapu, Satish K; Marschner, Julian A; Müller, Susanna; Anders, Hans-Joachim

    2015-03-01

    The metabolic and hemodynamic alterations in diabetes activate podocytes to increase extracellular matrix (ECM) production, leading to thickening of the glomerular basement membrane (GBM). We hypothesized that diabetes would activate parietal epithelial cells (PECs) in a similar manner and cause thickening of Bowman's capsules. Periodic acid Schiff staining of human kidney biopsies of 30 patients with diabetic nephropathy (DN) revealed a significantly thicker Bowman's capsule as compared with 20 non-diabetic controls. The average thickness was 4.55±0.21 μm in the group of patients with DN compared with 2.92±0.21 μm in the group of non-diabetic controls (PBowman's capsule showed strong association with CD44-positive PECs. In summary, metabolic alterations in diabetes activate PECs to increase the expression and secretion of Bowman's capsule proteins. This process may contribute to the thickening of the Bowman's capsule, similar to the thickening of the GBM that is driven by activated podocytes. These data may also imply that activated PECs contribute to ECM production once they migrate to the glomerular tuft, a process resulting in glomerular scaring, for example, in diabetic glomerulosclerosis.

  2. Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

    Directory of Open Access Journals (Sweden)

    L. Khaouane

    2013-03-01

    Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

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

    Science.gov (United States)

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

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

  4. Optimization of Conditions for Obtaining Alginate/Olive Oil Capsules for Application in Dairy Industry

    Directory of Open Access Journals (Sweden)

    Poirieux Magalie

    2017-06-01

    Full Text Available Encapsulation is a process of incorporation of bioactive substances in a specific matrix. It results in increasing and/or maintaining of the biological agent concentration in the food matrix or the fermentation system. The encapsulation process is influenced by various factors. The aim of the present work was to investigate the influence of alginate type and concentration, homogenization rate and the oil phase amount in the preparation of capsules rich in olive oil. It has been found that emulsions obtained with medium viscosity alginate were characterized by better stability. To establish the joint influence of the factors was used screening design experiment, the optimization features selected being temperature, centrifugal and microscopic stability. The optimal levels of the factors were established and they we applied for capsule preparation. The obtained capsules showed maximum stability and possibility to be used in dairy product manufacture.

  5. Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

    Directory of Open Access Journals (Sweden)

    Danielle S Bassett

    2010-04-01

    Full Text Available Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.

  6. Analytical Model for the Probability Characteristics of a Crack Penetrating Capsules in Capsule-Based Self-Healing Cementitious Materials

    Directory of Open Access Journals (Sweden)

    Zhong LV

    2017-08-01

    Full Text Available Autonomous crack healing using pre-embedded capsules containing healing agent is becoming a promising approach to restore the strength of damaged structures. In addition to the material properties, the size and volume fraction of capsules influence crack healing in the matrix. Understanding the crack and capsule interaction is critical in the development and design of structures made of capsule-based self-healing materials. Continuing our previous study, in this contribution a more practical rupturing mode of capsules characterizing the rupturing manner of capsules fractured by cracks in cementitious materials is presented, i.e., penetrating mode. With the underlying assumption that a crack penetrating capsules undoubtedly leads to crack healing, geometrical probability theory is employed to develop the quantitative relationship between crack size and capsule size, capsule concentration in capsule-based self-healing virtual cementitious material. Moreover, an analytical expression of probability of a crack penetrating with randomly dispersed capsules is developed in two-dimensional material matrix setup. The influences of the induced rupturing modes of capsules embedded on the self-healing efficiency are analyzed. Much attention is paid to compare the penetrating probability and the hitting probability, in order to assist the designer to make a choice of the optimal rupturing modes of capsules embedded. The accuracy of results of the theoretical model is also compared with Monte-Carlo numerical analysis of crack interacting with capsules. It shows that the developed probability characteristics of a crack interaction with capsules for different rupturing modes is helpful to provide guidelines for designer working with capsule-based self-healing cementitious materials.DOI: http://dx.doi.org/10.5755/j01.ms.23.3.16888

  7. Introduction of a theoretical splashing degree to assess the performance of low-viscosity oils in filling of capsules.

    Science.gov (United States)

    Niederquell, Andreas; Kuentz, Martin

    2011-03-01

    These days an alternative to soft capsules is liquid-filled hard capsules. Their filling technology was investigated earlier with highly viscous formulations, while hardly any academic research focused on low-viscosity systems. Accordingly, this work addressed the filling of such oils that are splashing during the dosing process. It was aimed to first study capsule filling, using middle-chain triglycerides as reference oil, in order to then evaluate the concept of a new theoretical splashing degree for different oils. A laboratory-scale filling machine was used that included capsule sealing. Thus, the liquid encapsulation by microspray technology was employed to seal the dosage form. As a result of the study with reference oil, the filling volume and the temperature were found to be significant for the rate of leaking capsules. The filling volume was also important for weight variability of the capsules. However, most critical for this variability was the diameter of the filling nozzle. We proposed a power law for the coefficient of weight variability as a function of the nozzle diameter and the obtained exponent agreed with the proposed theory. Subsequently, a comparison of different oils revealed that the relative splashing degree shared a correlation with the coefficient of the capsule weight variability (Pearson product moment correlation of r=0.990). The novel theoretical concept was therefore found to be predictive for weight variability of the filled capsules. Finally, guidance was provided for the process development of liquid-filled capsules using low-viscosity oils. © 2011 American Association of Pharmaceutical Scientists

  8. Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    Sloep, P. B. (2009). Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation. In V. Hornung-Prähauser & M. Luckmann (Eds.), Kreativität und Innovationskompetenz im digitalen Netz - Creativity and Innovation Competencies in the Web, Sammlung von

  9. A Process Model of Small Business Owner-Managers' Learning in Peer Networks

    Science.gov (United States)

    Zhang, Jing; Hamilton, Eleanor

    2009-01-01

    Purpose: The purpose of this study is to explore how owner-managers of small businesses can learn in peer networks to improve their management skills. It aims to offer a new way of understanding owner-managers' learning as part of a social process, by highlighting the complex, interactive relationship that exists between the owner-manager, his or…

  10. The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe

    NARCIS (Netherlands)

    Mahdavi, M. (Mahdi); J. Vissers (Jan); S. Elkhuizen (Sylvia); Van Dijk, M. (Mattees); Vanhala, A. (Antero); Karampli, E. (Eleftheria); R. Faubel (Raquel); P. Forte (Paul); Coroian, E. (Elena); J.J. van de Klundert (Joris)

    2018-01-01

    textabstractBackground While health service provisioning for the chronic condition Type 2 Diabetes (T2D) often involves a network of organisations and professionals, most evidence on the relationships between the structures and processes of service provisioning and the outcomes considers single

  11. A System for Acquisition, Processing and Visualization of Image Time Series from Multiple Camera Networks

    Directory of Open Access Journals (Sweden)

    Cemal Melih Tanis

    2018-06-01

    Full Text Available A system for multiple camera networks is proposed for continuous monitoring of ecosystems by processing image time series. The system is built around the Finnish Meteorological Image PROcessing Toolbox (FMIPROT, which includes data acquisition, processing and visualization from multiple camera networks. The toolbox has a user-friendly graphical user interface (GUI for which only minimal computer knowledge and skills are required to use it. Images from camera networks are acquired and handled automatically according to the common communication protocols, e.g., File Transfer Protocol (FTP. Processing features include GUI based selection of the region of interest (ROI, automatic analysis chain, extraction of ROI based indices such as the green fraction index (GF, red fraction index (RF, blue fraction index (BF, green-red vegetation index (GRVI, and green excess (GEI index, as well as a custom index defined by a user-provided mathematical formula. Analysis results are visualized on interactive plots both on the GUI and hypertext markup language (HTML reports. The users can implement their own developed algorithms to extract information from digital image series for any purpose. The toolbox can also be run in non-GUI mode, which allows running series of analyses in servers unattended and scheduled. The system is demonstrated using an environmental camera network in Finland.

  12. Analysis and Control of Epidemics: A survey of spreading processes on complex networks

    OpenAIRE

    Nowzari, Cameron; Preciado, Victor M.; Pappas, George J.

    2015-01-01

    This article reviews and presents various solved and open problems in the development, analysis, and control of epidemic models. We are interested in presenting a relatively concise report for new engineers looking to enter the field of spreading processes on complex networks.

  13. Reduced Connectivity in the Self-Processing Network of Schizophrenia Patients with Poor Insight

    NARCIS (Netherlands)

    Liemburg, Edith J.; van der Meer, Lisette; Swart, Marte; Curcic-Blake, Branislava; Bruggeman, Richard; Knegtering, Henderikus; Aleman, Andre

    2012-01-01

    Lack of insight (unawareness of illness) is a common and clinically relevant feature of schizophrenia. Reduced levels of self-referential processing have been proposed as a mechanism underlying poor insight. The default mode network (DMN) has been implicated as a key node in the circuit for

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

    Science.gov (United States)

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

    2017-03-31

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

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

    Science.gov (United States)

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

    2017-03-01

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

  16. In-Network Processing of an Iceberg Join Query in Wireless Sensor Networks Based on 2-Way Fragment Semijoins

    Science.gov (United States)

    Kang, Hyunchul

    2015-01-01

    We investigate the in-network processing of an iceberg join query in wireless sensor networks (WSNs). An iceberg join is a special type of join where only those joined tuples whose cardinality exceeds a certain threshold (called iceberg threshold) are qualified for the result. Processing such a join involves the value matching for the join predicate as well as the checking of the cardinality constraint for the iceberg threshold. In the previous scheme, the value matching is carried out as the main task for filtering non-joinable tuples while the iceberg threshold is treated as an additional constraint. We take an alternative approach, meeting the cardinality constraint first and matching values next. In this approach, with a logical fragmentation of the join operand relations on the aggregate counts of the joining attribute values, the optimal sequence of 2-way fragment semijoins is generated, where each fragment semijoin employs a Bloom filter as a synopsis of the joining attribute values. This sequence filters non-joinable tuples in an energy-efficient way in WSNs. Through implementation and a set of detailed experiments, we show that our alternative approach considerably outperforms the previous one. PMID:25774710

  17. In-Network Processing of an Iceberg Join Query in Wireless Sensor Networks Based on 2-Way Fragment Semijoins

    Directory of Open Access Journals (Sweden)

    Hyunchul Kang

    2015-03-01

    Full Text Available We investigate the in-network processing of an iceberg join query in wireless sensor networks (WSNs. An iceberg join is a special type of join where only those joined tuples whose cardinality exceeds a certain threshold (called iceberg threshold are qualified for the result. Processing such a join involves the value matching for the join predicate as well as the checking of the cardinality constraint for the iceberg threshold. In the previous scheme, the value matching is carried out as the main task for filtering non-joinable tuples while the iceberg threshold is treated as an additional constraint. We take an alternative approach, meeting the cardinality constraint first and matching values next. In this approach, with a logical fragmentation of the join operand relations on the aggregate counts of the joining attribute values, the optimal sequence of 2-way fragment semijoins is generated, where each fragment semijoin employs a Bloom filter as a synopsis of the joining attribute values. This sequence filters non-joinable tuples in an energy-efficient way in WSNs. Through implementation and a set of detailed experiments, we show that our alternative approach considerably outperforms the previous one.

  18. An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

    Science.gov (United States)

    Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

    2018-01-01

    Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

  19. Dissociable intrinsic functional networks support noun-object and verb-action processing.

    Science.gov (United States)

    Yang, Huichao; Lin, Qixiang; Han, Zaizhu; Li, Hongyu; Song, Luping; Chen, Lingjuan; He, Yong; Bi, Yanchao

    2017-12-01

    The processing mechanism of verbs-actions and nouns-objects is a central topic of language research, with robust evidence for behavioral dissociation. The neural basis for these two major word and/or conceptual classes, however, remains controversial. Two experiments were conducted to study this question from the network perspective. Experiment 1 found that nodes of the same class, obtained through task-evoked brain imaging meta-analyses, were more strongly connected with each other than nodes of different classes during resting-state, forming segregated network modules. Experiment 2 examined the behavioral relevance of these intrinsic networks using data from 88 brain-damaged patients, finding that across patients the relative strength of functional connectivity of the two networks significantly correlated with the noun-object vs. verb-action relative behavioral performances. In summary, we found that verbs-actions and nouns-objects are supported by separable intrinsic functional networks and that the integrity of such networks accounts for the relative noun-object- and verb-action-selective deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

    Directory of Open Access Journals (Sweden)

    B. N. Holben

    2018-01-01

    Full Text Available Over the past 24 years, the AErosol RObotic NETwork (AERONET program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

  1. Improved Seismic Acquisition System and Data Processing for the Italian National Seismic Network

    Science.gov (United States)

    Badiali, L.; Marcocci, C.; Mele, F.; Piscini, A.

    2001-12-01

    A new system for acquiring and processing digital signals has been developed in the last few years at the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system makes extensive use of the internet communication protocol standards such as TCP and UDP which are used as the transport highway inside the Italian network, and possibly in a near future outside, to share or redirect data among processes. The Italian National Seismic Network has been working for about 18 years equipped with vertical short period seismometers and transmitting through analog lines, to the computer center in Rome. We are now concentrating our efforts on speeding the migration towards a fully digital network based on about 150 stations equipped with either broad band or 5 seconds sensors connected to the data center partly through wired digital communication and partly through satellite digital communication. The overall process is layered through intranet and/or internet. Every layer gathers data in a simple format and provides data in a processed format, ready to be distributed towards the next layer. The lowest level acquires seismic data (raw waveforms) coming from the remote stations. It handshakes, checks and sends data in LAN or WAN according to a distribution list where other machines with their programs are waiting for. At the next level there are the picking procedures, or "pickers", on a per instrument basis, looking for phases. A picker spreads phases, again through the LAN or WAN and according to a distribution list, to one or more waiting locating machines tuned to generate a seismic event. The event locating procedure itself, the higher level in this stack, can exchange information with other similar procedures. Such a layered and distributed structure with nearby targets allows other seismic networks to join the processing and data collection of the same ongoing event, creating a virtual network larger than the original one. At present we plan to cooperate with other

  2. Using data- and network science to reveal iterations and phase-transitions in the design process

    DEFF Research Database (Denmark)

    Piccolo, Sebastiano; Jørgensen, Sune Lehmann; Maier, Anja

    2017-01-01

    Understanding the role of iterations is a prevalent topic in both design research and design practice. Furthermore, the increasing amount of data produced and stored by companies leaves traces and enables the application of data science to learn from past design processes. In this article, we...... analyse a documentlog to show the temporal evolution of a real design process of a power plant by using exploratory data analysis and network analysis. We show how the iterative nature of the design process is reflected in archival data and how one might re-construct the design process, involving...

  3. Cross-coherent vector sensor processing for spatially distributed glider networks.

    Science.gov (United States)

    Nichols, Brendan; Sabra, Karim G

    2015-09-01

    Autonomous underwater gliders fitted with vector sensors can be used as a spatially distributed sensor array to passively locate underwater sources. However, to date, the positional accuracy required for robust array processing (especially coherent processing) is not achievable using dead-reckoning while the gliders remain submerged. To obtain such accuracy, the gliders can be temporarily surfaced to allow for global positioning system contact, but the acoustically active sea surface introduces locally additional sensor noise. This letter demonstrates that cross-coherent array processing, which inherently mitigates the effects of local noise, outperforms traditional incoherent processing source localization methods for this spatially distributed vector sensor network.

  4. Imbalance of default mode and regulatory networks during externally focused processing in depression

    Science.gov (United States)

    Belleau, Emily L.; Taubitz, Lauren E.

    2015-01-01

    Attentional control difficulties likely underlie rumination, a core cognitive vulnerability in major depressive disorder (MDD). Abnormalities in the default mode, executive and salience networks are implicated in both rumination and attentional control difficulties in MDD. In the current study, individuals with MDD (n = 16) and healthy controls (n = 16) completed tasks designed to elicit self-focused (ruminative) and externally-focused thinking during fMRI scanning. The MDD group showed greater default mode network connectivity and less executive and salience network connectivity during the external-focus condition. Contrary to our predictions, there were no differences in connectivity between the groups during the self-focus condition. Thus, it appears that when directed to engage in self-referential thinking, both depressed and non-depressed individuals similarly recruit networks supporting this process. In contrast, when instructed to engage in non-self-focused thought, non-depressed individuals show a pattern of network connectivity indicative of minimized self-referential processing, whereas depressed individuals fail to reallocate neural resources in a manner consistent with effective down regulation of self-focused thought. This is consistent with difficulties in regulating self-focused thinking in order to engage in more goal-directed behavior that is seen in individuals with MDD. PMID:25274576

  5. A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing

    Science.gov (United States)

    Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

    2011-01-01

    The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. PMID:22163948

  6. A wireless sensor network for vineyard monitoring that uses image processing.

    Science.gov (United States)

    Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

    2011-01-01

    The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.

  7. Deployment of wireless sensor network in pyrochemical processing of metallic fuels

    International Nuclear Information System (INIS)

    Baghyalakshmi, D.; Shrikrishnan, T.S.; Ebenezer, Jemimah; Madhusoodanan, K.; Satya Murty, S.A.V.; Vannia Perumal, S.; Venkatesh, P.; Prabhakara Reddy, B.

    2016-01-01

    With the advent of wireless sensor networking technology, industries started adapting the wireless monitoring systems in phases to measure and control various process parameters. To test the feasibility for implementing Wireless Sensor Network to measure the potentials of an electrochemical cell and the temperatures of actinide drawdown process at Pyrochemical process studies laboratory, at Chemistry Group, IGCAR, Kalpakkam, experiments have been carried out. An experimental setup with two Wireless Sensor Networking nodes has been deployed inside argon atmosphere glove boxes. The Electrorefining studies on U and U based alloys and the studies on actinide recovery from the electrolyte salt in actinide drawdown process are carried out in the glove box. The WSN measuring system was tested and validated by measuring the potentials of an electrochemical cell and the temperatures of actinide drawdown process. The WSN system is proposed to be installed in the hot cells of the Chemistry Group where irradiated U-Zr fuel is reprocessed. This paper briefs the need for remote measuring in pyrochemical reprocessing and validation of the remote signals by measuring the potentials of an electrochemical cell and the temperatures of the actinide draw down process. (author)

  8. Pharmaceutical 3D printing: Design and qualification of a single step print and fill capsule.

    Science.gov (United States)

    Smith, Derrick M; Kapoor, Yash; Klinzing, Gerard R; Procopio, Adam T

    2018-06-10

    Fused deposition modeling (FDM) 3D printing (3DP) has a potential to change how we envision manufacturing in the pharmaceutical industry. A more common utilization for FDM 3DP is to build upon existing hot melt extrusion (HME) technology where the drug is dispersed in the polymer matrix. However, reliable manufacturing of drug-containing filaments remains a challenge along with the limitation of active ingredients which can sustain the processing risks involved in the HME process. To circumvent this obstacle, a single step FDM 3DP process was developed to manufacture thin-walled drug-free capsules which can be filled with dry or liquid drug product formulations. Drug release from these systems is governed by the combined dissolution of the FDM capsule 'shell' and the dosage form encapsulated in these shells. To prepare the shells, the 3D printer files (extension '.gcode') were modified by creating discrete zones, so-called 'zoning process', with individual print parameters. Capsules printed without the zoning process resulted in macroscopic print defects and holes. X-ray computed tomography, finite element analysis and mechanical testing were used to guide the zoning process and printing parameters in order to manufacture consistent and robust capsule shell geometries. Additionally, dose consistencies of drug containing liquid formulations were investigated in this work. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. A Study on the Manufacturing Properties of Crack Self-Healing Capsules Using Cement Powder for Addition to Cement Composites

    Directory of Open Access Journals (Sweden)

    Yun-Wang Choi

    2017-01-01

    Full Text Available We fabricated crack self-healing capsules using cement powder for mixing into cement composites and evaluated the properties of the capsule manufacturing process in this study. The manufacture of the self-healing capsules is divided into core production processing of granulating cement in powder form and a coating process for creating a wall on the surfaces of the granulated cement particles. The produced capsules contain unhardened cement and can be mixed directly with the cement composite materials because they are protected from moisture by the wall material. Therefore, the untreated cement is present in the form of a capsule within the cement composite, and hydration can be induced by moisture penetrating the crack surface in the event of cracking. In the process of granulating the cement, it is important to obtain a suitable consistency through the kneading agent and to maintain the moisture barrier performance of the wall material. We can utilize the results of this study as a basis for advanced self-healing capsule technology for cement composites.

  10. Network-Guided Key Gene Discovery for a Given Cellular Process

    DEFF Research Database (Denmark)

    He, Feng Q; Ollert, Markus

    2018-01-01

    Identification of key genes for a given physiological or pathological process is an essential but still very challenging task for the entire biomedical research community. Statistics-based approaches, such as genome-wide association study (GWAS)- or quantitative trait locus (QTL)-related analysis...... have already made enormous contributions to identifying key genes associated with a given disease or phenotype, the success of which is however very much dependent on a huge number of samples. Recent advances in network biology, especially network inference directly from genome-scale data...

  11. Low cost fabrication and assembly process for re-usable 3D polydimethylsiloxane (PDMS) microfluidic networks

    CSIR Research Space (South Africa)

    Land, K

    2011-09-01

    Full Text Available and assembly process for re-usable 3D polydimethylsiloxane (PDMS) microfluidic networks Kevin J. Land, Mesuli B. Mbanjwa, Klariska Govindasamy, and Jan G. Korvink Citation: Biomicrofluidics 5, 036502 (2011); doi: 10.1063/1.3641859 View online: http... polydimethylsiloxane (PDMS) microfluidic networks Kevin J. Land,1,2,a) Mesuli B. Mbanjwa,1,3 Klariska Govindasamy,1 and Jan G. Korvink2,4 1Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa 2University of Freiburg, Department...

  12. A wireless capsule system with ASIC for monitoring the physiological signals of the human gastrointestinal tract.

    Science.gov (United States)

    Xu, Fei; Yan, Guozheng; Zhao, Kai; Lu, Li; Gao, Jinyang; Liu, Gang

    2014-12-01

    This paper presents the design of a wireless capsule system for monitoring the physiological signals of the human gastrointestinal (GI) tract. The primary components of the system include a wireless capsule, a portable data recorder, and a workstation. Temperature, pH, and pressure sensors; an RF transceiver; a controlling and processing application specific integrated circuit (ASIC); and batteries were applied in a wireless capsule. Decreasing capsule size, improving sensor precision, and reducing power needs were the primary challenges; these were resolved by employing micro sensors, optimized architecture, and an ASIC design that include power management, clock management, a programmable gain amplifier (PGA), an A/D converter (ADC), and a serial peripheral interface (SPI) communication unit. The ASIC has been fabricated in 0.18- μm CMOS technology with a die area of 5.0 mm × 5.0 mm. The wireless capsule integrating the ASIC controller measures Φ 11 mm × 26 mm. A data recorder and a workstation were developed, and 20 cases of human experiments were conducted in hospitals. Preprocessing in the workstation can significantly improve the quality of the data, and 76 original features were determined by mathematical statistics. Based on the 13 optimal features achieved in the evaluation of the features, the clustering algorithm can identify the patients who lack GI motility with a recognition rate reaching 83.3%.

  13. Simulation-Aided Design of Tubular Polymeric Capsules for Self-Healing Concrete

    Science.gov (United States)

    Šavija, Branko; Feiteira, João; Araújo, Maria; Chatrabhuti, Sutima; Raquez, Jean-Marie; Van Tittelboom, Kim; Gruyaert, Elke; De Belie, Nele; Schlangen, Erik

    2016-01-01

    Polymeric capsules can have an advantage over glass capsules used up to now as proof-of-concept carriers in self-healing concrete. They allow easier processing and afford the possibility to fine tune their mechanical properties. Out of the multiple requirements for capsules used in this context, the capability of rupturing when crossed by a crack in concrete of a typical size is one of the most relevant, as without it no healing agent is released into the crack. This study assessed the fitness of five types of polymeric capsules to fulfill this requirement by using a numerical model to screen the best performing ones and verifying their fitness with experimental methods. Capsules made of a specific type of poly(methyl methacrylate) (PMMA) were considered fit for the intended application, rupturing at average crack sizes of 69 and 128 μm, respectively for a wall thickness of ~0.3 and ~0.7 mm. Thicker walls were considered unfit, as they ruptured for crack sizes much higher than 100 μm. Other types of PMMA used and polylactic acid were equally unfit for the same reason. There was overall good fitting between model output and experimental results and an elongation at break of 1.5% is recommended regarding polymers for this application. PMID:28772370

  14. Simulations of laser imprint for Nova experiments and for ignition capsules. Revision 1

    International Nuclear Information System (INIS)

    Weber, S.V.; Glendinning, S.G.; Kalantar, D.H.; Key, M.H.; Remington, B.A.; Rothenberg, J.L.; Wolfrum, E.; Verdon, C.P.; Knauer, J.P.

    1996-12-01

    In direct drive ICF, nonuniformities in laser illumination seed ripples at the ablation front in a process called ''imprint''. These nonuniformities grow during the capsule implosion and, if initially large enough, can penetrate the capsule shell, impede ignition, or degrade burn. Imprint has been simulated for recent experiments performed on the Nova laser at LLNL examining a variety of beam smoothing conditions. Most used laser intensities similar to the early part of an ignition capsule pulse shape, 1 ≅ 10 13 W/cm 2 . The simulations matched most of the measurements of imprint modulation. The effect of imprint upon National Ignition Facility (NIF) direct drive ignition capsules has also been simulated. Imprint is predicted to give modulation comparable to an intrinsic surface finish of ∼10 nm RMS. Modulation growth was examined using the Haan [Phys. Rev. A 39, 5812 (1989)] model, with linear growth factors as a function of spherical harmonic mode number obtained from an analytic dispersion relation. Ablation front amplitudes are predicted to become substantially nonlinear, so that saturation corrections are large. Direct numerical simulations of two-dimensional multimode growth were also performed. The capsule shell is predicted to remain intact, which gives a basis for believing that ignition can be achieved. 27 refs., 10 figs

  15. Impacts of Implosion Asymmetry And Hot Spot Shape On Ignition Capsules

    Science.gov (United States)

    Cheng, Baolian; Kwan, Thomas J. T.; Wang, Yi-Ming; Yi, S. Austin; Batha, Steve

    2017-10-01

    Implosion symmetry plays a critical role in achieving high areal density and internal energy at stagnation during hot spot formation in ICF capsules. Asymmetry causes hot spot irregularity and stagnation de-synchronization that results in lower temperatures and areal densities of the hot fuel. These degradations significantly affect the alpha heating process in the DT fuel as well as on the thermonuclear performance of the capsules. In this work, we explore the physical factors determining the shape of the hot spot late in the implosion and the effects of shape on Î+/-particle transport. We extend our ignition theory [1-4] to include the hot spot shape and quantify the effects of the implosion asymmetry on both the ignition criterion and capsule performance. We validate our theory with the NIF existing experimental data Our theory shows that the ignition criterion becomes more restrictive with the deformation of the hot spot. Through comparison with the NIF data, we demonstrate that the shape effects on the capsules' performance become more explicit as the self-heating and yield of the capsules increases. The degradation of the thermonuclear burn by the hot spot shape for high yield shots to date can be as high as 20%. Our theory is in good agreement with the NIF data. This work was performed under the auspices of the U.S. Department of Energy by the Los Alamos National Laboratory under Contract No. W-7405-ENG-36.

  16. Controllable fabrication and characterization of biocompatible core-shell particles and hollow capsules as drug carrier

    Science.gov (United States)

    Hao, Lingyun; Gong, Xinglong; Xuan, Shouhu; Zhang, Hong; Gong, Xiuqing; Jiang, Wanquan; Chen, Zuyao

    2006-10-01

    SiO 2@CdSe core-shell particles were fabricated by controllable deposition CdSe nanoparticles on silica colloidal spheres. Step-wise coating process was tracked by the TEM and XRD measurements. In addition, SiO 2@CdSe/polypyrrole(PPy) multi-composite particles were synthesized based on the as-prepared SiO 2@CdSe particles by cationic polymerization. The direct electrochemistry of myoglobin (Mb) could be performed by immobilizing Mb on the surface of SiO 2@CdSe particles. Immobilized with Mb, SiO 2@CdSe/PPy-Mb also displayed good bioelectrochemical activity. It confirmed the good biocompatible property of the materials with protein. CdSe hollow capsules were further obtained as the removal of the cores of SiO 2@CdSe spheres. Hollow and porous character of CdSe sub-meter size capsules made them becoming hopeful candidates as drug carriers. Doxorubicin, a typical an antineoplastic drug, was introduced into the capsules. A good sustained drug release behavior of the loading capsules was discovered via performing a release test in the PBS buffer (pH 7.4) solution at 310 k. Furthermore, SiO 2@CdSe/PPy could be converted to various smart hollow capsules via selectively removal of their relevant components.

  17. Multivoxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

    DEFF Research Database (Denmark)

    Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.

    2013-01-01

    The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection, and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations...... within a multivoxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was used to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while...... human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during...

  18. A Sparse Auto Encoder Deep Process Neural Network Model and its Application

    Directory of Open Access Journals (Sweden)

    Xu Shaohua

    2017-01-01

    Full Text Available Aiming at the problem of time-varying signal pattern classification, a sparse auto-encoder deep process neural network (SAE-DPNN is proposed. The input of SAE-DPNN is time-varying process signal and the output is pattern category. It combines the time-varying signal classification method of process neural network (PNN and the data feature extraction and hierarchical sparse representation mechanism of sparse automatic encoder (SAE. Based on the feedforward PNN model, SAE-DPNN is constructed by stacking the process neurons, SAE network and softmax classifier. It can maintain the time-sequence and structure of the input signal, express and synthesize the process distribution characteristics of multidimensional time-varying signals and their combinations. SAE-DPNN improves the identification of complex features and distinguishes between different types of signals, realizes the direct classification of time-varying signals. In this paper, the feature extraction and representation mechanism of time-varying signal in SAE-DPNN are analyzed, and a specific learning algorithm is given. The experimental results verify the effectiveness of the model and algorithm.

  19. Modeling delay in genetic networks: from delay birth-death processes to delay stochastic differential equations.

    Science.gov (United States)

    Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Bennett, Matthew R; Josić, Krešimir; Ott, William

    2014-05-28

    Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

  20. Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Bennett, Matthew R. [Department of Biochemistry and Cell Biology, Rice University, Houston, Texas 77204, USA and Institute of Biosciences and Bioengineering, Rice University, Houston, Texas 77005 (United States); Josić, Krešimir [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Department of Biology and Biochemistry, University of Houston, Houston, Texas 77204 (United States)

    2014-05-28

    Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

  1. Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

    International Nuclear Information System (INIS)

    Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William; Bennett, Matthew R.; Josić, Krešimir

    2014-01-01

    Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay

  2. Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

    KAUST Repository

    Alsibyani, Hassan M.

    2018-05-15

    Cloud computing usage is increasing and a common concern is the privacy and security of the data and computation. Third party cloud environments are not considered fit for processing private information because the data will be revealed to the cloud provider. However, Trusted Execution Environments (TEEs), such as Intel SGX, provide a way for applications to run privately and securely on untrusted platforms. Nonetheless, using a TEE by itself for stream processing systems is not sufficient since network communication patterns may leak properties of the data under processing. This work addresses leaky topology structures and suggests mitigation techniques for each of these. We create specific metrics to evaluate leaks occurring from the network patterns; the metrics measure information leaked when the stream processing system is running. We consider routing techniques for inter-stage communication in a streaming application to mitigate this data leakage. We consider a dynamic policy to change the mitigation technique depending on how much information is currently leaking. Additionally, we consider techniques to hide irregularities resulting from a filtering stage in a topology. We also consider leakages resulting from applications containing cycles. For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing system.

  3. Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

    Science.gov (United States)

    Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

    2018-06-01

    Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

  4. Radiation research of materials using irradiation capsules

    International Nuclear Information System (INIS)

    Chamrad, B.

    1976-01-01

    The methods are briefly characterized of radiation experiments on the WWR-S research reactor. The irradiation capsule installed in the reactor including the electronic instrumentation is described. Irradiated samples temperature is stabilized by an auxiliary heat source placed in the irradiation space. The electronic control equipment of the system is automated. In irradiation experiments, experimental and operating conditions are recorded by a digital measuring centre with electric typewriter and paper tape data recording and by an analog compensating recorder. The irradiation experiment control system controls irradiated sample temperature, the supply current size and the heating element temperature of the auxiliary stabilizing source, inert and technological pressures of the capsule atmosphere and the thermostat temperature of the thermocouple junctions. (O.K.)

  5. Relationships between music training, speech processing, and word learning: a network perspective.

    Science.gov (United States)

    Elmer, Stefan; Jäncke, Lutz

    2018-03-15

    Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

  6. Stochastic dynamical model of a growing citation network based on a self-exciting point process.

    Science.gov (United States)

    Golosovsky, Michael; Solomon, Sorin

    2012-08-31

    We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40,195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.

  7. Networks of power in digital copyright law and policy political salience, expertise and the legislative process

    CERN Document Server

    Farrand, Benjamin

    2014-01-01

    In this book, Benjamin Farrand employs an interdisciplinary approach that combines legal analysis with political theory to explore the development of copyright law in the EU. Farrand utilises Foucault's concept of Networks of Power and Culpepper's Quiet Politics to assess the adoption and enforcement of copyright law in the EU, including the role of industry representative, cross-border licensing, and judicial approaches to territorial restrictions. Focusing in particular on legislative initiatives concerning copyright, digital music and the internet, Networks of Power in Digital Copyright Law and Policy: Political Salience, Expertise and the Legislative Process demonstrates the connection between copyright law and complex network relationships. This book presents an original socio-political theoretical framework for assessing developments in copyright law that will interest researchers and post-graduate students of law and politics, as well as those more particularly concerned with political theory, EU and c...

  8. Automatic blood detection in capsule endoscopy video

    Czech Academy of Sciences Publication Activity Database

    Novozámský, Adam; Flusser, Jan; Tachecí, I.; Sulík, L.; Bureš, J.; Krejcar, O.

    2016-01-01

    Roč. 21, č. 12 (2016), s. 1-8, č. článku 126007. ISSN 1083-3668 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : Automatic blood detection * capsule endoscopy video Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.530, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/flusser-0466936.pdf

  9. Small bowel endoluminal imaging (capsule and enteroscopy).

    Science.gov (United States)

    Murino, Alberto; Despott, Edward J

    2017-04-01

    Over the last 16 years, the disruptive technologies of small bowel capsule endoscopy and device-assisted enteroscopy have revolutionised endoluminal imaging and minimally invasive therapy of the small bowel. Further technological developments continue to expand their indications and use. This brief review highlights the state-of-the-art in this arena and aims to summarise the current and potential future role of these technologies in clinical practice.

  10. ICF ignition capsule neutron, gamma ray, and high energy x-ray images

    Science.gov (United States)

    Bradley, P. A.; Wilson, D. C.; Swenson, F. J.; Morgan, G. L.

    2003-03-01

    Post-processed total neutron, RIF neutron, gamma-ray, and x-ray images from 2D LASNEX calculations of burning ignition capsules are presented. The capsules have yields ranging from tens of kilojoules (failures) to over 16 MJ (ignition), and their implosion symmetry ranges from prolate (flattest at the hohlraum equator) to oblate (flattest towards the laser entrance hole). The simulated total neutron images emphasize regions of high DT density and temperature; the reaction-in-flight neutrons emphasize regions of high DT density; the gamma rays emphasize regions of high shell density; and the high energy x rays (>10 keV) emphasize regions of high temperature.

  11. Artificial neural network approach to modeling of alcoholic fermentation of thick juice from sugar beet processing

    Directory of Open Access Journals (Sweden)

    Jokić Aleksandar I.

    2012-01-01

    Full Text Available In this paper the bioethanol production in batch culture by free Saccharomyces cerevisiae cells from thick juice as intermediate product of sugar beet processing was examined. The obtained results suggest that it is possible to decrease fermentation time for the cultivation medium based on thick juice with starting sugar content of 5-15 g kg-1. For the fermentation of cultivation medium based on thick juice with starting sugar content of 20 and 25 g kg-1 significant increase in ethanol content was attained during the whole fermentation process, resulting in 12.51 and 10.95 dm3 m-3 ethanol contents after 48 h, respectively. Other goals of this work were to investigate the possibilities for experimental results prediction using artificial neural networks (ANNs and to find its optimal topology. A feed-forward back-propagation artificial neural network was used to test the hypothesis. As input variables fermentation time and starting sugar content were used. Neural networks had one output value, ethanol content, yeast cell number or sugar content. There was one hidden layer and the optimal number of neurons was found to be nine for all selected network outputs. In this study transfer function was tansig and the selected learning rule was Levenberg-Marquardt. Results suggest that artificial neural networks are good prediction tool for selected network outputs. It was found that experimental results are in very good agreement with computed ones. The coefficient of determination (the R-squared was found to be 0.9997, 0.9997 and 0.9999 for ethanol content, yeast cell number and sugar content, respectively.

  12. Capsules with evolving brittleness to resist the preparation of self-healing concrete

    Directory of Open Access Journals (Sweden)

    Gruyaert, E.

    2016-09-01

    Full Text Available Capsules for self-healing concrete have to possess multifunctional properties and it would be an enormous advantage in the valorization process when they could also be mixed in. Therefore, we aimed to develop capsules with evolving brittleness. Capsules with high initial flexibility were prepared by adding a plasticizer to an ethyl cellulose matrix. During hardening of the concrete, the plasticizing agent should leach out to the moist environment yielding more brittle capsules which break upon crack appearance. The tested capsules could easily be mixed in during concrete production. However, incompatibility issues between the capsule wall and the inner polymeric healing agent appeared. Moreover, the capsules became insufficiently brittle and the bond strength to the cementitious matrix was too weak. Consequently, multilayer capsules were tested. These capsules had a high impact resistance to endure concrete mixing and were able to break upon crack formation.Las cápsulas para la auto-reparación del hormigón tienen que poseer propiedades multifuncionales. Una enorme ventaja en el proceso para su valorización se obtendría si aquellas pudieran resistir con éxito el mezclado. Por lo tanto, nos propusimos desarrollar cápsulas cuya fragilidad evoluciona. Cápsulas con una alta flexibilidad inicial se prepararon mediante la adición de un plastificante a una matriz de etil celulosa. Durante el endurecimiento del hormigón, el agente plastificante debe filtrarse hacia el medio ambiente húmedo produciendo cápsulas más frágiles que se rompen con el surgimiento de fisuras. Las cápsulas pudieron ser fácilmente mezcladas durante la producción de hormigón. Sin embargo, aparecieron problemas de incompatibilidad entre la pared de la cápsula y el agente de curación polimérico interior. Por otra parte, las cápsulas se comportaron insuficientemente frágiles y con una baja adherencia hacia la matriz cementicia. En consecuencia, se probaron las c

  13. A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

    Science.gov (United States)

    Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

    2011-01-01

    To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. Collapse of experimental capsules under external pressure

    International Nuclear Information System (INIS)

    Simonen, F.A.; Shippell, R.J. Jr.

    1980-01-01

    Stress analyses and developmental tests of capsules fabricated from thick-walled tubing were performed for an external pressure design condition. In the design procedure no credit was taken for the expected margin in pressure between yielding of the capsule wall and catastrophic collapse or flattening. In tests of AISI-1018 low carbon steel capsules, a significant margin was seen between yield and collapse pressure. However, the experimental yield pressures were significantly below predictions, essentially eliminating the safety margin present in the conservative design approach. The differences between predictions and test results are attributed to deficiencies in the plasticity theories commonly in use for engineering stress analyses. The results of this study show that the von Mises yield condition does not accurately describe the yield behavior of the AISI-1018 steel tubing material for the triaxial stress conditions of interest. Finite element stress analyses successfully predicted the transition between uniform inward plastic deformation and ovalization that leads to catastrophic collapse. After adjustments to correct for the unexpected yield behavior of the tube material, the predicted pressure-deflection trends were found to follow the experimental data

  15. Risk-based design of process systems using discrete-time Bayesian networks

    International Nuclear Information System (INIS)

    Khakzad, Nima; Khan, Faisal; Amyotte, Paul

    2013-01-01

    Temporal Bayesian networks have gained popularity as a robust technique to model dynamic systems in which the components' sequential dependency, as well as their functional dependency, cannot be ignored. In this regard, discrete-time Bayesian networks have been proposed as a viable alternative to solve dynamic fault trees without resort to Markov chains. This approach overcomes the drawbacks of Markov chains such as the state-space explosion and the error-prone conversion procedure from dynamic fault tree. It also benefits from the inherent advantages of Bayesian networks such as probability updating. However, effective mapping of the dynamic gates of dynamic fault trees into Bayesian networks while avoiding the consequent huge multi-dimensional probability tables has always been a matter of concern. In this paper, a new general formalism has been developed to model two important elements of dynamic fault tree, i.e., cold spare gate and sequential enforcing gate, with any arbitrary probability distribution functions. Also, an innovative Neutral Dependency algorithm has been introduced to model dynamic gates such as priority-AND gate, thus reducing the dimension of conditional probability tables by an order of magnitude. The second part of the paper is devoted to the application of discrete-time Bayesian networks in the risk assessment and safety analysis of complex process systems. It has been shown how dynamic techniques can effectively be applied for optimal allocation of safety systems to obtain maximum risk reduction.

  16. Information processing in echo state networks at the edge of chaos.

    Science.gov (United States)

    Boedecker, Joschka; Obst, Oliver; Lizier, Joseph T; Mayer, N Michael; Asada, Minoru

    2012-09-01

    We investigate information processing in randomly connected recurrent neural networks. It has been shown previously that the computational capabilities of these networks are maximized when the recurrent layer is close to the border between a stable and an unstable dynamics regime, the so called edge of chaos. The reasons, however, for this maximized performance are not completely understood. We adopt an information-theoretical framework and are for the first time able to quantify the computational capabilities between elements of these networks directly as they undergo the phase transition to chaos. Specifically, we present evidence that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layer toward the edge of chaos is computationally useful. As a consequence, our study suggests self-organized ways of improving performance in recurrent neural networks, driven by input data. Moreover, the networks we study share important features with biological systems such as feedback connections and online computation on input streams. A key example is the cerebral cortex, which was shown to also operate close to the edge of chaos. Consequently, the behavior of model systems as studied here is likely to shed light on reasons why biological systems are tuned into this specific regime.

  17. The improvement of maintenance service for traction networks equipment on the base of process approach

    Directory of Open Access Journals (Sweden)

    D. V. Mironov

    2014-12-01

    Full Text Available Purpose. The new methods development for improving the maintenance service for equipment of traction networks in order to increase its efficiency and quality. Methodology. In world practice of solving problems related to the quality of products and services is usually achieved by introducing quality management system in to the enterprises. The provisions of quality management system were used for solving the problem. The technologies of process engineering were used for describing the main stages of maintenance service. Findings. The development of high-speed movement and growth of its intensity, the use of electric rolling stock of a new generation require the introduction of new methods diagnostics of equipment technical state and improvement of the existing maintenance system and repair of power supply. Developing a model of business-processes, their optimization with using techniques of process engineering and system management is needed for the transition to the management system based on the process approach. From the standpoint of the process approach and in accordance with the requirements of the quality management system (ISO 9001-2009, the operation of the E (Department of electrification and power supply infrastructure sector is represented as a scheme of business-processes in which the guaranteed supply with electricity of railway and third-party consumers is defined as the main business-process of management. Each of the sub-process of power supply for consumers is described in details. The use methods and main stages of process approach for sample management system reorganization were investigated. The methodology and the application method of PDCA (Plan-Do-Check-Act closed loop to the equipment maintenance system were described. The monitoring process of traction networks maintenance using the process approach was divided into components after investigations. The technical documentation of maintenance service was investigated in

  18. Hot cell examination on the surveillance capsule and HANARO capsule in IMEF

    International Nuclear Information System (INIS)

    Choo, Yong Sun; Oh, Wan Ho; Yoo, Byung Ok; Jung, Yang Hong; Ahn, Sang Bok; Baik, Seung Je; Song, Wung Sup; Hong, Kwon Pyo

    2000-01-01

    For the maintenance of integrity and safety of pressurizer of commercial power plant until its life span, it is required by US NRC 10CFR50 APP. G and H and ASTM E185-94 to periodically monitor irradiation embrittlement by neutron irradiation. In order to accomplished the requirement reactor operator has been carrying out the test by extracting the monitoring capsule embeded in reactor during the period of planned preventive maintenance. In relation to this irradiation samples are being used for prediction of reactor vessel life span and reactor vessel's adjusted reference temperature by irradiation of neutron flux enough to reach to end of life span. And also irradiation capsules with and without instrumentation are used for R and D on nuclear materials. Each capsule contains high radioactivity, therefore, post irradiation examination has to be handled by all means in the hot cell. The facility available for this purpose is Irradiated material examination facility (IMEF) to handle such works as capsule receiving, capsule cut and dismantling, sample classification, various examination, and finally development and improvement of examination equipment and instrumentation. (Hong, J. S.)

  19. Preparation of novel polysulfone capsules containing zirconium phosphate and their properties for Pb{sup 2+} removal from aqueous solution

    Energy Technology Data Exchange (ETDEWEB)

    Ma Xiaojie [College of Chemistry and Chemical Engineering, State Key Laboratory of Applied Organic Chemistry, College of Resources and Environment, Institute of Biochemical Engineering and Environmental Technology, Lanzhou University, Lanzhou 730000 (China); Li Yanfeng, E-mail: liyf@lzu.edu.cn [College of Chemistry and Chemical Engineering, State Key Laboratory of Applied Organic Chemistry, College of Resources and Environment, Institute of Biochemical Engineering and Environmental Technology, Lanzhou University, Lanzhou 730000 (China); Li Xiaoli; Yang Liuqing [College of Chemistry and Chemical Engineering, State Key Laboratory of Applied Organic Chemistry, College of Resources and Environment, Institute of Biochemical Engineering and Environmental Technology, Lanzhou University, Lanzhou 730000 (China); Wang Xueyan [Yantai Professional School of Automobile Engineering, Yantai 265500 (China)

    2011-04-15

    Zirconium phosphate (ZrP) was immobilized by microencapsulation process of polysulfone (PSF) to form the polysulfone capsules containing ZrP (PSF-ZrP capsules) successfully by using phase inversion precipitation technique, and the PSF-ZrP was employed as capsules adsorbents to remove Pb{sup 2+} presented in aqueous solution. The result shows that an encapsulation capacity of 50% (mass ratio, PSF: ZrP = 1:1) should be the optimal proportion of ZrP encapsulated with PSF. The characterization of the macroscopical and microcosmic physical properties of the resulting PSF-ZrP capsules was carried out by the DTA-TG, XRD, BET and SEM. Meanwhile, the adsorption properties of the PSF-ZrP capsules for Pb{sup 2+} were investigated by batch methods. It was found that the adsorption of the PSF-ZrP capsules for Pb{sup 2+} would be pH dependent due to the ion-exchange mechanism, and the uptake of Pb{sup 2+} was slightly influenced with the concentration of coexisting cations (Na{sup +}, K{sup +}) in a low range. Furthermore, the calculated thermodynamics parameters exhibit that the nature of the adsorption process is spontaneous and exothermic. After six times of adsorption-regeneration cycles, no significant loss of adsorption capacity was observed, indicating the good stability of the PSF-ZrP capsules. Consequently, the PSF-ZrP capsules in this work can provide a potential application for treatment process of Pb{sup 2+}-containing wastewater.

  20. Reduced connectivity in the self-processing network of schizophrenia patients with poor insight.

    Directory of Open Access Journals (Sweden)

    Edith J Liemburg

    Full Text Available Lack of insight (unawareness of illness is a common and clinically relevant feature of schizophrenia. Reduced levels of self-referential processing have been proposed as a mechanism underlying poor insight. The default mode network (DMN has been implicated as a key node in the circuit for self-referential processing. We hypothesized that during resting state the DMN network would show decreased connectivity in schizophrenia patients with poor insight compared to patients with good insight. Patients with schizophrenia were recruited from mental health care centers in the north of the Netherlands and categorized in groups having good insight (n= 25 or poor insight (n = 19. All subjects underwent a resting state fMRI scan. A healthy control group (n = 30 was used as a reference. Functional connectivity of the anterior and posterior part of the DMN, identified using Independent Component Analysis, was compared between groups. Patients with poor insight showed lower connectivity of the ACC within the anterior DMN component and precuneus within the posterior DMN component compared to patients with good insight. Connectivity between the anterior and posterior part of the DMN was lower in patients than controls, and qualitatively different between the good and poor insight patient groups. As predicted, subjects with poor insight in psychosis showed decreased connectivity in DMN regions implicated in self-referential processing, although this concerned only part of the network. This finding is compatible with theories implying a role of reduced self-referential processing as a mechanism contributing to poor insight.

  1. Information theory and signal transduction systems: from molecular information processing to network inference.

    Science.gov (United States)

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. ‘Living' theory: a pedagogical framework for process support in networked learning

    Directory of Open Access Journals (Sweden)

    Philipa Levy

    2006-12-01

    Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.

  3. Process Network Approach to Understanding How Forest Ecosystems Adapt to Changes

    Science.gov (United States)

    Kim, J.; Yun, J.; Hong, J.; Kwon, H.; Chun, J.

    2011-12-01

    Sustainability challenges are transforming science and its role in society. Complex systems science has emerged as an inevitable field of education and research, which transcends disciplinary boundaries and focuses on understanding of the dynamics of complex social-ecological systems (SES). SES is a combined system of social and ecological components and drivers that interact and give rise to results, which could not be understood on the basis of sociological or ecological considerations alone. However, both systems may be viewed as a network of processes, and such a network hierarchy may serve as a hinge to bridge social and ecological systems. As a first step toward such effort, we attempted to delineate and interpret such process networks in forest ecosystems, which play a critical role in the cycles of carbon and water from local to global scales. These cycles and their variability, in turn, play an important role in the emergent and self-organizing interactions between forest ecosystems and their environment. Ruddell and Kumar (2009) define a process network as a network of feedback loops and the related time scales, which describe the magnitude and direction of the flow of energy, matter, and information between the different variables in a complex system. Observational evidence, based on micrometeorological eddy covariance measurements, suggests that heterogeneity and disturbances in forest ecosystems in monsoon East Asia may facilitate to build resilience for adaptation to change. Yet, the principles that characterize the role of variability in these interactions remain elusive. In this presentation, we report results from the analysis of multivariate ecohydrologic and biogeochemical time series data obtained from temperate forest ecosystems in East Asia based on information flow statistics.

  4. Using the artificial neural network to control the steam turbine heating process

    International Nuclear Information System (INIS)

    Nowak, Grzegorz; Rusin, Andrzej

    2016-01-01

    Highlights: • Inverse Artificial Neural Network has a potential to control the start-up process of a steam turbine. • Two serial neural networks made it possible to model the rotor stress based of steam parameters. • An ANN with feedback enables transient stress modelling with good accuracy. - Abstract: Due to the significant share of renewable energy sources (RES) – wind farms in particular – in the power sector of many countries, power generation systems become sensitive to variable weather conditions. Under unfavourable changes in weather, ensuring required energy supplies involves hasty start-ups of conventional steam power units whose operation should be characterized by higher and higher flexibility. Controlling the process of power engineering machinery operation requires fast predictive models that will make it possible to analyse many parallel scenarios and select the most favourable one. This approach is employed by the algorithm for the inverse neural network control presented in this paper. Based on the current thermal state of the turbine casing, the algorithm controls the steam temperature at the turbine inlet to keep both the start-up rate and the safety of the machine at the allowable level. The method used herein is based on two artificial neural networks (ANN) working in series.

  5. The relationship between context, structure, and processes with outcomes of 6 regional diabetes networks in Europe.

    Science.gov (United States)

    Mahdavi, Mahdi; Vissers, Jan; Elkhuizen, Sylvia; van Dijk, Mattees; Vanhala, Antero; Karampli, Eleftheria; Faubel, Raquel; Forte, Paul; Coroian, Elena; van de Klundert, Joris

    2018-01-01

    While health service provisioning for the chronic condition Type 2 Diabetes (T2D) often involves a network of organisations and professionals, most evidence on the relationships between the structures and processes of service provisioning and the outcomes considers single organisations or solo practitioners. Extending Donabedian's Structure-Process-Outcome (SPO) model, we investigate how differences in quality of life, effective coverage of diabetes, and service satisfaction are associated with differences in the structures, processes, and context of T2D services in six regions in Finland, Germany, Greece, Netherlands, Spain, and UK. Data collection consisted of: a) systematic modelling of provider network's structures and processes, and b) a cross-sectional survey of patient reported outcomes and other information. The survey resulted in data from 1459 T2D patients, during 2011-2012. Stepwise linear regression models were used to identify how independent cumulative proportion of variance in quality of life and service satisfaction are related to differences in context, structure and process. The selected context, structure and process variables are based on Donabedian's SPO model, a service quality research instrument (SERVQUAL), and previous organization and professional level evidence. Additional analysis deepens the possible bidirectional relation between outcomes and processes. The regression models explain 44% of variance in service satisfaction, mostly by structure and process variables (such as human resource use and the SERVQUAL dimensions). The models explained 23% of variance in quality of life between the networks, much of which is related to contextual variables. Our results suggest that effectiveness of A1c control is negatively correlated with process variables such as total hours of care provided per year and cost of services per year. While the selected structure and process variables explain much of the variance in service satisfaction, this is

  6. Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

    Science.gov (United States)

    Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

    2018-05-01

    The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

  7. Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

    Science.gov (United States)

    Raskovic, Dejan

    Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

  8. Effects of food on a gastrically degraded drug: azithromycin fast-dissolving gelatin capsules and HPMC capsules.

    Science.gov (United States)

    Curatolo, William; Liu, Ping; Johnson, Barbara A; Hausberger, Angela; Quan, Ernest; Vendola, Thomas; Vatsaraj, Neha; Foulds, George; Vincent, John; Chandra, Richa

    2011-07-01

    Commercial azithromycin gelatin capsules (Zithromax®) are known to be bioequivalent to commercial azithromycin tablets (Zithromax®) when dosed in the fasted state. These capsules exhibit a reduced bioavailability when dosed in the fed state, while tablets do not. This gelatin capsule negative food effect was previously proposed to be due to slow and/or delayed capsule disintegration in the fed stomach, resulting in extended exposure of the drug to gastric acid, leading to degradation to des-cladinose-azithromycin (DCA). Azithromycin gelatin capsules were formulated with "superdisintegrants" to provide fast-dissolving capsules, and HPMC capsule shells were substituted for gelatin capsule shells, in an effort to eliminate the food effect. Healthy volunteers were dosed with these dosage forms under fasted and fed conditions; pharmacokinetics were evaluated. DCA pharmacokinetics were also evaluated for the HPMC capsule subjects. In vitro disintegration of azithromycin HPMC capsules in media containing food was evaluated and compared with commercial tablets and commercial gelatin capsules. When the two fast-dissolving capsule formulations were dosed to fed subjects, the azithromycin AUC was 38.9% and 52.1% lower than after fasted-state dosing. When HPMC capsules were dosed to fed subjects, the azithromycin AUC was 65.5% lower than after fasted-state dosing. For HPMC capsules, the absolute fasting-state to fed-state decrease in azithromycin AUC (on a molar basis) was similar to the increase in DCA AUC. In vitro capsule disintegration studies revealed extended disintegration times for commercial azithromycin gelatin capsules and HPMC capsules in media containing the liquid foods milk and Ensure®. Interaction of azithromycin gelatin and HPMC capsules with food results in slowed disintegration in vitro and decreased bioavailability in vivo. Concurrent measurement of serum azithromycin and the acid-degradation product DCA demonstrates that the loss of azithromycin

  9. Thermal characteristic test for saturated temperature type capsule

    International Nuclear Information System (INIS)

    Niimi, Motoji; Someya, Hiroyuki; Kobayashi, Toshiki; Ohuchi, Mitsuo; Harayama, Yasuo

    1989-08-01

    The Japan Material Testing Reactor Project is developing a new type capsule so-called 'Saturated Temperature Capsule', as a part of irradiation technique improvement program. This type capsule, in which the water is supplied and boiled, bases on the conception of keeping the coolant at the saturated temperature and facilitating the temperature setting of specimens heated by gamma-ray in reactor. However, out-pile test was planned, because there were few usable data for design and operation of the capsule into which the coolant was injected. A out-pile apparatus, simulated the capsule with electric heaters, was fabricated and experiments were carried out, to obtain data concerning design and operation for the capsule into which the water was injected. As a structure of simulated capsule, a type of downward coolant supply was adopted. The downward coolant tube type injectes the water in the bottom of capsule by tube through the upper flange. Major objects of experiences were to grasp thermal features under operation and to provide performances of capsule control equipment. Experimental results proved that the temperature of water within the capsule was easily varied by controlling supply water flow rate, and that the control equipment was operated stably and safety. (author)

  10. Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

  11. Node-making process in network meta-analysis of nonpharmacological treatment are poorly reported.

    Science.gov (United States)

    James, Arthur; Yavchitz, Amélie; Ravaud, Philippe; Boutron, Isabelle

    2018-05-01

    To identify methods to support the node-making process in network meta-analyses (NMAs) of nonpharmacological treatments. We proceeded in two stages. First, we conducted a literature review of guidelines and methodological articles about NMAs to identify methods proposed to lump interventions into nodes. Second, we conducted a systematic review of NMAs of nonpharmacological treatments to extract methods used by authors to support their node-making process. MEDLINE and Google Scholar were searched to identify articles assessing NMA guidelines or methodology intended for NMA authors. MEDLINE, CENTRAL, and EMBASE were searched to identify reports of NMAs including at least one nonpharmacological treatment. Both searches involved articles available from database inception to March 2016. From the methodological review, we identified and extracted methods proposed to lump interventions into nodes. From the systematic review, the reporting of the network was assessed as long as the method described supported the node-making process. Among the 116 articles retrieved in the literature review, 12 (10%) discussed the concept of lumping or splitting interventions in NMAs. No consensual method was identified during the methodological review, and expert consensus was the only method proposed to support the node-making process. Among 5187 references for the systematic review, we included 110 reports of NMAs published between 2007 and 2016. The nodes were described in the introduction section of 88 reports (80%), which suggested that the node content might have been a priori decided before the systematic review. Nine reports (8.1%) described a specific process or justification to build nodes for the network. Two methods were identified: (1) fit a previously published classification and (2) expert consensus. Despite the importance of NMA in the delivery of evidence when several interventions are available for a single indication, recommendations on the reporting of the node

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

    Science.gov (United States)

    Adelina, W.; Kusumastuti, R. D.

    2017-01-01

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

  13. The improving of the heat networks operating process under the conditions of the energy efficiency providing

    Directory of Open Access Journals (Sweden)

    Blinova Tatiana

    2016-01-01

    Full Text Available Among the priorities it is important to highlight the modernization and improvement of energy efficiency of housing and communal services, as well as the transition to the principle of using the most efficient technologies used in reproduction (construction, creation of objects of municipal infrastructure and housing modernization. The main hypothesis of this study lies in the fact that in modern conditions the realization of the most important priorities of the state policy in the sphere of housing and communal services, is possible in the conditions of use of the most effective control technologies for the reproduction of thermal networks. It is possible to raise the level of information security Heat Distribution Company, and other market participants by improving business processes through the development of organizational and economic mechanism in the conditions of complex monitoring of heat network operation processes

  14. Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

    Science.gov (United States)

    Navarro, Robert

    2006-01-01

    The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

  15. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  16. Determination of Optimal Opening Scheme for Electromagnetic Loop Networks Based on Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Yang Li

    2016-01-01

    Full Text Available Studying optimization and decision for opening electromagnetic loop networks plays an important role in planning and operation of power grids. First, the basic principle of fuzzy analytic hierarchy process (FAHP is introduced, and then an improved FAHP-based scheme evaluation method is proposed for decoupling electromagnetic loop networks based on a set of indicators reflecting the performance of the candidate schemes. The proposed method combines the advantages of analytic hierarchy process (AHP and fuzzy comprehensive evaluation. On the one hand, AHP effectively combines qualitative and quantitative analysis to ensure the rationality of the evaluation model; on the other hand, the judgment matrix and qualitative indicators are expressed with trapezoidal fuzzy numbers to make decision-making more realistic. The effectiveness of the proposed method is validated by the application results on the real power system of Liaoning province of China.

  17. Mastering the political Process of Building Innovation Networks - A Case from the Danish Construction Industry

    DEFF Research Database (Denmark)

    Stissing Jensen, Jens; Koch, Christian; Thomassen, Mikkel

    2008-01-01

    Drawing on network of innovation and organizational politics perspectives this paper analyzes the role of an innovation broker organization in developing and supporting an inter-organizational innovation process in the Danish construction industry. The aim is to implement an ICT-based product...... configuration tool to support the production, sale, and installation of balconies. It is suggested that the innovation broker was successful in stabilizing the innovation process by supplying minimal structures which provided a template which facilitated a combination of individual flexibility and overall...... the network. The innovation thus grew strong enough to replace existing practices and identities and to embed new ones into new organizational structures and a new business-concept...

  18. Administrative professional's role in the processing, retrieval, dissemination and repackaging of information in the networked enterprise

    OpenAIRE

    2008-01-01

    The purpose of this research was to establish the administrative professional's role in the processing, retrieval, dissemination and repackaging of digital information in the networked enterprise, and to determine how the administrative professional can add value to the organisation and enhance its competitive position in industry. The digital economy has changed business practices to such an extent that research of the digital office environment and the administrative professional’s role in ...

  19. ANALYTIC NETWORK PROCESS AND BALANCED SCORECARD APPLIED TO THE PERFORMANCE EVALUATION OF PUBLIC HEALTH SYSTEMS

    Directory of Open Access Journals (Sweden)

    Marco Aurélio Reis dos Santos

    2015-08-01

    Full Text Available The performance of public health systems is an issue of great concern. After all, to assure people's quality of life, public health systems need different kinds of resources. Balanced Scorecard provides a multi-dimensional evaluation framework. This paper presents the application of the Analytic Network Process and Balanced Scorecard in the performance evaluation of a public health system in a typical medium-sized Southeastern town in Brazil.

  20. Status of Utilizing Social Media Networks in the Teaching-Learning Process at Public Jordanian Universities

    OpenAIRE

    Muneera Abdalkareem Alshdefait; Mohammad . S. Alzboon

    2018-01-01

    This study aimed at finding out the status of utilizing social media networks in the teaching-learning process at public Jordanian Universities. To achieve the goal of the study, the descriptive developmental method was used and a questionnaire was developed, consisting of (35) statements. The questionnaire was checked for its validity and reliability. Then it was distributed to a sample of (382) male and female students from the undergraduate and graduate levels. The study results showed tha...

  1. Physical removal of metallic carbon nanotubes from nanotube network devices using a thermal and fluidic process

    International Nuclear Information System (INIS)

    Ford, Alexandra C; Shaughnessy, Michael; Wong, Bryan M; Kane, Alexander A; Krafcik, Karen L; Léonard, François; Kuznetsov, Oleksandr V; Billups, W Edward; Hauge, Robert H

    2013-01-01

    Electronic and optoelectronic devices based on thin films of carbon nanotubes are currently limited by the presence of metallic nanotubes. Here we present a novel approach based on nanotube alkyl functionalization to physically remove the metallic nanotubes from such network devices. The process relies on preferential thermal desorption of the alkyls from the semiconducting nanotubes and the subsequent dissolution and selective removal of the metallic nanotubes in chloroform. The approach is versatile and is applied to devices post-fabrication. (paper)

  2. Quality evaluation of probiotic capsule prepared from alginate, carrageenan and tofu waste flour based on bacterial activity and organoleptic test

    Science.gov (United States)

    Muhardina, V.; Ermaya, D.; Aisyah, Y.; Haryani, S.

    2018-02-01

    Probiotic capsule is an innovation in functional food sector. It is used to preserve the living cells of probiotic bacteria during processing and storage. In this research, the improvement of probiotic viability is studied by using two kinds of encapsulating biomaterials and different concentration of tofu waste flour. Extrusion is selected method for encapsulation process. The purpose of this study is to examine the quality of probiotic capsule by evaluating the lactic acid bacteria performance and its physical characteristic. The article provides the data of probiotic bacteria activity related to their living cells present in capsule, activity in fermentation media compare to uncapsulated bacteria, and panelists’ preferences of capsule’s physical properties. The data is analyzed statistically by using ANOVA. The result shows that variables in this study affect the number of bacteria, their metabolic activity in producing acid during fermentation, and physical appearance of the capsule. Combination of alginate and tofu waste flour allows the multiplication of bacteria to a high number, and forms elastic, yellow and cloudy capsule, while with carrageenan, it causes the growth of a few numbers of bacteria which affects to a moderate pH and produces elastic, creamy and transparent capsule.

  3. Analysis of the packet formation process in packet-switched networks

    Science.gov (United States)

    Meditch, J. S.

    Two new queueing system models for the packet formation process in packet-switched telecommunication networks are developed, and their applications in process stability, performance analysis, and optimization studies are illustrated. The first, an M/M/1 queueing system characterization of the process, is a highly aggregated model which is useful for preliminary studies. The second, a marked extension of an earlier M/G/1 model, permits one to investigate stability, performance characteristics, and design of the packet formation process in terms of the details of processor architecture, and hardware and software implementations with processor structure and as many parameters as desired as variables. The two new models together with the earlier M/G/1 characterization span the spectrum of modeling complexity for the packet formation process from basic to advanced.

  4. Forward and reverse mapping for milling process using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Rashmi L. Malghan

    2018-02-01

    Full Text Available The data set presented is related to the milling process of AA6061-4.5%Cu-5%SiCp composite. The data primarily concentrates on predicting values of some machining responses, such as cutting force, surface finish and power utilization utilizing using forward back propagation neural network based approach, i.e. ANN based on three process parameters, such as spindle speed, feed rate and depth of cut.The comparing reverse model is likewise created to prescribe the ideal settings of processing parameters for accomplishing the desired responses as indicated by the necessities of the end clients. These modelling approaches are very proficient to foresee the benefits of machining responses and also process parameter settings in light of the experimental technique. Keywords: ANN, Forward mapping, Reverse mapping, Milling process

  5. Business Strategy Formulation By Shareholders and Company Management using The Analytical Network Process (ANPBusiness Strategy Formulation by Shareholders and Company Management Using Analytical Network Process (ANP

    Directory of Open Access Journals (Sweden)

    Faizal Faizal

    2016-11-01

    Full Text Available This research aimed to identify the business strategy formulation by the shareholders and the management of the company. Ten companies were selected to be the objects of this research. Those companies were the information technology, telecommunication, printing, mining, construction and chemical companies in Indonesia. The research was conducted by using the Analytical Network Process (ANP and considering the chosen respondents as the decision makers (experts of those companies. The respondents were chosen by using the non-probabilitty sampling method. The result shows that the roles of the company managements are considered m ore influental (0,57143 than the roles of the shareholders (0,28571. From the output of stakeholder’s condition, the best-stratified priority strategies are differentiation (0,600515, cost of leadership (0,230754 and focus (0,168731.

  6. Statistical learning problem of artificial neural network to control roofing process

    Directory of Open Access Journals (Sweden)

    Lapidus Azariy

    2017-01-01

    Full Text Available Now software developed on the basis of artificial neural networks (ANN has been actively implemented in construction companies to support decision-making in organization and management of construction processes. ANN learning is the main stage of its development. A key question for supervised learning is how many number of training examples we need to approximate the true relationship between network inputs and output with the desired accuracy. Also designing of ANN architecture is related to learning problem known as “curse of dimensionality”. This problem is important for the study of construction process management because of the difficulty to get training data from construction sites. In previous studies the authors have designed a 4-layer feedforward ANN with a unit model of 12-5-4-1 to approximate estimation and prediction of roofing process. This paper presented the statistical learning side of created ANN with simple-error-minimization algorithm. The sample size to efficient training and the confidence interval of network outputs defined. In conclusion the authors predicted successful ANN learning in a large construction business company within a short space of time.

  7. Self-processing and the default mode network: Interactions with the mirror neuron system

    Directory of Open Access Journals (Sweden)

    Istvan eMolnar-Szakacs

    2013-09-01

    Full Text Available Recent evidence for the fractionation of the default mode network (DMN into functionally distinguishable subdivisions with unique patterns of connectivity calls for a reconceptualization of the relationship between this network and self-referential processing. Advances in resting-state functional connectivity analyses are beginning to reveal increasingly complex patterns of organization within the key nodes of the DMN - medial prefrontal cortex (MPFC and posterior cingulate cortex (PCC – as well as between these nodes and other brain systems. Here we review recent examinations of the relationships between the DMN and various aspects of self-relevant and social-cognitive processing in light of emerging evidence for heterogeneity within this network. Drawing from a rapidly evolving social cognitive neuroscience literature, we propose that embodied simulation and mentalizing are processes which allow us to gain insight into another's physical and mental state by providing privileged access to our own physical and mental states. Embodiment implies that the same neural systems are engaged for self- and other-understanding through a simulation mechanism, while mentalizing refers to the use of high-level conceptual information to make inferences about the mental states of self and others. These mechanisms work together to provide a coherent representation of the self and by extension, of others. Nodes of the DMN selectively interact with brain systems for embodiment and mentalizing, including the mirror neuron system, to produce appropriate mappings in the service of social cognitive demands.

  8. Motion of an elastic capsule in a square microfluidic channel.

    Science.gov (United States)

    Kuriakose, S; Dimitrakopoulos, P

    2011-07-01

    In the present study we investigate computationally the steady-state motion of an elastic capsule along the centerline of a square microfluidic channel and compare it with that in a cylindrical tube. In particular, we consider a slightly over-inflated elastic capsule made of a strain-hardening membrane with comparable shearing and area-dilatation resistance. Under the conditions studied in this paper (i.e., small, moderate, and large capsules at low and moderate flow rates), the capsule motion in a square channel is similar to and thus governed by the same scaling laws with the capsule motion in a cylindrical tube, even though in the channel the cross section in the upstream portion of large capsules is nonaxisymmetric (i.e., square-like with rounded corners). When the hydrodynamic forces on the membrane increase, the capsule develops a pointed downstream edge and a flattened rear (possibly with a negative curvature) so that the restoring tension forces are increased as also happens with droplets. Membrane tensions increase significantly with the capsule size while the area near the downstream tip is the most probable to rupture when a capsule flows in a microchannel. Because the membrane tensions increase with the interfacial deformation, a suitable Landau-Levich-Derjaguin-Bretherton analysis reveals that the lubrication film thickness h for large capsules depends on both the capillary number Ca and the capsule size a; our computations determine the latter dependence to be (in dimensionless form) h ~ a(-2) for the large capsules studied in this work. For small and moderate capsule sizes a, the capsule velocity Ux and additional pressure drop ΔP+ are governed by the same scaling laws as for high-viscosity droplets. The velocity and additional pressure drop of large thick capsules also follow the dynamics of high-viscosity droplets, and are affected by the lubrication film thickness. The motion of our large thick capsules is characterized by a Ux-U ~ h ~ a(-2

  9. Effect of polysaccharide capsule of the microalgae Staurastrum iversenii var. americanum on diffusion of charged and uncharged molecules, using EPR technique

    International Nuclear Information System (INIS)

    Freire-Nordi, Cristina S.; Nascimento, Otaciro R.; Vieira, Armando A.H.; Nakaie, Clovis R.

    2006-01-01

    The existence of a mucilaginous envelope, sheath or capsule is usual in many desmids, but few data concerning its function are available. Previous studies of the transport function and permeation of molecules through the algae capsules were done using the algae Spondylosium panduriforme and Nephrocytium lunatum, the Electron Paramagnetic Resonance (EPR) technique, and different spin labels. The results suggested that the capsule functions as a selective diffusion medium. In the present work charged and uncharged molecules (spin labels group A) and Staurastrum iversenii var. americanum (Desmids),whose alga presents a great mucilaginous capsule, were used. Charged nitroxide molecules similar to amino acids (spin labels group B) were also used allowing a better understanding of the electrostatic effect in the permeation process across the capsule. The role of the cell capsule in the solute diffusion was evaluated by determining the capsulated and decapsulated cell permeation times. The permeation times for all spin labels tested in the cells lacking capsules were always shorter than those containing this physical barrier. The decay times of spin labels group A observed for S. iversenii were compared to other studied algae. The results regarding the diffusion of charged spin labels group B suggested that the interaction of cell capsule occurs more strongly with negatively charged molecules than with positively charged ones. The results obtained in this work with spin labels group A confirm that the capsule is an essential structure for the cell, and that due to the polar interactions with the spin labels, it plays an important role in the selection of small molecules. Several parameters, mainly those of electrostatic nature, seem to control the permeation across the algal capsules of spin labels group B, showing that structures which are similar to amino acids could diffuse across the interior of the algal cell. (author)

  10. On-the-fly detection of images with gastritis aspects in magnetically guided capsule endoscopy

    Science.gov (United States)

    Mewes, P. W.; Neumann, D.; Juloski, A. L.; Angelopoulou, E.; Hornegger, J.

    2011-03-01

    Capsule Endoscopy (CE) was introduced in 2000 and has since become an established diagnostic procedure for the small bowel, colon and esophagus. For the CE examination the patient swallows the capsule, which then travels through the gastrointestinal tract under the influence of the peristaltic movements. CE is not indicated for stomach examination, as the capsule movements can not be controlled from the outside and the entire surface of the stomach can not be reliably covered. Magnetically-guided capsule endoscopy (MGCE) was introduced in 2010. For the MGCE procedure the stomach is filled with water and the capsule is navigated from the outside using an external magnetic field. During the examination the operator can control the motion of the capsule in order to obtain a sufficient number of stomach-surface images with diagnostic value. The quality of the examination depends on the skill of the operator and his ability to detect aspects of interest in real time. We present a novel computer-assisted diagnostic-procedure (CADP) algorithm for indicating gastritis pathologies in the stomach during the examination. Our algorithm is based on pre-processing methods and feature vectors that are suitably chosen for the challenges of the MGCE imaging (suspended particles, bubbles, lighting). An image is classified using an ada-boost trained classifier. For the classifier training, a number of possible features were investigated. Statistical evaluation was conducted to identify relevant features with discriminative potential. The proposed algorithm was tested on 12 video sequences stemming from 6 volunteers. A mean detection rate of 91.17% was achieved during leave-one out cross-validation.

  11. Design of special purpose database for credit cooperation bank business processing network system

    Science.gov (United States)

    Yu, Yongling; Zong, Sisheng; Shi, Jinfa

    2011-12-01

    With the popularization of e-finance in the city, the construction of e-finance is transfering to the vast rural market, and quickly to develop in depth. Developing the business processing network system suitable for the rural credit cooperative Banks can make business processing conveniently, and have a good application prospect. In this paper, We analyse the necessity of adopting special purpose distributed database in Credit Cooperation Band System, give corresponding distributed database system structure , design the specical purpose database and interface technology . The application in Tongbai Rural Credit Cooperatives has shown that system has better performance and higher efficiency.

  12. Analysis of Artificial Neural Network Backpropagation Using Conjugate Gradient Fletcher Reeves In The Predicting Process

    Science.gov (United States)

    Wanto, Anjar; Zarlis, Muhammad; Sawaluddin; Hartama, Dedy

    2017-12-01

    Backpropagation is a good artificial neural network algorithm used to predict, one of which is to predict the rate of Consumer Price Index (CPI) based on the foodstuff sector. While conjugate gradient fletcher reeves is a suitable optimization method when juxtaposed with backpropagation method, because this method can shorten iteration without reducing the quality of training and testing result. Consumer Price Index (CPI) data that will be predicted to come from the Central Statistics Agency (BPS) Pematangsiantar. The results of this study will be expected to contribute to the government in making policies to improve economic growth. In this study, the data obtained will be processed by conducting training and testing with artificial neural network backpropagation by using parameter learning rate 0,01 and target error minimum that is 0.001-0,09. The training network is built with binary and bipolar sigmoid activation functions. After the results with backpropagation are obtained, it will then be optimized using the conjugate gradient fletcher reeves method by conducting the same training and testing based on 5 predefined network architectures. The result, the method used can increase the speed and accuracy result.

  13. Models of neural networks temporal aspects of coding and information processing in biological systems

    CERN Document Server

    Hemmen, J; Schulten, Klaus

    1994-01-01

    Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregatio...

  14. Application of knowledge-based network processing to automated gas chromatography data interpretation

    International Nuclear Information System (INIS)

    Levis, A.P.; Timpany, R.G.; Klotter, D.A.

    1995-01-01

    A method of translating a two-way table of qualified symptom/cause relationships into a four layer Expert Network for diagnosis of machine or sample preparation failure for Gas Chromatography is presented. This method has proven to successfully capture an expert's ability to predict causes of failure in a Gas Chromatograph based on a small set of symptoms, derived from a chromatogram, in spite of poorly defined category delineations and definitions. In addition, the resulting network possesses the advantages inherent in most neural networks: the ability to function correctly in the presence of missing or uncertain inputs and the ability to improve performance through data-based training procedures. Acquisition of knowledge from the domain experts produced a group of imprecise cause-to-symptom relationships. These are reproduced as parallel pathways composed of Symptom-Filter-Combination-Cause node chains in the network representation. Each symptom signal is passed through a Filter node to determine if the signal should be interpreted as positive or negative evidence and then modified according to the relationship established by the domain experts. The signals from several processed symptoms are then combined in the Combination node(s) for a given cause. The resulting value is passed to the Cause node and the highest valued Cause node is then selected as the most probable cause of failure

  15. Moran model as a dynamical process on networks and its implications for neutral speciation

    Science.gov (United States)

    de Aguiar, Marcus A. M.; Bar-Yam, Yaneer

    2011-03-01

    In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.

  16. Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

    Science.gov (United States)

    Anderson, Brian A

    2017-03-01

    Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  17. Capsule development and utilization for material irradiation tests

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Young Hwan; Kim, B. G.; Joo, K. N. [and others

    2000-05-01

    The development program of advanced nuclear structural and fuel materials includes the in-pile tests using the instrumented capsule at HANARO. The tests were performed in the in-core test holes of CT, IR 1 and 2 and OR 4 and 5 of HANARO. Extensive efforts have also been made to establish design and manufacturing technology for the instrumented capsule and its related system, which should be compatible with the HANARO's characteristics. Since the first instrumented capsule(97M-01K) had been designed and successfully fabricated, five tests were done to support the users and provided the economic benefits to user by generating the essential in-pile information on the performance and structural integrity of materials. This paper describes the present status and future plans of these R and D activities for the development of the instrumented capsule including in-situ material property measurement capsules and nuclear fuel test capsules.

  18. Capsule development and utilization for material irradiation tests

    International Nuclear Information System (INIS)

    Kang, Young Hwan; Kim, B. G.; Joo, K. N.

    2000-05-01

    The development program of advanced nuclear structural and fuel materials includes the in-pile tests using the instrumented capsule at HANARO. The tests were performed in the in-core test holes of CT, IR 1 and 2 and OR 4 and 5 of HANARO. Extensive efforts have also been made to establish design and manufacturing technology for the instrumented capsule and its related system, which should be compatible with the HANARO's characteristics. Since the first instrumented capsule(97M-01K) had been designed and successfully fabricated, five tests were done to support the users and provided the economic benefits to user by generating the essential in-pile information on the performance and structural integrity of materials. This paper describes the present status and future plans of these R and D activities for the development of the instrumented capsule including in-situ material property measurement capsules and nuclear fuel test capsules

  19. Polar tent for reduced perturbation of NIF ignition capsules

    Science.gov (United States)

    Hammel, B. A.; Pickworth, L.; Stadermann, M.; Field, J.; Robey, H.; Scott, H. A.; Smalyuk, V.

    2016-10-01

    In simulations, a tent that contacts the capsule near the poles and departs tangential to the capsule surface greatly reduces the capsule perturbation, and the resulting mass injected into the hot-spot, compared to current capsule support methods. Target fabrication appears feasible with a layered tent (43-nm polyimide + 8-nm C) for increased stiffness. We are planning quantitative measurements of the resulting shell- ρR perturbation near peak implosion velocity (PV) using enhanced self-emission backlighting, achieved by adding 1% Ar to the capsule fill in Symcaps (4He + H). Layered DT implosions are also planned for an integrated test of capsule performance. We will describe the design and simulation predictions. Prepared by LLNL under Contract DE-AC52-07NA27344.

  20. Capsule-odometer: a concept to improve accurate lesion localisation.

    Science.gov (United States)

    Karargyris, Alexandros; Koulaouzidis, Anastasios

    2013-09-21

    In order to improve lesion localisation in small-bowel capsule endoscopy, a modified capsule design has been proposed incorporating localisation and - in theory - stabilization capabilities. The proposed design consists of a capsule fitted with protruding wheels attached to a spring-mechanism. This would act as a miniature odometer, leading to more accurate lesion localization information in relation to the onset of the investigation (spring expansion e.g., pyloric opening). Furthermore, this capsule could allow stabilization of the recorded video as any erratic, non-forward movement through the gut is minimised. Three-dimensional (3-D) printing technology was used to build a capsule prototype. Thereafter, miniature wheels were also 3-D printed and mounted on a spring which was attached to conventional capsule endoscopes for the purpose of this proof-of-concept experiment. In vitro and ex vivo experiments with porcine small-bowel are presented herein. Further experiments have been scheduled.