HarmonizR: blocking and singular feature data adjustment improve runtime efficiency and data preservation by Simon Schlumbohm, Julia E. Neumann, Philipp Neumann

“…An additionally welcome update regarding improved feature rescue furthermore enhances the algorithms ability to quickly and robustly perform batch effect reduction.…”
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StrideHD: A Binary Hyperdimensional Computing System Utilizing Window Striding for Image Classification by Dehua Liang, Jun Shiomi, Noriyuki Miura, Hiromitsu Awano

“…As an extension, the iterative retraining mode of StrideHD averagely provides 11.33% accuracy improvement to its single-pass mode, which can be accomplished in fewer iterations in comparison with the baseline HD algorithms. The hardware implementation also demonstrates that StrideHD achieves over 9.9<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> and 28.8<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> reduction compared with baseline in area and power, respectively.…”
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Precision irrigation with AI-driven optimization of plant electrophysiology by Yiting Chen, Devon Scott, Hieu Trung Tran, Yan Sum Shirley Yip, Soomin Shin, Woo Soo Kim

“…By optimizing water consumption using the AI algorithm, our approach can achieve at least a 10 % reduction in water use while maintaining optimal water conditions for crops. …”
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Review of machine learning-assisted multi-property design of high-entropy alloys: phase structure, mechanical, tribological, corrosion, and hydrogen storage properties by Yunlong Li, Jialiang Tan, Cheng Qian, Xiaochao Liu, Rui Nie

“…It outlines the basic workflow, including data collection, data preprocessing, ML algorithm selection, hyperparameter optimization, model evaluation and model interpretability. …”
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Scalable Clustering of Complex ECG Health Data: Big Data Clustering Analysis with UMAP and HDBSCAN by Vladislav Kaverinskiy, Illya Chaikovsky, Anton Mnevets, Tatiana Ryzhenko, Mykhailo Bocharov, Kyrylo Malakhov

“…The study aims to apply unsupervised clustering algorithms to ECG data to detect latent risk profiles related to heart failure, based on distinctive ECG features. …”
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Harmonization of multi-center diffusion tensor tractography in neonates with congenital heart disease: Optimizing post-processing and application of ComBat by Benjamin Meyers, Vincent K. Lee, Lauren Dennis, Julia Wallace, Vanessa Schmithorst, Jodie K. Votava-Smith, Vidya Rajagopalan, Elizabeth Herrup, Tracy Baust, Nhu N. Tran, Jill V. Hunter, Daniel J. Licht, J. William Gaynor, Dean B. Andropoulos, Ashok Panigrahy, Rafael Ceschin

“…We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…This information-theoretic approach provided clear design priorities by measuring entropy reduction potential of each parameter. Interpretability analysis established optimal operating ranges for key parameters including MHPA equivalent thermal conductivity, power density, glass cover heat transfer coefficient, and air inlet temperature. …”
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Optimising Connectivity and Energy: The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by Izzah N. Buang, K. Zen, Syahrul N. Junaini

“…These approaches have demonstrated improvements in packet delivery ratios (PDRs), latency reduction, and energy efficiency within mobile IoT contexts. …”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The proposed procedure ensures building models of outstanding predictive power while using small training datasets, which is beyond the capabilities of benchmark algorithms.…”
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The innovation path of VR technology integration into music classroom teaching in colleges and universities by Yupeng Han, Lin Han, Chun Zeng, Wei Zhao

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Nonlinear Model Predictive Yaw Moment Control Through Electric Axle and Friction Brake Torque Distribution by Carmine Caponio, Gaetano Tavolo, Davide Tavernini, Ahu Ece Hartavi Karci, Javad Ahmadi, Basilio Lenzo, Giulio Reina, Giacomo Mantriota, Pietro Perlo, Aldo Sorniotti

“…With respect to benchmarking rule-based controllers, the results show that the NMPCs bring significant reductions of the yaw rate errors and friction brake power losses, while increasing the exit speed in acceleration-during-cornering conditions.…”
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Transforming Chiller Plant Efficiency with SC+BAS: Case Study in a Hong Kong Shopping Mall by Fong Ming-Lun Alan, Li Baonan Nelson

“…The application of SC+BAS falls into the realm of advanced Trim/Respond algorithms coupled with sophisticated sequencing algorithms that allow for refined optimization of the chiller operations in response to the dynamic demands of urban infrastructure. …”
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Enabling scalable single-cell transcriptomic analysis through distributed computing with Apache spark by Asif Adil, Namrata Bhattacharya, Aadam, Naveed Jeelani Khan, Mohammed Asger

“…In this study, we try to address this challenge and present a novel parallel analytical framework, scSPARKL, that leverages the power of Apache Spark to enable the efficient analysis of single-cell transcriptomic data. scSPARKL is fortified by a rich set of staged algorithms developed to optimize the Apache Spark’s work environment. …”
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Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis by Gunjan Shandilya, Sheifali Gupta, Salil Bharany, Ateeq Ur Rehman, Upinder Kaur, Hafizan Mat Som, Seada Hussen

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Mathematical model of a stacker crane with a slewing boom by Korytov M.S., Bezrodina A.E.

“…The widespread use of racking stacker cranes is due to the spread of automated warehouses. Reduction of energy costs when using stacker cranes is one of the main directions of their improvement. …”
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Machine Learning-Based Prediction of Resilience in Green Agricultural Supply Chains: Influencing Factors Analysis and Model Construction by Daqing Wu, Tianhao Li, Hangqi Cai, Shousong Cai

“…This research provides a risk prevention and control paradigm with both theoretical explanatory power and practical operability for agricultural product green supply chains, and promotes collaborative realization of the “carbon reduction–supply stability–efficiency improvement” goals, transforming them from policy vision to operational reality.…”
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Bridging the Gap: A Review of Machine Learning in Water Quality Control by Herlina Abdul Rahim, Nur Athirah Syafiqah Noramli, Indrabayu

“…Future directions explore IoT-edge systems (90% accurate TinyML sensors at 50 mW power), quantum-optimized adsorbents (2.5x mercury removal efficiency), and satellite-enabled global monitoring (85% microplastic detection accuracy). …”
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Combined Allocation of Renewable-Based Distributed Generators and Shunt Capacitor Banks in Distribution Networks with Electric Vehicle Load Penetration by Abhilasha Pawar, Rajkumar Viral, Divya Asija, Mohit Bansal

“…The simulation results demonstrate the effectiveness of the proposed method, achieving reductions in active power losses, reactive power losses, and voltage deviations by 80.53%, 76.88%, and 69.96%, respectively. …”
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Phasic and periodic change of drought under greenhouse effect by Yang Li, Zhicheng Zheng, Yaochen Qin, Haifeng Tian, Zhixiang Xie, Peijun Rong

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FiSC: A Novel Approach for Fitzpatrick Scale-Based Skin Analyzer&#x2019;s Image Classification by Guillermo Crocker Garcia, Muhammad Numan Khan, Aftab Alam, Josue Obregon, Tamer Abuhmed, Eui-Nam Huh

“…Our method involves modeling image features as a nine-dimensional feature vector, followed by a dimensionality reduction process to identify the most influential features and dominant areas within the feature space, enabling deployment on low-power devices. …”
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