Coverage, Throughput, and Energy Efficiency Enhancement in Beamspace Massive MIMO System Using Rate-Splitting and Orthogonal Precoding by David Alimo, Masanori Hamamura, Saifur Rahman Sabuj

“…Following that, we offer an alternating method to solve the approximate optimization issue and select an optimal solution. Furthermore, we deduce an analytic expression for the downlink cell coverage percentage and evaluate the effectiveness of the suggested method in terms of total throughput, energy efficiency, and cell coverage percentage. …”
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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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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

“…The cost control challenge in construction and installation projects has always been a critical concern for construction entities. The complexity of task collaboration among various equipment and nodes during the installation process leads to extended construction duration, resulting in increased construction costs. …”
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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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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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Identifying factors affecting the creation of social interactions and functional security (case study: Mehr housing in Boroujard city) by Seyed Mohammad Ali Ahmadi Tabatabaie, Ferial Ahmadi, Vahid Heidar Nattaj

“…by growth of population and the increasing need for housing, the establishment and design of Mehr housing complexes around cities began. However, due to reasons such as inappropriate location selection, the residence of individuals with different cultures, and the lack of a coherent plan, the quality does not meet the desired standards like a traditional Iranian house. …”
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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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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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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

“…This study proposes Air Quality Prediction-Mamba (AQP-Mamba), a video-based deep learning model that integrates a structured Selective State Space Model (SSM) with a selective scan mechanism and a hybrid predictor (HP) to estimate air quality. …”
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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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Research on Intrusion Detection Method Based on Transformer and CNN-BiLSTM in Internet of Things by Chunhui Zhang, Jian Li, Naile Wang, Dejun Zhang

“…With the widespread deployment of Internet of Things (IoT) devices, their complex network environments and open communication modes have made them prime targets for cyberattacks. …”
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H2O-balance-regulated cation–anion competitive coordination for selective elements extraction from spent lithium-ion batteries by Mingqiang Cheng, Yixin Hua, Qibo Zhang, Qihao Li, Hongda Li, Ding Wang, Xianshu Wang, Yun Zhao, Juanjian Ru, Baohua Li

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Incentivising cooperation by judging a group’s performance by its weakest member in neuroevolution and reinforcement learning by Jory Schossau, Bamshad Shirmohammadi, Arend Hintze, Arend Hintze

“…Notably, the introduced approach improves overall efficiency, as equitably-minded agents collectively achieve greater stability and higher individual outcomes than agents pursuing purely selfish strategies.DiscussionThis methodology aligns closely with biological mechanisms observed in nature, specifically group-level selection and inclusive fitness theory. …”
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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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Quantification and Flow Simulation of Ecosystem Service Supply and Demand in the Yellow River Delta High-Efficiency Eco-Economic Zone by Wenjun Liu, Xiangyi Ma, Qian Sun, Wei Qi, Xinyang Yu

“…This study selected the Yellow River Delta High-Efficiency Eco-Economic Zone in China as the case study area and assessed the habitat quality and carbon sequestration services for 2000, 2010, and 2020. …”
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DECISION SUPPORT SYSTEM IN PLANNING INVESTMENT PROJECTS by Viktor Kosenko

“…The following tasks were solved in the article: the model of complex planning was studied and the investment project was implemented, the method of selecting an optimal variant of investment project implementation was developed, the elements of the decision support system to select the investment method were specified. …”
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On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis by Banamali Panigrahi, Saman Razavi, Lorne E. Doig, Blanchard Cordell, Hoshin V. Gupta, Karsten Liber

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Methodolo- gical Aspects of Semantic Relationship Extraction for Automatic Thesaurus Generation by N. S. Lagutina, K. V. Lagutina, E. I. Mamedov, I. V. Paramonov

“…The main algorithm of generation consists of three stages: selection and preprocessing of a text corpus, recognition of thesaurus terms, and extraction of relations among terms. …”
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Graph-Based Warm Solutions for Optimal Resilience Enhancement of Water Distribution Networks by Mohsen Hajibabaei, Amin Minaei, Mohsen Shahandashti, Robert Sitzenfrei

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Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

“…The performance of the GLEO-coupled with the RFR model was compared with the standard Equilibrium Optimizer (EO) and other state-of-the-art algorithms in physical and physiological function estimation using biological signals.ResultsExperimental results showed that selected features and tuned hyperparameters demonstrated a significant improvement in root mean square error (RMSE), coefficient of determination (R2) and slope with values improving from 0.1330 to 0.1174, 0.7228 to 0.7853 and 0.6946 to 0.7414, respectively for the test dataset. …”
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