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

“…Key advantages of AI integration in endoscopy include improved sensitivity, minimized detection errors, and the potential to optimize clinical workflow efficiency. …”
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Simulation of Minefield Installation in a Video Game Engine by Maksym Maksymov, Oleksii Neizhpapa, Oleksandr Toshev, Maksym Kiriakidi

“…The first objective of this research is to improve damage prediction algorithms, enabling the simulation to more accurately estimate the consequences of ships passing through a minefield. …”
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Essay Answer Detection System Uses Cosine Similarity and Similarity Scoring in Sentences by Siti Yuliyanti, Diah Hidayatul Ula

“…The result, system's potential in educational contexts was demonstrated by testing it on essay responses. To improve accuracy and usability, future developments could use sophisticated text scoring algorithms and provide more features. …”
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DMSO-free cryopreservation of hiPSC-derived cardiomyocytes: low temperature characterization and protocol development by Akshat S. Mallya, Tessa Burrows, Jeanne Hsieh, Troy Louwagie, James R. Dutton, Brenda M. Ogle, Allison Hubel

“…A differential evolution (DE) algorithm was utilized to determine the optimal composition of a mixture of a sugar, sugar alcohol and amino acid to replace DMSO as the CPA. …”
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Determine train load and speed based on dynamic displacement results by Nhung Thi Cam NGUYEN, An Thai LE, Hoang Nguyen BUI, Thuc Van NGO, Huy Phan BUI, Minh Quang TRAN

“…By applying finite element models (FEM) and real-time displacement data analysis combined with optimization algorithms, the estimation of train load and speed is performed. …”
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Easy Data Augmentation untuk Data yang Imbalance pada Konsultasi Kesehatan Daring by Anisa Nur Azizah, Misbachul Falach Asy'ari, Ifnu Wisma Dwi Prastya, Diana Purwitasari

“…We employ the Indonesian thesaurus for changing synonyms in the EDA and do empirical experiments on parameters required by the algorithm to obtain optimal results of text augmentation. …”
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The integration of psychological education and moral dilemmas from a value perspective by XiaoFen Jia, WenQing Wu

“…Leveraging deep learning models, we aim to enhance both the scientific rigor and theoretical understanding of how these two domains intersect. …”
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Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study by Emanuele Frassini, Teddy S. Vijfvinkel, Rick M. Butler, Maarten van der Elst, Benno H. W. Hendriks, John J. van den Dobbelsteen

“…Future research should validate these findings across different procedural contexts and explore ways to optimize training times without losing accuracy. Integrating these models into clinical scheduling systems could improve efficiency in cath labs. …”
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Contributions to the Development of Tetrahedral Mobile Robots with Omnidirectional Locomotion Units by Anca-Corina Simerean, Mihai Olimpiu Tătar

“…The second prototype is presented as an advanced and improved version of the first model, integrating significant modifications in both the structural design and the robot’s functionality. …”
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A novel canopy water indicator for UAV imaging to monitor winter wheat water status by Meiyan Shu, Zhenghang Ge, Yang Li, Jibo Yue, Wei Guo, Yuanyuan Fu, Ping Dong, Hongbo Qiao, Xiaohe Gu

“…To develop robust estimation models, four machine learning algorithms were implemented across individual and combined growth stages, and their performance was validated using independent ground-measured datasets that were not used during the training process. …”
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Enhancing Dongba Pictograph Recognition Using Convolutional Neural Networks and Data Augmentation Techniques by Shihui Li, Lan Thi Nguyen, Wirapong Chansanam, Natthakan Iam-On, Tossapon Boongoen

“…Experimental results demonstrate that the proposed model achieves a classification accuracy of 99.43% and consistently outperforms other conventional methods, with its performance peaking at 99.84% under optimized training conditions—specifically, with 75 training epochs and a batch size of 512. …”
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Know your competitor! Analyzing and predicting the location of competing stores: The case study of Valora at Swiss railway stations by Thomas Wieland

“…Machine learning algorithms are used to check and optimize the predictive ability of the models. …”
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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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A survey of task deployment and recovery in space-air-ground integrated networks based on SDN and NFV by CAO Yilu, JIA Ziye, YOU Jiahao, ZHANG Lei, WU Qihui

“…Subsequently, in response to the above-mentioned challenges, based on the service function chain technology, corresponding strategies including the task-oriented service function chain optimized deployment, dynamic scheduling achieved through intelligent algorithms, and failure recovery accomplished via a matching game algorithm were proposed. …”
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LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network by Javier Viaña, Kyu-Ha Hwang, Zoë de Beurs, Jennifer C. Yee, Andrew Vanderburg, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Youn Kil Jung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge

“…We demonstrate a classification accuracy above 87.5% and anticipate further improvements as we expand our training set and continue to refine the algorithm.…”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Following hyperparameter tuning to improve the model's performance, the selected model was deployed in a real-world network environment to classify QoS into "Above Average," "Average," and "Below Average," categories. …”
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Characterizing Satellite Soil Moisture Drydown: A Bivariate Filtering Approach by Jhilam Sinha, Ashish Sharma, Lucy Marshall, Seokhyeon Kim

“…Although the algorithm assumes spatial stationarity, improvements exist across different soil properties and climatic conditions, providing a parsimonious alternative to better capture the dynamics of soil moisture loss.…”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…Our future studies will focus on long-term testing of the EcoTaskSched model in real-world IoT environments. We will also assess its applicability by integrating other ML models, which could provide enhanced insights for optimizing scheduling algorithms across diverse fog-cloud settings.…”
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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

“…Data pre-processing, specifically min-max normalization, is crucial for improving the accuracy of distance-based algorithms like KNN. …”
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