Information Bottleneck Driven Deep Video Compression—IBOpenDVCW by Timor Leiderman, Yosef Ben Ezra

“…Video compression remains a challenging task despite significant advancements in end-to-end optimized deep networks for video coding. This study, inspired by information bottleneck (IB) theory, introduces a novel approach that combines IB theory with wavelet transform. …”
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SE-TFF: Adaptive Tourism-Flow Forecasting Under Sparse and Heterogeneous Data via Multi-Scale SE-Net by Jinyuan Zhang, Tao Cui, Peng He

“…This paper presents SE-TFF, a multi-scale tourism-flow forecasting framework that couples a Squeeze-and-Excitation (SE) network with reinforcement-driven optimization to adaptively re-weight environmental, economic, and social features. …”
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SAR-PATT: A Physical Adversarial Attack for SAR Image Automatic Target Recognition by Binyan Luo, Hang Cao, Jiahao Cui, Xun Lv, Jinqiang He, Haifeng Li, Chengli Peng

“…In the digital world, we achieved an average fooling rate of up to 99.02% for three objects in six classification networks. …”
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Estimating Aggregate Capacity of Connected DERs and Forecasting Feeder Power Flow With Limited Data Availability by Amir Reza Nikzad, Amr Adel Mohamed, Bala Venkatesh, John Penaranda

“…However, forecasting, power flow analysis, and optimization of feeders for operational decision-making by individually modeling each of these numerous renewables in the absence of complete information are operationally challenging and technically impractical. …”
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Modeling of Battery Storage of Photovoltaic Power Plants Using Machine Learning Methods by Rad Stanev, Tanyo Tanev, Venizelos Efthymiou, Chrysanthos Charalambous

“…Among the main objectives of this study is to propose hyperparameter optimization for the included models, research the optimal training period for the available data, and find the best model from the ones included in the study. …”
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Forecasting sea level rise using enhanced deep learning models by M. Sami Zitouni, Leena Elneel, Naseeb Assad Albakri, Mohammed Q. Alkhatib, Hussain Al-Ahmad

“…This study evaluates statistical and deep learning models, including the Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, for predicting SLR and visualizing potentially inundated areas in the United Arab Emirates (UAE) via an interactive web interface. …”
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Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neura... by Mizuho Nishio, Osamu Sugiyama, Masahiro Yakami, Syoko Ueno, Takeshi Kubo, Tomohiro Kuroda, Kaori Togashi

“…For the DCNN method, CADx was evaluated using the VGG-16 convolutional neural network with and without transfer learning, and hyperparameter optimization of the DCNN method was performed by random search. …”
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Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance by Min Cheng, Jiawei Yu, Mingkang Wu, Yayao Zhang, Yihua Zhu, Yuanfu Zhu

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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…Nevertheless, the search for optimal task allocation and energy management in such environments continues. …”
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MS3D: A Multi-Scale Feature Fusion 3D Object Detection Method for Autonomous Driving Applications by Ying Li, Wupeng Zhuang, Guangsong Yang

“…This study introduces MS3D (Multi-Scale Feature Fusion 3D Object Detection Method), a novel approach to 3D object detection that leverages the architecture of a 2D Convolutional Neural Network (CNN) as its core framework. It integrates a Second Feature Pyramid Network to enhance multi-scale feature representation and contextual integration. …”
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Evaluation of Wireless LAN Quality of Service (QoS) in Primary Education Using TIPHON Standards by Hizkiana Ruli Oktaseli, Andika Agus Slameto

“…The evaluation was conducted using Wireshark to monitor network traffic. The results show that the average throughput for video streaming is 4.251 Kbps, browsing is 1.425 Kbps, and downloading is 3.106 Kbps. …”
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Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…This paper explores the application of algorithm-optimized back propagation neural networks and support vector machines in predicting the costs of office buildings. …”
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DynBlock: dynamic data encryption with Toffoli gate for IoT by Mubasher Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Moid Sandhu, Abd Ullah Khan, Hyundong Shin

“…DynBlock leverages Tofoli gates and XOR operations to reduce the number of computation operations required to achieve optimal throughput and energy efficiency. Security validation of DynBlock is performed considering various metrics, including an average key avalanche effect of 53.85%, average plain-text avalanche effect of 57.82%, differential cryptanalysis ( $$\Delta = 2^{-128}$$ ), and cryptanalysis ( $$\Lambda = 2^{-64}$$ ). …”
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Automatic segmentation and volume measurement of anterior visual pathway in brain 3D-T1WI using deep learning by Yongliang Han, Haixiang Wang, Qi Luo, Jingjie Wang, Chun Zeng, Qiao Zheng, Linquan Dai, Yiqiu Wei, Qiyuan Zhu, Wenlong Lin, Shaoguo Cui, Yongmei Li

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Research on Electric Vehicle Charging Load Prediction Methods Combining Signal Noise Reduction and Time Series Modeling by Liyun Liu, Xiaomei Xu, Jinsong Zhang, Dong Li

“…This study introduces a hybrid deep learning model combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Networks (CNN), Bi-directional Gated Recurrent Units (BiGRU), and Attention Mechanism (AM) to address the volatility in charging load patterns. …”
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An Innovation Machine Learning Approach for Ship Fuel-Consumption Prediction Under Climate-Change Scenarios and IMO Standards by Bassam M. Aljahdali, Yazeed Alsubhi, Ayman F. Alghanmi, Hussain T. Sulaimani, Ahmad E. Samman

“…Climate-change simulations showed that fuel consumption increases by an average of 22% for bulk carriers and 19% for container ships, highlighting the importance of operational optimizations. …”
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Lightweight Attention-Based CNN Architecture for CSI Feedback of RIS-Assisted MISO Systems by Anming Dong, Yupeng Xue, Sufang Li, Wendong Xu, Jiguo Yu

“…This approach not only improves network representational efficiency but also reduces redundant computations, leading to optimized computational complexity. …”
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Adaptive SDN switch migration mechanism based on coalitional game by Lan YAO, Julong LAN

“…The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.…”
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Predicting Olympic Medal Performance for 2028: Machine Learning Models and the Impact of Host and Coaching Effects by Zhenkai Zhang, Tengfei Ma, Yunpeng Yao, Ningjia Xu, Yujie Gao, Wanwan Xia

“…Great coaches can bring an average increase of 0.2 to 0.5 medals for each athlete. …”
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AI and Data Analytics in the Dairy Farms: A Scoping Review by Osvaldo Palma, Lluis M. Plà-Aragonés, Alejandro Mac Cawley, Víctor M. Albornoz

“…In the selected studies, the artificial neural network methods have considerable accuracy, recall, precision, and F1 Scores on average but with high ranges and standard deviations. …”
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