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  • Open Access

    ARTICLE

    Reinforcement Learning Based Quantization Strategy Optimal Assignment Algorithm for Mixed Precision

    Yuejiao Wang, Zhong Ma*, Chaojie Yang, Yu Yang, Lu Wei

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 819-836, 2024, DOI:10.32604/cmc.2024.047108

    Abstract The quantization algorithm compresses the original network by reducing the numerical bit width of the model, which improves the computation speed. Because different layers have different redundancy and sensitivity to data bit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determine the optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantization can effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In this paper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bit width is proposed,… More >

  • Open Access

    ARTICLE

    An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

    Tarek Sheltami1,*, Gamil Ahmed1, Ansar Yasar2

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2627-2647, 2024, DOI:10.32604/cmes.2023.044973

    Abstract Recently, Internet of Drones (IoD) has garnered significant attention due to its widespread applications. However, deploying IoD for area coverage poses numerous limitations and challenges. These include interference between neighboring drones, the need for directional antennas, and altitude restrictions for drones. These challenges necessitate the development of efficient solutions. This research paper presents a cooperative decision-making approach for an efficient IoD deployment to address these challenges effectively. The primary objective of this study is to achieve an efficient IoD deployment strategy that maximizes the coverage region while minimizing interference between neighboring drones. In deployment problem, the interference increases as the… More >

  • Open Access

    ARTICLE

    Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network

    Yuting Zhu1, Yanfang Fu2,*, Yang Ce3, Pan Deng1, Jianpeng Zhu1, Huankun Su1

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3867-3894, 2023, DOI:10.32604/cmc.2023.046772

    Abstract In light of the escalating demand and intricacy of services in contemporary terrestrial, maritime, and aerial combat operations, there is a compelling need for enhanced service quality and efficiency in airborne cluster communication networks. Software-Defined Networking (SDN) proffers a viable solution for the multifaceted task of cooperative communication transmission and management across different operational domains within complex combat contexts, due to its intrinsic ability to flexibly allocate and centrally administer network resources. This study pivots around the optimization of SDN controller deployment within airborne data link clusters. A collaborative multi-controller architecture predicated on airborne data link clusters is thus proposed.… More >

  • Open Access

    ARTICLE

    Joint On-Demand Pruning and Online Distillation in Automatic Speech Recognition Language Model Optimization

    Soonshin Seo1,2, Ji-Hwan Kim2,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2833-2856, 2023, DOI:10.32604/cmc.2023.042816

    Abstract Automatic speech recognition (ASR) systems have emerged as indispensable tools across a wide spectrum of applications, ranging from transcription services to voice-activated assistants. To enhance the performance of these systems, it is important to deploy efficient models capable of adapting to diverse deployment conditions. In recent years, on-demand pruning methods have obtained significant attention within the ASR domain due to their adaptability in various deployment scenarios. However, these methods often confront substantial trade-offs, particularly in terms of unstable accuracy when reducing the model size. To address challenges, this study introduces two crucial empirical findings. Firstly, it proposes the incorporation of… More >

  • Open Access

    ARTICLE

    Research on Human Activity Recognition Algorithm Based on LSTM-1DCNN

    Yuesheng Zhao1, Xiaoling Wang1,*, Yutong Luo2,*, Muhammad Shamrooz Aslam3

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3325-3347, 2023, DOI:10.32604/cmc.2023.040528

    Abstract With the rapid advancement of wearable devices, Human Activities Recognition (HAR) based on these devices has emerged as a prominent research field. The objective of this study is to enhance the recognition performance of HAR by proposing an LSTM-1DCNN recognition algorithm that utilizes a single triaxial accelerometer. This algorithm comprises two branches: one branch consists of a Long and Short-Term Memory Network (LSTM), while the other parallel branch incorporates a one-dimensional Convolutional Neural Network (1DCNN). The parallel architecture of LSTM-1DCNN initially extracts spatial and temporal features from the accelerometer data separately, which are then concatenated and fed into a fully… More >

  • Open Access

    ARTICLE

    Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

    Hang Yang1,2,*, Xunbo Li1, Witold Pedrycz2

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1531-1551, 2023, DOI:10.32604/iasc.2023.039256

    Abstract Energy supply is one of the most critical challenges of wireless sensor networks (WSNs) and industrial wireless sensor networks (IWSNs). While research on coverage optimization problem (COP) centers on the network’s monitoring coverage, this research focuses on the power banks’ energy supply coverage. The study of 2-D and 3-D spaces is typical in IWSN, with the realistic environment being more complex with obstacles (i.e., machines). A 3-D surface is the field of interest (FOI) in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN. The hybrid power bank deployment model is… More >

  • Open Access

    ARTICLE

    Overbooking-Enabled Task Scheduling and Resource Allocation in Mobile Edge Computing Environments

    Jixun Gao1,2, Bingyi Hu2, Jialei Liu3,4,*, Huaichen Wang5, Quanzhen Huang1, Yuanyuan Zhao6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1-16, 2023, DOI:10.32604/iasc.2023.036890

    Abstract Mobile Edge Computing (MEC) is proposed to solve the needs of Internet of Things (IoT) users for high resource utilization, high reliability and low latency of service requests. However, the backup virtual machine is idle when its primary virtual machine is running normally, which will waste resources. Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization. First, these virtual machines are deployed into slots randomly, and then some tasks with cooperative relationship are offloaded to virtual machines for processing. Different deployment locations have different resource utilization and average service response time. We want to find… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Virtualization Methodologies to Facilitate NFV Deployment

    Sumbal Zahoor1, Ishtiaq Ahmad1, Ateeq Ur Rehman2, Elsayed Tag Eldin3, Nivin A. Ghamry4, Muhammad Shafiq5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 311-329, 2023, DOI:10.32604/cmc.2023.035960

    Abstract The development of the Next-Generation Wireless Network (NGWN) is becoming a reality. To conduct specialized processes more, rapid network deployment has become essential. Methodologies like Network Function Virtualization (NFV), Software-Defined Networks (SDN), and cloud computing will be crucial in addressing various challenges that 5G networks will face, particularly adaptability, scalability, and reliability. The motivation behind this work is to confirm the function of virtualization and the capabilities offered by various virtualization platforms, including hypervisors, clouds, and containers, which will serve as a guide to dealing with the stimulating environment of 5G. This is particularly crucial when implementing network operations at… More >

  • Open Access

    ARTICLE

    Investigation on the Folding Mode and Deployment Process of an Inflatable Boarding Platform for the Marine Emergency Evacuation System

    Chongyang Nie, Fankai Kong*, Huaqiu Ding, Hongli Pan

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 483-510, 2023, DOI:10.32604/cmes.2022.021083

    Abstract The different folding and storage forms of an inflatable boarding platform will have a direct impact on the deployment effect of the marine emergency evacuation system. This paper proposes different folding and storage methods for an inflatable boarding platform in a marine emergency evacuation system. According to the difference between the fold line and the fold direction, the numerical models of a boarding platform with partial fold, “Z” type fold and inner spiral fold are established. The platform models with three folding modes are simulated by numerical simulation. According to the numerical results of the inflation process, the displacement changes… More > Graphic Abstract

    Investigation on the Folding Mode and Deployment Process of an Inflatable Boarding Platform for the Marine Emergency Evacuation System

  • Open Access

    ARTICLE

    Research on Evaluation of Multi-Timescale Flexibility and Energy Storage Deployment for the High-Penetration Renewable Energy of Power Systems

    Hongliang Wang1, Jiahua Hu1, Danhuang Dong1, Cenfeng Wang1, Feixia Tang2, Yizheng Wang1, Changsen Feng2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1137-1158, 2023, DOI:10.32604/cmes.2022.021965

    Abstract With the rapid and wide deployment of renewable energy, the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance. The output power of renewable energy is uncertain, and thus flexible regulation for the power balance is highly demanded. Considering the multi-timescale output characteristics of renewable energy, a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper. Through the multi-timescale decomposition algorithm on the basis of mathematical morphology, the multi-timescale components are separated to determine the flexibility requirements… More >

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