Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Utilizing remote sensing technology to accurately and efficiently extract paddy rice planting area is crucial for ensuring food security. …”
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Parameter optimization of Mg reduction by thermo-silicon method using Taguchi method, grey relational analysis and preference selection index by Quyen Vu Viet

“…An Fe-Si ratio of 1.3 consistently production efficiency and reducing agent costs. The results demonstrates the efficacy of multi-criteria decision-making techniques in refining complex metallurgical processes and elucidates the interdependencies among operating parameters, offering actionable insights to enhance magnesium yield and ferrosilicon efficiency.…”
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Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

“…The early diagnosis of AD is a challenging task due to complex pathophysiology caused by the presence and accumulation of neurofibrillary tangles and amyloid plaques. …”
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Explainable artificial intelligence with fusion-based transfer learning on adverse weather conditions detection using complex data for autonomous vehicles by Khaled Tarmissi, Hanan Abdullah Mengash, Noha Negm, Yahia Said, Ali M. Al-Sharafi

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Development of Decision Support Model for Selecting a Maintenance Plan Using a Fuzzy MCDM Approach: A Theoretical Framework by Fathia Sghayer Abdulgader, Rajeh Eid, Babak Daneshvar Rouyendegh

“…In complex decision making, using multicriteria decision-making (MCDM) methodologies is the most scientific way to ensure an informed and justified decision between several alternatives. …”
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Mechanisms for selective flotation separation of chalcopyrite and molybdenite using the novel depressant 2-(carbamimidoylthio)acetic acid: Experimental and DFT study by Xiangwen Lv, Anruo Luo, Xiong Tong, Jianhua Chen, Sheng Jian

“…This advancement addresses critical challenges in processing complex ores, offering environmental and economic benefits through reduced reagent consumption and improved resource utilization efficiency.…”
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Multi-head deep Q-learning for continuous beamforming with selective MC-CDMA operation in V2X highway communications by Nguyen Huu Trung, Nguyen Thuy Anh, Fuqiang Liu

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Resolving Non-Proportional Frequency Components in Rotating Machinery Signals Using Local Entropy Selection Scaling–Reassigning Chirplet Transform by Dapeng Quan, Yuli Niu, Zeming Zhao, Caiting He, Xiaoze Yang, Mingyang Li, Tianyang Wang, Lili Zhang, Limei Ma, Yong Zhao, Hongtao Wu

“…In response to these issues, an enhanced time–frequency analysis approach, termed Local Entropy Selection Scaling–Reassigning Chirplet Transform (LESSRCT), has been developed to improve the representation accuracy for complex non-stationary signals. …”
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A new scheme for boosting in situ Fenton-like reaction in plant pathogenic tissues for selective structural degradation of capsid proteins by Jun Ma, Ming Chen, Yujie Wang, Jiaying Li, Jian Tang, Shengjun Wu, Chi He, J. Paul Chen

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Micro-nano manufacturing of a pre-identified organic hydrogel surface for selective oil/water separation with ultra-high flux by Yun-yun Song, Jiang-shen Lu, Yang Zhang, Zhao-peng Yu, Yan Liu, Zhong-qiang Zhang

“…The oily wastewater system is complex and most membrane materials cannot separate various oil-water mixtures. …”
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A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

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Optimal Industrial Waste Management Strategy for Pakistan Steel Mill Corporation Using Complex Spherical Fuzzy Einstein Aggregation Information by Ijaz Ur Rahman, Shahzaib Ashraf, Bushra Batool, K. C. Gokul

“…Applying greater generality in the dimensions of the abovementioned applications could potentially enhance a lot of their efficiency. Einstein norms/application of Einstein operations have not been effectively applied within the complex spherical fuzzy sets (CSFSs) framework as such; this study now advances the application of Einstein operators in CSFS which would provide an adiaphorous approach to solving issues related to decision-making problems (DMPs). …”
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Multi-model MCDM framework for sustainable renewable energy selection in India: integrating CRITIC-EDAS-CODAS-CoCoSo by Shankha Shubhra Goswami, T. Tapankumar, N. Channa Keshava Naik, J. Gowrishankar, Nilesh Bhosle, Amrita Singh, G. Sanyasi Raju, D. Nagesh, A. Johnson Santhosh

“…Abstract The global boom in the importance of renewable energy (RE) resources has accelerated the transition from traditional energy sources to sustainable alternatives. Selecting an optimum RE power plant is a complex task influenced by geographical factors, climatic differences, and regional peculiarities. …”
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Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…Identifying LRRC through imaging is complex, due to the mismatch between fibrosis and inflammatory pelvic tissue. …”
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Selective disruption of aurora C kinase reveals distinct functions from aurora B kinase during meiosis in mouse oocytes. by Ahmed Z Balboula, Karen Schindler

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PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity by Nakul Mehta, Nitesh Bharot, John G. Breslin, Priyanka Verma

“…Coping strategies for such challenges frequently involve transferring data to a central location, which raises concerns about latency, efficiency, and privacy. To address these issues, Federated Learning (FL) was developed as a solution to mitigate both the privacy concerns of organizations and the complexities of networked systems. …”
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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling by Maqsood Ahmed, Xiang Zhang, Yonglin Shen, Tanveer Ahmed, Shahid Ali, Ayaz Ali, Aminjon Gulakhmadov, Won-Ho Nam, Nengcheng Chen

“…Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. …”
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Dynamic Reporting Nodes Selection Method for Network Awareness Based on Active–Passive Integrated Network Telemetry in LEO Satellite Networks by Hang Di, Tao Dong, Zhihui Liu, Shuotong Wei, Qiwei Zhang, Dingyun Zhang

“…Satellite network awareness is a key technology for obtaining the status of onboard resources and supporting efficient network management. However, the dynamic characteristics of the network topology results in dynamic transmission delays of awareness data, while the instability of satellite-ground links poses challenges in selecting awareness reporting nodes. …”
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An interpretable and adaptable data-driven model for performance prediction in thermal plants by G. Prokhorskii, M. Preißinger, S. Rudra, E. Eder

“…Data-driven models are a useful aid for monitoring and control of thermal power plants, but they require an effective feature selection to allow for an accurate, computationally efficient, and interpretable model. …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

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