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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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. …”
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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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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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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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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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Newly diagnosed acute myeloid leukemia in unfit patients: 2026 treatment algorithms by Naseema Gangat, Courtney D. Dinardo

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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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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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Optimal allocation of STATCOM for multi-objective ORPD problem on thermal wind solar hydro scheduling using driving training based optimization by Tushnik Sarkar, Sabyasachi Gupta, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Anagha Bhattacharya, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…The Driving Training Based Optimization (DTBO) method has been used to achieve the goals, and its performance has been compared to that of other optimization algorithms that have been reported in recent ORPD studies. …”
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Construction and Application of Agricultural Talent Training Model Based on AHP-KNN Algorithm by Shubing Qiu, Yong Liu, Xiaohong Zhou

“…To solve this problem, an improved AHP-KNN algorithm is proposed by combining the analytic hierarchy process (AHP) and the optimized K-nearest neighbor algorithm, and an agricultural talent training model is proposed based on this algorithm. …”
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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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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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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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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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Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

“…For future research, it is recommended to explore the combination of SVR with optimization techniques such as genetic algorithms to further improve the accuracy of soil texture and color predictions.…”
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A Data-Driven Parameter Adaptive Clustering Algorithm Based on Density Peak by Tao Du, Shouning Qu, Qin Wang

“…Clustering is an important unsupervised machine learning method which can efficiently partition points without training data set. However, most of the existing clustering algorithms need to set parameters artificially, and the results of clustering are much influenced by these parameters, so optimizing clustering parameters is a key factor of improving clustering performance. …”
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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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