Bayesian approach for localizing cardiac sources in Magnetocardiography using Vectorcardiography based total variational priors by Vikas R. Bhat, Karunakar Kotegar, H. Anitha

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An Overview of the Empirical Evaluation of Explainable AI (XAI): A Comprehensive Guideline for User-Centered Evaluation in XAI by Sidra Naveed, Gunnar Stevens, Dean Robin-Kern

“…Recent advances in technology have propelled Artificial Intelligence (AI) into a crucial role in everyday life, enhancing human performance through sophisticated models and algorithms. However, the focus on predictive accuracy has often resulted in opaque black-box models that lack transparency in decision-making. …”
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Disulfidptosis-related gene in acute myocardial infarction and immune microenvironment analysis: A bioinformatics analysis and validation. by Nan Huang, Chan Liu, Zheng Liu, Haibo Lei

“…Immune landscape analysis showed that hub genes were closely related to the immune microenvironment. By predictive analysis, we obtained four miRNAs, thirteen small molecule drugs, and five TFs closely related to hub genes. …”
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Phylogenetic quantification of intra-tumour heterogeneity. by Roland F Schwarz, Anne Trinh, Botond Sipos, James D Brenton, Nick Goldman, Florian Markowetz

“…The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. …”
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Advancements in Remote Sensing for Monitoring and Risk Assessment of Glacial Lake Outburst Floods by Serik Nurakynov, Nurmakhambet Sydyk, Zhaksybek Baygurin, Larissa Balakay

“…Central to this review is the exploration of multi-sensor data fusion for high-resolution lake dynamics mapping, machine learning algorithms for predictive risk modelling, and hydrodynamic simulations for flood propagation analysis. …”
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Early Warning Systems for Plant Diseases in delta regions: Machine Learning Approaches by Biswas Debarghya, Sharma Priti

“…Advanced data analytics and predictive modeling are used in these systems which use this to alert and give the farmers actionable insight into what they should do to prevent the disease from reaching cause irreparable damage before it happens. …”
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Review of Methods and Models for Forecasting Electricity Consumption by Kamil Misiurek, Tadeusz Olkuski, Janusz Zyśk

“…In conclusion, the authors highlight the lack of a universal forecasting approach and the need for further research on hybrid models that combine interpretability with high predictive accuracy. This review can serve as a valuable resource for decision-makers, grid operators, and researchers involved in energy system planning.…”
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Data-Driven Modeling and Enhancement of Surface Quality in Milling Based on Sound Signals by Paschalis Charalampous

“…In order to address this, a novel classification approach was developed that maps audio waveform data into predictive indicators of surface quality. In particular, an experimental dataset was employed consisting of sound signals that were captured during milling procedures applying various machining conditions, where each signal was labeled with a corresponding roughness quality obtained via offline metrology. …”
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Artificial intelligence techniques applications in the wastewater: A comprehensive review by Zakur Yahya, Márquez Fausto, Al-Taie Ali, Alsaidi Saif, Alsadoon Abeer, Mirashrafi Seyed Bagher, Flaih Laith, Zakoor Yousif

“…Also, the review discusses the application of the various (AI) algorithms on the various wastewater treatment plants (WWTPs), predicting (“WWTP”) effluent properties, the wastewater inflows, the anomaly detecting, and the energy optimization. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In recent years, machine learning techniques, such as artificial neural networks (ANNs), have been successfully applied to more efficiently extract valuable information from spectral data and to accurately predict quality traits. In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. …”
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A three-dimensional reconstruction method of coal mine tunnel fused with LiDAR and IMU by Qinghua MAO, Jianquan CHAI, Yanzhang CHEN, Xusheng XUE, Chuanwei WANG

“…Compared with the A-LOAM and LEGO-LOAM algorithms, the proposed algorithm has significantly improved the accuracy and global consistency of pose estimation. …”
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Patterns and risk factors of falls among older adults: a systematic review by Tetiana Yermakova

“…The model quality was assessed using the Perplexity Score (model prediction accuracy) and Coherence Score (topic coherence). …”
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Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

“…Finally, principal component analysis (PCA) and machine learning algorithms were applied for CWA classification. The obtained PCA plots showed significant differences between groups, and the narrow neural network among the machine learning algorithms achieves a prediction accuracy of nearly 100.0%. …”
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Intelligent building design based on green and low-carbon concept by Qian Lv

“…Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. …”
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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…This enables the reduction of computational resources during detection processing while maintaining detection accuracy, even when using fewer features and lightweight machine learning algorithms. …”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“…The research not only deepens the understanding of emotion classification algorithms but also provides valuable perspectives for their application in crucial areas such as mental health and personalized medical assistance. …”
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A Hybrid Model for Freight Train Air Brake Condition Monitoring by Alessandro Galimberti, Federico Zanelli, Gisella Tomasini

“…To achieve this goal, advanced algorithms for air brake modelling are required. This paper introduces a computationally efficient air brake model tailored for real-time diagnostic applications. …”
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Multi-Objective Optimization for Artificial Island Construction Scheduling Using Cooperative Differential Evolution by Tianju Zheng, Liping Sun, Jifeng Chen, Xinyuan Cui, Shuqi Li

“…Comparing MOCDE with established algorithms, results indicate that MOCDE improvements over previous SOTA models, achieving a reduction of 0.56% in Total Time, a decrease of 0.43% in Total Cost, and an enhancement of 7.38% in Total Quality. …”
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Online Non-Intrusive Efficiency Monitoring of Pumping Systems by Mohammad Javad Karimi, Ali Sadighi

“…This results in the overall reduction of energy consumption and consequently lowers the carbon footprint of pumping systems. …”
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Decision Feedback Equalization-Based Low-Complexity Interference Cancellation and Signal Detection Technique Based for Non-Orthogonal Signaling by Myung-Sun Baek, Hyoung-Kyu Song

“…To mitigate the effects of ISI, interference cancellation and signal detection processes are essential for FTN receivers. Conventional ISI reduction techniques often utilize trellis-based algorithms. …”
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