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11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2022

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putt...

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11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2022

ISBN: (纸本)9783031083402

the proceedings contain 35 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: Digitally Assisted Planning and Monitoring of Supportive Recommendations in Cancer Patients;CAIPI in Practice: Towards Explainable Interactive Medical Image Classification;a Deep Q Network-Based Multi-connectivity Algorithm for Heterogeneous 4G/5G Cellular systems;simulating Blockchain Consensus Protocols in Julia: Proof of Work vs Proof of Stake;Maximum Likelihood Estimators on MCMC Sampling Algorithms for Decision Making;employing Natural Language Processing Techniques for Online Job Vacancies Classification;Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study;proactive Buildings: A Prescriptive Maintenance Approach;performance Meta-analysis for Big-Data Univariate Auto-Imputation in the Building Sector;non-intrusive Diagnostics for Legacy Heat-Pump Performance Degradation;a 5G-Based Architecture for Localization Accuracy;anomaly Detection in Small-Scale Industrial and Household Appliances;an Innovative Software Platform for Efficient Energy, Environmental and Cost Planning in Buildings Retrofitting;deep Learning-Based Segmentation of the Atherosclerotic Carotid Plaque in Ultrasonic Images;An Intelligent Grammar-Based Platform for RNA H-type Pseudoknot Prediction;An Automated 2D U-Net Segmentation Method for the Identification of Cancer Brain Metastases Using MRI Images;the Use of Robotics in Critical Use Cases: the 5G-ERA Project Solution;fundamental Features of the Smart5Grid Platform Towards Realizing 5G Implementation;experimentation Scenarios for Machine Learning-Based Resource Management;efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases;5G for the Support of Smart Power Grids: Millisecond Level Precise distributed Generation Monitoring and Real-Time Wide Area Monitoring;monitoring Neurological Disorder Patients via Deep Learning Based Facial Expressions An

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parallel generation of inverted files for distributed text collections

Parallel generation of inverted files for distributed text c...

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Computer Science Society (SCCC) international conference Chilean FLAGGED

作者： B.A. Ribeiro-Neto J.P. Kitajima G. Navarro C.R.G. Sant'Ana N. Ziviani Computer Science Department Federal University of Minas Gerais Belo Horizonte Minas Gerais Brazil Computer Science Department University of Chile Santiago Chile

the authors present a scalable algorithm for the parallel computation of inverted files for large text collections. the algorithm takes into account an environment of a high bandwidth network of workstations with a shared-nothing memory organization. the text collection is assumed to be evenly distributed among the disks of the various workstations. Compression is used to save space in main memory (where inverted lists are kept) and to save time when data have to be moved across the network. the algorithm's average running cost is O(t/p) where t is the size of the whole text collection and p is the number of available processors. the authors implemented their algorithm and drew experimental results. In a 100 Mbits/s switched Ethernet network with 4 PentiumPro 200 MHz, 128 MB RAM on each processor they were able to invert 2 GB of TREC documents in 15 minutes. Further they also proposed an analytical model for the algorithm execution time.

关键词： Concurrent computing Indexing Computer science Costs Switches Information retrieval Vocabulary Hardware distributed computing Read-write memory

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Hybrid Energy Storage Review for Renewable Energy System Technologies and Applications

Hybrid Energy Storage Review for Renewable Energy System Tec...

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IEEE SSD international Multi-conference on systems, Signals and Devices

作者： Ahmed Samawi Alkafaji Ali Abedaljabar Al-Samawi Hafedh Trabelsi CES_Lab ENIS Sfax University Babylon Tunisia Iraq Al-Muthanna Iraq ENIS Sfax Tunisia

To illustrate the importance of renewable energy generation around the world. Renewable technology contributes to a remarkable amount of electricity to the grid. Renewable energy sources are the prime-movers of the microgrid. A microgrid is a small, parallel network of distributed generation (DG) power systems. In this paper, the hybrid energy sources resulting from nature and how to obtain the electrical energy from them, directly or indirectly, will be described, and the challenges facing hybrid power systems, in addition, the most important of which are to build appropriate control systems for each application. Fast response and support it by two or more sustainable energy sources increase the reliability of power production combined with (HRES). this study comprehensively reviews ESS technologies types, ESS structures, classifications, and ESS merits and demerits in MG applications.

关键词： Renewable energy sources Microgrids Production Control systems Hybrid power systems Power system reliability distributed power generation

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A distributed Method for Negative Content Spread Minimization on Social Networks 1

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18th international conference on Algorithmic Aspects in Information and Management, AAIM 2024

作者： Yan, Ruidong Guo, Zhenhua Wu, Weili Fan, Baoyu IEIT SYSTEMS Co. Ltd. Beijing100875 China Department of Computer Science The University of Texas at Dallas RichardsonTX75080 United States

ISBN: (数字)9789819777983

ISBN: (纸本)9789819777976

Currently, social networks have emerged as significant platforms for individuals to share personal information and social content. However, it is important to recognize that social networks have both positive and negative aspects. To effectively address the dissemination of negative social content such as rumors and misinformation, it is crucial to implement strategies that involve immediate blocking of associated links. this paper introduces a Negative Content Spread Minimization (NCSM) problem, which aims to minimize the spread of negative content by removing a set of edges from the network. We begin by demonstrating the NP-hardness of the NCSM problem through reduction from the Knapsack Problem. Furthermore, we establish that the objective function is not submodular under the Independent Cascade model. To address, we employ a distributed method which includes community partition and influential edges selection. the advantage of this approach is to reduce computational overhead by selecting key edges in parallel in each community. To evaluate proposed algorithm, we conduct experiments using real-world datasets and compare them against existing methods. the experimental results demonstrate that our method outperforms state-of-the-art algorithms. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： negative content spread non-submodularity Social network

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distributed Unsupervised Learning-Based Task Offloading for Mobile Edge computing systems 15th

Distributed Unsupervised Learning-Based Task Offloading for ...

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15th EAI international conference on Communications and Networking, ChinaCom 2020

作者： Wei, Jianming Liu, Qiuming Liu, Shumin Zeng, Yiping Xiong, Xin Department of Software Engineering Jiangxi University of Science and Technology Nanchang China

ISBN: (纸本)9783030677190

Mobile edge computing has emerged as a new paradigm to enhance computing capabilities by offloading complicated tasks to nearby cloud server. To conserve energy as well as maintain quality of service, algorithms with low time complexity for task offloading is required. In this paper, a multi-user with multiple tasks scenario is considered, taking full account of factors including data size, bandwidth, channel state information, we propose a distributed unsupervised learning-based offloading algorithm for task offloading, where distributed parallel networks are employed to guarantee the robustness of algorithm. Additionally, we exploit a memory pool to store input data and corresponding decisions as key-value pairs. Based on the experience mechanism, the proposed algorithm can omit the step of data calibration compared with supervised learning method. To further reduce the communication cost, we analyze four bandwidth allocation schemes. Results reveal that the channel state-based strategy cost 3% less than data size-based, mixed and user size-based. Besides, the proposed algorithm can save 14, 18% cost than local and edge schemes respectively. Numerous results show that the proposed algorithm can achieve near-optimal decisions timely as well as having high reliability. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Energy efficiency

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From a Store-Collect Object and Ω to Efficient Asynchronous Consensus

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18th international conference on Euro-Par parallel Processing

作者： Raynal, Michel Stainer, Julien Institut Universitaire de France France IRISA Université de Rennes 1 France

ISBN: (纸本)9783642328206

this paper presents an efficient algorithm that build a consensus object. this algorithm is based on an Omega failure detector (to obtain consensus liveness) and a store-collect object (to maintain its safety). A store-collect object provides the processes with two operations, a store operation which allows the invoking process to deposit a new value while discarding the previous value it has deposited and a collect operation that returns to the invoking process a set of pairs (i, val) where val is the last value deposited by the process p(i). A store-collect object has no sequential specification. While store-collect objects have been used as base objects to design wait-free constructions of more sophisticated objects (such as snapshot or renaming objects), as far as we know, they have not been explicitly used to built consensus objects. the proposed store-collect-based algorithm, which is round-based, has several noteworthy features. First it uses a single store-collect object (and not an object per round). Second, during a round, a process invokes at most once the store operation and the value val it deposits is a simple pair < r,v > where r is a round number and v a proposed value. third, a process is directed to skip rounds according to its view of the current global state (thereby saving useless computation rounds). Finally, the algorithm benefits from the adaptive wait-free implementations that have been proposed for store-collect objects, namely, the number of shared memory accesses involved in a collect operation is O(k) where k is the number of processes that have invoked the store operation. this makes the proposed algorithm particularly efficient and interesting for multiprocess programs made up of asynchronous crash-prone processes that run on top of multicore architectures.

关键词： Asynchronous shared memory system Building block Concurrent object Consensus distributed algorithm Eventual leader Failure detector Fault-tolerance Modularity Multicore systems Process crash Store-collect object

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Towards Robust Resource Allocations via Performance Modeling with Stochastic Process Algebra

Towards Robust Resource Allocations via Performance Modeling...

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IEEE international conference on Computational Science and Engineering

作者： Ioana Banicescu Srishti Srivastava Department of Computer Science & Engineering Mississippi State University Mississippi State USA

ISBN: (纸本)9781467382984

Recent developments in the field of parallel and distributed computing have led to a proliferation in solving large and computationally intensive mathematical, science, or engineering problems, which consist of several parallelizable parts and several non-parallelizable (sequential) parts. However, such computational environments are often prone to unpredictable variations due to problem, algorithm, and system characteristics. therefore, a robustness study of resource allocations and application scheduling is required to guarantee a desired level of performance. Given an initial workload, a mapping of applications to resources is considered to be robust if that mapping optimizes the execution performance and guarantees a desired level of performance in the presence of unpredictable perturbations at runtime. In this research, a stochastic process algebra, Performance Evaluation Process Algebra (PEPA), is used for obtaining performance of various resource allocations via a numerical analysis of performance modeling of the parallel execution of applications on parallel computing resources. the PEPA performance model is translated into an underlying mathematical Markov chain model for obtaining performance measures. Further, a robustness analysis of various allocations is performed for finding a robust mapping from a set of initial mapping schemes. the numerical results obtained from this performance modeling of resource allocations have been validated by the simulation results of earlier research which were made available in the existing literature, thus underscoring the significance and benefits of using stochastic process algebra models and the related numerical analysis in providing a cost effective and low overhead analysis of robustness.

关键词： Performance modeling Performance evaluation Robustness analysis parallel computing Process algebra Stochastic computing environment

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Asynchronously parallel Decoding For Automatic Speech Recognition Services

Asynchronously Parallel Decoding For Automatic Speech Recogn...

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international Joint conference on Computer Science and Software Engineering (JCSSE)

作者： Nattapong Kurpukdee Surasak Boonkla Phuttapong Sertsi Vataya Chunwijitra NECTEC National Science and Technology Development Agency (NSTDA) Pathum Thani Thailand

We proposed a new automatic speech recognition (ASR) service architecture that is extendable to medium-scale ASR service and more flexible than the previous architecture. Improvement aims to substitute the distributed processing approach with an asynchronous parallel thread for decoding multiple voice streams. We replace our TCP-based communication protocol with a remote procedure call developed by Google (gRPC) that makes our ASR service become a developer-friendly, less overhead connection. Besides, the API gateway is employed to reinforce the ASR services by multiple servers so that we can increase our new ASR service to a larger scale. the experimental result shows that our new architecture performs faster than the previous architecture in terms of real-time factor.

关键词： Protocols systems architecture Computer architecture Logic gates Real-time systems Decoding Time factors

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A GPU-based Fast Solution for Riesz Space Fractional Reaction-Diffusion Equation

A GPU-based Fast Solution for Riesz Space Fractional Reactio...

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international conference on Network-Based Information systems (NBIS)

作者： Qinglin Wang Jie Liu Chunye Gong Yang Zhang Zuocheng Xing Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China College of Aerospace Science and Engineering National University of Defense Technology Changsha China Science and Technology on Space Physics Laboratory Beijing China

the fast numerical solutions of Riesz fractional equation have computational cost of O(NMlogM), where M, N are the number of grid points and time steps. In this paper, we present a GPU-based fast solution for Riesz space fractional equation. the GPU-based fast solution, which is based on the fast method using FFT and implemented with CUDA programming model, consists of parallel FFT, vector-vector addition and vector-vector multiplication on GPU. the experimental results show that the GPU-based fast solution compares well with the exact solution. Compared to the known parallel fast solution on 8-core Intel E5-2670 CPU, the overall performance speedup on NVIDIA GTX650 GPU reaches 2.12 times and that on NVIDIA K20C GPU achieves 10.93 times.

关键词： Graphics processing units Instruction sets Mathematical model Arrays Yttrium Approximation methods parallel processing

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Workshop 6: HIPS High-level parallel Programming Models and Supportive Environments

Workshop 6: HIPS High-level Parallel Programming Models and ...

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IEEE international Symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Dong Li Heike Jagode University of California Merced University of Tennessee Knoxville

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

the 25th HIPS workshop, a full-day meeting on May 18th at the IEEE IPDPS 2020 conference in New Orleans (now virtual), focuses on high-level programming of multiprocessors, compute clusters, and massively parallel machines. Like previous workshops in the series, which was established in 1996, this event serves as a forum for research in the areas of parallel applications, language design, compilers, runtime systems, and programming tools. It provides a timely forum for scientists and engineers to present the latest ideas and findings in these rapidly changing fields. In our call for papers, we especially encouraged innovative approaches in the areas of emerging programming models for large-scale parallel systems and many-core architectures.

关键词： conferences Hip distributed processing parallel programming Computational modeling

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