Parallel Fractal Compression Method for Big Video Data by Shuai Liu, Weiling Bai, Gaocheng Liu, Wenhui Li, Hari M. Srivastava

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Real-time classroom student behavior detection based on improved YOLOv8s by Xiaojing Sheng, Suqiang Li, Sixian Chan

“…With the rapid advancement of behavior detection technology, identifying classroom behaviors of students is becoming increasingly common in educational settings. However, the field still faces specific challenges, primarily concerning the accuracy of identifying student behaviors within complex and variable classroom environments, as well as the real-time capabilities of detection algorithms. …”
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Joint NTAV/SPA 2012 Conference Lodz University of Technology Poland, September 27 – 29, 2012 by Paweł STRUMIŁŁO

“…On behalf of the conference co-organizers the Polish Section of the Audio Engineering Society and the Polish Association of Theoretical and Applied Electrotechnics the NTAVSPA 2012 Organizing Committee acknowledges the financial support of the Ministry of Science and Higher Education.…”
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Spammer group detection based on cascading and clustering of core figures by Qianqian Jiang, Chunrong Zhang, Ning Li, Dickson K. W. Chiu, Xianwen Fang, Shujuan Ji

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Smartphone sensor-based depression detection in campus environments: a proof-of-concept study with small-sample behavioral analysis by Yichen Bai, Yueze Liu, Yang Zhang, Amr Tolba

“…Feature selection was conducted using Pearson correlation, and model validation was performed using leave-one-out cross-validation with common classification algorithms.ResultsThe results yielded accuracy rates between 73.11% and 88.24%. …”
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STBNA-YOLOv5: An Improved YOLOv5 Network for Weed Detection in Rapeseed Field by Tao Tao, Xinhua Wei

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Using artificial intelligence for sustainable crop production – a comprehensive review with a focus on potato production by Magdalena Piekutowska

“…High technology costs and the need for extensive education and training for farmers can hinder widespread AI adoption. …”
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Mechanisms of Disinformation Amplification in Hybrid Warfare: The Case of the Conflict in Ukraine by Rafał ROMAŃSKI

“…The findings indicate that disinformation is not a one-off communicative act but an iterative structure supported by three interrelated domains: propaganda communication, cognitive psychology, and algorithmic technologies. In conclusion, the research question is addressed, and five strategic action areas are proposed: media literacy education, cooperation with digital platforms, international coordination, support for independent media, and the development of cognitive resilience within society. …”
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Continuous Glucose Monitoring: A Transformative Approach to the Detection of Prediabetes by Liu X, Zhang J

“…Despite challenges such as cost and the need for effective utilization through training and education, CGM’s potential to revolutionize prediabetes management is evident. …”
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Introduction to the Special Thematic Issue "Virtual Reality and Eye Tracking" by Béatrice Hasler, Rudolf Groner

“…Simultaneously, eye tracking in VR poses new challenges to gaze analyses and requires the establishment of new tools and best practices in gaze interaction and psychological research from controlling influence factors, such as simulator sickness, to adaptations of algorithms in various situations. This thematic special issue introduces and discusses novel applications, challenges and possibilities of eye tracking and gaze interaction in VR from an interdisciplinary perspective, including contributions from the fields of psychology, human-computer interaction, human factors, engineering, neuroscience, and education. …”
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Facilitate Sustainable Architecture Through Computational Integration: A Three-Phase Framework by Passaint Massoud

“…The first phase, the Smart Learning Design Studio, Custom programmed algorithms are used to enhance the learning process in architectural education. …”
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Expert methods use in undergraduate political science programs by D. Yu. Znamenskiy

“…The key factors of successful expert methods application in educational process include the approach to the experts selection, their informational and organizational-methodological preparation for work, and strict adherence to the prescribed algorithms in the course of expertise.…”
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Elderly travel mode choice in Thailand-evaluating MNL and machine learning models by Anantaya Philuek, Panuwat Wisutwattanasak, Fareeda Watcharamaisakul, Chinnakrit Banyong, Anon Chantaratang, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

“…Results indicate that the Random Forest algorithms achieved the highest predictive performance on the comprehensive dataset (99.83% accuracy), while CatBoost demonstrated excellent performance on test data (94%). …”
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A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures by Sajjad Hussain, Carman Ka Man Lee, Yung Po Tsang, Saad Waqar

“…This dataset was used to train both ML and DL algorithms. ML algorithms included Bayesian regression (BR), K-nearest neighbors (KNN), Random Forest (RF), Decision Tree (DT), and DL algorithm convolutional neural network (CNN). …”
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Budget impact analysis of using procalcitonin to optimize antimicrobial treatment for patients with suspected sepsis in the intensive care unit and hospitalized lower respiratory t... by Osvaldo Ulises Garay, Gonzalo Guiñazú, Wanda Cornistein, Javier Farina, Ricardo Valentini, Gabriel Levy Hara

“…<h4>Results</h4>The model predicted that using procalcitonin-guided algorithms would result in 734.5 [95% confidence interval (CI): 1,105.2;438.8] thousand fewer antibiotic treatment days, 7.9 [95% CI: 18.5;8.5] thousand antibiotic-resistant cases avoided, and 5.1 [95% CI: 6.7;4.2] thousand fewer Clostridioides difficile cases. …”
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Time-Distributed Vision Transformer Stacked With Transformer for Heart Failure Detection Based on Echocardiography Video by Mgs M. Luthfi Ramadhan, Adyatma W. A. Nugraha Yudha, Muhammad Febrian Rachmadi, Kevin Moses Hanky Jr Tandayu, Lies Dina Liastuti, Wisnu Jatmiko

“…The time-distributed vision transformer learns the spatial feature and then feeds the result to the transformer to learn the temporal feature and make the final prediction afterward. We also proposed a frame sampling algorithm by squeezing the video and sampling the frame after a certain interval. …”
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A Systematic Survey of AI Models in Financial Market Forecasting for Profitability Analysis by Bilal Hassan Ahmed Khattak, Imran Shafi, Abdul Saboor Khan, Emmanuel Soriano Flores, Roberto Garcia Lara, Md. Abdus Samad, Imran Ashraf

“…We observed that ensemble and hybrid models with long short-term memory (LSTM) and support vector machines (SVM) are being more adopted for financial trends and price prediction. Moreover, hybrid models employing AI algorithms for feature engineering have great potential at par with ensemble techniques. …”
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AAMS-YOLO: enhanced farmland parcel detection for high-resolution remote sensing images by Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang

“…During feature enhancement, to effectively detect targets of different scales, the Attentional Scale Sequence Fusion with P2 network (ASFP2Net) integrates the Triple Feature Encoder (TFE) module and Scale Sequence Feature Fusion (SSFF) module. In the prediction stage, a Multi-Scale Attention Head (MSAHead) enhances adaptability through multi-scale attention mechanisms. …”
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A Deep Learning Method for Pneumoconiosis Staging on Chest X-Ray Under Label Noise by Wenjian Sun, Dongsheng Wu, Jiang Shen, Yang Luo, Hao Wang, Li Min, Chunbo Luo

“…In the coarse screening procedure, the proposed sample selection strategy divides the pneumoconiosis dataset into &#x2018;confident&#x2019; and &#x2018;less-confident&#x2019; subsets based on the logical relationship between the prediction correctness and confidence of multiple expert networks. …”
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A Machine Learning Platform for Isoform-Specific Identification and Profiling of Human Carbonic Anhydrase Inhibitors by Lisa Piazza, Miriana Di Stefano, Clarissa Poles, Giulia Bononi, Giulio Poli, Gioele Renzi, Salvatore Galati, Antonio Giordano, Marco Macchia, Fabrizio Carta, Claudiu T. Supuran, Tiziano Tuccinardi

“…In this work, we present a machine learning (ML)-based platform for the isoform-specific prediction and profiling of small molecules targeting hCA I, II, IX, and XII. …”
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