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检索条件"主题词=software algorithms"

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Righteous: Automatic Right-Sizing for Complex Edge Deployments

Righteous: Automatic Right-Sizing for Complex Edge Deploymen...

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IEEE/ACM Symposium on Edge Computing (SEC)

作者： Aniruddha Rakshit Salil Reddy Rajiv Ramnath Anish Arora Jayson Boubin School of Computing Binghamton University Department of Computer Science and Engineering Ohio State University

ISBN: (数字)9798350378283

ISBN: (纸本)9798350378290

Edge deployments perform complex deep learning inference and analysis in the wild in highly resource constrained environment. They are positioned everywhere from our largest cities to the bottom of our oceans, and often necessitate significant financial resources and labor to create and deploy. These properties make correctness of edge deployments simultaneously extremely important and difficult to verify a priori. In the past decade, a series of IoT and cloud testbeds have emerged to facilitate this testing. They provide users with access to resources and, less often, sensors that can be used to emulate workloads before deployment. While developers can use these resources to verify the correctness of their configurations, often users would like to “right-size” their deployments - that is, to find a minimal resource configuration that guarantees correctness - to decrease cost and prevent over-provisioning. The current suite of cloud and IoT testbeds does not provide this capability. We present Righteous, an automatic deployment right-sizing tool for edge deployments. Righteous treats configuration as a hyperparameter optimization problem, testing hyperparameter combinations to find a near-optimal configuration as quickly as possible. Righteous uses a new optimization algorithm, informed Pareto Simulated Annealing (iPSA) to find near-optimal configurations faster than other leading approaches. We use Righteous in conjunction with the PROWESS testbed to optimize a drone swarm deployment workload. Our results demonstrate that Righteous configurations use up to 3.5X less resources than those identified by leading hyperparameter tuning and resource allocation techniques, and does so up to 76.3X faster.

关键词： software algorithms Urban areas Simulated annealing Hyperparameter optimization software Sensors Resource management Optimization Tuning Testing

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Context-Aware Personalized Route Recommendations for Bicycle Users Using Large-Scale Mobility Data

Context-Aware Personalized Route Recommendations for Bicycle...

引用

IEEE Annual International Computer software and Applications Conference (COMPSAC)

作者： Francesco Maria Turno Aleksejs Vesjolijs Jelena Kijonoka Irina Yatskiv Jackiva Engineering Faculty Transport and Telecommunication Institute Latvia LV

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

This research addresses the challenge of personalized bike route suggestions, an essential aspect of enhancing Mobility as a Service. The focus is on developing routes that balance efficiency (speed and distance) with the user's safety, preferences, and needs, filling a gap in modern urban mobility solutions. The approach involves analyzing the Sussex-Huawei Locomotion Dataset based on individual's historical mobility patterns, using a hybrid clustering method, Density-based Medoids, to pinpoint user's most significant locations. The accuracy of these identified hotspots is validated through metrics like the Silhouette score, Davies-Bouldin index, and Calinski-Harabasz index. Subsequently, a “bikeability” network is constructed, incorporating bike-related Points of Interest and real-time road incident data. This semantically enriched graph underpins a modified Dijkstra's algorithm, tailored for context-aware route recommendations. The effectiveness of these personalized routes is evaluated against alternatives generated by Yen's K shortest paths algorithm, using criteria such as path length, travel time, incidence of bike Points of Interest, and potential safety hazards. This study contributes to the development of smarter, safer, and more personalized urban recommendations, paving the way for future advancements in sustainable urban mobility.

关键词： Mobility as a service Measurement Roads Clustering methods software algorithms software Real-time systems

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A Digital Avatar System for Telepresence Services in 6G Toward HolNetVerse

A Digital Avatar System for Telepresence Services in 6G Towa...

引用

Cluster, Cloud and Internet Computing Workshops (CCGridW), IEEE/ACM International Symposium on

作者： Varvara Mineeva Alexander Zhitov Volkov Artem Ammar Muthanna Andrey Koucheryavy Department of Telecommunication Networks and Data Transmission Saint-Petersburg State University of Telecommunications Saint Petersburg Russia

ISBN: (数字)9798350377514

ISBN: (纸本)9798350377521

This paper focuses on the development and testing of a digital avatar system for telepresence services in the context of IMT-2030 networks. Digital avatar is an innovative telepresence system designed to shape the user experience of interacting with virtual and robotic infrastructures. This study investigates the technological aspects of IMT-2030 networks, specifically the latest QoS techniques, and their application to the creation of a digital avatar. The paper details the system development process, including selecting and integrating software components that provide realistic interaction and data transfer. The conducted experiment demonstrates the different behavior of the digital avatar under changes in the QoS method and key characteristics of the data smoothing algorithm. The experimental results present conclusions and optimal parameters for the perceptual behaviour of the digital avatar. The results confirm the effectiveness of the proposed digital avatar system and its potential for various applications in the HolNetVerse concept.

关键词： Telepresence Smoothing methods Shape Avatars software algorithms Quality of service User experience software Robots Testing

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Design of cavity permittivity measurement system based on Python-CST Co-Simulation

Design of cavity permittivity measurement system based on Py...

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International Conference on Electronics Technology (ICET)

作者： Hai Zhang Wenshen Zhong Chengjie Yao Anjun Wang Junchen Wei Yipeng Wu School of Information Engineering Nanchang Institute of Technology Nanchang China

ISBN: (数字)9798350363951

ISBN: (纸本)9798350363968

Accurately obtaining the permittivity of materials is one of the key technologies in modern communication. In this paper, a novel approach with Python-CST co-simulation and design of the cylindrical cavity permittivity system at 3.5 GHz is introduced. Firstly, the basic design of the cavity is demonstrated based on the mode chart method. Then, according to the coupler which is the key of the measurement system, the collaborative simulation and optimization including python optimization algorithm and CST electromagnetic simulation is given. Finally, the cavity has a clear TE011 mode.

关键词： Three-dimensional displays Permittivity measurement Simulation software algorithms Couplers software Permittivity

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CKMImageNet: A Comprehensive Dataset to Enable Channel Knowledge Map Construction via Computer Vision

CKMImageNet: A Comprehensive Dataset to Enable Channel Knowl...

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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Di Wu Zijian Wu Yuelong Qiu Shen Fu Yong Zeng National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

Environment-aware communication and sensing is one of the promising paradigm shifts towards 6G, which fully leverages prior information of the local wireless environment to optimize network performance. One of the key enablers for environment-aware communication and sensing is channel knowledge map (CKM), which provides location-specific channel knowledge that is crucial for channel state information (CSI) acquisition. To support the efficient construction of CKM, large-scale location-specific channel data is essential. However, most existing channel datasets do not have the location information nor visual representations of channel data, making them inadequate for exploring the intrinsic relationship between the channel knowledge and the local environment, nor for applying advanced artificial intelligence (AI) algorithms such as computer vision (CV) for CKM construction. To address such issues, in this paper, a large-scale dataset named CKMImageNet is established, which can provide both location-tagged numerical channel data and visual images, providing a holistic view of the channel and environment. Built using commercial ray tracing software, CKMImageNet captures electromagnetic wave propagation in different scenarios, revealing the relationships between location, environment and channel knowledge. By integrating detailed channel data and the corresponding image, CKMImageNet not only supports the verification of various communication and sensing algorithms, but also enables CKM construction with CV algorithms.

关键词： 6G mobile communication Wireless communication Visualization Computer vision Wireless sensor networks software algorithms Ray tracing software Sensors Artificial intelligence

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Client-Server Framework for FPGA Acceleration of Fan-Vercauteren-Based Homomorphic Encryption

Client-Server Framework for FPGA Acceleration of Fan-Vercaut...

引用

International Conference on Microelectronics, ICM

作者： Simon Bothe Hassan Nassar Lars Bauer Jörg Henkel Chair for Embedded Systems (CES) Karlsruhe Institute of Technology (KIT) Germany

ISBN: (数字)9798350379396

ISBN: (纸本)9798350379402

Cloud computing is becoming increasingly popular and widely used in daily services. However, traditional computation on the cloud involves decryption and processing plaintext on the server side, raising privacy and security concerns. Homomorphic encryption enables computations on encrypted data without decryption, but is significantly slower. Accelerating these computations through hardware and arithmetic optimizations, like FPGA usage, is essential. Previous works focused on implementing building blocks for constructing a homomorphic encryption system, but do not provide a full framework to perform full operations. In this work, we go in a different direction: We design a client-server framework with a communication channel and an FPGA-based acceleration for the Fan-Vercauteren algorithm, as it has several open-source implementations and can be easily deployed. Using the framework we evaluate the end-to-end performance of the algorithm. The client employs software for encryption, decryption, and key generation, while the server utilizes FPGA hardware to accelerate the computation. We evaluate the timing needed and compare it to executing a full software version of the system.

关键词： Cloud computing software algorithms Seals software Timing Servers Homomorphic encryption Field programmable gate arrays Optimization Hardware acceleration

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Optimizing Variable-Strength Combinatorial Test Suite Generation via Fuzzy Adaptive Sine Cosine Algorithm (FASCA)

Optimizing Variable-Strength Combinatorial Test Suite Genera...

引用

Cyber Security and Computing (CyberComp), International Conference on

作者： Nur Syabila Zabidi Noraini Ibrahim Mazidah Mat Rejab MasrulEhsan Mamat Sumaira Nazir Nurul Hawani Mat Tuselim Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia (UTHM) Parit Raja Batu Pahat MALAYSIA Department of Software Engineering National University of Modern Languages Islamabad PAKISTAN Business Intelligence Section Industrial Research Management Centre SIRIM Berhad Shah Alam MALAYSIA

ISBN: (数字)9798350387728

ISBN: (纸本)9798350387735

Combinatorial test suite generation is a critical aspect of software testing, particularly for systems with variable-strength interactions. Traditional optimization algorithms often struggle to efficiently generate minimal test suites while maintaining coverage. This research introduces the Fuzzy Adaptive Sine Cosine Algorithm (FASCA), a variant of the Sine Cosine Algorithm (SCA), tailored specifically for optimizing variable-strength combinatorial test suite generation. FASCA incorporates fuzzy adaptation mechanisms to dynamically balance exploration and exploitation, addressing the limitations of standard SCA in handling diverse interaction strengths. Experimental evaluations demonstrate that FASCA significantly reduces test suite size and execution time compared to the original SCA, offering a more efficient solution for combinatorial test optimization. These results highlight FASCA's potential as a robust tool for enhancing the efficiency of software testing processes.

关键词： Fuzzy logic Heuristic algorithms software algorithms Metaheuristics Switches Minimax techniques Linguistics Inference algorithms Standards Gravity

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Solving Time-Dependent Vehicle Routing Problem with Modulo Operation Genetic Algorithm Integrated with ALNS

Solving Time-Dependent Vehicle Routing Problem with Modulo O...

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Yuedong Jia Huanzhe Li Hebei GEO University Shijiazhuang China

ISBN: (数字)9798331506612

ISBN: (纸本)9798331506629

In the era of rapid growth in online shopping, e-commerce and food delivery have become new shopping methods. This paper focuses on the time-constrained vehicle routing problem in logistics, aiming to minimize the number of vehicles and optimize vehicle dispatch routes as a combinatorial optimization objective. An improved strategy for the traditional genetic algorithm is proposed, which integrates a large neighborhood search algorithm and incorporates modulo operation concepts to enhance the traditional genetic algorithm (ALNS-MGA). In the selection strategy, a combination of elite selection and k-tournament selection is employed to ensure global search capability. During the crossover process, a modulo random linear combination operator (MRLCO) and a multi-path optimal cost operator (MOCO) are introduced for chromosome gene exchange. The former ensures sufficient crossover, while the latter accelerates convergence and enhances the algorithm’s local optimization capability. Finally, ALNS is utilized to improve solution quality. The proposed algorithm is tested on the standard Solomon dataset and compared with ALNS-GA, DBO, ALNS algorithms, and the best-known solutions. The experimental results show that the ALNS-MGA algorithm proposed in this paper is closer to the optimal solution than the other compared algorithms, and in some cases, even surpasses the known optimal solutions.

关键词： Costs Vehicle routing software algorithms Routing Electronic commerce Vehicle dynamics Optimization Standards Genetic algorithms software engineering

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Audio Book Creation System Using Artificial Intelligence

Audio Book Creation System Using Artificial Intelligence

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International Computer Sciences and Information Technologies (CSIT)

作者： Yurii Kryvenchuk Oleksandr Duda Computer Science Department Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

Automated audiobook generation systems are software programs that convert textual content into high-quality audio formats using artificial intelligence and machine learning techniques. These systems utilize algorithms to analyze text and generate natural-sounding speech, enhancing accessibility for visually impaired individuals and providing convenience for users during various activities. With the increasing demand for audiobooks, particularly in the Ukrainian language, automated audiobook generation systems have become essential in meeting user needs and improving the efficiency of audiobook production. In this article, I will explore how automated audiobook generation systems work, the types of speech synthesis methods, and their challenges and limitations. I will also discuss advancements in automated audiobook generation systems and their future implications.

关键词： Machine learning algorithms software algorithms Refining Production Machine learning Speech enhancement Rendering (computer graphics) software Natural language processing Text to speech

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Optimized Test Data Generation for Path Testing Using Improved Combined Fitness Function with Modified Particle Swarm Optimization Algorithm

Optimized Test Data Generation for Path Testing Using Improv...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： AmirHossein Damia Mohammadreza Parvizimosaed Alireza Bakhshai Mojtaba Salehi Faculty of Computer Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Queen's University Kingston Canada Faculty of Computer Engineering Khorramabad Branch Islamic Azad University Khorramabad Iran

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

software testing is essential for assuring the reliability and excellence of software systems. Nevertheless, already used optimization techniques, such Particle Swarm Optimization (PSO), sometimes get stuck in local optima during testing. This study suggests innovative improvements to the PSO algorithm to address and overcome this constraint. Initially, we propose a method in which every particle keeps track of a collection of superior particles and chooses a global best (gbest) at random. This approach helps to explore a wider range of solutions and reduces the likelihood of being stuck in local minima. Furthermore, we use an enhanced crowding method to specifically tackle the discrepancy between the exploration and exploitation stages. This approach prioritizes extensive exploration and exploitation during the early phases of the search, progressively shifting towards a strategy that focuses more on exploitation as the algorithm advances. We present a thorough explanation of these changes, specifically highlighting the modifications made to the pbest section and the use of a novel fitness function that enhances the search process in the given space. The method that we offer has the potential to improve software testing methods by optimizing PSO-based techniques, leading to better performance and efficiency. The experimental findings have shown that our method outperforms numerous existing evolutionary or meta-heuristic algorithms in terms of test data generation speed and achieves superior coverage with fewer evaluations. The algorithms being compared are the Adaptive Genetic Algorithm (AGA), Dandelion Optimizer (DO), Chaotic Flower-Fruit Fly Optimization Algorithm (CFFFOA), Imperialist Competitive Algorithm (ICA), Chaos Adaptive Particle Swarm Optimization Algorithm (CAPSO), Particle Swarm Optimization Algorithm with Empirical Balance Strategy (PSOEBS), and Teaching Learning-Based Optimization (TLBO).

关键词： software testing Chaos software algorithms Metaheuristics Education Flowering plants software systems

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