Overview of Startups Developing Artificial Intelligence for the Energy Sector by Naiyer Mohammadi Lanbaran, Darius Naujokaitis, Gediminas Kairaitis, Gabrielė Jenciūtė, Neringa Radziukynienė

“…Startup companies in this revolution use AI technologies like Machine Learning (ML), predictive analytics, and optimization algorithms to improve energy efficiency, optimize grid management, and incorporate renewable energy sources. …”
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Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…There has been relatively little study on explainability, especially when dealing with malware imagery data, irrespective of the fact that DL/ML algorithms have revolutionized malware detection. Explainability techniques such as SHAP, LIME, and Grad-CAM approaches are employed to present a complete comprehension of feature significance and local or global predictive behavior of the model over various malware categories. …”
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Behavior Modeling and Bio-Hybrid Systems: Using Reinforcement Learning to Enhance Cyborg Cockroach in Bio-Inspired Swarm Robotics by Le Minh Triet, Nguyen Truong Thinh

“…Future work will explore scaling the swarm system and integrating advanced sensors and AI algorithms.…”
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Exploring the comprehensive integration of artificial intelligence in optimizing HVAC system operations: A review and future outlook by Shengze Lu, Shiyu Zhou, Yan Ding, Moon Keun Kim, Bin Yang, Zhe Tian, Jiying Liu

“…The main features of the AI technology are first introduced. The main algorithms of supervised learning, reinforcement learning, and deep learning are then analyzed in the fields of air conditioning operation optimization, energy consumption prediction and control, indoor environmental protection, and fault detection and diagnosis. …”
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Research on economic dispatching strategy for active distribution network considering high penetration of renewable energy source by ZHANG Yu, YUAN Bo, HUANG Shicheng, SHI Jinyue, AN Yichen

“…Finally, building upon the multi-agent deep deterministic policy gradient (MADDPG) algorithm, the bidirectional gated recurrent unit (BiGRU) is employed instead of fully connected layers for renewable energy output prediction, effectively mitigating the impact of renewable energy fluctuations. …”
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A continuous multi-night sleep database for exploring sleep structure similarity by Shaofei Ying, Junze Fu, Lin Wang, Haokai Zhang, Yue Yu, Hongqiong Wang, Jiaxin Xie, Tiejun Liu

“…It provides valuable opportunities to investigate the physiological mechanisms of sleep structure continuity, advancing sleep features recognition and prediction algorithms, and designing individualised templates for closed-loop sleep stimulation. …”
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Characterization of the immune cell infiltration patterns in lung adenocarcinoma to facilitate immunotherapy by Haili Li, Zanmei Qin, Xuemei Huang, Zuyou Wei, JingMin Deng

“…Herein, ESTIMATE and CIBERSORT algorithms were conducted to characterize the ICI patterns of 1155 patients with LUAD. …”
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Calculation of the Respiratory Modulation of the Photoplethysmogram (DPOP) Incorporating a Correction for Low Perfusion by Paul S. Addison, Rui Wang, Scott J. McGonigle, Alberto A. Uribe, Sergio D. Bergese

“…We implemented an automated DPOP algorithm with an optional correction for low perfusion. …”
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Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO by Mao Li, Hao Ding, Meiqi Wang, Xingda Yang, Bin Kong

“…Firstly, the chaotic map is introduced into the population initialization process of the golden jackal algorithm. In the later stage of the algorithm iteration, random disturbance is introduced with optimization algebra as the switching condition to obtain an improved optimization algorithm, and the performance index of the optimization algorithm is verified to be superior to other algorithms. …”
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Automated Fillet Weld Inspection Based on Deep Learning from 2D Images by Ignacio Diaz-Cano, Arturo Morgado-Estevez, José María Rodríguez Corral, Pablo Medina-Coello, Blas Salvador-Dominguez, Miguel Alvarez-Alcon

“…Following an extensive review of available solutions, algorithms, and networks based on this convolutional strategy, it was determined that the You Only Look Once algorithm in its version 8 (YOLOv8) would be the most suitable for object detection due to its performance and features. …”
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Recent Advances in Creep Modelling Using the <i>θ</i> Projection Method by William Harrison

“…Using a power law approach along with optimisation algorithms, the residual error between predicted and experimentally observed creep curves is reduced. …”
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Comprehensive VR dataset for machine learning: Head- and eye-centred video and positional dataThe Adaptive Mind Datahub by Alexander Kreß, Markus Lappe, Frank Bremmer

“…Researchers can leverage this extensive dataset to develop and refine algorithms requiring comprehensive and annotated video and positional data. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…Logistic regression (n = 459) remains the most widely used algorithm, while neural networks (n = 183) show promising potential. …”
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The interpretable machine learning model for depression associated with heavy metals via EMR mining method by Site Xu, Mu Sun

“…The optimal model was selected after parameter tuning with a Genetic Algorithm (GA). To enhance the interpretability of the model’s predictions, we applied SHapley Additive exPlanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) algorithms. …”
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Spectroscopy-Based Methods and Supervised Machine Learning Applications for Milk Chemical Analysis in Dairy Ruminants by Aikaterini-Artemis Agiomavriti, Maria P. Nikolopoulou, Thomas Bartzanas, Nikos Chorianopoulos, Konstantinos Demestichas, Athanasios I. Gelasakis

“…Currently, the advancements and utilization of spectroscopy-based techniques combined with machine learning algorithms have made the development of analytical tools and real-time monitoring and prediction systems in the dairy ruminant sector feasible. …”
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Deep Learning Based Early Intrusion Detection in IIoT using Honeypot by Abbasgholi Pashaei, Mohammad Esmaeil Akbari, Mina Zolfy Lighvan, Asghar Charmin

“…The accuracy of DL algorithms has been shown across a range of scientific fields. …”
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Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…Recent advances in artificial intelligence (AI) have further enhanced the field by improving target prediction and streamlining data analysis. AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
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Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets by Weichuan Xiong, Yian Zhan, Rui Xiao, Fangpeng Liu

“…Prediction models were constructed and validated using six machine learning algorithms, achieving high accuracy (AUC > 0.75). …”
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Mir-494-3p enhances aggressive phenotype of non-small cell lung cancer cells by regulating SET/I2PP2A by Yuwen Du, Taisuke Kajino, Yukako Shimada, Takashi Takahashi, Ayumu Taguchi

“…Integration of RNA sequencing analysis of NSCLC cells with miR-494-3p inhibition and a bioinformatic search of miRNA target prediction algorithms resulted in identification of SET/I2PP2A as a direct target of miR-494-3p. …”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

“…The system is able to function independently thanks to the use of machine learning algorithms, including LSTM for prediction, Kalman filter for data cleaning, Isolation Forest for anomaly detection, and K-means for clustering sleep patterns.…”
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