Unsupervised Action Anticipation Through Action Cluster Prediction by Jiuxu Chen, Nupur Thakur, Sachin Chhabra, Baoxin Li

“…Predicting near-future human actions in videos has become a focal point of research, driven by applications such as human-helping robotics, collaborative AI services, and surveillance video analysis. …”
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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

“…The integration of machine and deep learning algorithms has improved automated trait classification but the comparative reliability of these approaches remains unclear. …”
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Unveiling the art of video enhancement: a comprehensive examination of content selection and sequencing for optimal quality in conventional and AR/VR environments by Mehrunnisa, Mikolaj Leszczuk, Dawid Juszka

“…Integrating machine learning algorithms into data sets alongside scenario-based criteria can be an essential solution to such problems. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

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REDalign: accurate RNA structural alignment using residual encoder-decoder network by Chun-Chi Chen, Yi-Ming Chan, Hyundoo Jeong

“…REDalign significantly reduces computational complexity compared to Sankoff-style algorithms and effectively handles non-nested structures, including pseudoknots, which are challenging for traditional alignment methods. …”
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Enhancing SQL Learning: Gamified tutorials and flipped classroom synergy by Sandor Kiraly, Tamas Balla, Dora Kiraly, Geoffrey Vaughan

“…Teaching students to think algorithmically is a common goal for school educators; however, SQL's declarative nature demands a distinct approach to problem-solving. …”
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Genetic Variation Analysis of Four Local Varieties of Indonesian Black Rice (Oryza sativa L.) Based on Partially rbcL cpDNA Gene Sequence by Abdul Basith, Estri Laras Arumingtyas, Widodo Widodo

“…Dendogram was carried out using the UPGMA method with the Kimura 2-parameter algorithmic calculation model using the MEGA5 version 5.2.2 program. …”
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Conjugate gradient neural network in prediction of clay behavior and parameters sensitivities by Hamed Memarian fard

“…In our benchmark experiments the resulting highly scalable algorithms converge about an order of magnitude faster than ordinary stochastic gradient descent. …”
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CHDPL-Net: a lightweight network for Chinese herbal decoction pieces detection by Chuhe Lin, Zhijun Xie, Xing Jin, Hangjuan Lin, Renguang Shan

“…Abstract To advance the integration of traditional Chinese medicine (TCM) with next-generation information technologies, the intelligent identification of Chinese herbal decoction pieces (CHDP) has become a crucial research direction. However, the performance of current algorithms remains unsatisfactory. …”
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A redundant weight removal method inspired by specific immunotherapy for boosting transfer learning security by Qing Huang, Hongli Deng, Junxiang Wang, Tao Yang, Bochuan Zheng

“…Abstract Redundant weights bring security risks to transfer learning, how to remove redundant weights effectively is an important research topic in transfer learning. Currently, redundant weights are removed mainly through pruning algorithms designed by correlating student data with teacher model nodes. …”
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ADF-SL: An Adaptive and Fair Scheme for Smart Learning Task Distribution by Ahmed A. Al-Saedi, Veselka Boeva

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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…Against this backdrop, research on Intrusion Detection Systems (IDSs) leveraging machine learning in IoT environments has been actively conducted. …”
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Intelligent Recognition and Automated Production of Chili Peppers: A Review Addressing Varietal Diversity and Technological Requirements by Sheng Tai, Zhong Tang, Bin Li, Shiguo Wang, Xiaohu Guo

“…The main current research challenges are listed including the environmental adaptability/robustness, efficiency/real-time performance, multi-cultivar adaptability/flexibility, system integration, and cost-effectiveness. …”
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Analyzing the Impact of Geoenvironmental Factors on the Spatiotemporal Dynamics of Forest Cover via Random Forest by Hendaf N. Habeeb, Yaseen T. Mustafa

“…This study investigates the spatiotemporal dynamics of forest cover in the Duhok District in the Kurdistan Region of Iraq over a decade (2013–2023), emphasizing the impact of geoenvironmental factors via Random Forest algorithms and Landsat data. This research integrates datasets including fractional vegetation cover (FVC), groundwater levels, climate data, topography, and soil moisture data, offering a comprehensive analysis of the factors influencing forest cover. …”
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New insights into measurement variability in glaucomatous visual fields from computer modelling. by Richard A Russell, David F Garway-Heath, David P Crabb

“…This study highlights that, overall, MD variability increases as the level of damage increases, but variability is highly dependent on the pattern of VF damage. Future research, using VF simulations, could be employed to provide benchmarks for measuring the performance of VF progression detection algorithms and developing new strategies for measuring VF progression.…”
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Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…Predicting survival outcomes in critical accidents has been a focal point in machine learning research. This study addresses several limitations of existing methods, including insufficient management of data imbalance, lack of emphasis on hyperparameter tuning, and proneness to overfitting. …”
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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…Recently, with the swift advancement of social networking, group recommendation has emerged as a compelling research area, enabling personalized recommendations for groups of users. …”
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AI-Driven Predictive Modeling for Lung Cancer Detection and Management Using Synthetic Data Augmentation and Random Forest Classifier by Nisreen Innab, Asma Aldrees, Dina Abdulaziz AlHammadi, Abeer Hakeem, Muhammad Umer, Shtwai Alsubai, Silvia Trelova, Imran Ashraf

“…The application of machine learning algorithms enables medical researchers to examine large amounts of data accurately, which leads to the development of precise and effective treatment approaches. …”
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A novel deep learning approach for investigating liquid fuel injection in combustion system by Syed Azeem Inam, Abdullah Ayub Khan, Noor Ahmed, Tehseen Mazhar, Tariq Shahzad, Sunawar Khan, Mamoon M. Saeed, Habib Hamam

“…However, the current work serves as a baseline for future research because relatively few studies have used data-driven methodologies to assess the temperature of liquid fuel injections in combustion systems. …”
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Acute Bronchiolitis in Children. Current Approaches to Diagnosis and Therapy by A. A. Baranov, L. S. Namazova-Baranova, V. K. Tatochenko, I. V. Davydova, M. D. Bakradze, E. A. Vishnyova, L. R. Selimzyanova, A. S. Polyakova

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