Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…However, system heterogeneity, communication costs, and data imbalance remain critical. Oversampling techniques, model optimization, and reduced communication rounds were used to mitigate the issues. …”
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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…For example, AI-based support systems offer data-driven insights that improve diagnostic accuracy and patient outcomes thus transforming healthcare delivery 3. …”
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Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation paramet... by Xin-Yue Song, Xin-Peng Xie, Wen-Jing Xu, Yu-Jia Cao, Bin-Miao Liang

“…We evaluated the effectiveness of various supervised ML algorithms and identified the optimal configurations for these applications. …”
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HOW I TREAT PH+ ACUTE LYMPHOBLASTIC LEUKEMIA by Robin Foà

“…I have been asked to cover ‘How I Treat Ph+ALL’, which more appropriately should be ‘How Should I Treat Ph+ LL’ Based on the 25-year experience gathered through the GIMEMA trials, the optimal algorithm should be: i) Identify the presence of the BCR/ABL gene lesion within one week from diagnosis; ii) During this time treat patients with steroids; iii) Start induction with dasatinib or ponatinib plus steroids, with no systemic chemotherapy; iv) CNS prophylaxis should be carried out; v) MRD should be monitored molecularly at given timepoints; vi) After induction, all patients should be consolidated with multiple cycles of blinatumomab (up to 5 in our protocols); vii) TKI should not be stopped. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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Corrective soft bus-bar splitting for reliable operation of hybrid AC/DC grids by Basel Morsy, Matthew Deakin, Adolfo Anta, Jochen Cremer

“…As the original problem is NP-hard, this paper utilizes a column-and-constraint generation algorithm. Case studies on IEEE 5, 24, 39, and 67 hybrid AC/DC systems show superiority of the proposed method, manifested as significant improvement in operating costs, security, and converter redispatch needs, under different loading conditions.…”
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LSTM-MM: Efficient LSTM-Based Mobility Management for Power Inspection Vehicles in Smart Grids by Xiaoyan Wang, Xianfeng Xie, Shengnan Zhao

“…This scheme leverages Software-Defined Networking (SDN) technology to centrally manage vehicle communication and network traffic, integrating trajectory prediction algorithms to forecast the future movements of power inspection vehicles, optimizing route planning, and improving operational efficiency and network performance. …”
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Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…This Special Issue on “Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data” presents innovative strategies leveraging remote sensing technologies, artificial intelligence (AI), and non-destructive testing (NDT) to optimize road infrastructure assessment. The ten papers published in this issue explore diverse methodologies, including novel deep learning algorithms for road inventory, novel methods for pavement crack detection, AI-enhanced ground-penetrating radar (GPR) imaging for subsurface assessment, high-resolution optical satellite imagery for unpaved road assessment, and aerial orthophotography for road mapping. …”
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Construction of Industrial Economic Management Decision Model Based on Three Parameter Interval Grey Numbers by Pao-Ching Lin, Tzu-Jung Wu, Jui-Chan Huang

“…In addition, through comparative experiments with other decision models, this model has shown superiority in improving profit margins, increasing sales, reducing unit costs, and reducing prediction errors. …”
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Approaches to Extracting Patterns of Service Utilization for Patients with Complex Conditions: Graph Community Detection vs. Natural Language Processing Clustering by Jonas Bambi, Hanieh Sadri, Ken Moselle, Ernie Chang, Yudi Santoso, Joseph Howie, Abraham Rudnick, Lloyd T. Elliott, Alex Kuo

“…Once extracted, PSUs can provide quality assurance/quality improvement (QA/QI) efforts with the information required to optimize service system structures and functions. …”
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Large-scale S-box design and analysis of SPS structure by Lan ZHANG, Liangsheng HE, Bin YU

“…A class of optimal linear transformation P over a finite field<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> <msup> <mrow> <mrow><mo>(</mo> <mrow> <msubsup> <mi>F</mi> <mn>2</mn> <mi>m</mi> </msubsup> </mrow> <mo>)</mo></mrow></mrow> <mn>4</mn> </msup> </mrow></math></inline-formula> was constructed based on cyclic shift and XOR operation.Using the idea of inverse proof of input-output relation of linear transformation for reference, a proof method was put forward that transformed the objective problem of optimal linear transformation into several theorems of progressive relation, which not only solved the proof of that kind of optimal linear transformation, but also was suitable for the proof of any linear transformation.By means of small-scale S-box and optimal cyclic shift-XOR linear transformation P, a large-scale S-box model with 2-round SPS structure was established, and a series of lightweight large-scale S-boxes with good cryptographic properties were designed.Only three kind of basic operations such as look-up table, cyclic shift and XOR were used in the proposed design scheme, which improved the linearity and difference uniformity of large-scale S-boxes.Theoretical proof and case analysis show that, compared with the existing large-scale S-box construction methods, the proposed large-scale S-box design scheme has lower computational cost and better cryptographic properties such as difference and linearity, which is suitable for the design of nonlinear permutation coding of lightweight cryptographic algorithms.…”
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AI-Driven Belt Failure Prediction and Prescriptive Maintenance with Motor Current Signature Analysis by João Paulo Costa, José Torres Farinha, Mateus Mendes, Jorge O. Estima

“…The incorporation of LSTM networks and swarm intelligence algorithms led to a significant improvement in predictive capabilities, allowing for the early detection of degradation patterns and timely intervention. …”
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A Distributed Collaborative Navigation Strategy Based on Adaptive Extended Kalman Filter Integrated Positioning and Model Predictive Control for Global Navigation Satellite System/... by Wanqiang Chen, Yunpeng Jing, Shuo Zhao, Lei Yan, Quancheng Liu, Zichang He

“…This framework predicts and optimizes each robot’s kinematic model, thereby improving the system’s collaborative operations and dynamic decision-making capabilities. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Extended Abstract Introduction Today, one of the most popular and controversial topics of discussion in accounting and auditing is blockchain technology. …”
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Reducing bias in coronary heart disease prediction using Smote-ENN and PCA. by Xinyi Wei, Boyu Shi

“…Its treatment and prevention face challenges such as high costs, prolonged recovery periods, and limited efficacy of traditional methods. …”
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Enhanced CLIP-GPT Framework for Cross-Lingual Remote Sensing Image Captioning by Rui Song, Beigeng Zhao, Lizhi Yu

“…Remote Sensing Image Captioning (RSIC) aims to generate precise and informative descriptive text for remote sensing images using computational algorithms. Traditional &#x201C;encoder-decoder&#x201D; approaches face limitations due to their high training costs and heavy reliance on large-scale annotated datasets, hindering their practical applications. …”
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Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees by Cheng Shen, Yuewei Liu

“…Traditional defect detection methods predominantly rely on manual inspection, which suffers from low efficiency and high costs. Some machine learning algorithms and artificial intelligence models for defect detection, such as Convolutional Neural Networks (CNNs), present outstanding performance, but they are often data-dependent and cannot provide guarantees for new test samples. …”
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Diabetes mellitus in the Russian Federation: dynamics of epidemiological indicators according to the Federal Register of Diabetes Mellitus for the period 2010–2022 by I. I. Dedov, M. V. Shestakova, O. K. Vikulova, A. V. Zheleznyakova, M. A. Isakov, D. V. Sazonova, N. G. Mokrysheva

“…The information-analytical system FDR is a key tool for systematizing the most important epidemiological and clinical characteristics of DM based on data from real clinical practice, which allows optimizing the algorithm of patient management and improving the quality of care for diabetes.…”
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Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review by Claire R. van Genugten, Claire R. van Genugten, Melissa S. Y. Thong, Melissa S. Y. Thong, Melissa S. Y. Thong, Wouter van Ballegooijen, Wouter van Ballegooijen, Wouter van Ballegooijen, Annet M. Kleiboer, Annet M. Kleiboer, Donna Spruijt-Metz, Arnout C. Smit, Mirjam A. G. Sprangers, Mirjam A. G. Sprangers, Yannik Terhorst, Yannik Terhorst, Heleen Riper, Heleen Riper, Heleen Riper

“…Regarding the current state of studies, initial findings on usability, feasibility, and effectiveness appear positive.ConclusionsJITAIs for mental health are still in their early stages of development, with opportunities for improvement in both development and testing. For future development, it is recommended that developers utilize complex analytical techniques that can handle real-or near-time data such as machine learning, passive monitoring, and conduct further research into empirical-based decision rules and points for optimization in terms of enhanced effectiveness and user-engagement.…”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…SHAP are also illustrated to improve model interpretability by highlighting the most influential features, thereby aiding physician understanding. …”
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