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共 2709 条记录，以下是21-30 订阅

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the Need for Accuracy and Smoothness in Numerical Simulations 15th

The Need for Accuracy and Smoothness in Numerical Simulat...

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15th international conference on parallel Processing and applied Mathematics, PPAM 2024

作者： Kjelgaard Mikkelsen, Carl Christian López-Villellas, Lorién Department of Computing Science Umeå University Umeå90187 Sweden Universidad de Zaragoza Zaragoza Spain

ISBN: (纸本)9783031856969

We consider the problem of estimating the error when solving a system of differential algebraic equations. Richardson extrapolation is a classical technique that can be used to judge when computational errors are irrelevant and estimate the discretization error. We have simulated molecular dynamics with constraints using the GROMACS library and found that the output is not always amenable to Richardson extrapolation. We derive and illustrate Richardson extrapolation using a variety of numerical experiments. We identify two necessary conditions that are not always satisfied by the GROMACS library. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Extrapolation

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Enhanced Detection of Down Syndrome through Convolutional Neural Networks: A Deep Learning Approach

Enhanced Detection of Down Syndrome Through Convolutional Ne...

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： Archana Saini Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

Down syndrome is a chromosomal anomaly caused by having an extra copy of chromosome 21 in millions of people worldwide. Early identification of Down syndrome is critical for delivering prompt therapies and assistance that improve the quality of life for affected persons and their families. In this article, a unique technique for detecting Down syndrome using convolutional neural networks (CNNs) is presented. the solution uses deep learning algorithms to analyze children's facial photos and automatically detect probable signs of Down syndrome. the experimental findings illustrate the efficiency of the proposed CNN-based technique in reliably identifying Down syndrome, with high accuracy, sensitivity, and specificity. In this article, three different batch sizes are applied with epoch 100, and the performance of the model is evaluated. At batch size 8 the loss is 0.3560 and the accuracy is 0.8419. Similarly, at batch size 16, the loss is 0.3420 and the accuracy is 0.8474 and lastly, at epoch 32 the minimum loss is measured as 0.3388, and the maximum accuracy of 0.8501 is achieved. the highest AUC, precision, and recall are also calculated at batch size 32 which is 0.9297, 0.8380, and 0.8670 respectively.

关键词： Deep learning Pediatrics Accuracy Sensitivity and specificity Size measurement Loss measurement Reliability Convolutional neural networks Biological cells Mobile computing

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Exploring the Role of Interpretability in Adversarial Defense Mechanisms based Malware Classification

Exploring The Role of Interpretability in Adversarial Defens...

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： t Assem Alhawari Sahar Ebadinezhad Department of Computer Information Systems Near East University Nicosia Cyprus Department of Computer Information Systems Computer Information Systems Research and Technology Centre (CISRTC) Near East University Nicosia Turkey

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

this systematic literature review (SLR) presents a comprehensive overview of the current state of interpretability techniques in malware classification based on adversarial defense mechanisms, challenges, and future directions. Several ML and DL approaches have been integrated into the malware detection and classification defense systems, where adversarial attacks represent a crucial security threat against these defense systems. the interpretability techniques have been found very important to be applied to enhance the performance of these security systems and develop more explainable models and decisions for users and security experts. the SLR was conducted by combining and reviewing scientific literature on adversarial defense mechanisms-based interpretability techniques in the field of malware classification published between 2013 and 2024. this SLR presents a new insight into the categorization of interpretability techniques' implications in adversarial defense systems. We evaluate the importance and effectiveness of interpretability techniques by investigating ML models, adversarial attacks, evaluation methods, datasets, user trust, and malware features. Furthermore, the study provides challenges and future research directions for further existing issues

关键词： Analytical models Decision making Malware Informatics Computer security Mobile computing Systematic literature review

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Collaborative Model for Sustainable Energy Utilization in Cloud Infrastructure

Collaborative Model for Sustainable Energy Utilization in Cl...

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： Manikandan Rajagopal K.Sathesh Kumar S. Prabagar Ramkumar Sivasakthivel Gobinath Ramar CHRIST University Bangalore Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore Karnataka

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

As the infrastructures of cloud computing provides paramount services to worldwide users, persistent applications are congregated using large scale data centres at the customer sides. For such wide platforms, virtualization technique has been incorporated for multiplexing the essential sources available. Due to the extensive application variations in the workloads, it is significant to handle the resource allocation methodologies of the virtual machines (VM) for assuring the Quality of Service (QoS) of cloud. On concentrating this, the paper proposed a Decentralized Energy-Aware Collaborative Model (DEACM) for effectively managing the data centres in cloud infrastructures. Initially, the optimal model for system management and power management are declared. then, functions of workload vectors and data collection about workloads has been carried out for optimal selection of virtual machines to migrate for balancing loads efficiently. this can be further applied for Target-based VM Migration Algorithm for determining the migrating target for VM. Moreover, the algorithm involved in energy utilization with managed QoS. the developed DEACM is evaluated using CloudSim platform and the results are discussed. the results exemplify that the DEACM can balance the workload across variety of machines optimally and provide reduced energy consumption to the complete system efficiently.

关键词： Cloud computing Data centers Computational modeling Power system management Collaboration Quality of service Virtual machines Vectors Resource management Load modeling

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Physical Exergames Movements and Pattern Recognition using Convolutional Neural Network

Physical Exergames Movements and Pattern Recognition using C...

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international conference on Advancements in Computational Sciences (ICACS)

作者： Tanvir Fatima Naik Bukht Ahmad Jalal Faculty of Computing & Artificial Intelligence Air University Islamabad Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

this paper proposes a novel framework for accurately recognizing physical exergames interaction in video sequences. the developed approach uses image processing and machine learning tools to correctly extract and classify the features. the framework comprises five main steps: Silhouette extraction, preprocessing, feature extraction, feature optimization and classification. Image contrast is improved by power law transformation, silhouette is extracted by the Multiple Object Tracking (MOT) algorithm and graph-based segmentation. We extract ORB and geometric skeleton based keypoints to capture discriminative features, and apply Fast Independent Component Analysis (FICA) to optimize feature representation. thirdly, the Convolutional Neural Network algorithm is used to classify the optimized features, with a macro average accuracy of 0.85 and a weighted average accuracy of 0.87%. the proposed framework effectively recognizes physical exergames interaction and can be applied in many domains, such as human-human interaction and surveillance.

关键词： Image segmentation Machine learning algorithms Accuracy Surveillance Video sequences Independent component analysis Feature extraction Classification algorithms Convolutional neural networks Optimization

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Smart Grid Solutions for Sustainable Mining: A Cost-Effective Energy Management Framework with Optimization Algorithms

Smart Grid Solutions for Sustainable Mining: A Cost-Effectiv...

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： Sravani Parvathareddy Abid Yahya Lilian Livutse Amuhaya Ravi Samikannu Department of Electrical and Communications Systems Engineering Botswana International University of Science and Technology Botswana Department of EEE New Era Engineering College Botswana

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

this research work focuses on conceptualizing and modeling smart grid infrastructure. the project's main objective is to develop a smart grid infrastructure to improve energy management in industrial processes. Regenerate has deployed a system that uses renewable energy sources like solar photovoltaic (PV) arrays and wind turbines combined with batteries for energy storage. this research work describes a method that first creates synthetic data and then uses a polynomial function to precisely model the statistical fluctuations inherent in the output of renewable energy sources. the process is carried out using MATLAB. A simulation model created using Simulink is also applied to build a smart grid that includes dynamic load control, demand side management DSM, and various control system configurations. the simulation demonstrates that it is possible to produce electricity with minimal or no depreciation related to an increased dependency on renewable energy sources. It can also function at a higher ratio of energy output produced by traditional sources than previously credited within New Zealand while having substantially fewer overall expenses associated with carbon emissions.

关键词： Photovoltaic systems Renewable energy sources Demand side management Electricity Mathematical models Smart grids Wind turbines Load flow control Load modeling Synthetic data

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A Hybrid Approach for Cardiovascular Disease Risk Evaluation

A Hybrid Approach for Cardiovascular Disease Risk Evaluation

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： U. Sesadri Shaik Jumlesha S.Hrushikesava Raju S. Adinarayna Nabanita Choudhury Vijaya Chandra Jadala Department of CSE Vardhaman College of Engineering Hyderabad Telangana Department of CSE Annamacharya Institute of Technology and Science Tirupati Chittoor(dt) AP Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur Department of Computer Science and Systems Engineering College of Engineering Andhra University Visakhapatnam Faculty of Computer Technology Assam down town University Guwahati Assam School of Computer Science and Artificial Intelligence SR University Hanumakonda Warangal Telangana India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

Nowadays, the risk estimators are to be applied based on the population characteristics of their country, which is termed as race attribute. there were specific tools to determine the risk of cardiovascular disease. Among many diseases, the mortality rate of the people is increasing due to a lack of quality lifestyle. In order to provide a guide to the individual based on their specific characteristics and lifestyle, would classify the risk into specific categories like severe (High), Moderate, and normal(Low) with pre-defined threshold constraints. the risk assessment estimators alert the individual to control certain modifiable attributes irrespective of their non-modifiable elements. the integration of random forests and intelligent rule mining would generate the CVD risk prediction. Efficiency as well as interpretability are important in this competitive hybrid model. the ultimate benefits assured are extending the lives of the patients by knowing the importance of daily work, habits, and their control food, presenting a powerful opportunity by practicing better personalization monitoring and improved patient care, and improved informed decisions for immediate action. the early prevention initiation by identifying the risk severity optimizes follow-up of better practices and treatment styles, resulting in improved decision making for better health care of the individual.

关键词： Measurement Calculators Prevention and mitigation Mortality Medical services Cardiovascular diseases Informatics Random forests Monitoring Mobile computing

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parallel Processing and applied Mathematics - 6th international conference, PPAM 2005, Revised Selected Papers

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6th international conference on parallel Processing and applied Mathematics, PPAM 2005

ISBN: (纸本)3540341412

the proceedings contain 135 papers. the topics discussed include: multi-version coherence for replicated shared objects;checkpointing speculative distributed shared memory;a self-stabilizing algorithm for finding a spanning tree in a polynomial number of moves;the distributed stigmergic algorithm for multi-parameter optimization;total exchange performance modeling under network contention;towards the performance visualization of web-service based applications;common due window assignment in parallel processor scheduling problem with nonlinear penalty functions;distributed architecture system for computer performance testing;towards distributed monitoring and performance analysis services in the K-WfGrid project;a new diagonal blocking format and model of cache behavior for sparse matrices;and an architecture for reconfigurable iterative MPI applications in dynamic environments.

关键词： parallel processing systems

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Reconfigurable Virtual Accelerator (ReVA) for Large-Scale Acceleration Circuits 30th

Reconfigurable Virtual Accelerator (ReVA) for Large-Scale A...

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30th international conference on parallel and Distributed Processing Techniques, PDPTA 2024, held as part of the World Congress in Computer Science, Computer Engineering and applied computing, CSCE 2024

作者： Yaguchi, Kazuki Maeda, Eriko Kawai, Shunya Teruya, Daichi Osana, Yasunori Miyoshi, Takefumi Nakajo, Hironori Department of Electrical Engineering and Computer Science Graduate School of Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Tokyo Koganei-shi184-8588 Japan Research and Education Institute for Semiconductors and Informatics Kumamoto University 2-39-1 Kurokami Kumamoto Chuo-ku860-8555 Japan WasaLabo LLC. K-2 Buransyu 6-5-20 Minaminaruse Tokyo Machida-shi194-0045 Japan Division of Advanced Information Technology and Computer Science Institute of Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Tokyo Koganei-shi184-8588 Japan

ISBN: (纸本)9783031856372

In recent years, hardware acceleration in large-scale computing fields such as Artificial Intelligence and High Performance computing, faces hardware resource shortages. To overcome this problem, we propose Reconfigurable Virtual Accelerator (ReVA), which allows a large-scale acceleration circuit built using multiple FPGAs, processors and memory subsystems, to accelerate application programs. We have designed and implemented a prototype of Virtual Accelerator (VA) Generator for ReVA to investigate its performance. the VA Generator prototype employs an open-source HLS automated split compilation tool, RapidStream, to automatically generate placed-and-routed virtual accelerators that can be implemented on multiple FPGAs based on HLS dataflow designs. the VA Generator, which places VAs on the appropriate regions of FPGAs, allows large circuits to be performed like a single accelerator using several FPGAs. In addition, RapidStream’s parallel compilation technology allows the VA Generator to suppress the increasing compilation time according to the circuit size. Moreover, with our VA Generator prototype we have built and evaluated a VA of a large-scale circuit which cannot be fit in a single FPGA with multiple FPGAs. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Reconfigurable hardware

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Vector Register Sharing Mechanism for High Performance Hardware Acceleration 30th

Vector Register Sharing Mechanism for High Performance Hard...

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作者： Tanaka, Tomoaki Kato, Michiya Osana, Yasunori Miyoshi, Takefumi Tada, Jubee Tanaka, Kiyofumi Nakajo, Hironori Department of Electrical Engineering and Computer Science Graduate School of Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Tokyo Koganei-shi184-8588 Japan Research and Education Institute for Semiconductors and Informatics Kumamoto University 2-39-1 Kurokami Kumamoto Chuo-ku860-8555 Japan WasaLabo LLC. K-2 Buransyu 6-5-20 Minaminaruse Tokyo Machida-shi194-0045 Japan Graduate School of Science and Engineering Yamagata University 1-4-12 Kojirakawa-machi Yamagata Yamagata-shi990-8560 Japan Japan Advanced Institute of Science and Technology 1-1 Asahidai Ishikawa Nomi923-1292 Japan Division of Advanced Information Technology Computer Science Institute of Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Tokyo Koganei-shi184-8588 Japan

In recent years, demand for data-parallel processing60;has been growing, and this parallelism often appears in AI processes. One method to accelerate these processes is using DSA, domain-specific architecture. A co... 详细信息

ISBN: (纸本)9783031856372

In recent years, demand for data-parallel processing has been growing, and this parallelism often appears in AI processes. One method to accelerate these processes is using DSA, domain-specific architecture. A common data transfer method on DSA is DMA, which is direct memory access. there are several studies on DMA-based accelerators. However, few studies focus on data transfer methods. In this paper, a vector register-sharing mechanism has been proposed as a new data transfer method. Our proposed mechanism is named "SHAVER". In this mechanism, a part of vector registers is directly shared with an accelerator. An open-source RISC-V vector co-processor is used to evaluate the mechanism’s potential. It has been implemented on an FPGA and a simulator for the evaluations. the results indicate the possibility of the proposal mechanism to achieve a maximum of 7.13% speedup over DMA transfer. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Vectors

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