Design of multi-key encryption method by Yuqing ZHONG, Hao WANG, Zebing LIN, Min WANG, Liye CHEN

“…In order to improve the security in the process of information transmission,the current encryption methods were studied,and the research status was reported which increased the security of encryption by processing the key.According to the principle of segmenting and grouping data in the process of sending and encrypting,a method of multi-key encryption was designed:the segmenting key group and grouping key group were generated by the source key and random number,and the corresponding key was selected for each segmented and grouped data by its sequence number according to the matching algorithm.This method realized the encryption of multi-key in the process of information transmission.Finally,on the one hand,MATLAB was used to test and verify the encryption efficiency of this method.On the other hand,the security of this method was analyzed from the theoretical and mathematical perspective,comparing with the traditional method.It is concluded that this method can increase the security of the traditional method without too much cost much cost.…”
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Fault Diagnosis of Vehicle Gearbox based on Support Vector Machine Optimized by Improved Beetle Antennae Search by Wenshan Qiao, Jin Hua, Meihong Chen

“…Aiming at the fact that the performance of support vector machine （SVM） in vehicle gearbox fault diagnosis is greatly affected by parameters，a new method of vehicle gearbox fault diagnosis based on improved SVM is proposed based on the research of beetle antennae search （BAS）. Compared with BAS，IBAS modified the step size formula and added Gaussian variation behavior，so that the search ability of the algorithm in the early and late period is balanced and has the ability to jump out of the local optimal，and better SVM parameters could be obtained. …”
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VNE-AFS:virtual network embedding based on artificial fish swarm by Qiang ZHU, Hui-qiang WANG, Hong-wu LV, Zhen-dong WANG

“…Recently virtual network embedding problem had been proposed as a research challenge in the cloud computing environment.In order to reduce the costs,a virtual network embedding algorithms based on artificial fish swarm(VNE-AFS)was proposed.A binary combinatorial optimization model was built according to the constraints on nodes and links between virtual network and substrate network,and the artificial fish swarm algorithm was used to achieve the approximate optimal mapping.The simulation results indicate that the costs of substrate network and computation time are reduced and the success rate,average revenue of embedding and average usage of links are increased compared with the existing virtual network embedding algorithms.…”
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GA optimization on single-chamber muffler hybridized with extended tube under space constraints by Y. -C. Chang, L. -J. Yeh, M. -C. Chiu

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Explicit and Implicit Knowledge in Large-Scale Linguistic Data and Digital Footprints from Social Networks by Maria Pilgun

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Vehicle speed measurement method using monocular cameras by Hao Lian, Meian Li, Ting Li, Yongan Zhang, Yanyu Shi, Yikun Fan, Wenqian Yang, Huilin Jiang, Peng Zhou, Haibo Wu

“…Finally, the algorithm is combined with You Only Look Once version 7 (YOLOv7) and Deep Simple Online and Realtime Tracking (DeepSORT) algorithms, integrating multiple model structures to optimize the network, achieving precise multi-target speed measurement. …”
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Artificial Intelligence for Fault Detection of Automotive Electric Motors by Federico Soresini, Dario Barri, Ivan Cazzaniga, Federico Maria Ballo, Gianpiero Mastinu, Massimiliano Gobbi

“…Fault detection is a critical research area, especially in the automotive sector, aiming to quickly assess component conditions. …”
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Prediction of SNR Based on SVR and Adaptive Transmission Power Method for Underwater Acoustic Communication by Jixing ZHENG, Yufan YUAN, Xiaoxiao ZHUO, Xuesong LU, Fengzhong QU, Yan WEI

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Partitioning Dichotomous Items Using Mokken Scale Analysis, Exploratory Graph Analysis and Parallel Analysis: A Monte Carlo Simulation by Gomaa Said Mohamed Abdelhamid, María Dolores Hidalgo, Brian F. French, Juana Gómez-Benito

“…Estimating the number of latent factors underlying a set of dichotomous items is a major challenge in social and behavioral research. Mokken scale analysis (MSA) and exploratory graph analysis (EGA) are approaches for partitioning measures consisting of dichotomous items. …”
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DBO-DELM Method for Predicting Rolling Forces in Cold Rolling by LI Xiaoyang, PIAO Chunhui, WANG Xuelei, ZHANG Mingzhi

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A study of O/X wave data assimilation and inversion for ionospheric vertical electron density profiles by Longlong Niu, Chen Zhou, Na Wei, Zhong-Xin Deng, Yun Ning, Rong Chen, Wen Liu

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Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments by Ouge Feng, Honghai Zhang, Weibin Tang, Fei Wang, Dikun Feng, Gang Zhong

“…In the implementation of path planning, compared with the A* and Weight-A* algorithms, the Parallel-A* algorithm demonstrates clear advantages in terms of lower average comprehensive risk and fewer turning points. …”
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Differential Evolution-Based Transient Search Optimizer for Image Multi-Thresholding Problem by Nitin Mittal, Supreet Singh, Lalit Kumar, Gurpreet Kaur, Vikas Mittal, A. Johnson Santhosh

“…The experimental investigation confirms that utilizing a benchmark image test suite with varying dimensions, the DETSO helps to get superior results in achieving better threshold values in terms of performance metrics, such as PSNR, SSIM, FSIM, MSE, etc., compared to the other competitive heuristic algorithms.…”
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Enhanced Real-Time Onboard Orbit Determination of LEO Satellites Using GPS Navigation Solutions with Signal Transit Time Correction by Daero Lee, Soon Sik Hwang

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Underwater acoustic signal denoising method based on DBO–VMD and singular value decomposition by A. Weiyi Chen, B. Shizhe Wang, C. Zongji Li, D. Li Dong

“…This method utilizes the Dung Beetle Optimization (DBO) algorithm to optimize Variational Mode Decomposition (VMD) and combines it with Singular Value Decomposition (SVD). …”
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A Comparison of YOLOv8 Series Performance in Student Facial Expressions Detection on Online Learning by Dewi Tresnawati, Shopi Nurhidayanti, Nina Lestari

“…One indicator of engagement is facial expression. However, research on facial expression detection in online learning environments is still limited, especially in the use of the YOLOv8 algorithm. …”
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Predicting soil organic carbon with ensemble learning techniques by using satellite images for precision farming by Shyamal Mundada, Pooja Jain

“…Soil organic carbon is crucial for many soil activities and ecological characteristics, is at the centre of sustainable agriculture. The goal of the research is to create a system for evaluating soil organic carbon based on topographic features and soil properties incorporating machine learning algorithms. …”
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Investigation on the Temperature Distribution of Asphalt Overlay on the Existing Cement Concrete Pavement in Hot-Humid Climate in Southern China by Zuzhong Li, Yayun Zhang, Chunguang Fa, Xiaoming Zou, Haiwei Xie, Huaxin Chen, Rui He

“…The distresses of asphalt overlay are closely related to its temperature, particularly in Guangxi, a hot-humid-climate region in China. This research is to analyze the impact of meteorological factors on temperature at 2 cm depth in asphalt overlay by ReliefF algorithm and also obtain the temperature prediction model using MATLAB. …”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…The results demonstrate that SVM significantly outperforms the ID3 algorithm in vowel classification, with an average accuracy of 92.09% for the three learner groups (92.38% for advanced, 92.25% for intermediate, and 91.63% for elementary), an improvement of 2.05 percentage points compared to ID3 (<i>p</i> < 0.05). …”
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