Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications by Lih-Jen Kau, Chin-Kun Tseng, Ming-Xian Lee

“…Overall, the proposed algorithm offers an effective balance between visual quality and computational performance, making it well suited for video transmission in bandwidth-constrained, resource-limited IoT and edge computing environments.…”
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Adaptive Real-Time Transmission in Large-Scale Satellite Networks Through Software-Defined-Networking-Based Domain Clustering and Random Linear Network Coding by Shangpeng Wang, Chenyuan Zhang, Yuchen Wu, Limin Liu, Jun Long

“…It also integrates real-time network state monitoring with optimization algorithms, within a multi-path scheduling strategy, enabling the dynamic selection of optimal transmission paths to accommodate frequent network topology changes and traffic variations. …”
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Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…In terms of intelligent control, deep reinforcement learning is used to optimize irrigation decision-making, and adaptive algorithms are combined to improve the flexibility of agricultural equipment scheduling. …”
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Adaptive Path Planning for Multi-Drone Systems Based on SFS, DPF, and Learning Based Refinement by Srwa Ahmed Mustafa, Amin Salih Kakshar

“…The existing algorithms, such as A*, Dijkstra’s, RRT, and ACO, fail to deliver satisfactory results while generating significant computational costs during real-time power consumption and dynamics avoidance attempts. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…This paper considers the single-machine scheduling problem of total tardiness minimization. Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

“…It is significant that the reduction of number of seed set selections T not only keeps the quality of solutions, but lowers the algorithm’s computational cost.…”
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ADeepWeeD: An adaptive deep learning framework for weed species classification by Md Geaur Rahman, Md Anisur Rahman, Mohammad Zavid Parvez, Md Anwarul Kaium Patwary, Tofael Ahamed, David A. Fleming-Muñoz, Saad Aloteibi, Mohammad Ali Moni, PhD

“…Efficient weed management in agricultural fields is essential for attaining optimal crop yields and safeguarding global food security. …”
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Qualitative Precipitation Estimation from Satellite Data Based on Distributed Domain-Specific Architecture by Sethakarn Prongnuch, Theerayod Wiangtong, Suchada Sitjongsataporn

“…The experimental results show that the proposed fast-satellite data processing algorithm is optimal for QPE processing on the DDSA platform, requiring 115.53 seconds processing time and low power consumption.…”
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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…Key algorithms are systematically integrated to optimize outcomes in urban planning, disaster management, and precision agriculture. …”
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Augmenting Naïve Bayes Classifiers with <i>k</i>-Tree Topology by Fereshteh R. Dastjerdi, Liming Cai

“…As powerful tools for classification tasks, Bayesian classifiers often require computing joint probability distributions, which can be computationally intractable due to potential full dependencies among feature variables. …”
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Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…We demonstrate the effectiveness of both the I-DFCM algorithm and the new validation indices through computational experiments using both synthetic and real-world datasets. …”
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Efficient Resources Provisioning Based on Load Forecasting in Cloud by Rongdong Hu, Jingfei Jiang, Guangming Liu, Lixin Wang

“…We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. …”
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BOLT LOOSENING ANGLE DETECTION METHOD BASED ON COLOR SEGMENTATION by KANG Jingjie, ZHANG Lijun, SUN Yuandong, YANG Xiaoyu, WANG Ruolan, ZHAO Tianhao

“…Then, the orientation vector of the connected domain in the anti-loose line image was determined by computing the geometric moments. Finally, the bolt loosening angle was determined through the four-quadrant arctangent function. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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Multi-Scale Feature Fusion and Context-Enhanced Spatial Sparse Convolution Single-Shot Detector for Unmanned Aerial Vehicle Image Object Detection by Guimei Qi, Zhihong Yu, Jian Song

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Epileptic Seizure Detection in EEG Signals Using Machine Learning and Deep Learning Techniques by Hepseeba Kode, Khaled Elleithy, Laiali Almazaydeh

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On the Achievable User Number of the Downlinks in Cellular-Based Machine-to-Machine Communications by Yingbo Li, Chen Chen, Lin Bai, Ye Jin

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The Sea-Based Waste Collection Routing Problem Using a Novel Value Recovery Function by Ricardo C. Alindayu II, Jayne Lois San Juan, Charlle L. Sy

“…A modified ant colony optimization algorithm was constructed to arrive at near-optimal solutions within a reasonable computing time given the problem’s NP-hard nature. …”
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Analysis of Energy Consumption in a Federated Learning-Based Zero-Touch Network by Urooj Yousuf Khan, Musharaf Ali Talpur, Umme Laila, Samar Raza Talpur

“…A pivotal point in Zero-Touch Networks is the selection of an optimal machine-learning algorithm. One such algorithm is Federated learning which relies on local updates of a global model. …”
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Intelligent Diagnosis of Rolling Element Bearings Under Various Operating Conditions Using an Enhanced Envelope Technique and Transfer Learning by Ali Davoodabadi, Mehdi Behzad, Hesam Addin Arghand, Somaye Mohammadi, Len Gelman

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