Shade Artifact Reduction in CBCT-to-MDCT: Fine-Tuning Based on Style Transfer and Human Feedback by Hyun-Cheol Park, Kiwan Jeon, Hyoung Suk Park, Sung Ho Kang

“…In this paper, we propose a fine-tuning method that integrates human feedback with style transfer techniques to effectively address this issue, thereby improving the model’s adaptability and performance. Our method involves re-training the Cycle-GAN generator to learn and replicate the feature distribution of clean MDCT images, significantly reducing shading artifacts and preserving morphological structures. …”
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A Novel Lightweight Deep Learning Approach for Drivers’ Facial Expression Detection by Jia Uddin

“…However, deploying such systems in resource-constrained environments like vehicles requires lightweight architectures to ensure real-time performance, efficient model updates, and compatibility with embedded hardware. …”
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A Decentralized Digital Watermarking Framework for Secure and Auditable Video Data in Smart Vehicular Networks by Xinyun Liu, Ronghua Xu, Yu Chen

“…D2WaVe consists of two core components: FIAE-GAN, a novel feature-integrated and attention-enhanced robust image watermarking model based on a Generative Adversarial Network (GAN), and BloVA, a <b>Blo</b>ckchain-based <b>V</b>ideo frames <b>A</b>uthentication scheme. …”
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A Reactive Power Partitioning Method Considering Source–Load Correlation and Regional Coupling Degrees by Jiazheng Ding, Xiaoyang Xu, Fengqiang Deng

“…Conventional static electrical distance-based partitioning methods struggle to adapt to dynamic coupling effects caused by renewable energy output fluctuations, leading to degraded partition decoupling performance. This study innovatively constructs a Copula function-based joint probability distribution model for source–load correlation. …”
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CoDAC: Autonomous Obstacle Avoidance Optimization for Unmanned Surface Vehicle Clusters via Multi-Modal Dynamic Perception and Collaborative Community Detection by Youhong Li, Jiawei Ye, Le Gao, Min Cai

“…Meanwhile, the Improved Velocity Obstacle Model (IVO-DWA) integrates Triangle Obstacle Zone (TOZ) prediction with multi-objective optimization, enabling real-time trade-offs among path length, smoothness, and compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Then, iTransformer is utilized for feature extraction to capture nonlinear dependencies among multivariate inputs and global temporal patterns. …”
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Quantification of Flavonoid Contents in Holy Basil Using Hyperspectral Imaging and Deep Learning Approaches by Apichat Suratanee, Panita Chutimanukul, Kitiporn Plaimas

“…Cross-validation demonstrated the model’s robust predictive capability in identifying antioxidant-rich samples. …”
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A novel mutual information-based Boolean network inference method from time-series gene expression data. by Shohag Barman, Yung-Keun Kwon

“…<h4>Results</h4>In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI) method. …”
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Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition by Ahmad S. Lateef, Mohammed Y. Kamil

“…Our method integrates multiple feature extraction algorithms within a user-friendly graphical interface, specifically designed in English to enhance usability. …”
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Study on the Quantitative Assessment of Impact Damage of Yellow Peaches Using the Combined Hyperspectral Technology and Mechanical Parameters by Feng Zhang, Bin Li, Hai Yin, Jiping Zou, Aiguo Ouyang

“…The results showed that there is a strong linear correlation between the spectral data and the mechanical parameters, and the prediction performance of the SNV-CARS-PLSR model is best, and the RP and RMSEP of the damaged area, absorbed energy, maximum contact force, and maximum stress of it were 0.920 and 86.452 mm2, 0.845 and 1.303 J, 0.943 and 49.666 N, 0.660 and 0.146 MPa, respectively. …”
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A hybrid prediction and multi-objective optimization framework for limestone calcined clay cement concrete mixture design by Xi Chen, Weiyi Chen, Zongao Li, Pu Zhang

“…A dataset of 387 LC3 specimens was constructed to develop ML models for predicting compressive strength. Multivariate Imputation by Chained Equations-Extreme Gradient Boosting (MICE-XGBoost) model achieved the highest accuracy of R2 = 0.928 (± 0.009). …”
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A Systematic Literature Review of Machine Learning-Based Personality Trait Detection Using Electroencephalographic Data by Celina Rieck, Pascal Penava, Ricardo Buettner

“…Deep learning models, particularly hybrid architectures, outperform traditional machine learning classifiers, highlighting the advantage of deep feature extraction in EEG data processing. …”
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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network by Le Han, Hui Zhang, Nan An

“…Furthermore, we incorporate a mechanism into the base prioritized experience replay (PER) and N-step updates, which combines the current temporal difference error (TD-error) with historical priorities and includes a policy entropy penalty term, thereby enhancing DQN’s ability to learn long-term dependencies. The performance of the PSO-DQN model is further improved through an enhanced <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ε</mi></semantics></math></inline-formula>-greedy policy and learning rate decay strategy. …”
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Detection Framework for Few-Shot Voltage Disturbances in Power Systems Using Evaluation Learning by Wenxia Sima, Han Zhang, Ming Yang

“…Data-driven detection models for voltage disturbance in power systems have performed exceptionally over the years. …”
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Can Broadening the Kidney Biopsy Criteria Reduce Misleading Diagnoses in Young Patients with End-Stage Renal Diseases? A Survey on the Sicilian Registry of Nephrology, Dialysis, an... by Vincenzo Calabrese, Giovanni Conti, Giulio Geraci, Ligia J. Dominguez, Valeria Cernaro, Maria Teresa Zicarelli, Guido Gembillo, Elisa Longhitano, Domenico Santoro

“…A Student T-test, Mann–Whitney test or Pearson Chi-Square test was performed. Logistic regression analysis detected the association between the variables and the unknown diagnosis, and variables with a <i>p</i>-value < 0.2 were added to the multivariate model. …”
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CNN-Based Object Recognition and Tracking System to Assist Visually Impaired People by Fahad Ashiq, Muhammad Asif, Maaz Bin Ahmad, Sadia Zafar, Khalid Masood, Toqeer Mahmood, Muhammad Tariq Mahmood, Ik Hyun Lee

“…Moreover, a score-based quantitative comparative analysis is performed using the supported features of devices. …”
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Immunohistochemical analysis of GFAP expression in the experimental sepsis-associated encephalopathy by T. V. Shulyatnikova, V. O. Tumaskyi

“…The aim of this study was determining immunohistochemical features of GFAP expression in various brain regions in the model of rodent experimental sepsis. …”
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Heart Rate Variability-Based Stress Detection and Fall Risk Monitoring During Daily Activities: A Machine Learning Approach by Ines Belhaj Messaoud, Ornwipa Thamsuwan

“…In the second phase, integrating the cluster labels obtained from the first phase together with HRV features into machine learning models for fall risk classification, we found that Gradient Boosting performed the best, achieving an accuracy of 95.45%, a precision of 93.10% and a recall of 85.71%. …”
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A Comparative Analysis of Machine Learning and Pedotransfer Functions Under Varying Data Availability in Two Greek Regions by Panagiotis Tziachris, Panagiota Louka, Eirini Metaxa, Miltiadis Iatrou, Konstantinos Tsiouplakis

“…These contrasting results emphasize the need for context-specific modeling strategies, careful feature selection, and caution against the assumption that more data or complexity inherently improves the predictive performance.…”
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COMPARATIVE CHARACTERISTICS OF THE STRUCTURE OF THE VENOUS WALL OF THE EXTREMITIES OF HUMANS AND DOGS by Дмитрий Алексеевич Евсюков, Антон Юрьевич Цуканов, Юрий Тихонович Цуканов, Вера Павловна Дорофеева, Илья Олегович Снитко, Мурат Ханапиевич Аликберов, Александр Николаевич Кузовкин, Илья Евгеньевич Винник

“…Most often, Wistar rats are used in experiments for morphological studies of the venous system of the lower extremities. However, modeling and studying varicose veins in dogs may be a more promising alternative. …”
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