Improving energy efficiency and network performance in IaaS cloud with virtual machine placement by Jian-kang DONG, Hong-bo WANG, Yang-yang LI, Shi-duan CHENG

“…The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.…”
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Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 by Henggang Zhang, Chenhui Zhu, Tianyu Jiao, Kaiyue Luo, Xu Ma, Mingyu Wang

“…Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. …”
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An Adaptive Weight Physics-Informed Neural Network for Vortex-Induced Vibration Problems by Ping Zhu, Zhonglin Liu, Ziqing Xu, Junxue Lv

“…In this study, a VIV dataset of a cylindrical body with different degrees of freedom is used to compare the performance of the PINN and three PINN optimization algorithms. The findings suggest that, compared to a standard PINN, the AW-PINN lowers the mean squared error (MSE) on the test set by 50%, significantly improving the prediction accuracy. …”
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A Design Framework for Scalable and Adaptive Multi-Agent Coordination in Dynamic Environments: Addressing Concurrent Agent and Environment Interactions by Raza Muhammad Kazim, Guoxin Wang, Zhenjun Ming, Jinhui Cao, Janet K. Allen, Farrokh Mistree

“…In this study, we explore the integration of surrogate response surface modeling (SRSM) with optimization algorithms, comparing Stochastic Gradient Descent (SGD) with a fixed learning rate, and adaptive learning rate (ALR) optimizers—including Adaptive Moment Estimation (ADAM) and Adaptive Approximate Direction Method Algorithm (AADMA)—to enhance MAS performance metrics, such as Agent Collision Rate (ACR), Agent Movement Frequency (AMF), and Task Completion Time (TCT). …”
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Quantum circuit unoptimization by Yusei Mori, Hideaki Hakoshima, Kyohei Sudo, Toshio Mori, Kosuke Mitarai, Keisuke Fujii

“…In this paper, we define and construct a quantum algorithmic primitive called quantum circuit unoptimization, which makes a given quantum circuit complex by introducing some redundancies while preserving circuit equivalence, i.e., the inverse operation of circuit optimization. …”
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High-Precision Indoor Visible Light Positioning Using Deep Neural Network Based on the Bayesian Regularization With Sparse Training Point by Haiqi Zhang, Jiahe Cui, Lihui Feng, Aiying Yang, Huichao Lv, Bo Lin, Heqing Huang

“…All of the aforementioned experimental results show that the algorithm and training data optimization we proposed provide a new solution for real-time and high-accuracy positioning with the neural network.…”
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YOLOv8 forestry pest recognition based on improved re-parametric convolution by Lina Zhang, Shengpeng Yu, Bo Yang, Shuai Zhao, Ziyi Huang, Zhiyin Yang, Helong Yu

“…This study aims to address these challenges by proposing an improved lightweight forestry pest detection algorithm, RSD-YOLOv8, based on YOLOv8.MethodsTo improve the performance of pest detection, we introduced several modifications to the YOLOv8 architecture. …”
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Efficient Resource Allocation and UAV Deployment in STAR-RIS and UAV-Relay Assisted Public Safety Networks for Video Transmission by Naveed Khan, Ayaz Ahmad, Abdulmalik Alwarafy, Munam Ali Shah, Abderrahmane Lakas, Muhammad Moazam Azeem

“…This optimization is subject to several constraints. The formulated optimization problem is non-convex, posing a challenge in solving it. …”
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Fractional-Order Adaptive P-Laplace Equation-Based Art Image Edge Detection by Ming Chen

“…The experimental results demonstrate that the algorithm can remove the noise while preserving the texture and details of the image. …”
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Load-Balanced Dynamic SFC Migration Based on Resource Demand Prediction by Tian Sun, Hefei Hu, Sirui Zhang

“…Therefore, we propose the Resource Predictive Load Balancing SFC Migration (RP-LBM) algorithm in this paper. The algorithm uses CNN-AT-LSTM to predict VNF resource demands in advance, eliminating the delays associated with dynamic migrations and determining the optimal migration timing. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…Abstract Forest fires are severe ecological disasters worldwide that cause extensive ecological destruction and economic losses while threatening biodiversity and human safety. …”
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Extraction of Levees from Paddy Fields Based on the SE-CBAM UNet Model and Remote Sensing Images by Hongfu Ai, Xiaomeng Zhu, Yongqi Han, Shinai Ma, Yiang Wang, Yihan Ma, Chuan Qin, Xinyi Han, Yaxin Yang, Xinle Zhang

“…We developed the SCA-UNet model by optimizing the UNet algorithm and enhancing its network architecture through the integration of the Convolutional Block Attention Module (CBAM) and Squeeze-and-Excitation Networks (SE). …”
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A QoS-based network planning method for power fiber to the home by Shuai SHAO, Zhijun SHANG, Zhongfeng WANG, Guoliang XIN, Yueyue LI, Xiangyu KONG, Xujing PENG

“…A QoS-based network planning method for power fiber to the home was proposed.Firstly,the distribution structure of different buildings was combined to carry out targeted ODN line path design.Secondly,in the ONU packet cluster planning stage,in order to meet the QoS requirements of multi-service differentiation,the communication cost as the optimization goal was uesd,and the optimization problem model was established with the constraints of access capacity,reliability and delay.At the same time,intelligent algorithms were used to solve the optimization problem model.Finally,the optical path attenuation of the planned network was calculated to meet the actual application needs.The simulation results show that the proposed QoS-based network planning method for power fiber to the home can save network construction cost while ensuring service reliability and delay requirements.…”
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Adaptive Multi-Robot Exploration for Unknown Environments Using Edge-Weighted Path Planning by Farhad Baghyari, Tyler Parsons, Jaho Seo, Byeongjin Kim, Mingeuk Kim, Hanmin Lee

“…Experimental results demonstrate that the algorithm achieves improved exploration efficiency and adaptability compared to a real-time scheduling method while maintaining computational feasibility. …”
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Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks by Dongsup Jin, Minho Jang, Ji-Woong Jang, Gyuyeol Kong

“…This paper addresses the rendezvous problem in asymmetric cognitive radio networks (CRNs) by proposing a novel reinforcement learning (RL)-based channel-hopping algorithm. Traditional methods like the jump-stay (JS) algorithm, while effective, often struggle with high time-to-rendezvous (TTR) in asymmetric scenarios where secondary users (SUs) have varying channel availability. …”
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Dense Matching with Low Computational Complexity for Disparity Estimation in the Radargrammetric Approach of SAR Intensity Images by Hamid Jannati, Mohammad Javad Valadan Zoej, Ebrahim Ghaderpour, Paolo Mazzanti

“…Notably, unlike traditional local and global models, the computational complexity of the proposed approach remains stable as the input size or kernel dimensions increase while memory consumption stays low. Compared to a pyramid-based local normalized cross-correlation (NCC) algorithm and adaptive semi-global matching (SGM) models, the proposed method maintains good accuracy comparable to adaptive SGM while reducing processing time by up to 50% relative to pyramid SGM and achieving a 35-fold speedup over the local NCC algorithm with an optimal kernel size. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The optimized algorithm is then used for video skilled movement detection processing to obtain cropped frame images. …”
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Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

“…YOLOv3 and a coal mine key position personnel unsafe behavior recognition method based on improved YOLOv7 and ByteTrack experienced missed detections and false positives based on enhanced images, while the proposed pedestrian detection algorithm effectively mitigated these issues.…”
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Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications by Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong

“…While cylinder fitting algorithms provide a three-dimensional (3D) solution for trunk detection, their performance in complex forest environments remains limited due to sensitivity to parameters like distance thresholds. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…Interestingly, while the more complex optimization models yield better overall welfare results, the improvements over simpler methods are small. …”
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