Coupled memory sampled-data control for fractional stochastic wind energy conversion models by Girija Panneerselvam, Prakash Mani

“…Theoretically, this paper introduces a permanent magnet synchronous generator (PMSG)-based WECS, which is crucial in predicting and optimizing system behavior without physical implementation and also useful in analyzing the various operating conditions. …”
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Exosomal microRNA signatures in youth at clinical high risk for bipolar disorder by Xinyu Meng, Shengmin Zhang, Yingzhen Xu, Zaohui Ma, Shuzhe Zhou, Yantao Ma, Hong Ma, Xin Yu, Lili Guan

“…Using machine-learning algorithms, target miRNAs were selected from differentially expressed candidates. …”
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ML-Enabled Millimeter-Wave Software-Defined Radio With Programmable Directionality by Marc Jean, Murat Yuksel, Xun Gong

“…We design and implement Q-learning, Double Q-learning, and Deep Q-learning algorithms that passively inspect the Received Signal Strength (RSS) of the mmWave beam and autonomously determine the predicted AoA. …”
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Constitutional-Legal Aspect of Creating Large Language Models: the Problem of Digital Inequality and Linguistic Discrimination by I. G. Ilin

“…While direct forms of discrimination can be detected in predictive algorithms, generative models create more subtle but no less significant cumulative effects. …”
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AgrUNet: A Multi-GPU UNet Based Model for Crops Classification by Andrea Miola, Enrico Calore, Sebastiano Fabio Schifano

“…This approach requires high-performance computing systems since DL algorithms are known to be very computing-heavy, and recent multi-GPU HPC systems can boost by one or two orders of magnitude the processing power of classical computing systems based only on CPUs. …”
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Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree‐support vector machine models by Mohammad H. Kadkhodaei, Ebrahim Ghasemi, Jian Zhou, Melika Zahraei

“…This study mainly focuses on developing two practical models to predict pillar stability status. For this purpose, two robust models were developed using a database including 236 case histories from seven underground hard rock mines, based on gene expression programming (GEP) and decision tree‐support vector machine (DT‐SVM) hybrid algorithms. …”
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View Score: An early warning score to detect possible complications among COVID-19 patients by Meenakshi Bhakare, Rajkumar Nikalje, Reshma Patil, Urvi Shukla, Rupesh Bokade, Gajanan Sakhare, Shardul Joshi, Aditi Pais

“…Spirometry indices, patient symptoms, and vital statistics were used to calculate the VIEW™ score using machine learning algorithms. Result: The Bland–Altman plots showed that FEV1 reduced slightly up to 21–28 days and comes back to normal around 42 days. …”
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Computational identification of phospho-tyrosine sub-networks related to acanthocyte generation in neuroacanthocytosis. by Lucia De Franceschi, Giovanni Scardoni, Carlo Tomelleri, Adrian Danek, Ruth H Walker, Hans H Jung, Benedikt Bader, Sara Mazzucco, Maria Teresa Dotti, Angela Siciliano, Antonella Pantaleo, Carlo Laudanna

“…To reduce the network complexity, we combined several algorithms of topological network analysis including cluster determination by shortest path analysis, protein categorization based on centrality indexes, along with annotation-based node filtering. …”
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Early detection of bloodstream infection in critically ill children using artificial intelligence by Hye-Ji Han, Kyunghoon Kim, June Dong Park

“…Conclusions We developed a machine learning model that predicts BSI with acceptable performance. Further research is necessary to validate its effectiveness.…”
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Understanding Acceleration-Based Load Metrics: From Concepts to Implementation by João Freitas, Alexandre Moreira, João Carvalho, Filipe Conceição, Luisa Estriga

“…However, a multitude of acceleration-derived metrics, each employing different algorithms, has led to inconsistent and incomparable outcomes across studies and devices. …”
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Stability indicators in network reconstruction. by Michele Filosi, Roberto Visintainer, Samantha Riccadonna, Giuseppe Jurman, Cesare Furlanello

“…The number of available algorithms to infer a biological network from a dataset of high-throughput measurements is overwhelming and keeps growing. …”
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Edge Artificial Intelligence Device in Real-Time Endoscopy for Classification of Gastric Neoplasms: Development and Validation Study by Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee

“…Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. …”
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Smart city planning focused on the US cities in need of policing innovations and public health safety technologies and strategies by Delores Springs

“…In particular, the article proposes the following for implementation: identifying crime hotspots by means of advanced geographic information systems, applying machine learning algorithms to predict future crime trends, using advanced real-time surveillance technologies and firearms detection systems, applying geospatial analysis to optimise patrol routes, dynamically adjusting patrol routes depending on real-time data analytics, deploying mobile command centres. …”
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The future of 3D printing in instrumented implantable polymer meta-stents by C. Brosseau, G. Nocchiero, J. Ville

“…Thirdly, virtual replica digital twin technology can facilitate personalized stent design based on individual patient characteristics, medical history, and real-time physiological data. This new predictive analysis in healthcare systems relies largely on the use of deep learning algorithms, appropriate for managing massive data integration. …”
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Artificial Intelligence in Pathology: Past, Present, and Future Perspectives by Isma Balaj, Sibora Bërdica, Teona Bushati

“…Conclusion: There has been a significant increase in the development and application of AI tools, including image-based algorithms, in pathology services, and they are expected to dominate the field in the coming years. …”
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Use of Artificial Intelligence in Imaging Dementia by Manal Aljuhani, Azhaar Ashraf, Paul Edison

“…Artificial intelligence algorithms (machine learning and deep learning) enable automation of neuroimaging interpretation and may reduce potential bias and ameliorate clinical decision-making. …”
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Diagnosing Autoimmune Bullous Diseases—An Indian Perspective by Adhyatm Bhandari, Dipankar De, Shikha Shah, Debajyoti Chatterjee, Vinod Kumar, Rahul Mahajan, Sanjeev Handa

“…It also provides with practically applicable diagnostic algorithms for pragmatic diagnosis of AIBDs in Indian scenario.…”
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Artificial Intelligence Driven Human Identification by Purushottam Sharma, Aazar Imran Khan, Samyak Jain, Abhishek Srivastava

“…Human Identification has been widely implemented to enhance the efficiency of surveillance systems, however, systems based on common CCTV (closed-circuit television) cameras are mostly incompatible with the advanced identification algorithms which aim to extract the facial features or speech of an individual for identification. …”
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Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“…By generating computational data, predicting the efficacy of pharmaceuticals, and assessing their safety, AI and quantum computing can accelerate and optimize the process of identifying potential drug candidates. …”
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Optimizing Small Wind Turbine Blades: A BEMT Approach Optimizing Small Wind Turbine Blades: A BEMT Approach by Tshepo Sithole, Lukas W. Snyman, Vasudeva R. Veeredhi, Thembelani Sithebe

“…This paper explores the optimization of small wind turbine blades, focusing on the design and utilization of theoretical algorithms such as computational fluid dynamics (CFD), blade elementary method (BEM) theory, and the vortex wake system (VWS). …”
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