CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Addressing this obstacle is crucial for improving diagnostic accuracy and optimizing treatment strategies for those affected by AD. …”
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Performance of M-QAM MIMO PNC Based on MRC and ZR Techniques by Alaa A. Yassin, Ebtihal H. G. Yousif, Rashid A. Saeed, Hashim Elshafie, Abdullah Alenizi, Hesham Alhumyani

“…Maximum Ratio Combining (MRC) and Zero-Forcing (ZF) for the receive/transmit diversity techniques are used at the relay node to reduce multi-user interference. The system model is based on denoise-and-forward (DNF) relaying along with the Latin Square (LS) mapping algorithm at the relay node and square M-ary Quadrature Amplitude Modulation (M-QAM) at all nodes. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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Emergency evacuation planning in natural disasters under diverse population and fleet characteristics by Evangelia Baou, Vasilis P. Koutras, Vasileios Zeimpekis, Ioannis Minis

“…Design/methodology/approach – The problem is formulated using a mixed integer linear programming model and solved using a heuristic algorithm. The authors analyze the selected heuristic with respect to key parameters and use it to address theoretical and practical case studies. …”
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Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. …”
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Dynamic Pricing Strategy for Data Product Through Deep Reinforcement Learning by Junxin Shen, Yashi Wang, Fanghao Xiao

“…First, the dynamic pricing problem for data products is modeled as a Markov Decision Process (MDP). Then, a dynamic pricing algorithm based on the Deep Q-learning algorithm is designed, incorporating an annealing mechanism to optimize the exploration strategy. …”
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Numerical Methodology for Enhancing Heat Transfer in a Channel with Arc-Vane Baffles by Piphatpong Thapmanee, Arnut Phila, Khwanchit Wongcharee, Naoki Maruyama, Masafumi Hirota, Varesa Chuwattanakul, Smith Eiamsa-ard

“…The calculations utilize the finite volume method, and the SIMPLE algorithm is executed with the QUICK scheme. For the analysis of turbulent flow, the finite volume method with the Renormalization Group (RNG) <i>k-ε</i> turbulence model was used. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…Globally, enterprises are undergoing significant transformation in line with developments based on industrial revolution by leveraging extensive computing resources, data capture technologies, information processing systems, and advanced data science models that span analytics, optimization, and algorithmic intelligence. …”
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Parallel Machine Production and Transportation Operations’ Scheduling with Tight Time Windows by Yang Jiang, Tong He, Jie Xiong, Xin Wu, Yao Chen

“…The results show that the use of the system coordination model in this method obviously improves the number of successful transfers and deliveries.…”
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Risk Limiting Based Resilient Operation Method for Power Grid by Xiyue WANG, Hao ZHANG, Chaoyi PENG

“…By deriving three intermediate state models of RLB and their analytical solutions, we present an iterative RLB solution algorithm based on intermediate state models and provide a rigorous proof of its global optimality. …”
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Full lifecycle security management scheme for terminal keys under power IoT by Wang Hui, Yuan Jiahui, Shi Zhentong, Fang Mu

“…Firstly, the two-stage key distribution architecture based on the state secret algorithm is adopted in the scheme to achieve secure access authentication of power terminals at different stages. …”
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Vibration Control of Wind Turbine Blade Based on Data Fitting and Pole Placement with Minimum-Order Observer by Tingrui Liu, Lin Chang

“…It not only ensures certain accuracy, but also greatly improves the speed of calculation. The Wilson method, developed on the basis of the blade momentum theory, is adopted to optimize the structural parameters of the blade, with all parameters fitted as general model Sin6 (Sum of Sine) fitting curves. …”
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Three-Dimensional in Vivo Imaging of Green Fluorescent Protein-Expressing T Cells in Mice with Noncontact Fluorescence Molecular Tomography by Anikitos Garofalakis, Giannis Zacharakis, Heiko Meyer, Eleftherios N. Economou, Clio Mamalaki, Joseph Papamatheakis, Dimitris Kioussis, Vasilis Ntziachristos, Jorge Ripoll

“…By measuring multiple projections, large data sets can be obtained, thus improving the accuracy of the inversion models used for quantitative three-dimensional reconstruction of fluorochrome distribution, as well as facilitating a higher spatial resolution. …”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…However, existing high-precision detection algorithms are challenging to deploy on performance-constrained IoT underwater devices due to their large computational complexity and model size. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…We propose CWA-YOLO, a detection framework integrating multi-scale feature fusion and an enhanced small-object detection head into YOLOv8 to improve accuracy across variable conditions. Additionally, a federated learning (FL) system tailored for substations enables collaborative model training without centralized data sharing, addressing privacy concerns and data heterogeneity. …”
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Enhancing Energy Efficiency of Sensors and Communication Devices in Opportunistic Networks Through Human Mobility Interaction Prediction by Ambreen Memon, Sardar M. N. Islam, Muhammad Nadeem Ali, Byung-Seo Kim

“…The contribution of this research is that it highlights the limitations of existing mobility prediction models and develops new resource optimization and energy-efficient opportunistic networks that overcome these limitations.…”
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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

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The Influence of Process and Slag Parameters on the Liquid Slag Layer in Continuous Casting Mold for Large Billets by Zhijun Ding, Chao Wang, Xin Wang, Pengcheng Xiao, Liguang Zhu, Shuhuan Wang

“…In the continuous casting of special steel blooms, low casting speeds result in slow renewal of the molten steel surface in the mold, adversely affecting mold flux melting and liquid slag layer supply, which may lead to surface cracks, slag entrapment, and breakout incidents. To optimize the flow and heat transfer behavior in the mold, a three-dimensional numerical model was developed based on the VOF multiphase flow model, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>−</mo><mi>ϵ</mi></mrow></semantics></math></inline-formula> RNG turbulence model, and DPM discrete phase model, employing the finite volume method with SIMPLEC algorithm for solution. …”
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Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). …”
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