Intelligent energy management of microgrids using machine learning: Leveraging random forest models for solar and wind power by Hasanur Zaman Anonto, Md Ismail Hossain, Abu Shufian, Md. Shaoran Sayem, S M Tanvir Hassan Shovon, Protik Parvez Sheikh, Sadman Shahriar Alam

“…The shift to renewable power demands the development of microgrids involving solar and wind power. Since solar and wind sources are inherently not continuous, it is a tremendous challenge to integrate the sources into microgrids effectively. …”
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A Machine Learning-Based Real-Time Remaining Useful Life Estimation and Fair Pricing Strategy for Electric Vehicle Battery Swapping Stations by Seyit Alperen Celtek, Seda Kul, A. Ozgur Polat, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…The paper evaluates various machine learning algorithms for real-time RUL estimation regarding accuracy, computation time, and memory usage. …”
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Analysis of follow-up data in large biobank cohorts: a review of methodology by Anastassia Kolde, Anastassia Kolde, Merli Koitmäe, Merli Koitmäe, Meelis Käärik, Märt Möls, Krista Fischer, Krista Fischer

“…We address four primary issues: left-truncation of the data, computational inefficiency of standard model-fitting algorithms, relatedness among individuals, and model misspecification. …”
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UEF-HOCUrdu: Unified Embeddings Ensemble Framework for Hate and Offensive Text Classification in Urdu by Kifayat Ullah, Muhammad Aslam, Muhammad Usman Ghani Khan, Faten S. Alamri, Amjad Rehman Khan

“…For this purpose, an extensive comparison of different learning algorithms were conducted. As a result, the most efficient models, namely FastText, XLM-RoBERTa, ULMFiT, and XGBoost were incorporated in the proposed ensemble approach to achieve the best results in both classification and mitigation of NLP issues. …”
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MSPO: A machine learning hyperparameter optimization method for enhanced breast cancer image classification by Haonan Li, Vijay Govindarajan, Tan Fong Ang, Zaffar Ahmed Shaikh, Amel Ksibi, Yen-Lin Chen, Chin Soon Ku, Ming Chern Leong, Fatiha Hana Shabaruddin, Wan Zamaniah Wan Ishak, Lip Yee Por

“…Tests using the CEC 2022 benchmark functions reveal that MSPO surpasses leading algorithms regarding optimization precision and convergence rate. …”
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Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2... by Monoronjon Dutta, Md Rashedul Islam Sujan, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty, Ahmed Al Marouf, Jon G. Rokne, Reda Alhajj

“…In this work, deep learning algorithms were, therefore, employed for the identification and classification of rice leaf diseases from images of crops in the field. …”
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The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review by Xi Wang, Yujia Zhou, Guangyu Zhou

“…However, to ensure ethical and effective implementation, comprehensive safeguards—particularly around privacy, algorithmic bias, and responsible user engagement—must be established.…”
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Goal-oriented autonomous decision-making for social robots via collaborative interactive inverse reinforcement learning approach by Mingyue Luo, Hui Li, Wanbo Luo, Hewei Li, Jianan Li

“…Abstract Since the practical constraints of unknown pedestrian goal information, research on inverse reinforcement learning (IRL) applied to social robots has focused on trajectory planning based on current motion direction, other pedestrians, and obstacles. …”
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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

“…., two-dimensional signal, 2-D CNNs or other relevant architectures are deployed. Since 2D-represented ECG signals facilitate better feature extraction, it is a common practice to convert an ECG signal into a scalogram image using a continuous wavelet transform (CWT) approach and then subject it to a DL architecture such as 2-D CNN. …”
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Downscaling air temperatures for high-resolution niche modeling in a valley of the Amazon lowland forests: A case study on the microclima R package. by M J Pohl, L Lehnert, B Thies, K Seeger, M B Berdugo, S R Gradstein, M Y Bader, J Bendix

“…Despite problems with the distinction between CAD and non-CAD events the microclima algorithms show difficulties in correctly modeling the diurnal course of the temperature data and the amplitudes of elevational temperature gradients. …”
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Interdisciplinary Distance Learning Workshop for IT Students by I. A. Andrianov, S. A. Rzheutskaya, M. V. Kharina

“…An example of using the learning workshop in the course “Mathematical Logic and Theory of Algorithms” is presented, in which the implementation of automatic checking of problem solutions required non-standard solutions to refine the learning workshop. …”
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Features of tactics of inspection of accident sites in the investigation of illegal interference in the activities of energy facilities using unmanned vehicles by S. L. Kislenko, A. B. Smushkin

“…At the same time, the importance of urgently studying the volatile memory of a working device is stated.Conclusions about the achievement of the research goal: the paper proposes adaptive algorithms for the investigator's actions in various investigative situations: when the functioning of the device was suppressed by electronic warfare; when the UAV was physically damaged or destroyed; when an attacker with a UAV control device (remote control, smartphone, laptop, special glasses, etc.) was detained at the scene; when the control device is detected, but the attacker himself has disappeared; when the attacker has destroyed the control device; when information from the UAV (video and sensor readings) was transmitted not only to the operator's device, but also to another addressee; when the operator was detained on the territory of the fuel and energy complex. …”
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Can Measurement and Input Uncertainty Explain Discrepancies Between the Wheat Canopy Scattering Model and SMAPVEX12 Observations? by Lilangi Wijesinghe, Andrew W. Western, Jagannath Aryal, Dongryeol Ryu

“…Realistic representation of microwave backscattering from vegetated surfaces is important for developing accurate soil moisture retrieval algorithms that use synthetic aperture radar (SAR) imagery. …”
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Adverse events associated with vismodegib: insights from a real-world pharmacovigilance study using the FAERS database by Bingqing Wang, Kaidi Zhao, Ningyi Xian, Landong Ren, Jiashu Liu, Chen Tu, Dewu Zhang

“…Disproportionality analysis was conducted using four algorithms: Reporting odds ratio, proportional reporting ratio, multi-item gamma Poisson shrinker, and Bayesian confidence propagation neural network to assess the safety profile of vismodegib in clinical practice. …”
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Phase tomography with axial structured illumination by Nishant Goyal, Kedar Khare

“…Despite this algorithmic framework shift, the HT system hardware still largely uses the multi-angle illumination geometries that were suitable for reconstructions based on the Fourier diffraction theorem. …”
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Visual analysis of research trends in diabetes-associated dry eye via bibliometrics by Zhe Yang, Jia-Yi Jiang, Xiao-Hui Zhang

“…Building risk prediction models using machine learning algorithms is a promising future research direction, enabling physicians to identify high-risk individuals and implement early interventions.…”
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How real is the long-lasting effect of tumor necrosis factor α inhibitors? Focus on immunogenicity by D.E. Karateev

“…The risk that the need to increase the dose because of gradual loss of effectiveness of therapy with ADA and INF, was 4.9- and 28-fold higher, respectively, as compared to ETN. Therapeutic algorithms make it possible to control therapy with TGFα inhibitors (development of ADAbs, blood concentration of drug), as well as to switch to using another biological drug. …”
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Real-World Safety Profile of Proton Pump Inhibitors in Infants as Reported in the FDA Adverse Event Reporting System (FAERS): Tiny Tummies, Key Decisions by Hülya Tezel Yalçın, Nadir Yalçın, Karel Allegaert

“…Integrating neonatal-specific algorithms could enhance drug safety evaluations, strengthen evidence-based decision-making, and improve risk–benefit assessments in neonates and infants.…”
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Non-invasive liver fibrosis markers are increased in obese individuals with non-alcoholic fatty liver disease and the metabolic syndrome by Anders Askeland, Rikke Wehner Rasmussen, Mimoza Gjela, Jens Brøndum Frøkjær, Kurt Højlund, Maiken Mellergaard, Aase Handberg

“…We used MRI (T1 relaxation times (T1) and liver stiffness), circulating biomarkers (CK18, PIIINP, and TIMP1), and algorithms (FIB-4 index, Forns score, FNI, and MACK3 score) to assess their potential in predicting liver fibrosis risk. …”
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DATA MINING IN RELATIONAL SYSTEMS by Valentin Filatov, Valerii Semenets, Oleg Zolotukhin

“…One of the problems is the algorithmic complexity of finding frequently occurring itemsets, since as the number of items grows, the number of potential itemsets grows exponentially.…”
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