Pedagogical aspects of digital professional teaching skills development by Victoria V. Levchenko, Elena V. Zharkikh, Olga A. Mironova

“…The findings of the research illustrate how the teachers’ training professional development can be based on the algorithm, which allows transforming the acquired skills into the ability to apply them in new, changing conditions.…”
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2D DOA Estimation with a Two-Parallel Array Consisting of Two Uniform Large-Spacing Linear Arrays by Sheng Liu, Jing Zhao, Yu Zhang

“…Compared with the existed PM algorithms based on conventional uniform two-parallel linear array, the proposed PM algorithm based on the large-spacing linear arrays has higher estimation precision. …”
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A recurrent sigma pi sigma neural network by Fei Deng, Shibin Liang, Kaiguo Qian, Jing Yu, Xuanxuan Li

“…Abstract In this paper, a novel recurrent sigma‒sigma neural network (RSPSNN) that contains the same advantages as the higher-order and recurrent neural networks is proposed. The batch gradient algorithm is used to train the RSPSNN to search for the optimal weights based on the minimal mean squared error (MSE). …”
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Dual-station pseudo-Doppler localization method based on particle filtering with stable distribution noise by shuang QIUTian, zhe QIYin

“…Traditional pseudo-Doppler bearing estimation algorithm could accurately calculate the angle of arrival (AOA) with Gaussian noise and high signal to noise ratio (SNR), but it was less robust with stable distribution noise. …”
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A Novel Mining Approach for Data Analysis and Processing Using Unmanned Aerial Vehicles by Ali Alenezi, Ahmad Sawalmeh, Hazim Shakhatreh, Muhannad Almutiry, Nasser Aedh Alreshidi

“…Because the problem is non-convex, the particle swarm optimization algorithm is used to solve it and determine an efficient location and trajectory of the UAV.…”
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Big data classification method of non relational distributed submission information under differentiated requirements by Lu HAN, Weiyu CHEN, Fei ZHANG, Jianfeng HE, Huaizhen SU

“…The classification method of non-relational distributed submitted information big data under the differentiated demand was studied, aiming at the problem of multi-source heterogeneous, widely distributed submitted information with more differentiated application requirements and inability to distinguish the available information.Firstly, the usability, openness and expansibility of the non-relational distributed submission information database were analyzed.The unstructured database storage TRIP was used to store non-relational distributed submission information by combining the basic requirements of field types.Then, the hashing process within the Hamming hash family was analyzed.Under the constraint of linearity level requirements, cellular automata with multiple attractors were used to optimize the system.The optimal parameters of the multiple attractor cellular automata classifier were improved through genetic algorithm, thus improving the big data classification method.Experimental results show that this method can effectively identify and classify structured data and unstructured data in non relational distributed submission information, and has high classification accuracy.…”
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Kruskal-Wallis-Based Computationally Efficient Feature Selection for Face Recognition by Sajid Ali Khan, Ayyaz Hussain, Abdul Basit, Sheeraz Akram

“…In order to eliminate those redundant features, computationally efficient algorithm is used to select the more discriminative face features. …”
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On the Domination Number of Cartesian Product of Two Directed Cycles by Zehui Shao, Enqiang Zhu, Fangnian Lang

“…Based on the established result, the exact values of γ(Cm□Cn) are determined for m=7 and 10 by the combination of the dynamic algorithm, and an upper bound for γ(C13□Cn) is provided.…”
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Energy Efficiency Adaptation for Multihop Routing in Wireless Sensor Networks by Abdellah Chehri, Hussein T. Mouftah

“…The simulation results show that the proposed algorithm can, theoretically, reduce the consumed energy of the sensor nodes almost to half.…”
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Joint time-frequency interference alignment in the frequency-selective Gaussian interference channel by JING Zhen-hai1, BAI Bao-ming1, MA Xiao3

“…To make up for the limitation that the traditional interference alignment can only align the signal in one dimensional domain,a novel joint time-frequency interference alignment scheme was put forward in the frequency-selective Gaussian interference channel（GIC）.After the frequency-selective GIC was changed into a set of parallel GICs,a set of time-frequency alignment matrices were employed which aligned the interference signal not only in time domain but also in frequency domain.An algorithm for calculating the time-frequency alignment matrices was presented based on the convex optimization.Computer simulations show that the joint time-frequency interference alignment can obtain the same performance as the traditional interference alignment while the joint time-frequency interference alignment can shorten the decoding time or reduce the occupation of the frequency resource.The joint time-frequency interference alignment scheme is an extension of the traditional interference alignment and provides a more flexible resource allocation approach between time domain and frequency domain.…”
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Joint task offloading and trajectory optimization for multi-UAV assisted mobile edge computing by Jiequ JI, Kun ZHU, Changyan YI, Ran WANG

“…An unmanned aerial vehicle (UAV)-assisted mobile edge computing system was proposed in which multiple UAVs equipped with computing resources were employed to provide computation offloading opportunities for mobile users with limited local resources.The computing tasks of each user can be divided into two parts.One portion was offloaded to its associated UAV for computing and the remaining portion was processed locally.It was aimed at minimizing the sum of the maximum delay among all user devices by jointly optimizing the user scheduling and the UAV trajectory in a finite period.The proposed problem was a mixed-integer non-convex optimization problem.To facilitate solving this problem, it was equivalently converted into a more tractable problem by introducing some auxiliary variables, and then a penalty concave-convex procedure algorithm was proposed to solve the converted problem.Simulation results show that the proposed joint optimization scheme achieves significantly better performance than other benchmark schemes.…”
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Developing a Travel Time Estimation Method of Freeway Based on Floating Car Using Random Forests by Juan Cheng, Gen Li, Xianhua Chen

“…Different from other machine learning algorithm as black boxes, Random Forests can provide interpretable results through variable importance. …”
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Social media user geolocalization based on multiple mention relationships by Yaqiong QIAO, Xiangyang LUO, Jiangtao MA, Chenliang LI, Meng ZHANG, Ruixiang LI

“…Aiming at the problem that the existing joint user geolocalization methods based on social media text and social relationships do not sufficiently mine the location correlation between heterogeneous data in social media, a social media user geolocalization method based on multiple mention relationships was proposed.First, a heterogeneous network was constructed by comprehensively considering the mention relationship between users, the user's mention relationship with location indicative words, and the user's mention relationship with geographic nouns.Then, a network simplification strategy was proposed to construct a user-location heterogeneous network that connects users live nearby more closely based on the common mention relationship.After that, a biased random walk algorithm was proposed for the graph node sampling to fully explore the network structure and alleviate the sparsity problem of known locations.Finally, a neural network classifier based on a multilayer perceptron was used to infer the user's location.Experimental results on three representative Twitter data sets of GEOTEXT, TW-US and TW-WORLD show that the proposed method can significantly improve the user geolocalization accuracy.…”
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Study on Effect of Consumer Information in Personal Credit Risk Evaluation by Hongmei Wen, Xin Sui, Shaopeng Lu

“…This study selects Chinese borrowers’ information from a platform that has both online shopping and consumer loan service as sample, studies the effect of consumer information in personal credit risk evaluation, and uses the lLogistic regression model, light gradient boosting machine (LightGBM) algorithm, and Shapley Additive Explanation (SHAP). …”
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Research on the evolution of college online public opinion risk based on improved Grey Wolf Optimizer combined with LSTM model. by Chao Cao, Ziyu Li, Lingzhi Li, Fanglu Luo

“…This research proposes a public opinion crisis prediction model that applies the Grey Wolf Optimizer (GWO) algorithm combined with long short-term memory (LSTM) and implements it to analyze a trending topic on Sina Weibo to validate its prediction accuracy. …”
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Radar Selection Method Based on an Improved Information Filter in the LPI Radar Network by Zhenkai Zhang, Bing Zhang, Zhibin Xie, Yi Yang

“…Simulation results show that the proposed algorithm not only saves much more radar resources than other methods but also has excellent tracking accuracy.…”
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Position Tracking Control for Permanent Magnet Linear Motor via Continuous-Time Fast Terminal Sliding Mode Control by Wei Gao, Xiuping Chen, Haibo Du, Song Bai

“…For the position tracking control problem of permanent magnet linear motor, an improved fast continuous-time nonsingular terminal sliding mode control algorithm based on terminal sliding mode control method is proposed. …”
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Efficient and real-time lane detection using CUDA-based implementation by El Boussaki Hoda, Latif Rachid, Saddik Amine

“…We implemented and tested this optimised lane detection algorithm on the NVIDIA Jetson Nano and on a desktop, providing a comparative analysis of improvements in efficiency and speed. …”
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Non-uniform Fourier transform based image classification in single-particle Cryo-EM by ZiJian Bai, Jian Huang

“…Leveraging the capabilities of the non-uniform discrete Fourier transform (NUDFT), we have developed an algorithm for the rotation-invariant classification. …”
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Minimizing Sensor Failures in Wireless Rechargeable Sensor Networks With Obstacles Through Fresnel Diffraction Model by Kun Wang, Zhejun Shen

“…Besides, we also design an effective obstacle avoidance navigation algorithm, which can enable the Mobile Chargers (MCs) to avoid obstacles effectively reducing the moving distances. …”
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