Zero-Shot Prediction of Conversational Derailment With Large Language Models by Kenya Nonaka, Mitsuo Yoshida

“…Previous studies have trained machine learning algorithms to detect conversational derailment using supervised methods. …”
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Energy-Saving Optimization of HVAC Systems Using an Ant Lion Optimizer with Enhancements by Bin Hu, Yuhu Guo, Wenjun Huang, Jianxiang Jin, Mingxuan Zou, Zhikun Zhu

“…This work will contribute to the development of energy-saving and emission-reduction technologies.…”
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A convolutional neural network model and algorithm driven prototype for sustainable tilling and fertilizer optimization by Sajeev Magesh

“…A 30-year simulation comparing conventionally-tilled and algorithm-tilled farms showed a reduction in carbon emission by 57%, fertilizer usage by 43%, and runoff by 86% demonstrating the transformative potential of this algorithm. …”
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A reduced dimension multiple signal classification–based direct location algorithm with dense arrays by Jianfeng Li, Gaofeng Zhao, Baobao Li, Xianpeng Wang, Mengxing Huang

“…Aiming at the issue of parameter matching in conventional two-step location, a reduced dimension multiple signal classification direct position determination algorithm based on multi-array is proposed. Based on the idea of dimension reduction, the algorithm avoids multi-dimensional search in spatial domain and attenuation coefficient domain and reduces the search complexity. …”
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Systems Biology of Human Microbiome for the Prediction of Personal Glycaemic Response by Nikhil Kirtipal, Youngchang Seo, Jangwon Son, Sunjae Lee

“…We explore how the gut microbiota affects glucose metabolism and insulin sensitivity by examining a variety of -omics data, including genomics, transcriptomics, epigenomics, proteomics, metabolomics, and metagenomics. Machine learning algorithms and genome-scale modeling are now being applied to find microbiological biomarkers associated with diabetes risk, predicted disease progression, and guide customized therapy. …”
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Smart Grid Security: Proactive Prediction of Advanced Persistent Threats by Motahareh Dehghan, Erfan Khosravain

“…This paper proposes the use of Deep Reinforcement Learning to enhance cybersecurity in smart grids by leveraging the ProAPT model, which is specifically designed to predict and mitigate Advanced Persistent Threats. …”
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Recent advances in AI-based toxicity prediction for drug discovery by Hyundo Lee, Jisan Kim, Ji-Woon Kim, Yoonji Lee, Yoonji Lee

“…Ongoing advances in databases, algorithms, and computational power have further expanded AI’s role in pharmaceutical research. …”
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Computational analysis and experimental validation of gene predictions in Toxoplasma gondii. by Joseph M Dybas, Carlos J Madrid-Aliste, Fa-Yun Che, Edward Nieves, Dmitry Rykunov, Ruth Hogue Angeletti, Louis M Weiss, Kami Kim, Andras Fiser

“…Commonly used gene prediction algorithms produce very disparate sets of protein sequences, with pairwise overlaps ranging from 1.4% to 12%. …”
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Cuproptosis genes in predicting the occurrence of allergic rhinitis and pharmacological treatment. by Ting Yi

“…Finally, AR signature genes were used as targets for drug prediction and molecular docking to identify candidate drugs that may affect SAR.…”
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Urban Microcirculation Traffic Network Planning Method Based on Fast Search Random Tree Algorithm by Ning YU

“…By incorporating target gravity into the RRT algorithm, a growth guidance function is obtained, optimising the planned path and completing urban microcirculation traffic network planning. …”
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Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

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Miniaturized NIRS Coupled with Machine Learning Algorithm for Noninvasively Quantifying Gluten Quality in Wheat Flour by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…The improved whale optimization algorithm iWOA-based SVR (iWOA-SVR) model exhibited the strongest predictive capability among the five optimal wavelengths-based models, achieving comparable accuracy to the full-range spectra SVR for all gluten parameters (R_P = 0.9190–0.9385, RMSEP = 0.3927–0.5743%, and RPD = 3.0424–3.2509). …”
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An Improved Artificial Neural Network Model for Effective Diabetes Prediction by Muhammad Mazhar Bukhari, Bader Fahad Alkhamees, Saddam Hussain, Abdu Gumaei, Adel Assiri, Syed Sajid Ullah

“…Data analytics, machine intelligence, and other cognitive algorithms have been employed in predicting various types of diseases in health care. …”
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Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions by Serdar Erisen

“…Dense predictions are deployed to augment the efficacy of dense-attention-boosting modules and dense-attention-fusion networks, enabling the extraction of global context feature maps in the encoder. …”
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Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer by Ruowu Wu, Yandan Liang, Lianlei Lin, Zongwei Zhang

“…Finally, we demonstrated the excellent effect of STWPM in multivariate spatiotemporal field weather prediction by comprehensively evaluating the proposed algorithm with classical algorithms on the ERA5 dataset in a global region.…”
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Integration of geospatial techniques and machine learning in land parcel prediction by Nekkanti Haripavan, Subhashish Dey, Chimakurthi Harika Mani Chandana

“…The integration of geospatial techniques and machine learning algorithms has revolutionized our ability to analyze and predict changes in land parcels. …”
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Credit card default prediction using ML and DL techniques by Fazal Wahab, Imran Khan, Sneha Sabada

“…Subsequently, various techniques are employed to preprocess the unprocessed data and visually present the outcomes through the use of exploratory data analysis (EDA). Furthermore, the algorithms are hypertuned to evaluate the enhancement in prediction. …”
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Predicting Court Judgment in Criminal Cases by Text Mining Techniques by Mohammad Farhadishad, Mohammad Kazemifard, Zahra Rezaei

“…Due to high pressures and stress, it may be difficult for them to carefully examine documents and evidence, which leads to more subjective judgments. Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. …”
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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

“…To tackle these issues, our research focused on developing a predictive model for STEM students using advanced ensemble machine learning algorithms. …”
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Prediction-Based Tip-Over Prevention for Planetary Exploration Rovers by Siddhant Shete, Raúl Domínguez, Ravisankar Selvaraju, Mariela De Lucas Álvarez, Frank Kirchner

“…By leveraging deep learning algorithms, the system evaluates predictions and true measurements in real time to identify potential tip-overs. …”
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