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Digital Analysis and Processing, Intelligent Computation (DAPIC), International Conference on

作者： Can Wu Dan Liu College of Computer Science and Technology Changchun University of Science and Technology Changchun China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

In the context of industrial upgrading, the exponential growth of computational demands for big data processing has emerged as a critical challenge. Cloud computing, with its evolving technological capabilities, presents a viable solution to address these escalating computational requirements. This study focuses on optimizing resource allocation efficiency through the establishment of a multiobjective optimization framework for cloud computing systems. Specifically, we formulate mathematical representations of objective functions and constraints while detailing corresponding encoding/decoding methodologies. The research employs the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to resolve task scheduling dilemmas in cloud environments, simultaneously optimizing makespan and total computational time through innovative applications of nondominated sorting and congestion distance comparison. A series of multi-scale comparative experiments demonstrate the algorithm's superior performance over conventional scheduling approaches.

关键词： Cloud computing Job shop scheduling Processor scheduling Optimization models linear programming Computational efficiency Resource management Optimization Sorting Convergence

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Feedback Indicators for Providing Carbon Impact of Vehicle Charging to Electric Vehicle Users

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Transportation Research Procedia 2023年 70卷 347-355页

作者： Nana Kofi Twum-Duah Lucas Hajiro Neves Mosquini Muhammad Salman Shahid Frédéric Wurtz Benoît Delinchant Univ. Grenoble Alpes CNRS Grenoble INP G2Elab F-38000 Grenoble France Univ. Grenoble Alpes CNRS Grenoble INP G-SCOP F-38000 Grenoble France University of Applied Sciences of Western Switzerland Energy Institute HEIA-FR 1700 Fribourg Switzerland

The purpose of this article is to introduce two indicators designed to evaluate and consequently influence the indirect emissions related to the operation of an EV. The first indicator, denoted as “Electric Vehicle CarbonFlex Potential” indicator, evaluates an EV's maximum and minimum achievable carbon emissions using an optimization approach and compares the user's resultant indirect carbon emissions to these boundaries, therefore, this indicator compares the users behavior to the optimal best and worst cases. The second indicator is “EcoCharge Time” indicator, which provides feedback to an EV user based on their charging behavior on the best and worst times of charging the vehicle in a day. Since human behavior cannot be controlled, such indicators are essential tools for influencing the behavior of EV users toward a desired optimal, in this case, a charging schedule with the lowest possible overall indirect emissions. The proposed indicators were tested on an EV dataset using the carbon intensity data from a number of countries and the results show that there exists considerable flexibility potential. Additionally, the results also showed the best charging times, which were typically clustered around, allowing for ease of use and understanding.

关键词： Indirect Carbon Emissions Energy Transition Carbon-free Transportation Feedback Indicators linear programming

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Improving GAN Performance Using Confidence-Aware Discrimination

Improving GAN Performance Using Confidence-Aware Discriminat...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jinfeng Wu Wu Shi Southern University of Science and Technology Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shanghai Artificial Intelligence Laboratory

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Generative Adversarial Networks (GAN) involve the competition between a generator and a discriminator. The large variance of training data can bring difficulty to GAN resulting in mode collapse, training instability and low quality. As the distribution of generated samples evolves, the discriminator will have different levels of confidence for its predictions. To mitigate these problems, we introduce confidence-aware discrimination (CAD) to guide the training and sampling of GANs. To adapt confidence estimation for GANs, we design a new architecture based on StyleGAN2, and propose a confidence-aware adversarial loss. Extensive experiments are conducted on face, scene and object generation benchmarks. In the training stage, CAD can progressively learn the training data with the guide of confidence estimation and lead to a better convergence. In the inference stage, the confidence score can provide a new dimension of metric to assess the quality of generated samples and can further improve the performance by resampling and finetuning.

关键词： Training Measurement Estimation Training data Signal processing Generative adversarial networks linear programming Generators Speech processing Faces

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Enhancing Boundary-Handling Strategies for Convolutional Sparse Representation Model with 46 × 46 Convolution-Multiplication Properties

Enhancing Boundary-Handling Strategies for Convolutional Spa...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuto Tsukiashi Yoshimitsu Kuroki National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Convolutional sparse representation (CSR) extends the standard form by incorporating convolutional operations and has achieved notable success in image processing applications, offering a shift-invariant representation model. Recent studies typically redesign the initial model by exploiting the convolution-multiplication property of the discrete Fourier transform to solve the involved convex optimizations efficiently, which imposes periodic boundary handling and risks introducing boundary artifacts. This paper generalizes this approach by leveraging 46 × 46 convolution-multiplication properties while requiring only extra element-wise operations, enabling model designs that combine periodic, antiperiodic, and 40 symmetric boundary handlings for each dimension and across convolutions. These newly accepted models demonstrated better representation performance than the conventional model in our experiments, indicating the benefits of selecting appropriate boundary handlings.

关键词： Convolution Sparse approximation Computational modeling Image processing Memory management Transforms linear programming Convex functions Speech processing Standards

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On Evaluating the Impact of Automatic Text Summarization on Large Document Classification: An Empirical Study

On Evaluating the Impact of Automatic Text Summarization on ...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Moustafa Sadek Kahil Makhlouf Derdour Amira Bouamrane Kouzou Abdellah Mohamed Deriche Abdelatif Sahraoui Laboratory of Artificial Intelligence and Autonomous Things Larbi Ben M'hidi University Oum EI Bouaghi Algeria LAADI Laboratory University of Djelfa Algeria College of Engineering and Information Technologie Ajman University UAE LAMIS Laboratory Larbi Tebessi University Tebessa Algeria

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Document categorization continues to be a significant area of research, particularly in the context of automating the indexing of diverse web content such as blogs and forums. However, large document classification poses challenges in relation with both performance and processing time. This paper empirically investigates the impact of text summarization on document classification. For that, we compare classification performance before and after applying summarization techniques, focusing on two key aspects: (1) computational time and (2) classification performance, measured through accuracy, loss, and F1-score metrics. Our findings demonstrate the effectiveness of the proposed method, highlighting its potential to enhance the efficiency and accuracy of document categorization processes.

关键词： Accuracy Pipelines Semantics Text summarization Focusing linear programming Loss measurement Time measurement Natural language processing Indexing

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CLFace: A Scalable and Resource-Efficient Continual Learning Framework for Lifelong Face Recognition

CLFace: A Scalable and Resource-Efficient Continual Learning...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Md Mahedi Hasan Shoaib Meraj Sami Nasser Nasrabadi West Virginia University Morgantown West Virginia USA

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

An important aspect of deploying face recognition (FR) algorithms in real-world applications is their ability to learn new face identities from a continuous data stream. However, the online training of existing deep neural network-based FR algorithms, which are pre-trained offline on large-scale stationary datasets, encounter two major challenges: (I) catastrophic forgetting of previously learned identities, and (II) the need to store past data for complete retraining from scratch, leading to significant storage constraints and privacy concerns. In this paper, we introduce CLFace, a continual learning framework designed to preserve and incrementally extend the learned knowledge. CLFace eliminates the classification layer, resulting in a resource-efficient FR model that remains fixed throughout lifelong learning and provides label-free supervision to a student model, making it suitable for open-set face recog-nition during incremental steps. We introduce an objective function that employs feature-level distillation to reduce drift between feature maps of the student and teacher models across multiple stages. Additionally, it incorpo-rates a geometry-preserving distillation scheme to maintain the orientation of the teacher model's feature embedding. Furthermore, a contrastive knowledge distillation is incor-porated to continually enhance the discriminative power of the feature representation by matching similarities between new identities. Experiments on several benchmark FR datasets demonstrate that CLFace outperforms baseline approaches and state-of-the-art methods on unseen identities using both in-domain and out-of-domain datasets.

关键词： Training Continuing education Data privacy Computer vision Face recognition Benchmark testing linear programming

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Situational Awareness Based Resource Allocation for Multi-Target Tracking in Distributed Radar Network

Situational Awareness Based Resource Allocation for Multi-Ta...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Mushen Lin Fenggang Yan Lingda Ren Xiangtian Meng Maria Greco Fulvio Gini Ming Jin School of Information Science and Engineering Harbin Institute of Technology Weihai China Department of Electrical and Electronic Engineering The University of Hong Kong China Department of Information Engineering University of Pisa Italy

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In this paper, we present a Situational Awareness based Resource Allocation (SA-RA) strategy for multi-target tracking (MTT) in distributed radar networks, where both the resource utilization and overall MTT accuracy can be improved. The fusion rule with probabilistic data association (PDA) is used to associate cumulative data with measurement data from radar nodes. We also further derive the Bayesian Cramér-Rao Lower Bound (BCRLB) under the PDA fusion rule. For the proposed SA-RA strategy, the targets behavior is analyzed to determine their importance weights, expected tracking accuracy, and the allocated beams for each target. Utilizing the PDA-BCRLB and the importance weights, the objective function of the SA-RA strategy is formulated as a weighted sum of target utility functions. By addressing this objective function, the optimal transmission power is determined. Simulation results verify the superiority both in terms of tracking performance and resource allocation.

关键词： Target tracking Accuracy Radar measurements Simulation Radar Radar tracking linear programming Bayes methods Acoustic beams Resource management

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Fast, Robust and Global Optimisation for Antenna Design using Meta Modelling

Fast, Robust and Global Optimisation for Antenna Design usin...

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European Conference on Antennas and Propagation, EuCAP

作者： Lasse Hjuler Christiansen Anders Eltved SØren Hartmann Sabine Fie Hansen Nafsika Memeletzoglou Edoardo Baldazzi Oscar Borries Min Zhou Erio Gandini Product Development and Technology Department TICRA Copenhagen Denmark RF Payloads & Technology Division European Space Agency Noordwijk The Netherlands

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This paper introduces a data-driven meta-modelling framework designed to optimize challenging antenna designs, addressing the limitations of traditional gradient-based - and global search methods. The framework utilizes Bayesian Op-timization (BO) and High-Order Gaussian Processes (HOGPs) to approximate black-box functions, substantially reducing the reliance on full simulations. Two case studies that 1) optimises a multi-section corrugated horn antenna and 2) balances gain and return loss in a dual-reflector system, demonstrate the framework's effectiveness in handling complex design challenges, offering a scalable and efficient tool for antenna engineers.

关键词： Design methodology Horn antennas Search methods Closed box Prototypes Optimization methods Europe Gaussian processes linear programming Electromagnetics

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Graph-Cuts Fusion of Distance Fidelity Maps for Volumetric Multi-view Stereo

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Chinese Journal of Electronics 2023年第3期18卷 449-454页

作者： Yebin Liu Qionghai Dai Wenli Xu Broadband Networks and Digital Media Laboratory Tsinghua University Beijing China

This paper presents a new graph-cuts based volumetric reconstruction technique for multi-view stereo. To refrain from the balloon constraint term widely used in 3D reconstruction approaches, we propose the using of a more sophisticated and high performance map, namely the distance fidelity map, for graph-cuts optimization. The approach first seeks to compute the optimal Distance fidelity map (DFM) of each view using photo-consistency, feature constraint, silhouette constraint and smoothness constraint. Occlusion robust and feature robust mechanism are also considered during this process. After this, according to our proposed objective function, multiple DFMs are fused into a graph-cuts framework to give a watertight surface that best capture the surface detail. Results demonstrate the high performance reconstruction quality using only 10 views and its generality to extensive actor structures.

关键词： Measurement Surface reconstruction Three-dimensional displays linear programming Surface treatment Optimization

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Overcurrent Relays Coordination of Interconnected Power System using Modified Objective Functions and Multiple Standardized Tripping Curves

Overcurrent Relays Coordination of Interconnected Power Syst...

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Sustainable Energy Technologies and Computational Intelligence (SETCOM), International Conference on

作者： Shanker D. Godwal Kartik S. Pandya Santosh C. Vora Chintan R. Mehta Vipul N Rajput Dept. Electrical Engineering Institute of Technology Nirma University Ahmedabad India Dept. of Electrical Engineering Parul Institute of Technology Parul University Vadodara India Dept. Electrical Engineering Institute of Technology Dr. Subhash University Junagarh India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

Over the last few decades, many researchers opt various techniques to achieve optimum time for coordination of overcurrent relays. The main motive of these techniques is to avoid mal operation among the main and secondary relays and to reduce time of operation of each relay as per required criteria. Some researchers have suggested modification in relay characteristics and objective functions to avoid mis-coordination. Three objective functions from the literature are examined in this paper, and new modified objective functions are the suggested after modification. A comparison is made between the standard objective function with modified obje ctive functions. Out of three modified objective functions, the best modified objective function is proposed. Further, three IEC standard relay characteristics have been adopted to analyze & compare the effectiveness & robustness of said objective functions. For the said comparison IEEE 14-bus modified distribution system is considered and a Harmony search algorithm is used.

关键词： Philosophical considerations linear programming Robustness Power systems Relays IEC Standards Standards Computational intelligence

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