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检索条件"任意字段=4th International Multi-Conference on Computing in the Global Information Technology"

共 11813 条记录，以下是11-20 订阅

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Enhancing trusted computing operation efficiency based on parallel file verification techniques 4

Enhancing trusted computing operation efficiency based on pa...

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4th international conference on Network Communication and information Security, ICNCIS 2024

作者： Zhang, Zhilong Pan, Fengyan Hou, Haibo Li, Yuan Shanghai Jiaotong University Shanghai China Beijing Chenguang Rongxin Technology Co. Beijing China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Trusted computing technology represents a significant element of cyber security systems, serving to guarantee the integrity and accessibility of data and systems. the incorporation of Trusted computing introduces a series of security detection and verification mechanisms to the host system, consequently impacting the performance of host system startup and application operation. In this paper, following an analysis of the verification mechanisms of Trusted computing, a parallel verification mechanism is proposed. the objective is to facilitate the parallel operation of the host system program and the TPM-based file verification process, thereby enhancing the operational efficiency of the trusted computing system. through the configurable and micro-intervention design scheme, flexible expansion and configuration within the existing Trusted computing technology framework can be achieved. © 2025 SPIE.

关键词： computing systems Design Computer security Process control Systems modeling Mathematical optimization Operating systems

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Optical reservoir computing based on the bagging trees 4

Optical reservoir computing based on the bagging trees

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4th international conference on Advanced Manufacturing technology and Electronic information, AMTEI 2024

作者： Xiao, Mujun Zhang, Ailing Wang, Chao Tianjin Key Laboratory of Thin Film Electronics and Communication Devices Engineering Research Center for Optoelectronic Devices and Communication Technology Ministry of Education School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China School of Engineering and Digital Arts University of Kent Canterbury United Kingdom

ISBN: (数字)9781510688247

ISBN: (纸本)9781510688230

In traditional optical reservoir computing, the least squares method are commonly used to train the output weights for regression tasks. Although these algorithms are highly versatile, their training efficiency and accuracy are somewhat inferior compared to current algorithms. Bagging trees, an ensemble learning method, works by resampling the dataset to train multiple models and then combining the predictions of these models, thus improving the stability and accuracy of the final prediction. By combining optical reservoir computing with the bagging trees, both the prediction accuracy and training efficiency are greatly improved, with the highest R-squared prediction reaching 99.56%. © 2025 SPIE.

关键词： Prediction models

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multi-scale Local and global Context-aware Network for Speech Enhancement in Insect Noise Environments 5

Multi-scale Local and Global Context-aware Network for Speec...

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5th international conference on Advances in Electrical, Electronics and computing technology, EECT 2025

作者： He, Jian Zhang, Chao Li, Guojing School of Computer Science and Technology Anhui University Hefei China

ISBN: (纸本)9798331541545

In the summer and autumn seasons, insect chirping (such as cicadas) emerges as the predominant environmental noise interference in outdoor audio data collection. Although existing speech enhancement models have made progress, they often fail to fully utilize multi-scale information and ignore feature interactions between scales. To address these limitations, this paper introduces a multi-scale Local and global Context-aware Network (MLGNet) for solving insect noise interference. MLGNet is based on UNet with Local-global Scale-Aware (LGSA) module, aiming to learn a wider range of multi-scale contextual features. LGSA consists of three key components. Specifically, multi-scale global-based Attention (MGA) module aggregates multi-scale information from different channel levels for global feature modeling and encodes causal position information. the multi-scale Interactive Convolution (MIC) module achieves cross-scale interaction modeling of local features through dual scale cross learning. Meanwhile, Context-aware Enhancement Fusion (CEF) module adaptivly learns of local and global feature weights and enhances nonlinearity, promoting high-quality dynamic fusion of features. the quantitative evaluation of the Insect Noise dataset and the Voice Bank+DEMAND dataset demonstrate that MLGNet outperformed other models and achieved excellent results in objective evaluation metrics. © 2025 IEEE.

关键词： Speech enhancement

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Implementing Resource-Aware Scheduling Algorithm for Improving Cost Optimization in Cloud computing 4

Implementing Resource-Aware Scheduling Algorithm for Improvi...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Reddy, Kiran Jagannadha Udayaraju, Pamula Pamaiahgari, Venkata Pradeep Reddy Kumar, V. Dilip Walmart BentonvilleAR United States Srm University Department of Cse AP India Wendys International Llc OH United States SRKR Engineering College Department of CSE India

ISBN: (纸本)9798331523923

An uncountable number of computational resources are shared for various applications using a transformative technology called Cloud computing. It is an emerging technology that can offer scalable and on-demand resources. However, cost optimization and resource allocation are critical issues due to the increasing number of cloud user and their request. It can be solved by optimising resource allocation by reducing the task/user queue. It is possible only if the requested resource is free;otherwise, it must schedule the same or relevant resource. this paper demonstrates a Resource-Aware Scheduling (RAS) algorithm to increase the speed of resource allocation by mapping the user request with the resource availability. the proposed algorithm examines the log information of the resources, workload behaviour, resource availability, price, task efficiency, and reduced wastage and allocates the resources dynamically. To do that, it maps user information with resource information and schedules based on availability and priority. the simulation-based experiment is carried out in a private cloud space and demonstrates the resource allocation, utilization, response time, and cost. It is also compared with the traditional scheduling algorithm to evaluate the performance of the RAS. the evaluation found that the RAS model is more suitable for cloud resource allocation. © 2025 IEEE.

关键词： Cloud computing Cost Optimization Resource Allocation Resource-Aware Scheduling Scheduling

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Integrated waveform design of radar-communication based on Gurobi 4

Integrated waveform design of radar-communication based on G...

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4th international conference on Advanced Manufacturing technology and Electronic information, AMTEI 2024

作者： Shen, Dong Tan, Xin Wang, Jiahao Xu, Haobo School of Electronic and Information Engineering Lanzhou Jiaotong University Gansu Lanzhou730070 China

ISBN: (数字)9781510688247

ISBN: (纸本)9781510688230

A low-complexity scheme based on Gurobi is proposed to address the problem of high complexity of waveform design solution algorithms in dual-functional radar-communication (DFRC) systems. Firstly, a DFRC system is constructed, and the objective function for minimizing downlink multi-user interference (MUI) energy is designed. Subsequently, the aforementioned non-convex quadratic constrained programming problem is addressed using Gurobi, a global solver for large-scale optimization. Finally, the results of the simulation experiments demonstrate that, under identical signal-to-noise ratio (SNR) conditions, the proposed scheme achieves a higher total transmission rate and significantly reduced complexity compared to the benchmark algorithms. Additionally, it effectively performs radar target detection concurrently with data communication within the DFRC system. © 2025 SPIE.

关键词： Signal to noise ratio

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information security requirements in monitoring e-government systems 4

Information security requirements in monitoring e-government...

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4th international conference on Evolutionary computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Gafurov, Azam Botirov, Fayzullajon 108 Amir Temur Tashkent Uzbekistan

this article examines the requirements for information security in monitoring e-government systems. It discusses the information security framework for eGoverment system, a model for organizing multi-level network security based on layered protection. this research study also covers the establishment of information security zones with eGovernment. and the importance of ensuring the local information securityand the process of connecting information security to a corporate network. It addresses the security measures for remote access and the use of automated control systems, such as VPN connections. © 2025 the Authors.

关键词： Corporate network E- government systems eGov information security system Monitoring Protection

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MLCDT: Fine-Grained multi-Task Learning for enhanced cognitive assessment in the clock drawing test 4

MLCDT: Fine-Grained Multi-Task Learning for enhanced cogniti...

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

作者： Yao, Lei Ma, Haomiao Sun, Haoran Zhang, Yingwei Liang, Shili Zhang, Lei Shang, Pan Sun, Shiwen The School of Physics Northeast Normal University Changchun130000 China Beijing Key Laboratory of Mobile Computing and Pervasive Device Institue of Computing Technology Chinese Academy of Sciences Beijing100190 China First People’s Hospital of Foshan Guangdong Foshan528010 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Artificial Intelligence (AI) is increasingly used in cognitive health assessments, with the Clock Drawing Test (CDT) being an effective cognitive evaluation tool. However, the complexity of CDT image structures, high subjectivity, and the lack of specialized cognitive health assessment datasets for specific populations pose significant challenges for feature learning and model construction using this method. To address these issues, we propose a fine-grained multi-task learning approach (MLCDT) for AI-assisted diagnosis of cognitive health using CDT. MLCDT integrates image pre-training models with a multi-task learning framework to capture fine-grained features of CDT images and constructs a final diagnostic support model through scientifically designed tasks. Experiments using real data from cognitive health assessments in a neurology department at a hospital validate the effectiveness of MLCDT in handling fine-grained tasks and aiding cognitive disorder assessments. © 2025 SPIE.

关键词： Electronic health record

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WOCP: Controller Placement using Whale Optimization in SDN-WAN 4

WOCP: Controller Placement using Whale Optimization in SDN-W...

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4th international conference on Evolutionary computing and Mobile Sustainable Networks, ICECMSN 2024

作者： thalapala, Vidya Sagar Guravaiah, Koppala Department of Computer Science & Engineering Indian Institute of Information Technology Kerala Kottayam686635 India

the established SDN multi-controller architecture faces the challenge of locating controllers to boost the scalability, reliability, and security of the network. Reliability is one of the important metric to handle when a failure event occurs in a network. In this paper, a Whale Optimization technique is used for controller placement and proposed Whale Optimization based Controller Placement (WOCP), that places the controllers in an optimized and efficient manner. the adequate placement of controllers minimizes the overall average latency with a high reliability index. the WOCP method resemblances with Minimizing Latency for Controller Placement (MLCP), resulting in an 18% reduction in latency in the Geant network topology. © 2025 the Authors. Published by Elsevier B.V.

关键词： Software reliability

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Ant Colony Optimization for multi-Label Correlation-based Feature Selection Method 10

Ant Colony Optimization for Multi-Label Correlation-based Fe...

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10th international conference on Digital Arts, Media and technology and 8th ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI DAMT and NCON 2025

作者： Jungjit, Suwimol Prasitsupparote, Amonrat Nathan, Shelena Soosay Rattanakietkhajorn, thanawit Thaksin University Faculty of Science and Digital Innovation Phatthalung Thailand Prince of Songkla University College of Computing Phuket Thailand Universiti Tun Hussein Onn Center for Diploma Studies Dept of Information Technology Johor Malaysia Suratthani Rajabhat University Faculty of Science and Technology Suratthani Thailand

ISBN: (纸本)9798331543273

this paper proposes a new ant colony optimization for multi-Label Correlation-Based Feature Selection (ACO-ML-CFS). this ACO performs a global search within the space of candidate features to identify an optimal subset. the selected feature subset is used by a multi-Label k-Nearest Neighbors algorithm (ML-kNN), in this paper. the performance of ACO-ML-CFS is evaluated and compared with our previously works;Hill-Climbing algorithm for multi-Label Correlation-Based Feature Selection (HC-ML-CFS) and Genetic algorithm for multi-Label Correlation-Based Feature Selection (GA-ML-CFS) across four benchmark multi-label datasets. © 2025 IEEE.

关键词： Ant colony optimization

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Development of Fast Prediction System of User Action for a Fully Autonomous Smart Home System 4

Development of Fast Prediction System of User Action for a F...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Rajalakshmi, N.R. Sharmila, L. Prabu, S. Veeramakali, T. Arulkumaran, G. Chourasia, Pranshu Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu India School of Computing Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Chennai India School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India School of Computing and Information Technology Reva University Karnataka Bangalore560064 India

ISBN: (纸本)9798331523923

the HVAC system, energy storage building, distributed power supply, and other equipment are integrated into the scheduling algorithm, which is aimed at reducing household electricity consumption. It is also assumed that users can provide energy to the grid according to their own conditions. Taking electricity cost and comfort level as optimization targets, a home energy optimization control model for the coordinated management of hybrid energy sources is built. A smart scheduling mechanism based on the improved adaptive particle swarm optimization approach is proposed in order to derive the best time intervals for electric appliances, necessary power for the control of the room temperature for every time frame, and power for charging and discharging of the storage battery at various moments. Simulation results show that through the incorporation of distributed photovoltaic power generation, backup storage by battery, and home energy optimization control, the system efficiently balances between user comfort and electricity consumption. this offers great technical support to the development of home energy management systems. By using time-of-use electricity price for energy acquisition and supply, the optimization control goal is minimizing both power use and cost as well as preserving comfort levels. the hybrid energy management's proposed home energy optimization control model uses an adaptive particle swarm optimization algorithm to find the optimal operation schedules of the electrical appliances, the required power for temperature control in a room, and the charge/discharge power level of the storage battery at each time interval. As per the optimization principle, the proposed dynamic programming algorithm converts the multi-stage problem into a sequence of single-stage problems and solves them separately. this method successfully resolves intricate problems that cannot be addressed through greedy algorithms or divide-and-conquer. In this research, management ac

关键词： Decision making

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