Improved Channel Estimation for DVB-T2 Systems by Utilizing Side Information on OFDM Sparse Channel Estimation by S. Ghazi-Maghrebi, S.H. Hashemi-Rafsanjani

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Innovative Control Techniques for Enhancing Signal Quality in Power Applications: Mitigating Electromagnetic Interference by N. Manoj Kumar, Yousef Farhaoui, R. Vimala, M. Anandan, M. Aiswarya, A. Radhika

“…The used modulation scheme can effectively distribute the harmonic energy across a larger range of frequencies to largely eliminate EMI and boost the stability of the system. …”
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Fault Diagnosis of Rolling Bearing based on Sideband Correlation Algorithm and Hilbert Envelope Spectrum by Wang Miaoqing, Gu Jun, Liu Qing

“…Eventually,the size of the modulation frequency is got. The analysis and verification is carried out by using the vibration signal of rolling bearing experiment,finding out the modulation frequency of vibration signals under the condition of outer ring,inner ring,rolling body defect,the fault feature can be extracted effectively. …”
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A Comprehensive Analysis of Bandwidth and Size for Four-Types of Series-Combined Transformer-Based Doherty Output Networks: Theory and Examples by Seokchul Lee, John D. Cressler

“…To validate the circuit model, a design example was built through a detailed procedure as the best practice, and a layout-based full-EM structure achieved close-to-theoretical BW. For further verification, four SCT-based Doherty power amplifiers were simulated and compared.…”
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A N7-methylguanosine modified circular RNA, circIPP2A2, promotes malignant behaviors in hepatocellular carcinoma by serving as a scaffold in modulating the Hornerin/PI3K/AKT/GSK3β... by Zeyi Guo, Zhongzhe Li, Jinhao Guo, Luxiang Gan, Haiyu Mo, Jiajun Zhang, Yu Fu, Yi Wang, Meixian Jin, Yanping Wu, Qingyu Xie, Kunjiang Tan, Chunming Wang, Yuyan Xu, Guolin He, Lei Cai, Yi Gao, Mingxin Pan, Shunjun Fu

“…After the structure verification of circIPP2A2, loss-of-function studies using a lentiviral vector revealed that circIPP2A2 downregulation significantly inhibited HCC tumorigenesis and progression both in vitro and in vivo. …”
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Enhanced fire hazard detection in solar power plants: an integrated UAV, AI, and SCADA-based approach by Andrii Lysyi, Anatoliy Sachenko, Pavlo Radiuk, Mykola Lysyi, Oleksandr Melnychenko, Oleksii Ishchuk, Oleg Savenko

“…The Methods employed involve a synergistic architecture that combines an Unmanned Aerial Vehicle (UAV) equipped with high-resolution RGB and radiometric infrared cameras for rapid imaging, supplemented by dedicated Internet of Things (IoT) temperature sensors on PV module bypass diodes for critical component verification. …”
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Reducing False Alarm in Target Sidelobes Using Time-Varying Trajectories in Range-Doppler Diagram With Conditional 3D-DCNN by Jiyeon Choi, Daegun Oh, Youngwook Kim

“…The proposed method was validated using frequency-modulated continuous wave radar to detect low-RCS targets and demonstrated a reduction in FAs in clutter environments. …”
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CHAM-CLAS: A Certificateless Aggregate Signature Scheme with Chameleon Hashing-Based Identity Authentication for VANETs by Ahmad Kabil, Heba Aslan, Marianne A. Azer, Mohamed Rasslan

“…The signature and verification modules are also redesigned to address the identified vulnerabilities in Xiong’s scheme. …”
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Research on Target-detection and Tracking of Intelligent Mine Trucks in Open-pit Mines by LI Yuanzhengyu, HU Yunqing, LONG Teng, HUANG Wenyu, PAN Wenbo, LI Peijie

“…The algorithm includes point cloud feature extraction module, target tracking module and heterogeneous sensor fusion module. …”
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Network traffic anomaly detection model based on feature grouping and multi‐autoencoders integration by Yang Zhou, Haoyang Zeng, Zhourong Zheng, Wei Zhang

“…In the AUC and optimal threshold calculation module, the AUC of each AE is calculated according to the ROC curve of the verification data, and the optimal thresholds for each AE are determined using the Youden index. …”
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Design and implementation of codec based on BCH error correction algorithm by Wang Guan, Wei Jinghe, Yu Zongguang

“…Among them, the syndrome module, error location polynomial module and Chien search module in the decoding circuit adopt a three-stage pipeline structure, and the error correction and error detection stages can be carried out at the same time, which effectively improves the data processing speed and error correction speed. …”
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Design and Application of Vertical Temperature Profile Observation System for Arctic Sea Ice Melt Pond by ZUO Guangyu, DOU Yinke, WU Shunjie, CHANG Xiaomin, KOU Liwei, LI Wenlong, YANG Bo

“…[Methods] The system is composed of observation module, power supply module, data acquisition module, data transmission module, and auxiliary module. …”
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Development of JZ-8 Brake Control System for Locomotive by WANG Qiwei, XU Fenglei, LIU Ao, LI Li, WANG Lingjun

“…JZ-8 type brake control system was introduced, including the project origin, system structure, main functions, working principle, braking mode, system software, test verification, and loading application. The important components of the brake control system were described in detail, such as the functions of the brake controller, the action of the brake screen, the modular features of the brake control cabinet, and the function principle, function and architecture of the BCU module of the core control unit. …”
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Modeling of membrane separation of liquid mixture in Aspen HYSYS by A. V. Malygin, I. I. Emel’yanov, R. V. Semin, A. R. Fazlyev, N. N. Ziyatdinov, А. V. Klinov

“…To develop and subsequently verify the calculation block of the mass transfer process in the pervaporation membrane module based on a HybSi® ceramic membrane using experimental data as a basis for the verification process.Methods. …”
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Intelligent air traffic control using NLP-enhanced speech recognition and natural language generation by Amany M. Sarhan, Rawda Fathy, Hesham A. Ali

“…Extensive experiments were conducted for system verification on several datasets, where each dataset is targeted for a specific module of the system. …”
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MA-YOLO: A Pest Target Detection Algorithm with Multi-Scale Fusion and Attention Mechanism by Yongzong Lu, Pengfei Liu, Chong Tan

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Research of IGBT failure energy transmission and energy shock by MA Yao, XU Libin, YU Wei, LIU Min´an, REN Yadong

“…After initial expansion, the explosive gas will act on the shell in the form of shock wave energy and gas. When the module shell cannot bind the failure energy, the module shell will explode. …”
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An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model by Hao Yan, Fangcao Zhang, Xingao Li, Chenchen Zhang, Yunjia Zhang, Yongfei Feng

“…The strategy primarily consists of two modules: a subjective intention decline control module and a limb movement assessment module. …”
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MSTCNet: Toward Generalization Improving for Multiframe Infrared Small Target Detection by Ruining Cui, Na Li, Junfu Liu, Huijie Zhao

“…Finally, in the experimental part, we adopt the DG verification method, dividing the dataset into different source domains and target domains for experimental verification. …”
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Metric-based learning approach to botnet detection with small samples by Honggang LIN, Junjing ZHU, Lin CHEN

“…Botnets pose a great threat to the Internet, and early detection is crucial for maintaining cybersecurity.However, in the early stages of botnet discovery, obtaining a small number of labeled samples restricts the training of current detection models based on deep learning, leading to poor detection results.To address this issue, a botnet detection method called BT-RN, based on metric learning, was proposed for small sample backgrounds.The task-based meta-learning training strategy was used to optimize the model.The verification set was introduced into the task and the similarity between the verification sample and the training sample feature representation was measured to quickly accumulate experience, thereby reducing the model’s dependence on the labeled sample space.The feature-level attention mechanism was introduced.By calculating the attention coefficients of each dimension in the feature, the feature representation was re-integrated and the importance attention was assigned to optimize the feature representation, thereby reducing the feature sparseness of the deep neural network in small samples.The residual network design pattern was introduced, and the skip link was used to avoid the risk of model degradation and gradient disappearance caused by the deeper network after increasing the feature-level attention mechanism module.…”
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