Semi-active radar systems for critical facilities monitoring and protection by A. V. Barkhatov, V. I. Veremjev, A. A. Golovkov, V. M. Kutuzov, V. N. Malyshev, O. G. Petkau, N. S. Stenjukov, M. S. Shmyrin

“…Ulyanov (Lenin) and JSC «SRI "Vector"» in this direction are given. The advantages of semi-active radar systems, the possibility of coherent processing with a large accumulation time in com.bination with the digital formation of the directional diagrams of the receiving antenna arrays, as well as prospects of application systems semi-active radar for the protection of important sites and monitoring areas, including the detection and orbital support of ground, surface and aerial objects. …”
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Improvement of signal detection based on using machine learning by Bassam Abd

“…The proposed system depends on the support vector machine (SVM). The SVM is one of the most popular learning algorithms in different fields, such as signal processing, image processing, communication, and pattern recognition. …”
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THE APPLICATION OF PSO-SVM IN FAULT DIAGNOSIS OF CUTTING UNIT PLANETARY GEAR by REN Zhong, ZHANG TieShan

“…In this paper, first, a variety of failure signal of reducer is collected and the parameters of support vector machine are optimized using PSO and the optimal classifier is obtained. second the collected various signals are processed using classifier of Support Vector Machines. …”
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Ukraine-EU: economic integration strategy by Vitalina Babenko, Yana Biletska, Hanna Pelyak

“…The state and the prospects of the Ukraine’s economic integration into the EU were analyzed and the process of the Ukrainian foreign policy evolution in the European direction was studied. …”
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A diagnostic system for detecting COVID-19 patients depending on lexicon semantic and Biterm Topic Model-Based Feature Selection on WhatsApp Messages Classification by Raghad Hatem, Noor Hussein Eliwe

“…The system processes WhatsApp messages through multiple stages: initial data collection, Word2Vec embedding, lexicon semantic enhancement, vector-space model creation, Biterm Topic Model-based feature selection, and finally, Naive Bayes classification. …”
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A comprehensive review of machine learning applications in forecasting solar PV and wind turbine power output by Ian B. Benitez, Jai Govind Singh

“…Moreover, ensemble models, support vector machines, Gaussian processes, hybrid artificial neural networks, and decomposition-based hybrid models exhibit promising forecasting accuracy and reliability. …”
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Boundary-Value Problems for Weakly Nonlinear Delay Differential Systems by A. Boichuk, J. Diblík, D. Khusainov, M. Růžičková

“…The use of a delayed matrix exponential and a method of pseudoinverse by Moore-Penrose matrices led to an explicit and analytical form of sufficient conditions for the existence of solutions in a given space and, moreover, to the construction of an iterative process for finding the solutions of such problems in a general case when the number of boundary conditions (defined by a linear vector functional l) does not coincide with the number of unknowns in the differential system with a single delay.…”
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Real-time chiral dynamics at finite temperature from quantum simulation by Kazuki Ikeda, Zhong-Bo Kang, Dmitri E. Kharzeev, Wenyang Qian, Fanyi Zhao

“…By introducing a chiral chemical potential μ 5 through a quench process, we drive the system out of equilibrium and analyze the induced vector currents and their evolution over time. …”
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Polarization Imaging Descattering Based on Dark Channel Prior Background Light Estimation by Jiarui Zhang, Yaxin Cai, Ming Fang

“…By integrating polarization imaging with the dark channel prior (DCP) and fully utilizing the polarization information from the Stokes vector and the DCP, the interference of the target information in calculating the background information can be effectively eliminated. …”
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Plastic Litter as Pollutant in the Aquatic Environment: A mini-review by Rifka Rimbi Anggraini, Yenny Risjani, Uun Yanuhar

“…Nowadays, the negative impact of plastic litter occurs on an ongoing basis through the food chain process which until now has not been well studied. …”
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Advancing Over-the-Air Federated Learning through Deep Reinforcement Learning in UAV-Assisted Networks with Movable Antennas by Mohsen Ahmadzadeh, Saeid Pakravan, Ghosheh Hodtani

“…Then An MSE minimization problem is then formulated, involving the joint optimization of moveable antenna position vectors, and the beamforming vector at the UAV. This complex non-convex problem is reformulated as a Markov Decision Process (MDP) and solved using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm within the deep reinforcement learning (DRL) framework. …”
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Calculation and Dressing Simulation of the Profile of the Form Grinding Wheel for Modified ZI Worms by Jianxin Su, Jiewei Xu

“…Subsequently, the normal vector of the tooth surface is derived. After that, space meshing theory and matrix transformation methods are applied. …”
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A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification by Guizhou Wang, Jianbo Liu, Guojin He

“…First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. …”
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The mechanism of gene targeting in human somatic cells. by Yinan Kan, Brian Ruis, Sherry Lin, Eric A Hendrickson

“…Moreover, and in contrast to other systems, the positions of Holliday Junction resolution are evenly distributed along the homology arms of the targeting vector. Most unexpectedly, we demonstrate that when a meganuclease is used to introduce a chromosomal DSB to augment gene targeting, the mechanism of gene targeting is inverted to an ends-in process. …”
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Using Tractography to Distinguish SWEDD from Parkinson’s Disease Patients Based on Connectivity by Mansu Kim, Hyunjin Park

“…Diffusion magnetic resonance images of SWEDD (n=37) and PD (n=40) were obtained from a research database. Tractography, the process of obtaining neural fiber information, was performed using custom software. …”
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Hybrid feature learning framework for the classification of encrypted network traffic by S. Ramraj, G. Usha

“…Previous research has shown that deep learning methods are effective in the feature learning process, so this study uses a simple feed-forward Deep Neural Network (DNN) to improve the performance of the SVM algorithm. …”
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Multidimensional State Data Reduction and Evaluation of College Students’ Mental Health Based on SVM by Han Peiqing

“…In the experimental process, to reflect the difference in the effect of different models, various types of mathematical models were constructed for horizontal comparison; at the same time, to reflect the influence of the parameters of the same type of model, different combinations of parameters were constructed using a grid search algorithm to vertically compare the difference in the effect. …”
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Pavement condition detection using acceleration data collected by smartphones based on 1D convolutional neural network by Yudong Han, Zhaobo Li, Jiaqi Li

“…In this study, a public participation solution is proposed, and a one-dimensional convolutional neural network (1D-CNN) is introduced to directly process acceleration signals, addressing the limitations of traditional machine-learning classification methods. …”
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Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling by Ashraf Radaideh, Mu’men Bodoor, Ayman Al-Quraan

“…Adaptiveness against wind speed variation is achieved in an offline training process at a discretized wind speed domain. Lookup tables are used to store the optimal controller parameter and called upon during the online implementation. …”
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Long Term Solar Radiation Forecast Using Computational Intelligence Methods by João Paulo Coelho, José Boaventura-Cunha

“…The point prediction quality is closely related to the model that explains the dynamic of the observed process. Sometimes the model can be obtained by simple algebraic equations but, in the majority of the physical systems, the relevant reality is too hard to model with simple ordinary differential or difference equations. …”
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