Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…In conclusion, the study highlights the promising role of AI in gastrointestinal endoscopy while underscoring the importance of continued research, algorithmic refinement, and the establishment of regulatory frameworks to fully harness its clinical potential. …”
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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…To address these limitations, this study introduces Mamba RT-DETR (MRD), an optimized architecture featuring three principal innovations: (1) We devise an efficient vehicle detection Mamba (EVDMamba) network that strategically integrates a linear-complexity state space model (SSM) to substantially mitigate computational overhead while preserving feature extraction efficacy. (2) To counteract the constrained receptive fields and suboptimal spatial localization associated with conventional SSM sequence modeling, we implement a multi-branch collaborative learning framework that synergistically optimizes channel dimension processing, thereby augmenting the model’s capacity to capture critical spatial dependencies. (3) Comprehensive evaluations on the BDD100K benchmark demonstrate that MRD architecture achieves a 3.1% enhancement in mean average precision (mAP) relative to state-of-the-art RT-DETR variants, while concurrently reducing parameter count by 55.7%—a dual optimization of accuracy and efficiency.…”
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Efficient scheduling of multiple software projects for work continuity and identical completion time by Abdulrahman Aldhubaiban, Ali AlMatouq

“…Our continuous variable model was solved in the cloud for optimality for large instances of upto 40 different software projects and 100 employees in less than 21 min using nonlinear programming algorithms. • A continuous variable nonlinear model is developed to efficiently schedule large-scale software projects. • The model enables scheduling for multiple projects with identical completion times while ensuring work continuity. • A cloud-based program architecture is designed to facilitate the testing of multiple solvers online.…”
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CHIP: Clustering Hotspots in Layout Using Integer Programming by Rohit Reddy Takkala, Chris Chu

“…However, the clusters generated from generic clustering algorithms need not achieve optimal results. In this paper, we introduce two optimal integer linear programming formulations based on triangle inequality to solve the problem of minimizing cluster count while satisfying given constraints. …”
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Engineering and Technological Advancements in Repetitive Transcranial Magnetic Stimulation (rTMS): A Five-Year Review by Abigail Tubbs, Enrique Alvarez Vazquez

“…A structured review of peer-reviewed studies from 2019 to 2024 focused on technological and clinical advancements in rTMS, including AI-driven personalized treatments, portable devices, and integrated BCIs. AI algorithms have optimized patient-specific protocols, while portable devices have expanded access. …”
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In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

“…Background: The advancement of big data analytics calls for careful selection of processing frameworks to optimize machine learning effectiveness. Choosing the appropriate framework can significantly influence the speed and accuracy of data analysis, ultimately leading to more informed decision making. …”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…Additionally, the simulation results show that the slime mold agent model can rapidly generate foraging networks in complex environments due to its efficient organization and structural resilience, as well as optimize path selection according to behavioral objectives.ConclusionABM analysis, supported by advanced algorithms, considers the basic spatial information of the site and simulates individual behavior patterns using distributed computation rules, thereby providing a new paradigm for landscape design thinking. …”
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Toward Digital Twin of Off-Road Vehicles Using Robot Simulation Frameworks by Arianna Rana, Antonio Petitti, Angelo Ugenti, Rocco Galati, Giulio Reina, Annalisa Milella

“…Digital twins provide a powerful tool for testing and maintaining products and processes in several application fields, including manufacturing, smart cities, healthcare, and agriculture, aiming to optimize operational efficiency, resource usage, and planning accuracy. …”
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Developing and validating a machine learning-based model for predicting in-hospital mortality among ICU-admitted heart failure patients: A study utilizing the MIMIC-III database by De Su, Jie Zheng, Yue-kai Shao, Jun-ya Liu, Xin-xin Liu, Kun Yu, Bang-hai Feng, Hong Mei, Song Qin

“…Future research should further optimize the models and validate them in a broader patient population to enhance their practical utility and accuracy in real clinical settings.…”
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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…We used machine learning algorithms to analyze small RNAs with significant differences between the two groups, fit the model through training sets, and optimize the model through testing sets. …”
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Monitoring and Comparative Analysis of NO₂ and HCHO in Shanghai Using Dual-Azimuth Scanning MAX-DOAS and TROPOMI by Hongmei Ren, Ang Li, Zhaokun Hu, Nannan Shao, Xinyan Yang, Hairong Zhang, Jiangman Xu, Jinji Ma

“…These findings not only reveal the spatiotemporal distribution characteristics of regional pollutants but optimize the sampling time and distance parameters for satellite–ground observation validation, providing data support for improving and enhancing the accuracy of satellite retrieval algorithms.…”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Further prospective studies are warranted to confirm these findings and optimize clinical application strategies.…”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…The approach integrates quantum computing principles into classical control frameworks, creating a hybrid methodology that leverages quantum-inspired optimization while maintaining implementation feasibility on conventional hardware. …”
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Urban monitoring, evaluation and application of COVID-19 listed vaccine effectiveness: a health code blockchain study by Tao Wang, Hongyan Li, Chaoqun Li, Zheheng Li

“…Based on population mobility, the algorithm principle of urban optimal vaccination strategy is given. …”
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Immune Microenvironment Characterization and Machine Learning-Guided Identification of Diagnostic Biomarkers for Ulcerative Colitis by Zheng Q, Wang L, Zhang Y, Peng J, Hou J, Wang H, Ma Y, Tang P, Li Y, Li H, Chen Y, Li J, Chen Y

“…Immune cell infiltration was assessed via the ImmuCellAI algorithm, while differential expression analysis and WGCNA were performed to identify key immune-related genes. …”
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An efficient detection of Sinkhole attacks using machine learning: Impact on energy and security. by Muhammad Zulkifl Hasan, Zurina Mohd Hanapi, Zuriati Ahmad Zukarnain, Fahrul Hakim Huyop, Muhammad Daniel Hafiz Abdullah

“…This paper introduces SFlexCrypt, an innovative approach tailored to address these security challenges while optimizing energy consumption in WSNs. SFlexCrypt stands out by seamlessly integrating advanced machine learning algorithms to achieve high-precision detection and effective mitigation of sinkhole attacks. …”
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Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model. by Gahao Chen, Ziwei Yang

“…Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. …”
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基于IMU信号的人工智能上肢多关节运动状态识别系统构建——卒中后人工智能运动功能评估与检测系统建设前导研究 Construction of an Artificial Intelligence Upper Limb Multi-Joint Motion State Recognition System Based on IMU Signals—A Pre... by 程相鑫1，张烁1，杜松骏1，刘子阳1，周宏宇2，3，贾伟丽2，3，李子孝2，3，刘涛1 (CHENG Xiangxin1, ZHANG Shuo1, DU Songjun1, LIU Ziyang1, ZHOU Hongyu2,3, JIA Weili2,3, LI Zixiao2,3, LIU Tao1 )

“…This suggested that optimizing sensor deployment (e.g., reducing upper arm IMUs) can reduce system complexity while maintaining high performance. …”
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