LiveDrive AI: A Pilot Study of a Machine Learning-Powered Diagnostic System for Real-Time, Non-Invasive Detection of Mild Cognitive Impairment by Firas Al-Hindawi, Peter Serhan, Yonas E. Geda, Francis Tsow, Teresa Wu, Erica Forzani

“…The implications of this work suggest a transformative step towards scalable, real-world solutions for early AD diagnosis, with the potential to improve patient outcomes and disease management.…”
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AMEND 2.0: module identification and multi-omic data integration with multiplex-heterogeneous graphs by Samuel S. Boyd, Chad Slawson, Jeffrey A. Thompson

“…AMEND was applied to two real-world multi-omic datasets: renal cell carcinoma data from The cancer genome atlas and an O-GlcNAc Transferase knockout study. …”
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Strategies for inclusive digital education: problem/project-based learning, cooperative learning, and service learning for students with special educational needs by Paola D’Elia, Aleksandra Stalmach, Sergio Di Sano, Gino Casale

“…., Google Docs) facilitate structured dialogue, peer collaboration, and shared responsibility, thereby increasing engagement; in SL, linking learning to real-world practice and designing experiences that reflect students’ abilities and interests emerge as crucial, especially for students with SEN.DiscussionThe implications of these findings suggest that educators should adopt flexible and adaptive strategies to successfully implement PBL, CL, and SL to ensure that they meet the diverse needs of students in digital environments. …”
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A novel inverse method for Advanced monitoring of lubrication conditions in sliding bearings through adaptive genetic algorithm by Zhenpeng Wu, Bowen Dong, Liangyi Nie, Adnan Kefal

“…The lubrication states of the experimental sliding bearing under loads of 100 N, 200 N, 300 N, and 400 N were successfully predicted, highlighting the method’s reliability in real-world applications. This study provides a new approach and perspective for health monitoring and fault diagnosis of sliding bearings, especially under extreme conditions.…”
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The Burden of Hypoxic Respiratory Failure in Preterm and Term/Near-term Infants in the United States 2011-2015 by Shivani Pandya, Onur Baser, George J. Wan, Belinda Lovelace, Jim Potenziano, An T. Pham, Xingyue Huang, Li Wang

“…The results show significant unmet medical need; further research is warranted to determine new treatments and real-world evidence for improved patient outcomes.…”
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Network Embedding-Aware Point-of-Interest Recommendation in Location-Based Social Networks by Lei Guo, Haoran Jiang, Xiyu Liu, Changming Xing

“…Experiments on two real-world datasets demonstrate the importance of the network embeddings and the effectiveness of our proposed method.…”
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Detecting Community Structures in Networks by Label Propagation with Prediction of Percolation Transition by Aiping Zhang, Guang Ren, Yejin Lin, Baozhu Jia, Hui Cao, Jundong Zhang, Shubin Zhang

“…Experimental results on synthetic networks and real-world networks show that the LPAp is more accurate, more sensitive to small community, and has the ability to identify a single community structure. …”
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Enhancing Wastewater Treatment Efficiency Using MBBR: A Media Selection Approach by Mehdi Shamsabadizadeh, Nasser Mehrdadi, Akbar Baghvand

“…Future studies should focus on scaling up the MBBR system with K5 media to further evaluate its long-term performance in real-world conditions.…”
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ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest by Andrey Ageev, Andrei Konstantinov, Lev Utkin

“…Our results validate the ADA-NAF’s effectiveness and versatility as a robust solution for real-world anomaly detection challenges with promising applications in cybersecurity, industrial monitoring, and healthcare diagnostics. …”
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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…The research results highlight significant implications regarding subsequent studies and real-world uses in SE prediction, accentuating the positive impacts of incorporating accurate data decomposition and adaptive optimized performance.…”
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Adaptive coordinated control for an under-actuated airplane–tractor system with parameter uncertainties by Pengjie Xu, Weining Huang, Tianrui Zhao, Wei Zhang, Tongwei Lu, Guiyan Qiang, Lin Zhang, Yanzheng Zhao

“…Model accuracy and controller effectiveness are validated by comparing with other methods, the robustness of the proposed method are validated under different conditions in both simulation and real-world environment.…”
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Automated 3D semantic segmentation of PCB X-ray CT images and netlist extraction by Adrian Phoulady, Yara Suleiman, Hongbin Choi, Nicholas May, Sina Shahbazmohamadi, Pouya Tavousi

“…Validation with both synthetic and real-world PCB datasets shows high accuracy and robustness, offering a scalable solution for PCB design reconstruction.…”
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Business Process Modeling Patterns for Blockchain Application Development by Fouzia Alzhrani, Kawther Saeedi, Liping Zhao

“…Through a trend analysis of real-world blockchain applications, we identified recurring business processes across domains and validated our patterns by comparing them to existing literature and a proof-of-concept application. …”
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Real-Time Quality Monitoring and Anomaly Detection for Vision Sensors in Connected and Autonomous Vehicles by Elena Politi, Charalampos Davalas, Christos Chronis, George Dimitrakopoulos, Dimitrios Michail, Iraklis Varlamis

“…On this basis we adopt a two-stage approach to validate the performance of the proposed methods against a baseline Convolutional Neural Network (CNN) in a controlled low-criticality environment, as well as in more complex real-world scenarios. Our experimental results demonstrate high accuracy and robustness for anomaly detection in comparison to existing supervised techniques, which is crucial for real-time and autonomous operations of CAVs.…”
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Terrain Adaptive Estimation of Instantaneous Centres of Rotation for Tracked Robots by Cuifeng Wang, Wenjun Lv, Xiaochuan Li, Mingliang Mei

“…On the other hand, the sudden changes in innovation are used to adjust the state transition probability during the recursive calculation of the Bayesian filter, thus increasing the accuracy of the terrain classification. A real-world experiment was undertaken on a tracked robot to validate the effectiveness of the proposed method. …”
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Computer Vision-assisted Wireless Channel Simulation for Millimeter Wave Human Motion Recognition by Zhenyu REN, Chenqing JI, Chao YU, Wanli CHEN, Rui WANG

“…Experimental results indicate that the deep neural network trained with the simulated dataset achieves an average recognition accuracy of 73.0% in real-world wireless motion recognition. Furthermore, he recognition accuracy can be increased to 93.75% via unlabeled transfer learning and fine-tuning with a small amount of actual data.…”
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GPS TRAJECTORY CLUSTERING FOR SPATIO – TEMPORAL BEHAVIOR ANALYSIS: THE APPLICATION OF HEATMAP TECHNIQUES AND SPATIO- TEMPORAL DUAL GRAPH NEURAL NETWORK by Mais Muhanad, Wadhah R.Baiee

“…The suggested method has been shown to identify relevant clusters effectively and reveal noteworthy spatio-temporal characteristics through experimental analysis on real-world GPS datasets. The research utilizes a dataset comprising 182 users for analysis. …”
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Applying fuzzy analytic hierarchy process to select models developed by abstraction and decision fusion architecture (case study: classification of Persian handwritten characters) by Mohammad Safaei, Somaye Moghari, Mohammad Kazem Fallah, Mehrdad Ghaznavi

“…The proposed methodology has three main phases: 1) developing models based on the ADFA, 2) defining evaluation criteria, and 3) selecting models using the Fuzzy Analytic Hierarchy Process (FAHP).Findings: The experimental results of this research demonstrate the effectiveness of this approach in developing suitable machine learning models for applications related to wearable devices, such as smart glasses.Originality/Value: This research introduces three innovations: 1) the use of ADFA for developing models for the classification of Persian handwritten characters, 2) defining a new abstraction for summarizing handwritten character images, and 3) developing a fuzzy multi-criteria decision-making approach for mapping the developed models in the ADFA to real-world applications.…”
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Discrete Train Speed Profile Optimization for Urban Rail Transit: A Data-Driven Model and Integrated Algorithms Based on Machine Learning by Kang Huang, Jianjun Wu, Xin Yang, Ziyou Gao, Feng Liu, Yuting Zhu

“…To fill this gap, according to the actual speed and energy data collected from the real-world urban rail system, this paper proposes a data-driven model and integrated heuristic algorithm based on machine learning to determine the optimal speed profile with minimum energy consumption. …”
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Recent Progress about Flight Delay under Complex Network by Tang Zhixing, Huang Shan, Han Songchen

“…Complex network was introduced into research studies on flight delays due to its low complexity, high flexibility in model building, and accurate explanation about real world. We surveyed recent progress about flight delay which makes extensive use of complex network theory in this paper. …”
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