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A Modified Extra-Gradient Method for Quadratic Optimization

A Modified Extra-Gradient Method for Quadratic Optimization

引用

international conference on Business computing and Global Informatization (BCGIN)

作者： Weiping Ding Zheng Peng Department of Mathematics Hunan Institute of Science and Technology Yueyang Hunan China College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian China

In this paper, we propose a modified extra-gradient method (MEGM) for solving quadratic optimization. In the MEGM method, we use a matrix parameter G k to balance the primal and dual variables. Numerical results show that the MEGM method significantly improves both computational cost and iteration number compared to the classical extra-gradient method.

关键词： Optimization convergence Computational efficiency Symmetric matrices Educational institutions Vectors

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A Compensating Power Control Method Based on Interference Detection

A Compensating Power Control Method Based on Interference De...

引用

international Joint conference on INC, IMS and IDC, NCM

作者： Jie Huang Lin Chen School of Co mputer National University of Defense Technology ChangSha China

Achieving network throughput maximization through power control has been a long standing open problem in interference-limited wireless networks. Firstly, we introduce the wireless channel propagation model. Secondly, basing on the model we put forward a compensation power control method named CPCMID (A Compensating Power Control Method Based on Interference Detection), which triggers the power control process by computing the network interference. The experiments results show that CPCMID is effective to reduce the shock of the network, and can get better network performance and convergence effects.

关键词： Interference Throughput Resource management Mobile communication Quality of service

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Virtual Machine Placement for Edge and Cloud computing 8th

Virtual Machine Placement for Edge and Cloud Computing

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1st international Workshop on Edge Adoption and Migration, EdgeWays 2020, 16th international Workshop on Engineering Service-Oriented Applications and Cloud Services, WESOACS 2020, ESOCC 2020 PhD Symposium, ESOCC 2020 EU Projects Track which took place at 8th European conference on Service-Oriented and Cloud computing, ESOCC 2020

作者： Partovi, Behdad Bagheri, Alireza Kazarji, Maryam Haddad Pahl, Claus Barzegar, Hamid R. Faculty of Computer Science and Engineering Shahid Beheshti University Tehran Iran Faculty of Computer Engineering Amirkabir University of Technology Hafez Tehran Iran Department of Computer Science Free University of Bozen-Bolzano Bolzano Italy

ISBN: (纸本)9783030719050

So far, the genetic algorithm has been presented for the energy-aware scheduling of virtual machines to minimize the total busy time of servers. However, this algorithm does not consider the criteria for service-level policies on real-time applications. The convergence speed of the genetic algorithm is quite low in solving many of the large hybrid optimization problems. In other similar studies, heuristic algorithms were used to solve the interval scheduling problem. Such algorithms are not able to find nearly optimal solutions to hard problems. Since the optimization of scheduling is part of the hard problems, it is wise to use meta-heuristic algorithms to find nearly optimal solutions. Accordingly, an energy-aware meta-heuristic scheduling algorithm is presented in this paper for real-time virtual machines. The main goal of this algorithm is to minimize the total busy time of the physical machines in an interval without violating the deadline for virtual machines. The results were collected from the genetic algorithm, the smart water drop algorithm, the optimization of the ant colony, and the first possible downward algorithm for comparison and evaluation. The optimization of the ant colony and the smart algorithm of water drops showed better results than did the other two algorithms. © 2021, Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Intelligent Dictionary Elements Extraction using Optical Character Recognition and Deep Learning based Object Detection

Intelligent Dictionary Elements Extraction using Optical Cha...

引用

international conference for convergence of technology (I2CT)

作者： Nigod Dayal Dhurke Sanjay Rabidas Sanket Vijay Narkhede Human Centred Design Computing Group Centre for Development of Advanced Computing (C-DAC) Pune India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

The Sanskrit Encyclopaedic Dictionary conceived and compiled by Deccan College Post Graduate Institute, Pune, India is available in paper format. For greater reach, there is a need for digitization of the dictionaries and conversion of these volumes into a comprehensive structured database. These volumes have Articles with a typical complex structure. In this paper, a novel approach for Automatic Lexical Element Extraction from Sanskrit Encyclopaedic Dictionary Pages (ALEE-SED) that consists of Sanskrit Dictionary Page Segmentation into articles and their meaning blocks using Optical Character Recognition (OCR) and Detectron2 Model further followed by an intelligent article wise dictionary (Lexical) element extraction is described.

关键词： Deep learning Dictionaries Databases Optical character recognition Object detection convergence

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A New Particle Swarm Optimization with Quadratic Crossover

A New Particle Swarm Optimization with Quadratic Crossover

引用

international conference on Advanced computing and Communications (ADCOM)

作者： Millie Pant Radha Thangaraj Department of Paper Technology Indian Institute of Technology Roorkee Saharanpur India

In this paper we have presented a new variant of diversity guided PSO algorithm named QIPSO for solving global optimization problems. The QIPSO algorithm makes use of a quadratic crossover operator to maintain the level of diversity in the swarm population, thereby maintaining a good balance between the exploration and exploitation phenomena and preventing premature convergence. We have compared it with Basic Particle Swarm Optimization (BPSO) and another diversity guided PSO called ARPSO. The numerical results show that QIPSO outperforms the other two algorithms in all the seventeen cases taken in this study.

关键词： Particle swarm optimization Diversity reception Humans Genetic mutations Equations Evolutionary computation Space exploration Birds Paper technology Stochastic processes

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A Study for Accelerating of Convolution Operations Based on Multiple GPUs with MPI 1

引用

11th international conference on Computer Science and its Applications, CSA 2019 and 14th KIPS international conference on Ubiquitous Information Technologies and Applications, CUTE 2019

作者： Hong, Boseon Kim, Geunmo Kim, Sungmin Kim, Jeong-Dong Kim, Bongjae Department of Computer and Electronics Convergence Engineering Sun Moon University Asan-si Korea Republic of Division of Computer Science and Engineering Sun Moon University 70 Sunmoon-Ro 221 Beon-Gil Tangjeong-Myeon Asan-si Chungcheongnam-do31460 Korea Republic of

ISBN: (数字)9789811593437

ISBN: (纸本)9789811593420

Advances in hardware and software can handle large-scale data in the field of deep learning. It generally uses a parallel GPU to perform large-scale operations, but there is a limit to the number of GPUs available on a single node. Using multiple nodes can overcome this constraint. In this paper, we designed and evaluated a convolution operation method using the Message Passing Interface (MPI) to accelerate the performance using constant memory which is a kind of the GPU’s memory, and multiple nodes with the multiple GPUs environment. According to the performance evaluation results, the use of constant memory of GPU reduces the convolution operation execution time and the convolution operation execution time decreases as the number of GPUs increases in the multiple computing nodes. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Message passing

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Research on Quantitative Evaluation technology for Intelligent Cabin

Research on Quantitative Evaluation Technology for Intellige...

引用

Intelligent computing, Communication & convergence (ICI3C), international conference on

作者： Sheng Zhou Wei Zhou Xin Geng Lu Liu Xuan Dong Research Institute of Highway Ministry of Transport Ministry of Transport Beijing China Key Laboratory of Operation Safety Technology on Transport Vehicles Ministry of Transport Beijing P.R. China

ISBN: (数字)9798350343922

ISBN: (纸本)9798350343939

In recent years, the development of intelligent cabins has been rapid, but testing and evaluation usually involves detecting a single component, lacking a quantitative evaluation method for the overall performance of intelligent cabins. To address this issue, firstly, study the visual interaction elements inside the cabin and summarize the visual interaction testing methods; Then, research auditory interaction testing methods and establish a noise library to achieve reproducible experiments on common external environments; Finally, establish a multi-dimensional comprehensive evaluation method for the intelligent cabin to achieve a comprehensive evaluation of the overall performance of the intelligent cabin.

关键词： Visualization Systematics Noise Libraries Indexes Research and development Human-vehicle systems Testing Vehicles convergence

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CurricularVPR: Curricular Contrastive Loss for Visual Place Recognition

CurricularVPR: Curricular Contrastive Loss for Visual Place ...

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2024 IEEE/RSJ international conference on Intelligent Robots and Systems, IROS 2024

作者： Zhang, Dongshuo Chen, Nanhua Wu, Meiqing Lam, Siew-Kei Nanyang Technological University College of Computing and Data Science 50 Nanyang Ave 639798 Singapore Beijing Institute of Technology School of Aerospace Engineering Beijing100081 China

ISBN: (纸本)9798350377705

Visual Place Recognition (VPR) techniques commonly utilize Contrastive Losses (CL) to train models that generate compact and discriminative global descriptors for images. These models often result in poor performance due to one of the following reasons during training: 1) loss functions that focus primarily on easier samples, 2) reliance on time-consuming hard sample mining methods to identify informative supervisory samples, which hinders effective learning from large-scale datasets. To enhance both learning efficiency and effectiveness, we propose a Curricular Contrastive Loss (CCL) and use graded similarity labels as a measure of sample difficulty. Inspired by human learning that begin with easier concepts and progressively tackle more challenging ones, our CCL dynamically emphasizes easier samples during the initial training stages to achieve rapid convergence. The learning gradually focuses on harder samples in later training stages to bolster robustness of the models under challenging conditions. Our proposed method has been extensively evaluated on popular datasets, and the results demonstrate its superior performance compared to the CL and Generalized CL functions. © 2024 IEEE.

关键词： Contrastive Learning

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Decentralized Adaptive Helper Selection in Multi-channel P2P Streaming Systems

Decentralized Adaptive Helper Selection in Multi-channel P2P...

引用

international conference on Distributed computing Systems Workshop

作者： Seyedakbar Mostafavi Mehdi Dehghan IT & Computer Engineering Dept. Amirkabir University of Technology (Tehran Polytechnic)

In Peer-to-Peer (P2P) multi-channel live streaming, helper peers with surplus bandwidth resources act as micro-servers to compensate the server deficiencies in balancing the resources between different channel overlays. With deployment of helper level between server and peers, optimizing the user/helper topology becomes a challenging task since applying well-known reciprocity-based choking algorithms is impossible due to the one-directional nature of video streaming from helpers to users. Because of selfish behavior of peers and lack of central authority among them, selection of helpers requires coordination. In this paper, we design a distributed online helper selection mechanism which is adaptable to supply and demand pattern of various video channels. Our solution for strategic peers' exploitation from the shared resources of helpers is to guarantee the convergence to correlated equilibria (CE) among the helper selection strategies. Online convergence to the set of CE is achieved through the regret-tracking algorithm which tracks the equilibrium in the presence of stochastic dynamics of helpers' bandwidth. The resulting CE can help us select proper cooperation policies. Simulation results demonstrate that our algorithm achieves good convergence, load distribution on helpers and sustainable streaming rates for peers.

关键词： Peer-to-peer computing Games Bandwidth Servers Algorithm design and analysis convergence Heuristic algorithms

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Computation of Limit Cycle in a Nonlinear Fractional-Order Feedback Control Plant with Time Delay

Computation of Limit Cycle in a Nonlinear Fractional-Order F...

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Electrical Power Engineering, Communication and computing technology(ODICON), Odisha international conference on

作者： Biresh Kumar Dakua Bibhuti Bhusan Pati V.S.S. University of Technology Burla Odisha India

ISBN: (纸本)9781728176642

This paper predicts the presence of the limit cycle for a class of nonlinear fractional-order feedback control plants with separable nonlinearities. The concept of describing function along with the Nyquist contour is extended to evaluate the amplitude and frequency of such periodic oscillations for a fractional-order time-delay system. The critical value of plant gain is evaluated below which the system response shows convergence and oscillations fail to sustain. The accuracy of the proposed technique has been substantiated by comparing it with the results from MATLAB/SIMULINK applications.

关键词： Time-frequency analysis Power engineering Delay effects Limit-cycles Nonlinear control systems Stability analysis Feedback control

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