Machine Learning Approaches to Code Similarity Measurement: A Systematic Review by Zixian Zhang, Takfarinas Saber

“…Following a rigorous systematic review protocol, we identified and analyzed 84 primary studies on a broad spectrum of dimensions covering application type, devised Machine Learning algorithms, used code representations, datasets, and performance metrics, as well as performance evaluations. …”
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Construction of a sugar and acid content estimation model for Miliang-1 kiwifruit during storage by LIU Li, YANG Tianyi, DONG Congying, SHI Caiyun, SI Peng, WEI Zhifeng, GAO Dengtao

“…This study aims to develop a reliable and efficient method for evaluating the quality of kiwifruit during storage without damaging the samples, thereby providing a more practical and economical solution for the kiwifruit industry. …”
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Machine learning approaches in the therapeutic outcome prediction in major depressive disorder: a systematic review by Veronica Atemnkeng Ntam, Tatjana Huebner, Michael Steffens, Catharina Scholl

“…The objective of the evaluation was to assess applicability of currently published ML-approaches for clinical settings in the EU on the basis of quality, ethical, social, and legal criteria.MethodsWe performed a bibliographic search on PubMed and Google Scholar for studies from January 2016 to December 2024 on ML-applications predicting treatment outcomes in MDD. …”
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Research of color models in digital graphics by Hetman Oksana, Shpetna Svitlana

“…The purpose of this article is to investigate the main color models, analyze their features, working principles, advantages, limitations, and areas of application in digital graphics. The research methods include the analysis of scientific sources, comparative evaluation of color models, and the study of practical cases of their implementation in graphic editors and specialized software. …”
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An Efficient Biobjective Heuristic for Scheduling Workflows on Heterogeneous DVS-Enabled Processors by Pengji Zhou, Wei Zheng

“…Energy consumption has recently become a major concern to multiprocessor computing systems, of which the primary performance goal has traditionally been reducing execution time of applications. In the context of scheduling, there have been increasing research interests on algorithms using dynamic voltage scaling (DVS), which allows processors to operate at lower voltage supply levels at the expense of sacrificing processing speed, to acquire a satisfactory trade-off between quality of schedule and energy consumption. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…Security analysis demonstrates that under the Canetti–Krawczyk (CK) model and the Decisional Diffie–Hellman (DDH) security assumption, the SEUS-VCS scheme satisfies the security of session keys. Performance evaluation indicates that compared to other key exchange schemes, the SEUS-VCS scheme shows a significant advantage in supporting national cryptographic algorithms and anonymity. …”
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A Review on Trending Machine Learning Techniques for Type 2 Diabetes Mellitus Management by Panagiotis D. Petridis, Aleksandra S. Kristo, Angelos K. Sikalidis, Ilias K. Kitsas

“…Our work indicates that Gradient Boosting and tree-based models are the most successful ones, the SHAPley and Wrapper algorithms being quite popular feature interpretation and evaluation methods, highlighting urinary markers and dietary intake as emerging diabetes predictors besides the typical invasive ones. …”
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Chaotic Hénon–Logistic Map Integration: A Powerful Approach for Safeguarding Digital Images by Abeer Al-Hyari, Mua’ad Abu-Faraj, Charlie Obimbo, Moutaz Alazab

“…Performance evaluation in terms of encryption time, throughput, and image quality metrics validates the effectiveness of the proposed integrated approach. …”
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Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…However, traditional chemical analysis methods are often time-consuming and costly, limiting their application in real-time quality control. Hyperspectral imaging (HSI) has shown significant effectiveness as a component detection tool in various agricultural applications. …”
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Improvement of Methodological Tools for Business Analysis of the Effective Company’s Performance by N. S . Plaskova

“…The practical application of the proposed adjusted procedures for calculating indicators contributes to getting a reliable and aimed assessment of the quality of the management system of organizations in the real sector of the economy. …”
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Investigation with Bluetooth Sensors of Bicycle Travel Time Estimation on a Short Corridor by Zhenyu Mei, Dianhai Wang, Jun Chen

“…Test data are used to measure the quality of bicycle travel time data collected by the Bluetooth sensors, and the results show that the new technology is a promising method for collecting high-quality travel time data that can be used as ground truth for evaluating other sources of travel time and other intelligent transportation system applications.…”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…Extensive simulations are conducted to evaluate the performance of the proposed method against state-of-the-art algorithms in terms of coverage quality and node count. …”
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Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

“…We propose a threshold-based transmission-decision policy based on the sensing quality and the network spatial deployment. We optimize the transmission thresholds using several approaches such as successive convex approximation, block coordinate descent methods, Voronoi diagrams, explainable machine learning, algorithms based on natural selection and social behavior, and Q-learning. …”
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Fuzzy LQR-based control to ensure comfort in HVAC system with two different zones by Elif Çinar, Tayfun Abut

“…The effectiveness of the proposed method (FLQR) is demonstrated through a comprehensive performance evaluation using Mean Squared Error (MSE) metrics, confirming its potential for intelligent HVAC applications.…”
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Image-Based Laser-Beam Diagnostics Using Statistical Analysis and Machine Learning Regression by Tayyab Imran, Muddasir Naeem

“…By integrating deterministic analysis with data-driven forecasting, this methodology offers a robust framework for real-time beam quality evaluation. It enhances sensitivity to subtle distortions and supports the future development of automated, self-correcting laser systems. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…This study synthesizes findings from 39 high-quality articles published between 2016 and 2024, evaluating various machine learning (ML), deep learning (DL), regression, and hybrid models in sectors such as construction, healthcare, manufacturing, and real estate. …”
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Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports by Sophia Wesely, Ella Hofer, Robin Curth, Shyam Paryani, Nicole Mills, Olaf Ueberschär, Julia Westermayr

“…Using triaxial accelerations and rotational speeds, various ML algorithms were employed to classify and evaluate the execution of tumbling manoeuvres. …”
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Using the power of artificial intelligence to improve the diagnosis and management of nonmelanoma skin cancer by Fahimeh Abdollahimajd, Fatemeh Abbasi, Alireza Motamedi, Narges Koohi, Reza Mohamoud Robati, Mona Gorji

“…Building patient trust is also essential for the successful implementation of AI in the clinical settings. AI algorithms may outperform experts in controlled environments but can fall short in the real-world clinical applications, indicating a need for more prospective studies to evaluate their effectiveness in the practical scenarios. …”
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Image Preprocessing Framework for Time-domain Astronomy in the Artificial Intelligence Era by Liang Cao, Peng Jia, Jiaxin Li, Yu Song, Chengkun Hou, Yushan Li

“…Image preprocessing, which involves standardizing images for training or deployment of various AI algorithms, encompasses essential steps such as image quality evaluation, alignment, stacking, background extraction, gray-scale transformation, cropping, source detection, astrometry, and photometry. …”
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Tennis Timing Assessment by a Machine Learning-Based Acoustic Detection System: A Pilot Study by Lucio Caprioli, Amani Najlaoui, Francesca Campoli, Aatheethyaa Dhanasekaran, Saeid Edriss, Cristian Romagnoli, Andrea Zanela, Elvira Padua, Vincenzo Bonaiuto, Giuseppe Annino

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