Influencing Factors and Clustering Characteristics of COVID-19: A Global Analysis by Tianlong Zheng, Chunli Zhang, Yueting Shi, Debao Chen, Sheng Liu

“…In addition, the epidemic clustering characteristics were analyzed through the spectral clustering algorithm. The visualization results of spectral clustering showed that the geographical distribution of global COVID-19 pandemic spread formation was highly clustered, and its clustering characteristics and influencing factors also exhibited some consistency in distribution. …”
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Features of interrogation of minors who are victims of violence by N. E. Miloradova, N. A. Pashko

“…The author has analyzed the algorithm of interrogation of a child based on the use of the following formula: “safe place + safe adult = safe child”; has provided recommendations to take into account the psychological and organizational features of different phases of the child’s interviewing; formulation of questions for minors who are victims of violence according to age and their psycho-emotional state. …”
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Optimal Design of Bus Stop Locations Integrating Continuum Approximation and Discrete Models by Xiaoling Luo, Wenbo Fan, Yangsheng Jiang, Jun Zhang

“…Then, the stop location problem is formulated into a multivariable nonlinear minimization problem with a given number of stop location variables and location constraint. The interior-point algorithm is presented to find the optimal design that is ready for implementation. …”
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Block level cloud data deduplication scheme based on attribute encryption by Wenting GE, Weihai LI, Nenghai YU

“…Due to the existing cloud data deduplication schemes mainly focus on file-level deduplication.A scheme was proposed, based on attribute encryption, to support data block-level weight removal.Double granularity weight removal was performed for both file-level and data block-level, and data sharing was achieved through attribute encryption.The algorithm was designed on the hybrid cloud architecture Repeatability detection and consistency detection were conducted by the private cloud based on file labels and data block labels.A Merkle tree was established based on block-level labels to support user ownership proof.When a user uploaded the cipher text, the private cloud utilized linear secret sharing technology to add access structures and auxiliary information to the cipher text.It also updated the overall cipher text information for new users with permissions.The private cloud served as a proxy for re-encryption and proxy decryption, undertaking most of the calculation when the plaintext cannot be obtained, thereby reducing the computing overhead for users.The processed cipher text and labels were stored in the public cloud and accessed by the private cloud.Security analysis shows that the proposed scheme can achieve PRV-CDA (Privacy Choose-distribution attacks) security in the private cloud.In the simulation experiment, four types of elliptic curve encryption were used to test the calculation time for key generation, encryption, and decryption respectively, for different attribute numbers with a fixed block size, and different block sizes with a fixed attribute number.The results align with the characteristics of linear secret sharing.Simulation experiments and cost analysis demonstrate that the proposed scheme can enhance the efficiency of weight removal and save time costs.…”
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High-Performance Wireless Piezoelectric Sensor Network for Distributed Structural Health Monitoring by Shang Gao, Xuewu Dai, Zheng Liu, Guiyun Tian

“…In addition to hardware, embedded signal processing and distributed data processing algorithm are designed as the intelligent “brain” of the proposed wireless monitoring network to extract features of the PZT signals, so that the data transmitted over the wireless link can be reduced significantly.…”
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Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach by DOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan

“…Only the feedback that has been categorized as negative by the algorithm is selected. In correspondence to this feedback, the existence of answers from the hotels is checked together with the response style. …”
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Retrospective evaluation of a novel ultrasound-based imaging analysis software for predicting radiofrequency ablation areas. by Masaya Sato, Ryosuke Tateishi, Yogev Zohar, Jiro Sato, Takeyuki Watadani, Makoto Moriyama, Taijiro Wake, Ryo Nakagomi, Mizuki Nishibatake Kinoshita, Takuma Nakatsuka, Tatsuya Minami, Koji Uchino, Kenichiro Enooku, Hayato Nakagawa, Yoshinari Asaoka, Ryo Yamada, Nitzan Even, Inbal Amitai, Yossi Abu, Mitsuhiro Fujishiro, Kazuhiko Koike

“…<h4>Methods</h4>BioTrace utilizes a proprietary algorithm to analyze the temporo-spatial behavior of thermal gas bubble activity during ablation, as seen in conventional B-mode ultrasound imaging. …”
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RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT by Guanwei Jia, Zhaoyu Shen, Hongye Sun, Jingbo Xin, Dongyu Wang

“…This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. …”
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Real-Time On-Orbit Estimation Method for Microthruster Thrust Based on High-Precision Orbit Determination by Qinglin Yang, Weijing Zhou, Hao Chang

“…By establishing a high-precision orbit dynamic model, the microthrust generated by a microthruster is modeled as a first-order Markov model, combined with a high-precision GNSS measuring device, and the satellite position is obtained through the cubature Kalman filter algorithm, velocity, and thrust real-time on-orbit estimates. …”
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Distance and Density Similarity Based Enhanced k-NN Classifier for Improving Fault Diagnosis Performance of Bearings by Sharif Uddin, Md. Rashedul Islam, Sheraz Ali Khan, Jaeyoung Kim, Jong-Myon Kim, Seok-Man Sohn, Byeong-Keun Choi

“…An enhanced k-nearest neighbor (k-NN) classification algorithm is presented, which uses a density based similarity measure in addition to a distance based similarity measure to improve the diagnostic performance in bearing fault diagnosis. …”
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A hardware prototype of wideband high‐dynamic range analog‐to‐digital converter by Satish Mulleti, Eliya Reznitskiy, Shlomi Savariego, Moshe Namer, Nimrod Glazer, Yonina C. Eldar

“…To avoid clipping, modulo folding can be used before sampling, followed by an unfolding algorithm to recover the true signal. Here, the authors present a modulo hardware prototype that can be used before sampling to avoid clipping. …”
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Automatic level control system for telephone communication channels of radio-transmitting devices by A. V. Tkacheva, A. P. Pavlov, I. E. Kashchenko

“…The presented automatic level control system provides a quick recovery of the output level without significant surge. А compression algorithm based on the Hamming window function is used to correct the spectral mask of the signal and increase the mean-square average power of the radio-transmission path. …”
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An Improved Extrapolation Scheme for Truncated CT Data Using 2D Fourier-Based Helgason-Ludwig Consistency Conditions by Yan Xia, Martin Berger, Sebastian Bauer, Shiyang Hu, Andre Aichert, Andreas Maier

“…The forward projection of the optimized ellipse can be used to complete the truncation data. The proposed algorithm is evaluated using simulated data and reprojections of clinical data. …”
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Improved Low-Complexity Demodulation: Integrating Minimum-Mean-Square-Error and Maximum-Likelihood Detection for Image-Sensor-Based Visible Light Communication by Yuki Ohira, Shintaro Arai, Kengo Fujii, Tomohiro Yendo

“…To address these limitations, this study introduces an improved error signal candidate selection algorithm that focuses on residual signals and channel matrix characteristics to refine the signal estimation result. …”
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Preliminary study on the construction of a data privacy protection course based on a teaching-in-practice range by Zhe SUN, Hong NING, Lihua YIN, Binxing FANG

“…Since China’s Data Security Law, Personal Information Protection Law and related laws were formalized, demand for privacy protection technology talents has increased sharply, and data privacy protection courses have been gradually offered in the cyberspace security majors of various universities.Building on longstanding practices in data security research and teaching, the teaching team of “Academician Fang Binxing’s Experimental Class” (referred to as “Fang Class”) at Guangzhou University has proposed a teaching method for data privacy protection based on a teaching-in-practice range.In the selection of teaching course content, the teaching team selected eight typical key privacy protection techniques including anonymity model, differential privacy, searchable encryption, ciphertext computation, adversarial training, multimedia privacy protection, privacy policy conflict resolution, and privacy violation traceability.Besides, the corresponding teaching modules were designed, which were deployed in the teaching practice range for students to learn and train.Three teaching methods were designed, including the knowledge and application oriented teaching method which integrates theory and programming, the engineering practice oriented teaching method based on algorithm extension and adaptation, and the comprehensive practice oriented teaching method for practical application scenarios.Then the closed loop of “learning-doing-using” knowledge learning and application was realized.Through three years of privacy protection teaching practice, the “Fang class” has achieved remarkable results in cultivating students’ knowledge application ability, engineering practice ability and comprehensive innovation ability, which provided useful discussion for the construction of the initial course of data privacy protection.…”
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Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine by Qiong Li, Tingting Zhao, Lingchao Zhang, Wenhui Sun, Xi Zhao

“…With the rapid development of computer image processing technology, neural network based on traditional gradient training algorithm can be used to recognize them. However, the feedforward neural network based on traditional gradient training algorithms for image segmentation creates many issues, such as needing multiple iterations to converge and easy fall into local minimum, which restrict its development heavily. …”
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Combined Heat and Mass Transfer of Fluid Flowing through Horizontal Channel by Turbulent Forced Convection by Jamal Eddine Salhi, Kamal Amghar, Hicham Bouali, Najim Salhi

“…A specifically developed numerical model was based on the finite-volume method to solve the coupled governing equations and the SIMPLE (Semi Implicit Method for Pressure Linked Equation) algorithm for the treatment of velocity-pressure coupling. …”
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Resilience-Oriented Scheduling of Shared Autonomous Electric Vehicles: A Cooperation Framework for Electrical Distribution Networks and Transportation Sector by Mohammad Hassan Amirioun, Saeid Jafarpour, Ali Abdali, Josep M. Guerrero, Baseem Khan

“…Afterward, SA runs a targeted algorithm to schedule trip assignments and charging cycles of SAEVs so that the required constraints of DSO are satisfied. …”
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Prediction and Evaluation of Coal Mine Coal Bump Based on Improved Deep Neural Network by Shuang Gong, Yi Tan, Wen Wang

“…To predict coal bump disaster accurately and reliably, we propose a depth neural network (DNN) prediction model based on the dropout method and improved Adam algorithm. The coal bump accident examples were counted in order to analyze the influencing factors, characteristics, and causes of this type of accidents. …”
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Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity by Guan Gui, Li Xu, Lin Shan, Fumiyuki Adachi

“…Broadband channel model is often described by very few dominant channel taps and they can be probed by compressive sensing based sparse channel estimation (SCE) methods, for example, orthogonal matching pursuit algorithm, which can take the advantage of sparse structure effectively in the channel as for prior information. …”
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