Short-Term Electricity Price Forecasting Using the Empirical Mode Decomposed Hilbert-LSTM and Wavelet-LSTM Models by Kunal Shejul, R. Harikrishnan, Amit Kukker

“…The proposed techniques show better performance in terms of rank correlation, mean square error, and root mean square error compared to the existing algorithms of LSTM and CNN-LSTM. The prediction results achieved with wavelet-LSTM and Hilbert-LSTM (1-month dataset of 8 years) are rank correlation 0.9746 and 0.9749, MSE 0.2962 and 0.1363, and RMSE 0.5443 and 0.3692, respectively. …”
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Implementation of a neural network model in the Statistica 12 for mudflow frequency forecasting by B. A. Ashabokov, A. A. Tashilova, L. A. Kesheva, N. V. Teunova

“…Based on deep learning algorithms, a mathematical model MPL 2-50-1 was developed, which is capable of learning on the used data (precipitation, temperature, number of mudflows for the period 1953-2015) and forecasting the number of mudflows based on the meteorological parameters (precipitation, temperature) entered into the model. …”
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Experimental Study of Coherent Collaborative Processing Method in Distributed Automotive Radar by A. A. Kuzin, S. E. Kuznetsov, A. V. Miakinkov, R. S. Fadeev, S. A. Shabalin

“…The resolution of a system consisting of two spaced radars was investigated experimentally using a fully functional layout. Algorithms for phase synchronization and collaborative digital signal processing, along with appropriate software, were developed.Results. …”
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Fraud Detection in Privacy Preserving Health Insurance System Using Blockchain Technology by Md. Mazharul Islam, Mubasshir Ahmed, Rajesh Palit, Mohammad Shahriar Rahman, Salekul Islam

“…Privacy is preserved using cryptographic techniques such as secure hashing and anonymous credentials, which ensure that sensitive patient information remains confidential throughout the claim process. Smart contract algorithms are utilized in two scenarios: patient‐submitted claims and healthcare provider‐submitted claims, ensuring accurate processing and validation while detecting fraudulent activities such as duplicate claims, inflated medical bills, billing for unprovided services, falsifying patient records, and submitting claims for nonexistent treatments. …”
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Detection of Malicious Office Open Documents (OOXML) Using Large Language Models: A Static Analysis Approach by Jonas Heß , Kalman Graffi

“…As a supplementary tool to contemporary antivirus software, it is currently able to assist in the analysis of malicious Microsoft Office documents by identifying and summarising potentially malicious indicators with a foundation in evidence, which may prove to be more effective with advancing technology and soon to surpass tailored machine learning algorithms, even without the utilisation of signatures and detection rules. …”
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REALISATION D’UN SYSTEME (PARADIS) POUR LA SYNTHESE DE LA PAROLE ARABE A PARTIR DU TEXTE by Noureddine Chenfour

“…Il est connu par sa capacité d’action directe sur le signal de parole et par le concept de séparation entre l’algorithme de codage et la tech-nique de synthèse. Il garantit ainsi une grande flexibilité au niveau suprasegmental et offre de très bonnes possibilités de variations prosodiques, ce qui apporte plus de naturel à la parole synthétique. …”
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Genomic selection optimization in blueberry: Data‐driven methods for marker and training population design by Paul Adunola, Luis Felipe V. Ferrão, Juliana Benevenuto, Camila F. Azevedo, Patricio R. Munoz

“…Our contribution in this study is threefold: (i) for the genotyping resource allocation, the use of genetic data‐driven methods to select an optimal set of markers slightly improved prediction results for all the traits; (ii) for the long‐term implication, we carried out a simulation study and emphasized that data‐driven method results in a slight improvement in genetic gain over 30 cycles than random marker sampling; and (iii) for the phenotyping resource allocation, we compared different optimization algorithms to select training population, showing that it can be leveraged to increase predictive performances. …”
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Advances and Challenges in Automated Drowning Detection and Prevention Systems by Maad Shatnawi, Frdoos Albreiki, Ashwaq Alkhoori, Mariam Alhebshi, Anas Shatnawi

“…Automatic drowning detection approaches could be further categorized into computer vision-based approaches, where camera-captured images are analyzed by machine learning algorithms to detect instances of drowning, and sensing-based approaches, where sensing instruments are attached to swimmers to monitor their physical parameters. …”
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Use of machine learning in occupational risk communication for healthcare workers: protocol for scoping review by Gabriela Laudares Albuquerque de Oliveira, Clarice Alves Bonow, Itiberê de Oliveira Castellano Rodrigues, Amanda Xavier Geraldo

“…Introduction With the development of technology, the use of machine learning (ML), a branch of computer science that aims to transform computers into decision-making agents through algorithms, has grown exponentially. This protocol arises from the need to explore the best practices for applying ML in the communication and management of occupational risks for healthcare workers.Methods and analysis This scoping review protocol details a search to be conducted in the academic databases, Public Medical Literature Analysis and Retrieval System Online, through the Virtual Health Library: Medical Literature Analysis and Retrieval System, Latin American and Caribbean Literature in Health Sciences, West Pacific Region Index Medicus, Nursing Database and Scientific Electronic Library Online, Scopus, Web of Science and IEEE Xplore Digital Library and Excerpta Medica Database. …”
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The Impact of AI-Generated Instructional Videos on Problem-Based Learning in Science Teacher Education by Nikolaos Pellas

“…The limited impact of the preview feature highlights the need for careful design and evaluation of instructional elements, such as interactivity and adaptive learning algorithms, to fully realize their potential.…”
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NLP for computational insights into nutritional impacts on colorectal cancer care by Shengnan Gong, Xiaohong Jin, Yujie Guo, Jie Yu

“…Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising among younger adults due to improved screening practices. However, existing algorithms for CRC prediction are frequently trained on datasets that primarily reflect older persons, thus limiting their usefulness in more diverse populations. …”
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A secure medical image encryption technique based on DNA cryptography with elliptic curves by V. N. Senthil Kumaran, T. Manikandan, Rajesh Kumar Dhanaraj, Taher Al-Shehari, Nasser A. Alsadhan, Shitharth Selvarajan

“…With progress in imaging technologies and biomedical processing algorithms, the amount of image data increases rapidly. …”
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Neighbor Similarity Based Agglomerative Method for Community Detection in Networks by Jianjun Cheng, Xing Su, Haijuan Yang, Longjie Li, Jingming Zhang, Shiyan Zhao, Xiaoyun Chen

“…The results show that the proposed method can detect high-quality community structures from networks steadily and efficiently and outperform the comparison algorithms significantly.…”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Phish-Jam utilizes a super learner ensemble that combines predictions from diverse Machine Learning (ML) algorithms to classify legitimate and phishing websites. …”
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Integrating direct observation and environmental DNA data to enhance species distribution models in riverine environments by Luca Carraro

“…Moreover, I propose optimized sampling strategies for both eDNA and direct sampling, with algorithms (included in the upgraded eDITH package) that mathematically translate rule-of-thumb criteria to maximize the spatial coverage of sites’ arrangement in a riverscape based on the peculiar features of each data type. …”
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An automation monitoring system for the production facility work by Артем Бронніков, Альона Коломієць, Олег Юрченко

“… The subject of research in the article is the application of technology and control algorithms in the automation system for monitoring the operation of the instrument building room. …”
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Leveraging Vision Foundation Model via PConv-Based Fine-Tuning with Automated Prompter for Defect Segmentation by Yifan Jiang, Jinshui Chen, Jiangang Lu

“…On two real-world defect segmentation datasets, PA-SAM achieves mean Intersections over Union of 73.87% and 68.30%, as well as mean Dice coefficients of 84.90% and 80.22%, outperforming other state-of-the-art algorithms, further demonstrating its robust generalization and application potential.…”
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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

“…However, persistent challenges include data scarcity in developing regions (only 12% of Sub-Saharan African monitoring stations provide real-time data), algorithmic bias (65% sensitivity loss in cross-regional models), and regulatory skepticism toward "black-box" systems. …”
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Inflow Prediction for Agricultural Reservoirs Using Disaster Prevention Measurement Data: A Comparison of TANK Model and Machine Learning by Bong-Kuk Lee, Joonyoung Choi, Kyoung Jae Lim, Jeongho Han

“…The results of this study demonstrate the potential of machine learning techniques for inflow prediction in agricultural reservoirs and suggest the need for further research on model improvement using various algorithms and input variables.…”
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Determining the Boundaries of Overlying Strata Collapse Above Mined-Out Panels of Zhomart Mine Using Seismic Data by Sara Istekova, Alexander Makarov, Dina Tolybaeva, Arman Sirazhev, Kuanysh Togizov

“…The state-of-the-art technologies of kinematic and dynamic analysis of wavefield have been widely used during data processing and interpretation targeted at identifying anomalies associated with the structural heterogeneity of the pays and rock mass, engaging modern algorithms and mathematical apparatuses of specialized geodata processing systems. …”
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