Comprehensive datasets for RNA design, machine learning, and beyond by Jan Badura, Agnieszka Rybarczyk, Tomasz Zok

“…Accurately predicting RNA secondary structures and designing sequences that fold into specific configurations remain significant challenges in computational biology, with far-reaching implications for medicine, synthetic biology, and biotechnology. While machine learning methodologies have been proposed to enhance prediction capabilities, they require high-quality training data. …”
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The Ghost of Middle Management: Automation, Control, and Heterarchy in the Platform Firm by Janet A. Vertesi, Diana Enriquez

“…In an effort to attend to the distinct organizational form of algorithmic management, we interrogate the arrangement of platform labor through the lens of the post-bureaucratic organization instead of that of the industrialized factory. …”
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Redefining the role of supervisors in the era of artificial intelligence: implications for hybrid postgraduate research governance by Bunmi Isaiah Omodan

“…This article examines the implications of AI on supervisory roles, focusing on how algorithmic systems are reshaping mentorship, academic oversight, and ethical accountability. …”
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Addressing grading bias in rock climbing: machine and deep learning approaches by B. O’Mara, M. S. Mahmud

“…The determination rock climbing route difficulty is notoriously subjective. While there is no official standard for determining the difficulty of a rock climbing route, various difficulty rating scales exist. …”
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Can Synthetic Data Protect Privacy? by Gidan Min, Junhyoung Oh

“…To systematically evaluate the privacy protection performance of synthetic data generation algorithms (Synthpop, CTGAN, RTVAE, TVAE, DataSynthesizer), this study applied various safety metrics. …”
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Bipartite consensus in coupled harmonic oscillators with local instantaneous interaction and measurement noise by Zhaoyan Wang, Hengyu Li, Jun Liu, Tiehui Zhang, Xinru Ma, Shaorong Xie, Jun Luo

“…In this sense, two consensus algorithms that only use sampled velocity data on the agents in a network are given. …”
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Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks by Haibo Luo, Minghua He, Zhiqiang Ruan, Xiaxia Zeng

“…Performance results show that our proposed algorithms can balance power consumption among nodes and improve power efficiency while guaranteeing packet latency is minimized.…”
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A systematic review of deep learning applications in database query execution by Bogdan Milicevic, Zoran Babovic

“…Furthermore, we discuss the key challenges associated with implementing deep learning algorithms in DBMS.…”
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Popularity Bias in Recommender Systems: The Search for Fairness in the Long Tail by Filippo Carnovalini, Antonio Rodà, Geraint A. Wiggins

“…Recommender systems are known to be affected by popularity bias, the disproportionate preference towards popular items. While this bias stems from human tendencies, algorithms used in recommender systems can amplify it, resulting in unfair treatment of end-users and/or content creators. …”
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Optimizing machine learning for enhanced automated ECG analysis in cardiovascular healthcare by Keyi Tang, Shuyuan Ma, Xiaohui Sun, Dongfang Guo

“…Ultimately, the findings underscore the potential of machine learning and deep learning algorithms in advancing automated ECG analysis for improved cardiovascular healthcare.…”
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Hydrogen Production Using PVs with MPPT Optimization by Kristián Ondrejička, Vladimír Goga, Šimon Berta, Michal Miloslav Uličný, Vladimír Kutiš

“…This study aims to enhance green hydrogen production by optimizing PV-PEMEL performance using commercial power electronics, while improving energy storage and reducing costs for sustainable hydrogen generation.…”
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Sparse transformer and multipath decision tree: a novel approach for efficient brain tumor classification by Pengcheng Li, Yuqi Jin, Monan Wang, Fengjie Liu

“…With advances in medical imaging technology, automated classification algorithms face challenges due to tumor diversity. Although Swin Transformer is effective in handling high-resolution images, it encounters difficulties with small datasets and high computational complexity. …”
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Temporal Attention-Enhanced Stacking Networks: Revolutionizing Multi-Step Bitcoin Forecasting by Phumudzo Lloyd Seabe, Edson Pindza, Claude Rodrigue Bambe Moutsinga, Maggie Aphane

“…The proposed Temporal Attention-Enhanced Stacking Network (TAESN) integrates the complementary strengths of diverse machine learning algorithms while emphasizing critical temporal features, leading to substantial improvements in forecasting accuracy over traditional methods. …”
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SMART Restaurant ReCommender: A Context-Aware Restaurant Recommendation Engine by Ayesha Ubaid, Adrian Lie, Xiaojie Lin

“…They provide personalized suggestions to assist with any task under consideration. While various machine learning algorithms have been developed for recommendation tasks, existing systems still face limitations. …”
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Application of embeddings for multi-class classification with optional extendability by Ф. Смілянець

“…The added embedding generation layers for both networks were then trained using Triplet Loss to extract the features from the output of the convolutional layers, while maintaining distinction between classes. Several simpler machine learning algorithms were then trained to classify on the produced embeddings. …”
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Changes in soil pH on the Tibetan Plateau from the 1980 s to 2020 s by Lirong Zhao, Bo Pang, Jiangtao Hong, Xinxin Zhang, Jinmei Li, Xiaodan Wang

“…Here, we utilized resampling methods and machine learning algorithms to explore the spatiotemporal variations and driving factors of soil pH on the Tibetan Plateau from the 1980 s to 2020 s. …”
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Evaluating Material Parameter Influence on Drapability Using VStitcher by Malin Schiller, Soraya Flohr, Jeanne Marisol Delmas, Anja Krüger, Anne-Marie Miene, Patrizia Zimmermann, Lena Wolf, Miriam Seffers, Michelle-Sophie Ruchay-Drammeh, Ulrike Reinhardt, Lilia Sabantina

“…The most significant effect on the drape coefficient (DC) is seen with increased bending stiffness, while changes in thickness, elongation, and shear stiffness have a minimal effect. …”
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Collision Avoidance for Wheeled Mobile Robots in Smart Agricultural Systems Using Control Barrier Function Quadratic Programming by Sairoel Amertet, Girma Gebresenbet

“…The primary challenge is to design feedback controls that enable robots to autonomously reach predetermined destinations while avoiding collisions with obstacles and other robots. …”
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Development and Validation of a Reduced DME Mechanism Applicable to Various Combustion Modes in Internal Combustion Engines by Gregory T. Chin, J.-Y. Chen, Vi H. Rapp, R. W. Dibble

“…The construction of reduced chemistry was carried out with automatic algorithms incorporating newly developed strategies. …”
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Constrained least-squares and maximum-likelihood calibration of absorption coefficients in reverberation time equations by Bellows Samuel D., Katz Brian F. G.

“…However, the number of available algorithms for calibrating room acoustics models remain limited. …”
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