A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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Service Function Chain Migration: A Survey by Zhiping Zhang, Changda Wang

“…Traditional optimization algorithms often fall short in large-scale, heterogeneous networks due to limited computational efficiency and scalability. …”
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Research on the effectiveness of data compression methods in relational and NoSQL DBMS by V. A. Egunov, V. S. Surin, P. S. Stupnitskiy, R. D. Akhmetova

“…Data compression in OpenSearch is more efficient than in MySQL when using standard algorithms. OpenSearch is an excellent choice if youneed to conserve storage resources while making optimal use of the processor, otherwise both systems will do the job well.…”
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Convolutional neural network model over encrypted data based on functional encryption by Chen WANG, Jiarun LI, Jian XU

“…Currently, homomorphic encryption, secure multi-party computation, and other encryption schemes are used to protect the privacy of sensitive data in outsourced convolutional neural network (CNN) models.However, the computational and communication overhead caused by the above schemes would reduce system efficiency.Based on the low cost of functional encryption, a new convolutional neural network model over encrypted data was constructed using functional encryption.Firstly, two algorithms based on functional encryption were designed, including inner product functional encryption and basic operation functional encryption algorithms to implement basic operations such as inner product, multiplication, and subtraction over encrypted data, reducing computational and communication costs.Secondly, a secure convolutional computation protocol and a secure loss optimization protocol were designed for each of these basic operations, which achieved ciphertext forward propagation in the convolutional layer and ciphertext backward propagation in the output layer.Finally, a secure training and classification method for the model was provided by the above secure protocols in a module-composable way, which could simultaneously protect the confidentiality of user data as well as data labels.Theoretical analysis and experimental results indicate that the proposed model can achieve CNN training and classification over encrypted data while ensuring accuracy and security.…”
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Addressing grading bias in rock climbing: machine and deep learning approaches by B. O’Mara, M. S. Mahmud

“…The primary three approaches were from a route-centric, climber-centric, or path finding and path generation context. Of these, the most optimal methods used natural language processing or recurrent neural network algorithms. …”
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Review of the Research on Underwater Explosion Ice-Breaking Technology by Xiao Huang, Zi-Xian Zhong, Xiao Luo, Yuan-Dong Wang

“…Key findings establish that shock waves initiate brittle fracture via stress superposition while bubble pulsation drives crack propagation through pressure oscillation; optimal ice fragmentation depends critically on charge weight, standoff distance, and ice thickness. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Regression and classification models were developed using gradient boosting, random forest, and CatBoost algorithms. Regression models predicted vault height as a continuous variable, while classification models categorized vault heights into binary and multi-class tasks. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…The fusion of Artificial intelligence (AI) with computational chemistry has revolutionized drug discovery by enhancing compound optimization, predictive analytics, and molecular modeling. …”
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ON TRAVERSABILITY COST EVALUATION FROM PROPRIOCEPTIVE SENSING FOR A CRAWLING ROBOT by Jakub Mrva, Martin Stejskal, Jan Faigl

“…This paper addresses the problem of traversability cost evaluation based on proprioceptive sensing for a hexapod walking robot while optimizing different criteria. We present several methods of evaluating the robot-terrain interaction that can be used as a cost function for an assessment of the robot motion that can be utilized in high-level path-planning algorithms.…”
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Advanced parameter tuning scheme for double CFO based fractional order composite controller synthesis method by Siyi Chen, Yang Shu, Haiyang Kuang, Dongqi Cheng, Ying Luo

“…This method sequentially employs D-decomposition and optimization algorithms to address these challenges. …”
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Utilizing UAVs in Wireless Networks: Advantages, Challenges, Objectives, and Solution Methods by Mohammad Javad Sobouti, Amirhossein Mohajerzadeh, Haitham Y. Adarbah, Zahra Rahimi, Hamed Ahmadi

“…Additionally, we discuss the main methods and algorithms employed for UAV placement and trajectory optimization. …”
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Deep Clustering of Student Code Strategies Using Multi-View Code Representation (CMVAE) by Zhengting Tang, Shizhou Wang, Liangyu Chen

“…The model captures structural features by transforming code into tree graphs and extracting centrality measures, while CodeBERT provides semantic embeddings. Through a joint optimization of reconstruction loss and clustering loss, the model effectively integrates multiple code representations. …”
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Integrated Waste Management in the Circular Economy Era: Insights from Research and Practice by Charisios Achillas, Christos Vlachokostas

“…Technological advancements, such as AI-driven waste sorting and route optimization algorithms, are highlighted alongside policy frameworks supporting circular economy principles. …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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Privacy-preserving method for face recognition based on homomorphic encryption. by Zhigang Song, Gong Wang, Wenqin Yang, Yunliang Li, Yinsheng Yu, Zeli Wang, Xianghan Zheng, Yang Yang

“…To overcome this limitation, this paper introduces an optimization scheme based on clustering algorithms to accelerate the facial recognition process within the HE_FaceNet framework. …”
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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

“…The paper provides an in-depth review of the literature, examining not only ML techniques but also optimization algorithms, evaluation methods, explainability techniques, and emerging technologies. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”
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In-situ data of occupant behavior and thermal comfort in 11 offices in a naturally ventilated building during 6 summersDataverse by Simon Bal-Fontaine, Pierre Bernaud, Kevin Campagna, Hugo Coulandreau, Aurélie Foucquier, Arnaud Jay, Merveil Muanda Lutete

“…This dataset also facilitates the development of ventilation control algorithms and cascade cooling strategies by analyzing the conditions under which occupants use desk fans, helping optimize mixed-mode ventilation systems for comfort and efficiency.…”
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Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach by Mohammed Aly, Mohamed H. Behiry

“…Abstract Three machine learning algorithms—Logistic Boosting, Random Forest, and Support Vector Machines (SVM)—were evaluated for anomaly detection in IoT-driven industrial environments. …”
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