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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Aristeidis Mastoras Sotiris Anagnostidis Albert– Jan N. Yzelman Computing Systems Laboratory Zurich Research Center Huawei Technologies Switzerland Data Analytics Laboratory Department of Computer Science ETH Zurich Switzerland

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

GraphBLAS is a recent standard that allows the expression of graph algorithms in the language of linear algebra and enables automatic code parallelization and optimization. GraphBLAS operations are executed either in blocking or in non-blocking mode. Although there exist multiple implementations of GraphBLAS for efficient blocking execution on both shared-and distributed-memory systems, none of these implementations supports full nonblocking execution to improve data locality. In this paper, we present a preliminary evaluation for two algorithms, Pagerank and Conjugate Gradient, that confirms the importance of nonblocking execution, by showing promising speedups over the corresponding blocking execution.

关键词： Analytical models Distributed processing Heuristic algorithms Instruction sets Distributed databases Manuals Linear algebra

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Distributionally Robust Decentralized Volt-Var Control with Network Reconfiguration

arXiv

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arXiv 2023年

作者： Byeon, Geunyeong Kim, Kibaek the School of Computing and Augmented Intelligence Arizona State University TempeAZ United States the Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States

This paper presents a decentralized volt-var optimization (VVO) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization;decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions. Copyright © 2023, The Authors. All rights reserved.

关键词： Electric power distribution

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Cooperative Air-Ground Instant Delivery by UAVs and Crowdsourced Taxis

Cooperative Air-Ground Instant Delivery by UAVs and Crowdsou...

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International Conference on Data Engineering

作者： Junhui Gao Qianru Wang Xin Zhang Juan Shi Xiang Zhao Qingye Han Yan Pan School of Computer Science Northwestern Polytechnical University School of Computer Science and Technology Xidian University National Key Laboratory of Information Systems Engineering National University of Defense Technology Air Force Engineering University Laboratory for Big Data and Decision National University of Defense Technology School of Management Science and Real Estate Chongqing University National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery.

关键词： Autonomous aerial vehicles Data engineering Air to ground communication Trajectory Batteries Time factors Task analysis

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Distributionally Robust Decentralized Volt-Var Control with Network Reconfiguration

TechRxiv

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TechRxiv 2023年

作者： Byeon, Geunyeong Kim, Kibaek The School of Computing and Augmented Intelligence Arizona State University TempeAZ United States The Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States

This paper presents a decentralized volt-var control (VVC) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization;decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions. © 2023, CC BY.

关键词： Electric power distribution

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Zero-shot Object Detection Based on Dynamic Semantic Vectors

Zero-shot Object Detection Based on Dynamic Semantic Vectors

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haoyu Li Jilin Mei Jiancong Zhou Yu Hu Research Center for Advanced Computing Systems Zhejiang Laboratory Hangzhou China UCAS Hangzhou Institute for Advanced Study Hangzhou China Research Center for Intelligent Computing Systems Chinese Academy of Sciences Institute of Computing Technology Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Zero-shot object detection has shown its ability to overcome the problems of data scarcity and novel classes. Existing methods generally utilize static semantic vectors to classify objects and guide the network to map visual features to semantic vectors. However, the distribution of semantic vectors cannot adequately represent visual features, which makes migration from seen to unseen classes difficult. This work explores the dynamic semantic vector method to align the distributions of semantic vectors and visual features. The main challenge is to get a more reasonable distribution of semantic vectors. To address this issue, we proposed a two-way classification branch network and introduce N-pair loss into the dynamic semantic vector optimization process. Experiments on the MS-COCO dataset and SiTi (a real-world autonomous driving dataset collected by us) demonstrate the effectiveness and generalization of our method. Our code is available at https://***/HaoyuLizju/ZSD_tcb

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Arbitrary State Preparation via Quantum Walks

Arbitrary State Preparation via Quantum Walks

引用

Quantum computing and Engineering (QCE), IEEE International Conference on

作者： Alvin Gonzales Rebekah Herrman Colin Campbell Igor Gaidai Ji Liu Teague Tomesh Zain H. Saleem Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA Department of Industrial and Systems Engineering University of Tennessee Knoxville Knoxville TN USA Infleqtion Chicago IL USA

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work we develop a mapping from dynamic CTQWs to the gate model of computation in the form of an algorithm to convert arbitrary single edge walks and single self loop walks, which are the fundamental building blocks of dynamic CTQWs, to their circuit model counterparts. We use this mapping to introduce an arbitrary quantum state preparation framework based on dynamic CTQWs. Our approach utilizes global information about the target state, relates state preparation to finding the optimal path in a graph, and leads to optimizations in the reduction of controls that are not as obvious in other approaches. Interestingly, classical optimization problems such as the minimal hitting set, minimum spanning tree, and shortest Hamiltonian path problems arise in our framework. We test our methods against uniformly controlled rotations methods, used by Qiskit, and find ours requires fewer CX gates when the target state has a polynomial number of non-zero amplitudes.

关键词： Quantum algorithm Heuristic algorithms Computational modeling Logic gates Quantum state Polynomials Integrated circuit modeling Optimization

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A GPU-based Distributed Algorithm for Linearized Optimal Power Flow in Distribution systems

arXiv

引用

arXiv 2023年

作者： Ryu, Minseok Byeon, Geunyeong Kim, Kibaek School of Computing and Augmented Intelligence Arizona State University TempeAZ United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States

We propose a GPU-based distributed optimization algorithm, aimed at controlling optimal power flow in multi-phase and unbalanced distribution systems. Typically, conventional distributed optimization algorithms employed in such scenarios rely on parallel execution with multiple CPUs. However, this often leads to significant computation time primarily due to the need for optimization solvers to solve subproblems for every iteration of the algorithms. To address this computational challenge, we propose a distributed optimization algorithm that eliminates solver dependencies and harnesses GPU acceleration. The central idea involves decomposing networks to yield subproblems with closed-form solutions based on matrix operations that GPU can efficiently handle. We demonstrate the computational performance of our approach through numerical experiments on four IEEE test instances ranging from 13 to 8500 buses. Our results affirm the scalability and superior speed of our GPU-based approach compared to the CPU-based counterpart. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphics processing unit

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Nested Named Entity Recognition: A Survey of Latest Research

引用

Expert systems 2025年第7期42卷

作者： Ji, Lixia Dang, Yiping Du, Yunlong Gao, Wenzhao Zhang, Han School of Cyber Science and Engineering Zhengzhou University Zhengzhou China College of Computer Science Sichuan University Chengdu China Intelligent Systems Research Centre School of Computing Engineering & Intelligent Systems Ulster University Belfast United Kingdom Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College Luzhou China

The research on nested named entity recognition (NER) is conducive to providing richer semantic representations and capturing the nested structure among entities, which is crucial for the execution of downstream tasks. This paper aims to summarise the nested NER methods that have been combined with emerging technologies in recent years. We summarise the nested NER methods that are integrated with emerging technologies from three dimensions: model, framework, and data. Additionally, we explore the research progress of nested NER in two scenarios: cross-lingual modality and multi-modal in different modalities. Furthermore, we discuss the practical applications of NER technology in five fields: biomedicine, justice, finance, media, and e-commerce. Through this review, we can clearly see the development trends of nested NER technology under emerging technologies and different modalities, as well as its broad application prospects in various fields. This provides a reference for future exploration directions in nested NER. © 2025 John Wiley & Sons Ltd.

关键词： application fields modal nested named entity recognition new technologies

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Biometric individual identification system based on the ECG signal 19th

Biometric individual identification system based on the ECG ...

引用

19th International Conference on Intelligent systems Design and Applications, ISDA 2019

作者： Hamza, Sihem Ben Ayed, Yassine Higher Institute of Computer Science and Multimedia ISIMS University of Sfax Sfax Tunisia Multimedia InfoRmation Systems and Advanced Computing Laboratory MIRACL University of Sfax Sfax Tunisia

ISBN: (纸本)9783030493417

Human biometric identification based on the ElectroCardioGram (ECG) is relatively new. This domain is intended to recognize individuals since the ECG has unique characteristics for each individual. These features are robust against forgery. In this study, feature extraction from ECG signals was performed using a combination of three new types of characteristics: MFCC, ZCR, and entropy. We proposed to apply classification methods: K Nearest Neighbors (KNN) and support vector machines (SVM) for human biometric identification. For evaluation we used two bases, namely MIT-BIH arrhythmia and normal sinus rhythm obtained from the Physionet database. For the MIT-BIH database, we used 47 individuals, each recording contains ECG data recorded for 15 s and in the SNR database, we used 18 individuals, the duration of each recording is 10 s. The analysis of the results obtained shows that the combination of all the features proposed makes it possible to improve the efficiency of our identification system to reach a performance rate equal to 100% for the two bases. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Electrocardiograms

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Assessing the Efficacy of Improved Learning in Hourly Global Irradiance Prediction

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computers, Materials & Continua 2023年第11期77卷 2579-2594页

作者： Abdennasser Dahmani Yamina Ammi Nadjem Bailek Alban Kuriqi Nadhir Al-Ansari Salah Hanini Ilhami Colak Laith Abualigah El-Sayed M.El-kenawy Department of Mechanical Engineering Faculty of Science and TechnologyGIDD Industrial Engineering and Sustainable Development LaboratoryUniversity of RelizaneBourmadiaRelizane48000Algeria Laboratory of Biomaterials and Transport Phenomena(LBMPT) University of MedeaUrban PoleMedea26000Algeria Energies and Materials Research Laboratory Faculty of Sciences and TechnologyUniversity of TamanghassetTamanrasset10034Algeria Sustainable Development and Computer Science Laboratory Faculty of Sciences and TechnologyAhmed Draia University of AdrarAdrarAlgeria CERIS Instituto Superior TécnicoUniversidade de LisboaLisbon1049-001Portugal Civil Engineering Department University for Business and TechnologyPristina10000Kosovo Department of Civil Environmental and Natural Resources EngineeringLulea University of TechnologyLulea97187Sweden Engineering and Architecture Faculty Nisantasi UniversityIstanbulTurkey Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia Department of Computing and Information Systems School of Engineering and TechnologySunway University MalaysiaPetaling Jaya27500Malaysia Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Increasing global energy consumption has become an urgent problem as natural energy sources such as oil,gas,and uranium are rapidly running *** into renewable energy sources such as solar energy is being pursued to counter *** energy is one of the most promising renewable energy sources,as it has the potential to meet the world’s energy needs *** study aims to develop and evaluate artificial intelligence(AI)models for predicting hourly global *** hyperparameters were optimized using the Broyden-FletcherGoldfarb-Shanno(BFGS)quasi-Newton training algorithm and STATISTICA *** from two stations in Algeria with different climatic zones were used to develop the *** error measurements were used to determine the accuracy of the prediction models,including the correlation coefficient,the mean absolute error,and the root mean square error(RMSE).The optimal support vector machine(SVM)model showed exceptional efficiency during the training phase,with a high correlation coefficient(R=0.99)and a low mean absolute error(MAE=26.5741 Wh/m^(2)),as well as an RMSE of 38.7045 Wh/m^(2) across all ***,this study highlights the importance of accurate prediction models in the renewable energy,which can contribute to better energy management and planning.

关键词： Renewable energy energy prediction global irradiation artificial intelligence BFGS quasi-Newton training algorithm

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