SUMMARIA — A XAI Support Methodology by Generating Composite Linguistic Summaries of Qualitative Data by Carlos Rafael Rodríguez-Rodríguez, Yeleny Zulueta-Veliz, Dainys Gainza-Reyes

“…The latter is increasingly significant as the demand for explainability grows with the rise of black-box AI applications. This paper proposes SUMMARIA, a XAI support methodology by generating composite (enriched) linguistic summaries of qualitative data. …”
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Vibration control and noise attenuation strategies via acoustic metamaterial in railway transportation: a state-of-the-art review by Cong Wang, Guifeng Wang, Zhenyu Chen, C. W. Lim, Weiqiu Chen

“…AMMs, characterized by their unique structural properties, enable targeted frequency control, efficient low-frequency vibration isolation, and compact designs. Additionally, integrating optimization algorithms and artificial intelligence (AI) enhances AMM design precision and scalability. …”
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Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges by Jielu Yan, Zhengli Chen, Jianxiu Cai, Weizhi Xian, Xuekai Wei, Yi Qin, Yifan Li

“…Recent advances in artificial intelligence—especially machine learning (ML), deep learning (DL), and pattern recognition—offer game-changing opportunities to accelerate AMP design and validation. By integrating video analysis with computational modelling, researchers can visualise and quantify AMP–microbe interactions at unprecedented levels of detail, thereby informing both experimental design and the refinement of predictive algorithms. …”
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Marine data assimilation in the UK: the past, the present, and the vision for the future by J. Skákala, J. Skákala, D. Ford, K. Haines, K. Haines, A. Lawless, A. Lawless, M. J. Martin, P. Browne, M. Chrust, S. Ciavatta, A. Fowler, A. Fowler, D. Lea, M. Palmer, A. Rochner, A. Rochner, J. Waters, H. Zuo, D. S. Banerjee, D. S. Banerjee, M. Bell, D. M. Carneiro, Y. Chen, Y. Chen, S. Kay, S. Kay, D. Partridge, D. Partridge, M. Price, R. Renshaw, G. Shapiro, J. While

“…We also advocate for integrated approaches, such as strongly coupled DA (ocean–atmosphere, physics–biogeochemistry, and ocean–sea ice) and the use of ML/AI components (e.g. for multivariate increment balancing, bias correction, model emulation, observation re-gridding, or fusion).…”
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Behavior Modeling and Bio-Hybrid Systems: Using Reinforcement Learning to Enhance Cyborg Cockroach in Bio-Inspired Swarm Robotics by Le Minh Triet, Nguyen Truong Thinh

“…Future work will explore scaling the swarm system and integrating advanced sensors and AI algorithms.…”
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Preliminary Study on Sensor-Based Detection of an Adherent Cell’s Pre-Detachment Moment in a MPWM Microfluidic Extraction System by Marius-Alexandru Dinca, Mihaita Nicolae Ardeleanu, Dan Constantin Puchianu, Gabriel Predusca

“…Image processing and deep learning algorithms determine object center coordinates, allowing the MPWM system to dynamically adjust suction parameters. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Abstract Chemoinformatics is a rapidly advancing field that integrates chemistry, computer science, and data analysis to enhance the study and application of chemical systems. …”
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Self‐Learning e‐Skin Respirometer for Pulmonary Disease Detection by Anand Babu, Getnet Kassahun, Isabelle Dufour, Dipankar Mandal, Damien Thuau

“…To empower the eSR with early diagnosis functionality, self‐learning capability is further added by integrating the respirometer with the machine learning algorithms. …”
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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

“…Future research should focus on optimizing ML algorithms, enhancing personalization, and addressing ethical concerns related to patient privacy.…”
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JMoE-FAP: A novel model for telecom network fraud victimization pattern analysis by Tuo Shi, Jing Hu, Danyang Li, Min Chen

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Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…Additionally, the LoL-MDC integrates a winning probability metric to quantitatively enhance the selection of pivotal game events, ensuring relevance in esports analytics. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…Other methods, such as Generative Adversarial Networks (GANs) and Autoencoders, are used for feature extraction, while Recurrent Neural Networks (RNNs) are employed for time-sequence modeling. Some models integrate with Internet of Things (IoT) frameworks or federated learning for real-time diagnostics and privacy, often paired with optimization algorithms. …”
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Advancements in Machine Learning (ML): Transforming the Future of Blood Cancer Detection and Outcome Prediction by Wiebke Rösler, Michael Roiss, Corinne Widmer

“…Recent studies demonstrate that ML algorithms can rapidly predict hematologic malignancies and patient outcomes, matching or exceeding the accuracy of experienced hematologists. …”
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“I exist because I adapt”: Evolving technology HR themes, HR roles with STARA competencies for performance by Vinit Ghosh, Gaurav Kabra

“…The paper aims to understand the research themes evolved from 2011-2024 in Human resource (HR) technology field and highlight key HR technology roles with STARA (Smart Technology, AI, Robotics and Algorithms) competencies. To capture the technology shift and research themes in the technology HR field pre- and post-pandemic period, we conducted bibliometric analysis for the two time periods viz., 2011-2019 and 2020-2024. …”
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An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion by Kavita Rawat, Trapti Sharma

“…The suggested method overcomes the shortcomings of earlier studies, which tended to concentrate on single-modality data, lacked thorough neurocardiac data fusion, and made use of less advanced machine learning algorithms. The comprehensive experimental findings, which provide an average improvement in accuracy of 2.72%, demonstrate that the suggested work performs better than other cutting-edge AI techniques and generalizes effectively across diverse datasets.…”
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Hybrid Series of Carbon‐Vacancy Electrodes for Multi Chemical Vapors Diagnosis Using a Residual Multi‐Task Model by Tianci Liu, Yun Ji Hwang, Lu Zhang, Jongwoo Hong, Teajong Hwang, Seong Chan Jun

“…Artificial intelligence (AI) integrated gas sensor systems effectively enable multi‐gas detection using specialized algorithms. …”
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Synergistic frameworks for sensor fault isolation and accommodation in grid-side converters by Faizan Mehmood, Lenos Hadjidemetriou, Panayiotis M. Papadopoulos, Marios M. Polycarpou

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Occupancy Monitoring Using BLE Beacons: Intelligent Bluetooth Virtual Door System by Nasrettin Koksal, AbdulRahman Ghannoum, William Melek, Patricia Nieva

“…Bluetooth low energy (BLE) technology is energy- and cost-efficient compared to other technologies. Integrating BLE Received Signal Strength Indicator (RSSI) signals with machine learning (ML) introduces a new Artificial Intelligence- (AI-) enhanced OM approach. …”
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AIoT-Driven Human Activity Recognition for Versatile Framework on Multipurpose Applications by Nanik Triwahyuni, Eni Wardihani, Aminuddin Rizal, Samuel Beta, Ricky Sambora, Rindang Oktaviani

“… This paper presents the implementation of an AIoT-based Human Activity Recognition (HAR) framework designed for multipurpose applications. The framework integrates sensor data from wearable IoT devices, which is then processed by AI algorithms to classify and predict human activities in real-time. …”
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Battery Health Monitoring and Remaining Useful Life Prediction Techniques: A Review of Technologies by Mohamed Ahwiadi, Wilson Wang

“…Data-driven techniques leverage historical data, AI, and machine learning algorithms to identify degradation trends and predict RUL, which can provide flexible and adaptive solutions. …”
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