An Area-Time Efficient Hardware Architecture for ML-KEM Post-Quantum Cryptography Standard by Trong-Hung Nguyen, Tuan-Kiet Dang, Duc-Thuan Dam, Khai-Duy Nguyen, Phuc-Phan Duong, Cong-Kha Pham, Trong-Thuc Hoang

“…To facilitate the integration of the NIST-standardized post-quantum cryptographic (PQC) algorithm, Module Lattice-based Key Encapsulation Mechanism (ML-KEM), into quantum-resistant devices and cryptosystems, this study introduces an area-time efficient hardware implementation. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
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Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…This study highlights the potential of UAV-based multi-temporal monitoring for post-fire forest assessment. Future research should focus on improving tree segmentation of SfM-MVS point clouds in dense canopies, optimizing co-alignment under varying environmental conditions, and integrating additional point cloud classification methods to improve accuracy in areas with complex species distribution.…”
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Identification of polynomial models of static load characteristics based on passive experiment results by N. L. Batseva, A. K. Zhuykov

“…In the paper, the technique based on the initial identification of the linear model, defined by EM-algorithm, and continued by the Lagrange multiplier method optimization with iterations by the Newton method is suggested.Results and discussion. …”
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A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network by Kui Liu, Sanyang Liu, Hailin Feng

“…The success rate of packet transmission is improved 15%. Simultaneously, this algorithm can keep the ant agents away from the nodes with less residual energy in searching for the optimal route. …”
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Comprehensive Analysis of Lightweight Cryptographic Algorithms for Battery-Limited Internet of Things Devices by Nahom Gebeyehu Zinabu, Yihenew Wondie Marye, Kula Kekeba Tune, Samuel Asferaw Demilew

“…Among the main trends that were covered were the trade-offs between resource limitations and security strength, hardware–software co-optimization, block and stream cipher optimization, and hybrid encryption techniques. …”
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Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour by Xinyi Dong, Ying Dong, Jinming Liu, Siting Wu

“…The model combines long short-term memory network (LSTM) data dimensionality reduction with partial least squares to detect multiple illicit additives in wheat flour. The Bayesian optimization algorithm was used to optimize the LSTM parameters. …”
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MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…Hyperparameters for the XGBoost model were fine-tuned using grid search techniques, resulting in optimal settings that significantly enhanced predictive accuracy with Mean Absolute Error (MAE) ranging from 0.016 – 0.757m and Root Mean Square Error (RMSE) ranging from 0.051 - 2.859m. …”
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Multi-Objective Intelligent Routing Algorithm for LEO Satellite Networks Based on DQN by LUO Zongyi, JIN Shichao, DONG Tao, YIN Jie

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Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…A short-term photovoltaic power forecasting method is proposed, integrating variational mode decomposition (VMD), an improved dung beetle algorithm (IDBO), and a deep hybrid kernel extreme learning machine (DHKELM). …”
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Optimal Integration of Multiple Shunt Reactive Compensators in Radial Distribution Systems for Loss Reduction using Modified Mountain Gazelle Optimizer (MMGO) by A. F. S. Yussif, E. Twumasi, E. A. Frimpong

“…This approach reduces the search space and improves the efficiency of the optimization process. …”
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Implementation of SVM Algorithm to Predict Song Popularity based on Sentiment Analysis of Lyrics by Quiin Latifah Almatin Lubis, Arif Akbarul Huda

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A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots by Anis Naema Atiyah Rafai, Noraziah Adzhar, Nor Izzati Jaini

“…This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
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Automatic strip layout design in progressive dies using the grouping genetic algorithm by Mehran Afshari, Behrooz Arezoo

“…In the present study, a new method is presented for the automatic strip layout design for progressive dies using the Grouping Genetic Algorithm. A two-objective function is used in the optimization process. …”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. These algorithms include Pearson correlation, hierarchical clustering, and decision tree (DT) models. …”
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Toward an algorithm of percutaneous microelectrolysis: a randomized clinical trial on invasive techniques by Carlos Eduardo Girasol, Nathaly Escobar Durán, Santiago Marcelo D’Almeida, Oscar Ariel Ronzio

“…CONCLUSIONS: All needling techniques demonstrated analgesic effects on myofascial trigger points, with the algorithm-enhanced MEP showing the most notable improvement in self-reported pain. …”
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Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

“…Traditional methods of group formation, such as teacher intervention and self-selection, often fail to create balanced and effective groups, especially in large online courses. The Louvain algorithm, known for its efficiency in modularity optimization, identifies clusters based on actual student interaction patterns. …”
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Machine learning-based optimization of photogrammetric JRC accuracy by Qinzheng Yang, Ang Li, Yipeng Liu, Hongtian Wang, Zhendong Leng, Fei Deng

“…Abstract To improve the accuracy of photogrammetric joint roughness coefficient (JRC) estimation, this study proposes two optimization models based on ground sample distance (GSD), point density, and the root mean square error (RMSE) of checkpoints. …”
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KAB: A new k-anonymity approach based on black hole algorithm by Lynda Kacha, Abdelhafid Zitouni, Mahieddine Djoudi

“…Clustering-based approaches have been successfully adapted for k-anonymization as they enhance the data quality, however, the computational complexity of finding an optimal solution has shown as NP-hard. Nature-inspired optimization algorithms are effective in finding solutions to complex problems. …”
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Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

“…However, performance varied with KNN, Naive Bayes, and Decision Tree, highlighting the importance of tailored approaches for optimal classification accuracy. Further optimization and experimentation are crucial for improving algorithm performance in real-world applications of brain tumor classification. …”
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