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共 66504 条记录，以下是121-130 订阅

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Mobile-Aware Placement: Optimizing Energy Consumption and Delay of Data Stream Applications in Edge computing 4

Mobile-Aware Placement: Optimizing Energy Consumption and De...

引用

4th international conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Jin, Pengcheng Wu, Yi Huang, Jingyu Ji, Ying Software Technology Co. Ltd. Jiangsu Suzhou China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

With the rapid development of 5G and IoT, traditional cloud computing faces limitations due to increasing demands. Edge computing addresses these issues by offloading tasks to nearby nodes, thereby improving efficiency and user experience for latency-sensitive applications such as live video and autonomous driving. However, balancing energy consumption and latency in heterogeneous edge devices remains a challenge, particularly as previous studies often overlook user mobility. In this work, we tackle the problem of data stream processing (DSP) task placement within dynamic user mobility scenarios, addressing the challenges posed by frequent movement. Additionally, we introduce a reinforcement learning approach to enhance the adaptability of DSP tasks, allowing the system to effectively adjust to changing user mobility patterns. Through simulation experiments, it is verified that compared with the traditional method, the algorithm proposed in this paper effectively optimizes energy consumption and delay while considering the mobility attributes, and improves the utilization rate of each edge node. © 2025 SPIE.

关键词： Mobile edge computing

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An Efficient Algorithm for software Reliability Prediction via Harris Hawks Optimization 2nd

An Efficient Algorithm for Software Reliability Prediction v...

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2nd international conference on Intelligent Manufacturing and Robotics, ICIMR 2024

作者： Kong, Li Sheng Jasser, Muhammed Basheer Issa, Bayan Ajibade, Samuel-Soma M. Majeed, Anwar P. P. Abdul Luo, Yang Department of Smart Computing and Cyber Resilience School of Computing and Artificial Intelligence Faculty of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Petaling Jaya47500 Malaysia Department of Data Science and Artificial Intelligence School of Computing and Artificial Intelligence Faculty of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Petaling Jaya47500 Malaysia Faculty of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Petaling Jaya47500 Malaysia Faculty of Informatics Engineering University of Aleppo Aleppo Syria School of Intelligent Manufacturing Ecosystem Xi’an Jiaotong-Liverpool University Suzhou Taicang215400 China

ISBN: (纸本)9789819639489

software reliability has become an increasingly important characteristic as software systems continue to be integrated into all parts of our lives. While the occurrence of failure after a period of time is within the nature of all software systems, the ability to estimate and predict failure is greatly beneficial to software development and maintenance. Hence, software Reliability Growth Models (SRGMs) were developed to fulfill this requirement. Conventional parameter estimation methods of SRGM functions were complex and left more to be desired. Consequently, metaheuristics such as Swarm Intelligence algorithms were introduced to estimate and optimize the parameters of SRGM functions. Likewise, Swarm Intelligence algorithms were found to be exceptionally effective in estimating and optimizing the parameters of SRGM functions. This paper presents a novel approach to parameter estimation on three different SRGM functions through Harris’ Hawks Optimization (HHO). The proposed HHO design is compared against numerous different variants of Swarm Intelligence algorithms and is shown to be significantly more efficient than the majority of the compared designs. Moreover, as the proposed design is a base variant of Swarm Intelligence algorithms, various avenues of future improvements have also been presented to improve its overall prediction accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Harris’ Hawks Optimization Parameter Estimation software Reliability Growth Models software Reliability Prediction Swarm Intelligence

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Astronomical Image Processing by the Lemur software 24

Astronomical Image Processing by the Lemur Software

引用

6th Asia conference on Machine Learning and computing, ACMLC 2024

作者： Khlamov, Sergii Savanevych, Vadym Briukhovetskyi, Oleksandr Vlasenko, Vladimir Dikov, Yevhen Dmytrenko, Artem Department of Media Systems and Technologies Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of systems engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Western Center of Radio Engineering Surveillance National Space Facilities Control and Test Center Kyiv Ukraine Space Research and Communication Center National Space Facilities Control and Test Center Kyiv Ukraine Department of Software Engineering GlobalLogic Incorporation Kharkiv Ukraine Institute of Astronomy V. N. Karazin Kharkiv National University Kharkiv Ukraine

ISBN: (纸本)9798400710018

The astronomical images are made by cameras with the charge-coupled device (CCD). They can be received from the different sources, like servers, clusters, predefined series, archives or "live" (online) data streams. The astronomical images processing is focused on but not limited to the following tasks: data mining, knowledge discovery, big astronomical data processing, filtering, background alignment, brightness equalization, segmentation, classification, image recognition, object's image detection, object's astrometry and photometry, moving object detection, parameters determination of the object's image and apparent motion, reference objects selection and others. The modern Lemur software of the Collection Light Technology (CoLiTec) project (https://***) was developed using the described above technologies and approaches. The Lemur software is designed to perform a sequence of the following main steps: pre-processing (astronomical information collection -> worst data rejection -> useful data extraction -> data mining -> classification -> background alignment -> brightness equalization), image processing (segmentation -> typical form analysis -> recognition patterns applying -> detection of the object's image -> astrometry -> photometry -> objects identification -> tracks detection), knowledge discovery (Solar System objects or artificial satellites to be discovered, tracks parameters for the investigation, light curves of the variable stars, scientific reports in the international formats). The paper describes the modern features for the astronomical image processing implemented in the Lemur software. It has assisted in making over 1700 discoveries of asteroids, including 5 NEOs, 21 Trojan asteroids of Jupiter, 1 Centaur. In total it has been used in about 800 000 observations, during which five comets were discovered. All such observations and discoveries have official observational circulares from the Minor Planet Center (MPC) of the international Ast

关键词： Asteroids

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Empirical Validation of software Defect Prediction Models Using Grid Search Gray Wolf Optimization 3rd

Empirical Validation of Software Defect Prediction Models Us...

引用

3rd international conference on computing and Communication Networks, ICCCN 2023

作者： Malhotra, Ruchika Meena, Shweta Department of Software Engineering Delhi Technological University Delhi110042 India

ISBN: (纸本)9789819726707

software engineering principles deal with the quality of software in consideration of various attributes. software defect prediction is one of the key domains in the field of software engineering. software defect prediction aims at providing non-defective softwares to the end user. In order to ensure the reliability and robustness of software, defects must be identified at each stage by conducting various review activities. In order to analyze the quality of software various defect prediction models are developed. In this study, a defect prediction model is modeled using Traditional Gray Wolf Optimization (TGWO) and Grid Search GWO (GSGWO). The performance of defect prediction models is analyzed on the basis of Within-Project Defect Prediction (WPDP_GWO), tenfold_GWO, TGWO, and GSGWO. Further, homogeneous cross-project defect prediction model is also developed under the consideration of predictive modeling. The performance of prediction models analyzed using AUC performance metric. Statistical tests are used for the validation of prediction models. Thus, RFGWO performed best for CPDP and GSGWO performed best for WPDP. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

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Source Code Pre-processing and Analysis to Extricate Features Using Abstract Syntax Tree 15th

Source Code Pre-processing and Analysis to Extricate Feature...

引用

15th international conference on Intelligent computing and Networking, IC-ICN 2024

作者： Kapse, Rahul Harsoor, Bharati Mumbai India PDA College of Engineering Visvesvaraya Technological University Karnataka Kalburgi India

ISBN: (纸本)9789819786305

The software is a collection of single files or many files which contain source code. The advances in Machine Learning algorithms and methods have inspired investigators to use these technical advancements for software program code assessment for software development work like software testing or defect prediction. This paper aims to pre-process the source code and apply machine learning strategies to do software program code analysis to extricate software program code features using AST and use these features of software program code for software engineering work. In the analysis, we analyse the Cyclomatic complexity of software program code and Halsted measures. Extricated sampled features are Max_cc: Maximum McCabe’s cyclomatic complexity, Moa: Measure, of Aggregation, Dam: Data Access Metric, Loc: Lines of Code, Lcom: Lack of cohesion in methods, Npm: Number of Public Methods, Cc: McCabe’s cyclomatic complexity, Ce: Efferent Couplings, Noc: Number of Children, Ca: Afferent couplings, Rfc: Response for a Class. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： software testing

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Proceedings - 5th IEEE international conference on Mobile Cloud computing, Services, and engineering, MobileCloud 2017

Proceedings - 5th IEEE International Conference on Mobile Cl...

引用

5th IEEE international conference on Mobile Cloud computing, Services and engineering, MobileCloud 2017

ISBN: (纸本)9781509063253

The proceedings contain 33 papers. The topics discussed include: Cowbird: a flexible cloud-based framework for combining smartphone sensors and IoT;HVC: a hybrid cloud computing framework in vehicular environments;MEC-ConPaaS: an experimental single-board based mobile edge cloud;an efficient double auction mechanism for on-demand transport services in cloud-based mobile commerce;social media intermediation robot for elderly people using external cloud-based services;cost efficient repository management for cloud-based on-demand video streaming;augmented resource allocation framework for disaster response coordination in mobile cloud environments;mobility prediction for efficient resources management in vehicular cloud computing;ROSAC: a round-wise fair scheduling approach for mobile clouds based on task asymptotic complexity;cloudlet-assisted heuristic offloading for mobile interactive applications;decision tree-based approaches for handling offloading decisions and performing adaptive monitoring in MCC systems;inferring mobile apps from resource usage patterns;extensible orchestration of elastic IP multimedia subsystem as a service using open bat;SoftAccess: cloud-based software defined virtualized wireless mobile access networks;HSC-IoT: a hardware and software co-verification based authentication scheme for Internet of Things;and a mobile cloud hierarchical trust management protocol for IoT systems.

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HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Quality Assessment Metric

HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Q...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zheng, Yuanming Yao, Jiaxuan Deng, Xiangyu Yang, Yuhong Liao, Ruiqi Tu, Weiping Lin, Cedar National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan China Guangdong OPPO Mobile Telecommunications Corp. Guangdong China

ISBN: (纸本)9798350368741

Spatial audio quality evaluation is essential for applications like virtual and augmented reality, where accurate sound reproduction enhances user immersion. While subjective listening tests are the gold standard, they are costly and time-consuming. To address this, we propose HAPG-SAQAM, an objective metric for assessing timbre quality, spatial quality, and overall quality of binaural audio, guided by human auditory perception. Our contributions include: (1) the Multi-scale Auditory Guided Feature Extraction (MAGFE) module, incorporating gammatone frequency cepstral coefficients for better alignment with human perception;(2) Perceptual Weighted Loss (PWL), optimizing the weighting of timbre quality (TQ) and spatial quality (SQ) loss based on subjective test data;and (3) data augmentation techniques to enhance robustness by amplifying perceptual distortions. Experimental results show HAPG-SAQAM improves correlation with subjective scores by 10%, with ablation studies confirming the contributions of its components to enhanced spatial and overall audio quality. © 2025 IEEE.

关键词： auditory perception spatial audio Speech and audio quality assessment subjective experiment timbre quality

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Improved Speaker-Emotion Voice Conversion with Limited Corpus based on Large Language Model and Pre-trained Model 6

Improved Speaker-Emotion Voice Conversion with Limited Corpu...

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6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Fanchang TangYaLing Yadav, Amit Sah, Abhishek Pratap Khan, Asif Department of Software Engineering Chengdu Neusoft University Chengdu China College of Engineering IT and Environment Charles Darwin University NT Australia School of Management Science and Engineering University of Electronic Science and Technology of China Chengdu China Department of Computer Application Integral University Lucknow India

ISBN: (纸本)9798331522667

Existing research on speaker and emotional voice conversion often focuses on separate tasks, neglecting their joint exploration. Furthermore, the limited availability of emotional corpora for target speakers poses a significant challenge for training robustness and generalized models. This paper proposes an improved scheme for speaker-emotion voice conversion with limited target speaker's emotional corpus, integrating a large language model and a pre-trained emotional speech synthesis model. It introduces several enhancements to enhance the quality of converted speech in terms of speaker similarity and emotional expressiveness. First, emotionally tagged text is generated using a large language model and emotional speech is synthesized from this text using a fine-tuned pre-trained emotional speech synthesis model. Then, a speaker-emotion voice conversion model is co-trained with both synthesized and real target emotional speech. Finally, the model is fine-tuned with the real target emotional speech to further boost the speaker and emotional similarity. © 2025 IEEE.

关键词： Speech enhancement

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Image Compression Algorithms - Comparative Analysis 3

Image Compression Algorithms - Comparative Analysis

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Niharika Reddy, G. Namrutha, M. Akshaya, Namratha Bhaskaran, Sreebha Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508456

Due to the abundance of the new digital media data, the issue of image quality and volume of data requiring compression has become a significant factor of concern, especially in media storage and transmitting. This work affords a comparative analysis of different image compression techniques with focus on the compression ratio, quality preservation, and complexity. A new hybrid model of Predictive Coding, Run Length Coding and Quantum Entropy Coding (QEC) is proposed and shown to exhibit negligible quality loss with substantial space saving. The experimental outcomes show that the proposed method reduces space 80 percent and works better than previous methods for areas requiring high speed and relative accuracy. These insights are timely, as practical computing-communication trade-offs are paramount in the new generation of social networks, medicine, and multimedia streaming. © 2025 IEEE.

关键词： Image compression

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Color Image Encryption Using Novel 5D Piecewise Map 5

Color Image Encryption Using Novel 5D Piecewise Map

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5th IEEE international conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Salunke, Bharti Salunke, Sharad Parul University Department of Computer Science & Engineering Vadodara India

ISBN: (纸本)9798350356236

This paper presents a novel color image encryption technique using a 5D piecewise chaotic map. In recent years, image encryption has become crucial for securing multimedia data in various applications, especially in communication over the internet. The proposed 5D piecewise map introduces complex chaotic behavior, ensuring higher security for color images. We extensively evaluate the performance of the encryption scheme using metrics such as correlation coefficient, information entropy, and keyspace. The results indicate that the proposed method achieves excellent security properties, and provides a substantial keyspace to prevent unauthorized access. Additionally, the comparison with recent methods demonstrates the superiority of our proposed encryption approach in terms of encryption speed, randomness, and robustness. © 2025 IEEE.

关键词： Authentication

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