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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： L. DeRose T. Hoover J.K. Hollingsworth Advanced Computing Technology Center IBM Research Yorktown Heights NY USA Tools Development Department IBM Poughkeepsie NY USA Computing Technology Center IBM Research Israel Computer Science Department University of Maryland College Park MD USA

ISBN: (纸本)0769509908

The complexity of both parallel architectures and parallel applications poses several problems for the development of performance analysis and optimization tools. In this paper, we describe the motivations and the main aspects of the design of the Dynamic Probe Class Library (DPCL), an object based C++ class library that provides an infrastructure to reduce the cost of writing instrumentation for performance tools. Additionally, we present some of the performance tools built on top of DPCL, which demonstrate the power and flexibility of the library.

关键词： Probes Libraries Instruments Costs Application software Writing Performance analysis Computer science Educational institutions Parallel architectures

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The Effect of Epoxidized Natural Rubber as A Compatibilizer on the Properties of Standard Malaysian Rubber/Ethylene Propylene Diene Monomer Blends 1

The Effect of Epoxidized Natural Rubber as A Compatibilizer ...

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1st International Conference on Green and Sustainable computing (ICoGeS)

作者： Alakrach, A. M. Hamzah, R. Noriman, N. Z. Dahham, Omar S. Shayfull, Z. Idrus, S. Z. Syed Sudin, S. Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) UniCITI Alam Campus Sungai Chucuh Padang Besar Perlis 02100 Malaysia School of Manufacturing Engineering Universiti Malaysia Perlis Arau 02600 Malaysia Green Design and Manufacture Research Group Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Universiti Malaysia Perlis Kangar 0100 Malaysia School of Human Development and Techno-communication (IKOM) Green Advanced Computing and Technology (GREAT) Research Group-CEGeoGTech Universiti Malaysia Perlis (UniMAP Malaysia School of Computer and Communication Engineering (SCCE) Green Advanced Computing and Technology (GREAT) Research Group - CEGeoGTech Universiti Malaysia Perlis (UniMAP) Malaysia

In this study, the effects of epoxidized natural rubber (ENR-50) as compatibilizer on the properties of Standard Malaysian Rubber/Ethylene Propylene Diene Monomer (SMR L/EPDM) blend were investigated. Standard Malaysian Rubber/Ethylene Propylene Diene Monomer/Epoxidized Natural Rubber (SMR L/EPDM/ENR-50) blends were prepared by two-roll mill with five different compositions (i.e., 80/20/0, 80/20/1, 80/20/3, 80/20/5, 80/20/7 and 80/20/10), which the (SMR L/EPDM) content fixed at 80/20 which is the optimum ratio for (SMR L/EPDM) depending on our previous study. Cure characteristics, mechanical properties studies were performed to determine the compatibility of SMR L/EPDM blends in the presence of ENR-50 as a compatibilizer. The optimum cure characteristics showed by SMR L/EPDM blends with the presence of ENR-50, which lower scorch time t2 and cure time t90 and increase the cure rate index CRI. In addition, SMR L/EPDM blends with the presence of ENR-50 have improved the physical properties such as swelling test, crosslink density and hardness test.

关键词： Rubber

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Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis

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Neuroscience and Biobehavioral Reviews 2025年 174卷 106201页

作者： Zhang, Lin Jian, Liwen Long, Yiming Ren, Zhihong Calhoun, Vince D. Passos, Ives Cavalcante Tian, Xinyu Xiang, Yuhong School of Psychology Central China Normal University Wuhan 430079 China Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU) Ministry of Education Wuhan 430079 China Key Laboratory of Human Development and Mental Health of Hubei Province School of Psychology Central China Normal University Wuhan 430079 China Tri-Institutional Center for Translational Research in Neuroimaging and Data Science Georgia State University Georgia Institute of Technology Emory University Atlanta GA United States Klaus Advanced Computing Building 266 Ferst Drive Atlanta 30332-0765 Georgia Department of Psychiatry School of Medicine Universidade Federal do Rio Grande do Sul RS Porto Alegre Brazil Laboratory of Molecular Psychiatry Centro de Pesquisa Experimental (CPE) and Centro de Pesquisa Clínica (CPC) Hospital de Clínicas de Porto Alegre (HCPA) RS Porto Alegre Brazil Department of Psychiatry School of Medicine Universidade Federal do Rio Grande do Sul R. Ramiro Barcelos 2400 Floresta RS Porto Alegre 90035002 Brazil

Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contrast, machine learning models have the potential to classify and diagnose MDD more effectively, reducing the risk of misdiagnosis associated with conventional methods. The aim of this meta-analysis is to evaluate the overall classification accuracy of machine learning models in MDD and examine the effects of machine learning algorithms, biomarkers, diagnostic comparison groups, validation procedures, and participant age on classification performance. As of September 2024, a total of 176 studies were ultimately included in the meta-analysis, encompassing a total of 60,926 participants. A random-effects model was applied to analyze the extracted data, resulting in an overall classification accuracy of 0.825 (95 % CI [0.810;0.839]). Convolutional neural networks significantly outperformed support vector machines (SVM) when using electroencephalography and magnetoencephalography data. Additionally, SVM demonstrated significantly better performance with functional magnetic resonance imaging data compared to graph neural networks and gaussian process classification. The sample size was negatively correlated to classification accuracy. Furthermore, evidence of publication bias was also detected. Therefore, while this study indicates that machine learning models show high accuracy in distinguishing MDD from healthy controls and other psychiatric disorders, further research is required before these findings can be generalized to large-scale clinical practice. © 2025 Elsevier Ltd

关键词： Big data Biomarkers Machine Learning Major Depressive Disorder

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Single-hop wavelength assignment using an ant algorithm in WDM MESH network

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WSEAS Transactions on Computers 2006年第2期5卷 294-300页

作者： Chin, Tan Saw Singh, Y.P. Faculty of Information Technology Multimedia University Jalan Multimedia 63100 Cyberjaya Malaysia Center for Development of Advanced Computing C-56/1. Sector-62 Noida U.P.-201307 India

In this paper, a RWA linear programming formulation was formulated and ILP solver was used along with good approximation techniques (heuristic) to solve the static RWA problem The objective was to maximize the one hop traffic, given a set of lightpath requests/traffic demand. However, the proposed heuristic has the limitation of stagnation. Thus we applied Ant colony optimization (ACO) combined with heuristic algorithm to solve the assignment problem to obtain best assignment with highest objective value. The ACO based algorithm can outperform the comparison scheme and provide a better performance and more reliable than the proposed heuristic and ILP solver. The claim made in the paper for the proposed new heuristic and ACO are supported by experimental results.

关键词： Computer networks

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A context aware engine for multimedia applications on smartphone

A context aware engine for multimedia applications on smartp...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Sangdo Park Junghyun Park Paul Barom Jeon Su Myeon Kim Intelligent Computing Laboratory Samsung Advanced Institute of Technology South Korea Data Intelligence Laboratory Software Research and Development Center Samsung Electronics Company Limited South Korea

High complexity of understanding user's current situation is a crucial barrier to popularize context aware applications on smartphone. In order to overcome this barrier, we propose a context aware engine which eases the development of intelligent applications. Key feature of the engine is dynamic reconfiguration of the knowledge base depending on the current environments using linked data. We validated the usefulness of this feature via two in-house applications.

关键词： Context-aware services Engines Context Multimedia communication Context modeling Motion pictures Knowledge based systems

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New Slow Release Fertilizer from ENR-50/RH/Urea Composites: Effect of Sodium Chloride Concentration 1

New Slow Release Fertilizer from ENR-50/RH/Urea Composites: ...

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1st International Conference on Green and Sustainable computing (ICoGeS)

作者： Al-Samarrai, Marwa N. Hamzah, R. Sam, S. T. Noriman, N. Z. Dahham, Omar S. Idrus, S. Z. Syed Sudin, S. Center of Excellence Geopolymer and Green Technology (CEGeoGTech) Faculty of Engineering Technology (FETech) Universiti Malaysia Perlis (UniMAP) UniCITI Alam Campus Sungai Chucuh Padang Besar Perlis 02100 Malaysia School of Bioprocess Engineering Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi 3 Perlis Arau 02600 Malaysia School of Human Development and Techno-communication (IKOM) Green Advanced Computing and Technology (GREAT) Research Group-CEGeoGTech Universiti Malaysia Perlis (UniMAP) Malaysia School of Computer and Communication Engineering (SCCE) Green Advanced Computing and Technology (GREAT) Research Group-CEGeoGTech Universiti Malaysia Perlis (UniMAP) Malaysia

A green and renewable slow release material (SRM) was developed using combination of urea, epoxidized natural rubber (ENR-50), NaCl and rice husk (RH). The RH was used as a support to store urea within its fibrous structure after chemical modification with 7% sodium hydroxide (NaOH). ENR-50/NaCl was used as a coating material for RH/urea beads. Two different content of salt (5% and 10% NaCl) was used to study the effect of pore formation on the composites. FTIR spectroscopy reveals that urea was successfully absorbed into RH and the recorded peaks were overlapped with the main components of RH such as cellulose, hemicellulose and lignin. UV-Vis reveals that at 10% salt loading releases urea higher than 5% salt loading. This is due to the formation of many pores in this ENR-50 composite.

关键词： Urea

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LOGISTICS MANAGEMENT SYSTEM: AN advanced DECISION SUPPORT SYSTEM FOR THE FOURTH DECISION TIER DISPATCH OR SHORT‐INTERVAL SCHEDULING

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Production and Operations Management 1992年第1期1卷 70-86页

作者： FORDYCE, KENNETH DUNKI‐JACOBS, RAY GERARD, BARRY SELL, RICHARD SULLIVAN, GERALD Mathematical Sciences and APL 2 Department 33VA Technical Computing Solutions Center International Business Machines Corp. Kingston New York 12401 Mail Station 284 United States Advanced Industrial Engineering and LMS Development Department 746 International Business Machines Corp. Burlington Vermont 05452 Building 965-3 Essex Junction United States

The Logistics Management System (LMS) is a real‐time transaction‐based system combining decision technologies from AI, MS/OR, and decision support system that serves very successfully as a dispatcher or short‐interval scheduler by monitoring and controlling the manufacturing flow of IBM's semiconductor facility near Burlington, Vermont. LMS coordinates the actions and decisions of several logically isolated participants in a serially dependent system of activities. Therefore, it balances the requirements of several goals (cycle time, output, serviceability, and inventory management) that compete for the same resource, exploits emerging opportunities on the manufacturing floor, and reduces the distortion from unplanned events. This paper provides an overview of the LMS application, the concept of interrelated decision tiers in manufacturing decision making, and the need for the dispatch decision tier to successfully reduce apparent randomness. Historically, production and operations management has ignored this decision tier. This has significantly limited our ability to make an impact on the performance of the manufacturing operation. Copyright © 1992 Production and Operations Management Society

关键词： MANUFACTURING SCHEDULING OPERATIONS RESEARCH/ARTIFICIAL INTELLIGENCE SEMICONDUCTORS

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Probability of spin-orbit torque driven magnetization switching assisted by spin-transfer torque

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Physical Review B 2023年第13期108卷 134431-134431页

作者： Tomohiro Taniguchi Shinji Isogami Shuji Okame Katsuyuki Nakada Eiji Komura Tomoyuki Sasaki Seiji Mitani Masamitsu Hayashi National Institute of Advanced Industrial Science and Technology Research Center for Emerging Computing Technologies Tsukuba Ibaraki 305-8568 Japan National Institute for Materials Science Tsukuba 305-0047 Japan Advanced Products Development Center Technology & Intellectual Property HQ TDK Corporation Ichikawa Chiba 272-8558 Japan Department of Physics The University of Tokyo Tokyo 113-8654 Japan

Spin-orbit torque (SOT) driven magnetization switching, assisted by spin-transfer torque (STT), enables field-free switching in ferromagnetic nanostructures and is expected to be a writing method for next-generation spintronic nonvolatile memory. The role of STT is to shift the magnetization pointing in an in-plane direction via the SOT to a different direction and ensure the switching. Here, we study the dependence of the switching probability on the STT strength using a numerical simulation of the Landau-Lifshitz-Gilbert (LLG) equation. While a monotonic increase of the switching probability with increasing STT strength is found in a relatively weak STT region, we find an unexpected increase in the error rate in a relatively large STT current close to a critical current. Based on the statistical analysis of the magnetization dynamics and solving the LLG equation analytically, we reveal that the origin of the switching error is the presence of an inactive region in the Bloch sphere where the magnetization dynamics becomes very slow compared with conventional SOT switching. Since this region exists far away from the initial state of the magnetization, a strong STT is necessary to reach the region. Accordingly, the switching error increases in a strong STT region. We also show that the issue can be solved by reducing the time only the STT is applied and/or enhancing the SOT strength.

关键词： Spintronics Magnetic multilayers Landau-Lifschitz-Gilbert equation

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Transcriptomic analysis of Andrias davidianus meat and experimental validation for exploring its bioactive components as functional foods

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Food Science and Human Wellness 2024年第1期13卷 166-172页

作者： Changge Guan Zhenglin Tan Shucheng Li Yi Wang Naoyuki Yamamoto Chong Zhang Songjun Wang Junjie Chen Xinhui Xing Key Laboratory for Industrial Biocatalysis Ministry of Education of ChinaDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China School of Life Science and Technology Tokyo Institute of TechnologyYokohama 226-0026Japan Sensing System Research Center National Institute of Advanced Industrial Science and TechnologyTsukuba 305-8565Japan Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China Henan Giant Salamander Protection and Development Association Luoyang 471000China Intelligent Computing Research Center Harbin Institute of TechnologyShenzhen 518071China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 518067China

Andrias davidianus(Chinese giant salamander,CGS)is the largest and oldest extant amphibian species in the world and is a source of prospective functional food in ***,the progress of functional peptides mining was slow due to lack of reference genome and protein sequence *** this study,we illustrated full-length transcriptome sequencing to interpret the proteome of CGS meat and obtain 10703 coding DNA *** functional annotation and amino acid composition analysis,we have discovered various genes related to signal transduction,and 16 genes related to *** have also found vast variety of functional peptides through protein coding sequence(CDS)analysis by comparing the data obtained with the functional peptide ***-Pro-Ile predicted by the CDS analysis was released from the CGS meat through enzymatic hydrolysis,suggesting that our approach is *** study suggested that transcriptomic analysis can be used as a reference to guide polypeptide mining in CGS meat,thereby providing a powerful mining strategy for the bioresources with unknown genomic and proteomic sequences.

关键词： Chinese giant salamander Transcriptomic analysis Bioactive components Functional peptides mining

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Global and local statistical regularities control visual attention to object sequences

Global and local statistical regularities control visual att...

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IEEE International Conference on development and Learning, ICDL

作者： Alexa Romberg Yayun Zhang Benjamin Newman Jochen Triesch Chen Yu Department of Human Development & Quantitative Methodology Center for Advanced Study of Language University of Maryland MD USA Department of Psychology & Brain Science School of Informatics and Computing Indiana University-Bloomington IN USA Frankfurt Institute for Advanced Studies Frankfurt Germany

ISBN: (纸本)9781509050703

Many previous studies have shown that both infants and adults are skilled statistical learners. Because statistical learning is affected by attention, learners' ability to manage their attention can play a large role in what they learn. However, it is still unclear how learners allocate their attention in order to gain information in a visual environment containing multiple objects, especially how prior visual experience (i.e., familiarly of objects) influences where people look. To answer these questions, we collected eye movement data from adults exploring multiple novel objects while manipulating object familiarity with global (frequencies) and local (repetitions) regularities. We found that participants are sensitive to both global and local statistics embedded in their visual environment and they dynamically shift their attention to prioritize some objects over others as they gain knowledge of the objects and their distributions within the task.

关键词： Visualization Statistical learning Psychology Tracking Monitoring Complexity theory Sensitivity

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