Leveraging machine learning to optimize cooling tower efficiency for sustainable power generation by M. A. Mujtaba, Muhammad Adeel Munir, Muhammad Akhtar, Bilal Mahmood, Talha Ansar, Zeeshan Khawar, Shayan Khalid, Abdul Basit, Saud Jamil, M. A. Kalam, Fayaz Hussain, Chiranjib Bhowmik

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Research on early warning model of coal spontaneous combustion based on interpretability by Huimin Zhao, Xu Zhou, Jingjing Han, Yixuan Liu, Zhe Liu, Shishuo Wang

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Multi-Step Span Loss Prediction in Optical Networks Using Multi-Head Attention Transformers by Maryam Hedayatnejad, Yinqing Pei, David Boertjes, Dacian Demeter, Christian Desrosiers, Christine Tremblay

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A model to simulate human cardio-respiratory responses to different fluid resuscitation treatments after hemorrhagic injury by Varghese Kurian, Varghese Kurian, Xin Jin, Xin Jin, Sridevi Nagaraja, Sridevi Nagaraja, Anders Wallqvist, Jaques Reifman

“…Decision-support systems based on artificial intelligence and machine learning algorithms can enhance the capability and capacity of medics to provide care for combat casualties during large-scale combat operations. …”
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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

“…Moreover, this paper provides a critical review of open research directions including the scalability of hybrid AI models, edge intelligence integration, and the evolution of standardised protocols for safe and smooth AI deployment in 6G networks.…”
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AirTrace-SA: Air Pollution Tracing for Source Attribution by Wenchuan Zhao, Qi Zhang, Ting Shu, Xia Du

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Automatic Endoscopic Navigation for Monocular Depth and Ego-Motion Estimation in Wireless Capsule Endoscopy Through Transformer Network by Junjun Huang, Tianran He, Juan Xu, Weiting Wu, Wei Wu

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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

“…Three machine learning models—Random Forest, Naïve Bayes, and Support Vector Machine (SVM) were trained and assessed based on Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and an Equivalent Accuracy metric. …”
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Solar Energy Forecasting Framework Using Prophet Based Machine Learning Model: An Opportunity to Explore Solar Energy Potential in Muscat Oman by Mazhar Baloch, Mohamed Shaik Honnurvali, Adnan Kabbani, Touqeer Ahmed, Sohaib Tahir Chauhdary, Muhammad Salman Saeed

“…The model evaluation metrics used in this study include the mean absolute error (MAE), the root mean squared error (RMSE), R², and mean bias deviation (MBD). …”
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Development of improved deep learning models for multi-step ahead forecasting of daily river water temperature by Mehdi Gheisari, Jana Shafi, Saeed Kosari, Samaneh Amanabadi, Saeid Mehdizadeh, Christian Fernandez Campusano, Hemn Barzan Abdalla

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Evaluation and deep learning-based calibration of nearshore sea surface wind speeds from FY-3E GNOS-II and Tianmu-1 missions by Xinhai Han, Xiaohui Li, Jingsong Yang, Wei Tao, Guoqi Han, Jiuke Wang, Yiqi Wang, Qinghua Bao, Lin Chen, Weiqiang Li

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A high-gain THz microstrip patch antenna designed for IoT and 6G communications with predicted efficiency using machine learning approaches by Md Sharif Ahammed, Redwan A. Ananta, Jun-Jiat Tiang, Mouaaz Nahas, Narinderjit Singh Sawaran Singh, Md. Ashraful Haque

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Transcription Factors Involved in Plant Stress and Growth and Development: NAC by Chenjia Zheng, Qin Yang, Xin Wang, Yu Chen, Ruoyu He, Xinmeng Li, Huanhuan Pan, Renying Zhuo, Tongbao Qu, Wenmin Qiu

“…To this end, this paper proposes to build an ‘NAC regulatory map database’ and use synthetic biology and artificial intelligence technology to design smarter, stress-tolerant and high-yielding crops, overcoming the limitations of traditional research.…”
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Validation of LLM-Generated Object Co-Occurrence Information for Understanding Three-Dimensional Scenes by Kenta Gunji, Kazunori Ohno, Shuhei Kurita, Ken Sakurada, Ranulfo Bezerra, Shotaro Kojima, Yoshito Okada, Masashi Konyo, Satoshi Tadokoro

“…The results revealed that GPT-4 achieved a high recall of 0.78 across various situation categories annotated by ScanNet v2, although its precision was relatively low at an average of 0.29. The root mean square error of the co-occurrence coefficient was 0.31. …”
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SYMMETRY PRINCIPLE AS A BASIS FOR INTEGRATION IN SCIENCE AND ITS VALUE FOR EDUCATION by V. L. Gapontsev, V. A. Fedorov, M. G. Gapontseva

“…Students’ thinking and consciousness become fragmented due to the exorbitant, permanently increasing amount of information that is presented for learning, but cannot be fully mastered by students. The root cause is imbalance in the curriculum levels of integration and differentiation (with a roll in the direction of the latter). …”
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Bridging IoT devices and machine learning for predicting power consumption: case study universitas Widya Dharma Pontianak by Genrawan Hoendarto, Ahmad Saikhu, Raden Venantius Hari Ginardi

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Deep learning-based novel ensemble method with best score transferred-adaptive neuro fuzzy inference system for energy consumption prediction by Birce Dağkurs, İsmail Atacak

“…Therefore, from the past to the present, numerous methods have been conducted using collected data, employing both statistical and artificial intelligence (AI)-based approaches, to achieve successful energy consumption predictions. …”
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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…The hybrid optimal intelligence algorithm (BOA-SVR) has improved model accuracy across multiple domains by combining BOA and SVR. …”
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Spatiotemporal inhomogeneity of accuracy degradation in AI weather forecast foundation models: A GNSS perspective by Junsheng Ding, Wu Chen, Junping Chen, Jungang Wang, Yize Zhang, Lei Bai, Yuyan Wang, Xiaolong Mi, Tong Liu, Duojie Weng

“…We calculated the mean deviation, mean absolute error, and root mean square error of these data. Using these metrics, we analyzed the spatiotemporal inhomogeneity in the accuracy degradation of foundation models, represented by Huawei Cloud Pangu-Weather, Google DeepMind GraphCast, and Shanghai AI Lab FengWu. …”
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Development of a GPT-4–Powered Virtual Simulated Patient and Communication Training Platform for Medical Students to Practice Discussing Abnormal Mammogram Results With Patients: M... by Dan Weisman, Alanna Sugarman, Yue Ming Huang, Lillian Gelberg, Patricia A Ganz, Warren Scott Comulada

“…These nascent developmental practices have not taken root in the literature to guide other researchers in developing their own simulations. …”
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