Exploring the Effectiveness of Machine Learning and Deep Learning Techniques for EEG Signal Classification in Neurological Disorders by Souhaila Khalfallah, William Puech, Mehdi Tlija, Kais Bouallegue

“…This study explores the use of machine learning (ML) and deep learning (DL) techniques in processing Electroencephalography (EEG) signals to detect various neurological disorders, including Epilepsy, Autism Spectrum Disorder (ASD), and Alzheimer’s disease. …”
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Cloning and expression analysis of OsSPL3 promoter in rice by ZENG Huiling, MO Zuyi, PU Qiaoxian, WANG Jiashu, FAN Kai, LI Zhaowei

“…It shows that OsSPL3 transcription factor plays a regulatory role in the process of coleoptile growth, new leaf formation, root extension and stem sheath elongation after seed germination, and OsSPL3 transcription factor is also involved in the response process of rice drought stress.…”
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Private detection of relatives in forensic genomics using homomorphic encryption by Fillipe D. M. de Souza, Hubert de Lassus, Ro Cammarota

“…HE not only permits the processing of PII as soon as it is collected and encrypted, such as at a crime scene, but also expands the potential for data processing by multiple entities and artificial intelligence services. …”
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AE-BPNN: autoencoder and backpropagation neural network-based model for lithium-ion battery state of health estimation by Abdullah Ahmed Al-Dulaimi, Muhammet Tahir Guneser, Raghad Al-Shabandar, Yeonghyeon Gu, Muhammad Syafrudin, Norma Latif Fitriyani

“…The AE-BPNN model demonstrated significant advantages over Gaussian Process Regression (GPR) and Support Vector Regression (SVR), yielding lower Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), alongside higher R² scores. …”
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Evaluating the efficacy and site-specific performance of machine learning approaches: A comprehensive review of autism detection models by Deblina Mazumder Setu, Tania Islam, Md Maklachur Rahman, Samrat Kumar Dey, Tazizur Rahman

“…For ML models, LR requires less processing time compared to others with high accuracy, making it a suitable choice for efficiency-driven applications, while CNN is optimal for neuroimaging-based autism detection. …”
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Fusion of Taq DNA polymerase with single-stranded DNA binding-like protein of Nanoarchaeum equitans-Expression and characterization. by Marcin Olszewski, Marta Śpibida, Maciej Bilek, Beata Krawczyk

“…A novel recombinant gene was obtained which was cloned into the pET-30 Ek/LIC vector and introduced into E. coli for expression. …”
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An enhanced classification system of various rice plant diseases based on multi-level handcrafted feature extraction technique by Yasmin M. Alsakar, Nehal A. Sakr, Mohammed Elmogy

“…The explosive growth in image processing, computer vision, and deep learning techniques provides effective and innovative agriculture solutions for automatically detecting and classifying these diseases. …”
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A Joint Forgetting Factor-Based Adaptive Extended Kalman Filtering Approach to Predict the State-of-Charge and Model Parameter of Lithium-Ion Battery by Satyaprakash Rout, Satyajit Das

“…The JFFAEKF approach evaluates uncertainties in the battery model and incorporates them into the SOC estimation process under dynamic operating conditions. By augmenting both the SOC and battery model parameters into a single state vector, the estimator concurrently updates these variables. …”
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A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification by Mohanad Azeez Joodi, Muna Hadi Saleh, Dheyaa Jasim Kadhim

“…Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. …”
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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This tool leverages the strengths of multiple regression-based and probabilistic machine learning methods, including LASSO (see the list of abbreviations in Appendix B), support vector machine, classification and regression trees, random forest, extreme gradient boosting, Gaussian process regression, and Bayesian ridge regression. …”
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Machine Learning-Based Cerrado Land Cover Classification Using PlanetScope Imagery by Thanan Rodrigues, Frederico Takahashi, Arthur Dias, Taline Lima, Enner Alcântara

“…A post-processing process was applied to avoid misclassification of forest in areas of savanna. …”
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Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…A new observation vector based on the magnitude matching is then constructed to effectively reduce the effect of outliers on the alignment process. …”
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Tuck-KGC: based on tensor decomposition for diabetes knowledge graph completion model integrating Chinese and Western medicine by Jiangtao ZhangSun, Yu Xin Yang, Beiji Zou, Qinghua Peng, Xiao Xia Xiao

“…This method maps the types of medical entities to vectors, which are seamlessly integrated into the knowledge graph representation learning process. …”
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Universal anomaly detection at the LHC: transforming optimal classifiers and the DDD method by Sascha Caron, José Enrique García Navarro, María Moreno Llácer, Polina Moskvitina, Mats Rovers, Adrián Rubio Jímenez, Roberto Ruiz de Austri, Zhongyi Zhang

“…We compare the performance of the DDD method with the Deep Robust One-Class Classification method (DROCC), which incorporates signals in the training process, and the Deep Support Vector Data Description (DeepSVDD) method, a well-established and well-performing method for anomaly detection. …”
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A method for IoT devices test case generation using language models by Sumit Kumar, Kiran Napte, Ruchi Rani, Sanjeev Kumar Pippal

“…The rapid growth of IoT and electronic systems has led to complex real-time data processing and management solutions. However, these systems present significant software and hardware testing challenges, often requiring manual, time-consuming testing efforts. …”
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Back to the Family: Rethinking the Role of Parents in Schooling (Сase of the Republic of Guinea) by Katerina V. Fofanova, Adama Conde

“…Passeron which reveals the principles of the educational system, the conditions for the success of the educational process, the influence of the cultural and linguistic capital of the family on the success of the child. …”
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Conceptual analysis of social responsibility of the person and its integration in pharmaceutical practice by N. O. Tkachenko, В. Р. Hromovyk

“…All this determines the multi-vector nature and variety of means of forming its social responsibility.…”
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Random Forest-Based Prediction of the Optimal Solid Ink Density in Offset Lithography by Laihu Peng, Hao Fan, Yubao Qi, Jianqiang Li

“…Solid ink density is an important control parameter in the manufacturing process of offset prints—the size of which has a significant impact on the color performance of the prints—in which the determination of the optimal solid ink density is critical for the pre-press phase of industrial production. …”
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A competency-based framework for preventing blood-borne pathogen occupational exposures in medical students: literature review and Delphi study by Pingping Wang, Minhong Cai, Yu Lv, Qian Xiang

“…Abstract Background Blood-borne pathogen occupational exposures pose significant hazard to medical students during clinical internships, with needlestick injuries being the primary transmission vector for blood-borne pathogens (hepatitis B virus, hepatitis C virus, human immunodeficiency virus). …”
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Extension Model for Safety Appraisal of Existing Concrete Members Based on an Improved Comprehensive Weighting Method by Hengyu Zhou, Yongbo Yuan, Chenlong Liu, Chao Wu, Mingyuan Zhang

“…It was found that the subjective weight vector calculated by IAHP consists of interval numbers. …”
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