Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments by Assala Bouguerra, Abd Essalam Badoud, Saad Mekhilef, Badreddine Kanouni, Mohit Bajaj, Ievgen Zaitsev

“…We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in adapting to varying conditions, including fluctuations in pressure and temperature. …”
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The Short‐Time Prediction of Thermospheric Mass Density Based on Ensemble‐Transfer Learning by Peian Wang, Zhou Chen, Xiaohua Deng, Jing‐Song Wang, Rongxing Tang, Haimeng Li, Sheng Hong, Zhiping Wu

“…In this paper, three machine‐learning prediction algorithms are investigated, including the Bidirectional Long Short‐Term Memory, the Transformer, and the Light Gradient Boosting Machine (LightGBM) ensemble model of the above models. …”
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Cortical Source Multivariate EEG Synchronization Analysis on Amnestic Mild Cognitive Impairment in Type 2 Diabetes by Dong Cui, Jing Liu, Zhijie Bian, Qiuli Li, Lei Wang, Xiaoli Li

“…Three multivariate synchronization algorithms (S-estimator (S), synchronization index (SI), and global synchronization index (GSI)) were used to measure the synchronization in five ROIs of sLORETA sources for seven bands. …”
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Diegif: An efficient and secured DICOM to EGIF conversion framework for confidentiality in machine learning training by Abdullah Al Siam, Md Maruf Hassan, Md Atikur Rahaman, Masuk Abdullah

“…The Diegif framework aims to enhance storage efficiency by decreasing file sizes by 66.32%, thereby improving data transport efficacy and cloud storage affordability while preserving strong encryption for data confidentiality. Pseudocode algorithms are provided for each phase, ensuring reproducibility and transparency. …”
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Testing the Strength of Chaotic Systems as Seeds in a Pseudo Random Bit Generator by Lazaros Moysis, Marcin Lawnik, Christos Volos, Murilo S. Baptista, Sotirios K. Goudos, George F. Fragulis

“…These observations can serve as guidelines for all future chaotic encryption algorithms, and chaos-based security-related applications in general.…”
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IMPROVE OF UNCERTAIN MICROSATELLITE MAGNETIC CLEANLINESS BASED ON MAGNETIC FIELD SPATIAL HARMONICS COMPENSATION by Б.І. Кузнецов, Т.Б. Нікітіна, І.В. Бовдуй, К.В. Чуніхін, В.В. Коломієць, Б.Б. Кобилянський

“…Both vector game solution calculated based on particles multi-swarm optimization (PMSO) algorithms from Pareto optimal solutions taking into account binary preference relations. …”
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Prediction of individual patient outcomes to psychotherapy vs medication for major depression by Devon LoParo, Boadie W. Dunlop, Charles B. Nemeroff, Helen S. Mayberg, W. Edward Craighead

“…Finally, the prediction algorithms and treatment recommendation tool were externally validated in an independent sample. …”
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Models for the marrow: A comprehensive review of AI‐based cell classification methods and malignancy detection in bone marrow aspirate smears by Tabita Ghete, Farina Kock, Martina Pontones, David Pfrang, Max Westphal, Henning Höfener, Markus Metzler

“…Abstract Given the high prevalence of artificial intelligence (AI) research in medicine, the development of deep learning (DL) algorithms based on image recognition, such as the analysis of bone marrow aspirate (BMA) smears, is rapidly increasing in the field of hematology and oncology. …”
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Solar Irradiance Prediction for Zaria Town Using Different Machine Learning Models by Ibrahim Abdulwahab, Sulaiman Haruna Sulaiman, Umar Musa, Ibrahim Abdullahi Shehu, Abdullahi Kakumi Musa, Ismaila Mahmud, Mohammed Musa, Abdullahi Abubakar, Abdulrahman Olaniyan

“… The research is set to predict solar irradiation using various machine learning algorithms. This is done in order to construct and develop a high-efficiency prediction model that uses actual meteorological data to predict daily solar irradiance for the town of Zaria, Nigeria. …”
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Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems by Wathiq Laftah Al-Yaseen, Zulaiha Ali Othman, Mohd Zakree Ahmad Nazri

“…Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). …”
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Nonlinear Control and Synchronization with Time Delays of Multiagent Robotic Systems by Yassine Bouteraa, Jawhar Ghommam, Nabil Derbel, Gérard Poisson

“…The developed control combines trajectory tracking and coordination algorithms. To address the time-delay problem in the cooperative network communication, the suggested synchronization control law is shown to synchronize multiple robots as well as to track given trajectory, taking into account the presence of the time delay. …”
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Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review by Athanasios Kallipolitis, Konstantinos Moutselos, Argyriοs Zafeiriou, Stelios Andreadis, Anastasia Matonaki, Thanos G. Stavropoulos, Ilias Maglogiannis

“…The review examines deep learning architectures and image processing algorithms for segmentation, feature extraction, and classification tasks employed for disease detection. …”
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Health & Gait: a dataset for gait-based analysis by Jorge Zafra-Palma, Nuria Marín-Jiménez, José Castro-Piñero, Magdalena Cuenca-García, Rafael Muñoz-Salinas, Manuel J. Marín-Jiménez

“…Health&Gait facilitates the progression of artificial vision algorithms for automated gait analysis.…”
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Distributed representations enable robust multi-timescale symbolic computation in neuromorphic hardware by Madison Cotteret, Hugh Greatorex, Alpha Renner, Junren Chen, Emre Neftci, Huaqiang Wu, Giacomo Indiveri, Martin Ziegler, Elisabetta Chicca

“…Moreover, it demonstrates that distributed symbolic representations serve as a highly capable representation-invariant language for cognitive algorithms in neuromorphic hardware.…”
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AI-Driven Sustainable Marketing in Gulf Cooperation Council Retail: Advancing SDGs Through Smart Channels by Hanadi Salhab, Munif Zoubi, Laith T. Khrais, Huda Estaitia, Lana Harb, Almotasem Al Huniti, Amer Morshed

“…While these benefits are real, data privacy and algorithmic bias remain valid concerns, thus underlining the need for ethics and transparency in the practice of AI. …”
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Hate Speech Detection Using Large Language Models: A Comprehensive Review by Aish Albladi, Minarul Islam, Amit Das, Maryam Bigonah, Zheng Zhang, Fatemeh Jamshidi, Mostafa Rahgouy, Nilanjana Raychawdhary, Daniela Marghitu, Cheryl Seals

“…Traditional methods for detecting hate speech, such as keyword matching, rule-based systems, and machine learning algorithms, often struggle to capture the subtle and context-dependent nature of hateful content. …”
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Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model by Victor Fernandez, Virgilio Pérez, Rosa Roig

“…Important aspects include analyzing power consumption, forecasting urban energy demand, and monitoring the State of Charge (SoC) of FEV batteries using innovative algorithms validated through real-world applications in Valencia (Spain) and Ljubljana (Slovenia). …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. …”
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A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters by Muhammad Asif, Maaz Bin Ahmad, Imtiaz A. Taj, Muhammad Tahir

“…Each layer of the proposed framework incorporates multiple innovative algorithms to shortlist the candidate prediction parameters prior to the RDO process. …”
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Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics by Muhammad Javed Iqbal, Ibrahima Faye, Brahim Belhaouari Samir, Abas Md Said

“…To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. …”
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