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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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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Enhanced Multiple Pulse Position Modulation Aided Reverse Polarity Optical OFDM System With Extended Dimming Control by Zixian Yang, Ming Jiang, Lin Zhang, Hong-Zhou Tan

“…It is shown that the proposed system with extended dimming control can achieve the highest effective spectral efficiency in most scenarios without substantially increasing the computational complexity, while still maintaining a power consumption level similar to those of the reference systems.…”
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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

“…On the basis of the blasting vibration data monitored during blasting excavation of the left abutment groove of the Baihetan hydropower station, the maximum charge per delay, distance from the blast face, height difference, and acoustic wave velocity were selected as the input parameters. Through a comprehensive evaluation of the running time results, the root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R2), a new algorithm, the grasshopper optimization algorithm (GOA), which is suitable for optimizing an ANN to predict PPV, is obtained. …”
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Leaching of heavy metals from post-neutralization sludge from zinc and lead metallurgy using complexing, alkaline and acidic agents by Milena Nocoń, Irena Korus, Gabriela Kamińska

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Integrate computation intelligence with Bayes theorem into complex construction installation: a heuristic two-stage resource scheduling optimisation approach by Jia Zhao, Wenhao Wang, Liyuan Zhang, Yan Ding

“…Experimental results demonstrate the effectiveness and efficiency of the MERD approach in reducing work time and cost in engineering projects.…”
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ChatGPT (GPT-4) versus doctors on complex cases of the Swedish family medicine specialist examination: an observational comparative study by Artin Entezarjou, Carl Wikberg, Ronny Gunnarsson, David Sundemo, Rasmus Arvidsson

“…Secondary: the correlation between differences in response length and response score; the intraclass correlation coefficient between reviewers; and the percentage of maximum score achieved by each group in different subject categories.Results The mean scores were 6.0, 7.2 and 4.5 for randomly selected doctor responses, top-tier doctor responses and GPT-4 responses, respectively, on a 10-point scale. …”
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Copper(I) Complexes with Terphenyl-Substituted NPN Ligands Bearing Pyridyl Groups: Synthesis, Characterization, and Catalytic Studies in the S-Arylation of Thiols by M. Trinidad Martín, Ana Gálvez del Postigo, Práxedes Sánchez, Eleuterio Álvarez, Celia Maya, M. Carmen Nicasio, Riccardo Peloso

“…These findings highlight the potential of well-defined Cu(I)–NPN complexes as efficient and versatile precatalysts for C–S bond formation.…”
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