Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach by Marko Martinović, Kristian Dokic, Dalibor Pudić

“…Predicting innovation outcomes at the firm level continues to be an important but challenging goal for researchers and practitioners alike. In this study, multiple machine learning models, encompassing both ensemble-based and single-model approaches, were applied to data from the Community Innovation Survey. …”
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Application of blade element momentum theory with guaranteed convergence to analyze a straight-blade horizontal axis wind turbine by Dang Huy Le, The Bao Nguyen, Van Minh Ngo

“…This type of turbine has much potential for practical applications, providing electricity to households and residential areas far from cities, but has not been fully researched. Straight-blade turbines with relatively large Re changes in blade spanwise direction often cause difficulties in the convergence of BEM algorithms. …”
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Long-Short Term Memory Networks and Synthetic Data for Heavy Vehicle Rollover Prevention by Guido Perboli, Antonio Tota, Filippo Velardocchia

“…Heavy vehicle rollover plays a pivotal role in road safety scenarios. Numerous researchers addressed the topic, with particular focus on drivers related injuries. …”
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Applying deep learning to teleseismic phase detection and picking: PcP and PKiKP cases by Congcong Yuan, Jie Zhang

“…The availability of a tremendous amount of seismic data demands seismological researchers to analyze seismic phases efficiently. Recently, deep learning algorithms exhibit a powerful capability of detecting and picking on P- and S-wave phases. …”
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A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

“…Despite the proliferation of machine learning and deep learning algorithms for fall detection, their efficacy remains hampered by resilience, robustness, and adaptability challenges across varied input scenarios. …”
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Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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Quality monitoring of hybrid welding processes: A comprehensive review by Solomon Habtamu Tessema, Dariusz Bismor

“…Furthermore, the review highlights the integration of sensor data with AI/ML algorithms and digital twin technologies, enhancing the capabilities of quality monitoring systems. …”
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Revolutionizing Education with Artificial Intelligence (AI)? Challenges, and Implications for Open and Distance Learning (ODL) by Mohd Rushidi Mohd Amin, Ismaanzira Ismail, Vinesh Maran Sivakumaran

“…By exploring these facets, educators, policymakers, and researchers gain valuable insights into mitigating risks and ensuring responsible AI deployment in ODL. …”
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The Convergence of AI and animal-inspired robots for ecological conservation by Naqash Afzal, Mobeen ur Rehman, Lakmal Seneviratne, Irfan Hussain

“…By harnessing the capabilities of AI-driven animal robots, researchers can gain a multifaceted toolkit to explore and understand the behaviors, communication patterns, and ecological roles of various species. …”
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Multiple pregnancy and solutions to the problem of its complications (a literature review) by M. O. Franchuk, L. M. Malanchuk, O. A. Franchuk

“…This review presents an opinion of most researchers about an association between multiple pregnancy and a significant number of complications that accompany it from early gestational age. …”
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A Secure and Efficient White-Box Implementation of SM4 by Xiaobo Hu, Yanyan Yu, Yinzi Tu, Jing Wang, Shi Chen, Yuqi Bao, Tengyuan Zhang, Yaowen Xing, Shihui Zheng

“…Differential Computation Analysis (DCA) leverages memory traces to extract secret keys, bypassing countermeasures employed in white-box designs, such as encodings. Although researchers have made great efforts to enhance security against DCA, most solutions considerably decrease algorithmic efficiency. …”
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Advancing agriculture with machine learning: a new frontier in weed management by Mohammad MEHDIZADEH, Duraid K. A. AL-TAEY, Anahita OMIDI, Aljanabi Hadi Yasir ABBOOD, Shavan ASKAR, Soxibjon TOPILDIYEV, Harikumar PALLATHADKA, Renas Rajab ASAAD

“…Validation and refinement of these algorithms are needed for practical application.…”
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Detection of cotton crops diseases using customized deep learning model by Hafiz Muhammad Faisal, Muhammad Aqib, Saif Ur Rehman, Khalid Mahmood, Silvia Aparicio Obregon, Rubén Calderón Iglesias, Imran Ashraf

“…Thanks to deep learning algorithms, researchers have developed innovative disease detection approaches that can help safeguard the cotton crop and promote economic growth. …”
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Shape Penalized Decision Forests for Imbalanced Data Classification by Rahul Goswami, Aindrila Garai, Payel Sadhukhan, Palash Ghosh, Tanujit Chakraborty

“…Finally, we provide a Python package, ‘imbalanced-spdf’, offering an accessible implementation for practitioners and researchers.…”
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Metagenome-Assembled Genomes (MAGs): Advances, Challenges, and Ecological Insights by Salvador Mirete, Mercedes Sánchez-Costa, Jorge Díaz-Rullo, Carolina González de Figueras, Pablo Martínez-Rodríguez, José Eduardo González-Pastor

“…By leveraging high-throughput sequencing, advanced assembly algorithms, and genome binning techniques, researchers can reconstruct microbial genomes without the need for cultivation. …”
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A Dynamic Load Balancing Architecture for Fog Computing using Tree Base Resource Arrangement and Flexible Task Prioritization by Bikash Sarma, R. Kumar, Themrichon Tuithung

“…A greater community of researchers widely studies fog computing as it reduces the massive data flow to the existing cloud-connected network and performs better for real-time systems that expect a quick response. …”
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GCV-SLAM: Ground Constrained Visual SLAM Through Local Ground Planes by Yu Fan, Peng Zhang, Zhi Wang, Chengbao Liu, Guang Zhang

“…The classical visual Simultaneous Localization and Mapping(SLAM) algorithms assume that the camera moves in a free 3D space, while it is not valid for ground vehicles whose poses are influenced by ground surfaces. …”
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«Obscenities give rise to thugs»: Obscene vocabulary in the practice of the poet Vsevolod Nekrasov (based on archive materials) by E. N. Penskaya

“…Without claiming to generalize, this material is focused on identifying patterns and searching for possible algorithms for classifying such phenomena. The case of Vsevolod Nekrasov is both characteristic and unique. …”
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The Invisible World of Images. From “Nonhuman” to “Undigital” Photography in Joanna Zylinska’s Reflections by Piotr Zawojski

“… The article presents the theoretical views and, to a lesser extent, artistic practices of Joanna Zylinska, who in her artistic activity combines epistemological strategies of a researcher and theorist with her activities in the field of art. …”
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LUNGINFORMER: A Multiclass of lung pneumonia diseases detection based on chest X-ray image using contrast enhancement and hybridization inceptionresnet and transformer by Hanafi Hanafi

“…To address the problem, many researchers have employed deep learning algorithms to develop an automated detection system for pneumonia. …”
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