A Feature-Extraction-Based Lightweight Convolutional and Recurrent Neural Networks Adaptive Computing Model for Container Terminal Liner Handling Volume Forecasting by Bin Li, Yuqing He

“…The abovementioned two deep learning experimental performances with FEB-LCR-ACM are so far ahead of the forecasting results by the classical machine learning algorithm that is similar to Gaussian support vector machine. …”
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ON THE SIMULATION OF MODES ОF ELECTRIC POWER SYSTEMS WITH FACTS by E. D. Halilov

“…In regard with the introduction of FACTS devices in power systems, there is an arising need to develop appropriate algorithms and implement them in the form of software for analyzing and controlling the established modes of power systems. …”
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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. Distinct AU patterns were found for all five phases, with gradient boosting machine and random forest models achieving the highest predictive accuracy. …”
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Mapping urban green structures using object-based analysis of satellite imagery: A review by Shivesh Kishore Karan, Bjørn Tobias Borchsenius, Misganu Debella-Gilo, Jonathan Rizzi

“…Future directions for UGS mapping include the integration of deep learning algorithms, advancements in satellite data technologies, and the development of standardized classification frameworks. …”
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A shallow convolutional neural network for cerebral neoplasm detection from magnetic resonance imaging by Hossein Sadr, Zeinab Khodaverdian, Mojdeh Nazari, Mohammad Yamaghani

“…Recently, machine learning algorithms have become increasingly important in medical imaging and information processing, offering a robust alternative to the time-consuming and error-prone manual diagnosis of brain tumors. …”
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Unfolder: fast localization and image rectification of a document with a crease from folding in half by A.M. Ershov, D.V. Tropin, E.E. Limonova, D.P. Nikolaev, V.V. Arlazarov

“…While there are many geometrical rectification methods, they were usually developed for arbitrary bends and folds. We consider such algorithms and propose a novel approach Unfolder developed specifically for images of documents with a crease from folding in half. …”
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A method of EEG signal feature extraction based on hybrid DWT and EMD by Xiaozhong Geng, Linen Wang, Ping Yu, Weixin Hu, Qipeng Liang, Xintong Zhang, Cheng Chen, Xi Zhang

“…Comparative experiments show that the classification accuracy of the proposed method reaches 91.32 %, which is significantly higher than other algorithms.…”
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Consensus on Severity for Ocular Emergency: The BAsic SEverity Score for Common OculaR Emergencies [BaSe SCOrE] by Jean-Louis Bourges, Isabelle Boutron, Dominique Monnet, Antoine P. Brézin

“…These ratings could be used to assess the severity of ocular emergency events, to serve in composite algorithms for emergency triage and standardizing research in ocular emergencies.…”
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Machine Learning Model-Based Applications for Food Management in Alzheimer’s Using Regression Analysis Approach by Sajadul Hassan Kumhar, Prabhakara Rao Kapula, Harveen Kaur, Radeep R. Krishna, Mudasir M Kirmani, Vijay Anant Athavale, Mohd Wazih Ahmad

“…Scientists are trying to find a solution using some machine learning (ML) techniques. The ML algorithms used for this purpose are neural networks, support vector machines, regression and many more. …”
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Model of asynchronous motor taking into account its magnetic system saturation on basis of Takagi–Sugeno method by N. M. Zaytseva

“…The algorithm implementing saturation of the engine magnetic system is developed with help of TakagiSugeno fuzzy inference. …”
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Digital relay protection complex testing method development for electric power equipment by A. V. Simakov, V. V. Kharlamov, V. I. Skorokhodov

“…The method can be used to build new digital protection algorithms that comply with IEC 61850.…”
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Impact and optimization of vehicle charging scheduling on regional clean energy power supply network management by Penghui Xu, Xiaobo Wang, Zhichao Li

“…The comprehensive model integrates electric vehicle charging stations, distributed photovoltaic power generation systems, wind farms, and battery energy storage devices and enables the charging process to be accurately controlled with real-time monitoring and intelligent algorithms. In particular, the demand forecasting model based on machine learning effectively solves the dilemma of matching the charging load with a clean energy supply. …”
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More Benefits of Adding Sparse Random Links to Wireless Networks: Yet Another Case for Hybrid Networks by Gunes Ercal

“…Further, we theoretically demonstrate that as long as k is polylogarithmic in the network size, G 1 has rapidly mixing random walks with high probability, which also exponentially improves upon the mixing time of the purely wireless random geometric graph, which yields direct improvement to the performance of distributed gossip algorithms as well as normalized edge connectivity. …”
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Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise by Volodymyr I. Ponomaryov, Hector Montenegro-Monroy, Luis Nino-de-Rivera, Heydy Castillejos

“…In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. …”
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Vehicle Flow Detection and Tracking Based on an Improved YOLOv8n and ByteTrack Framework by Jinjiang Liu, Yonghua Xie, Yu Zhang, Haoming Li

“…In the tracking module, we incorporate the ByteTrack algorithm and train unique vehicle re-identification (Re-ID) features, ensuring robust multi-object tracking in complex environments and improving the stability and accuracy of vehicle flow tracking. …”
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Neural Radiance Fields for High-Fidelity Soft Tissue Reconstruction in Endoscopy by Jinhua Liu, Yongsheng Shi, Dongjin Huang, Jiantao Qu

“…The experimental results show that our method can effectively focus on the soft tissue regions in the image, achieving higher fidelity in detail and geometric structural integrity in reconstruction compared to state-of-the-art algorithms. Feedback from the user study indicates high participant scores for our method.…”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. …”
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Method of flight operation of software and hardware for controlling parameters of the rotational motion of small spacecraft of the Aist series by A. V. Sedelnikov, Yu. Ya. Puzin, A. S. Filippov

“…The developed technique is aimed at improving the quality of the primary information on the state of the parameters of the rotational motion of the small spacecraft and the quality of the implemented algorithms for controlling the electromagnets. This facilitates both the creation of favorable conditions for the implementation of technological processes on board of the small spacecraft, and a significant improvement in the quality of telemetric information transmitted from the small spacecraft to Earth. …”
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

“…This research investigates three approaches for classifying skin cancer images. (1) Utilizing three fine-tuned pre-trained networks (VGG19, ResNet18, and MobileNet_V2) as classifiers. (2) Employing three pre-trained networks (ResNet-18, VGG19, and MobileNet v2) as feature extractors in conjunction with four machine learning classifiers (SVM, DT, Naïve Bayes, and KNN). (3) Utilizing a combination of the aforementioned pre-trained networks as feature extractors in conjunction with same machine learning classifiers. All these algorithms are trained using segmented images which are achieved by using the active contour approach. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug–target interactions from big data, enabling more accurate predictions and novel hypothesis generation. …”
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