Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method by Mustefa Badri Usman, Ram Sewak Singh, Satyasis Mishra, Davinder Singh Rathee

“…Spectrum sensing is a critical step in discovering spectrum gaps in CR. Matching filter detection, energy detection (ED), cyclostationary detection, correlation coefficient detection, and wavelet detection are some of the frequency band sensing techniques. …”
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Development and evaluation of KNLNTS-cement composites for use as piezoelectric sensors in structural health monitoring applications by Phongthorn Julphunthong, Pongsak Wiwatrojanagul, Pithiwat Tiantong, Theerachai Bongkarn, Rattiyakorn Rianyoi, Ruamporn Potong

“…Detailed investigations of dielectric properties revealed a consistent rise in piezoelectric coefficient (8.40–24.15 pC/N) with increasing KNLNTS content, making these composites suitable for sensitive detection of stress, strain, and cracking in concrete. …”
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Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection by Emmanuel Gbafore, Davies Rene Segera, Cosmas Raymond Mutugi Kiruki

“…These findings address important metaheuristic optimization gaps highlighting the model’s potential for power theft detection.…”
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Research on the Rapid Detection of Formaldehyde Emission From Wood-Based Panels Based on the AMSHKELM by Yinuo Wang, Huanqi Zheng, Hua Wang, Yucheng Zhou

“…To enable quick and accurate detection of formaldehyde emissions from wood-based panels and to address the complexities of the full-scale chamber method and the inaccuracy of sensor-based methods, a modified formaldehyde emission model based on AdaBoost-MSBKA-SVMD-HKELM (AMSHKELM) is proposed. …”
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Fault Detection and Protection Strategy for Multi-Terminal HVDC Grids Using Wavelet Analysis by Jashandeep Kaur, Manilka Jayasooriya, Muhammad Naveed Iqbal, Kamran Daniel, Noman Shabbir, Kristjan Peterson

“…Unlike AC systems, HVDC systems lack natural zero-crossing points, making fault isolation more complex. This paper presents the implementation of a wavelet-based protection algorithm to detect faults in a four-terminal VSC-HVDC grid, modelled in MATLAB and SIMULINK. …”
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Novel transfer learning based acoustic feature engineering for scene fake audio detection by Ahmad Sami Al-Shamayleh, Hafsa Riasat, Ala Saleh Alluhaidan, Ali Raza, Sahar A. El-Rahman, Diaa Salama AbdElminaam

“…The advent of audio fake attacks using speech combined with scene-manipulated audio represents a sophisticated challenge in fake audio detection. Fake audio detection, a critical technology in modern digital security, addresses the growing threat of manipulated audio content across various applications, including media, legal evidence, and cybersecurity. …”
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A Triple-Channel Network for Maritime Radar Targets Detection Based on Multi-Modal Features by Kaiqi Wang, Zeyu Wang

“…Sea surface target detectors are often interfered by various complex sea surface factors such as sea clutter. Especially when the signal-to-clutter ratio (SCR) is low, it is difficult to achieve high-performance detection. …”
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A Low-Friction Capsule Robot with Drive–Control–Sensing Integration for Gastrointestinal Lesion Detection by Ziying Wang, Hang Yin, Zilin Wei, Shisheng Chen, Jiameng Li, Jingyao Sun, Wei Zhao, Yejuan Jia

“…Here, a capsule robot with a low coefficient of friction is proposed to continuously detect pH and temperature. …”
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Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

“…To overcome the limitations of the residual chi-square method in detecting gradual faults, a cumulative residual detection approach with error coefficient amplification was proposed. …”
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GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling by Xin Wang, Changchun Li, Chenyi Zhao, Yinghua Jiao, Hengmao Xiang, Xifang Wu, Huabin Chai

“…Specifically, the model incorporates an Efficient Multi-scale Attention (EMA) mechanism, effectively mitigating the interference of background noise on detection results. Additionally, the ASF-Gather and Distribute (ASF-GD) module optimizes the feature extraction component of the original YOLOv7 network, improving the model’s robustness and accuracy in complex scenarios. …”
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UAV rice panicle blast detection based on enhanced feature representation and optimized attention mechanism by Shaodan Lin, Deyao Huang, Libin Wu, Zuxin Cheng, Dapeng Ye, Haiyong Weng

“…This design aims to enhance feature extraction and focus on critical image regions, addressing the challenges of detecting small and complex disease patterns in UAV-captured imagery. …”
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Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Furthermore, to improve detection speed, the structural tensor of the effective imaging region in infrared compound eye images is reconstructed, and the Representative Coefficient Total Variation method is employed to avoid complex singular value decomposition and regularization optimization computations. …”
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Detection of Bipolar Disorder and Schizophrenia Employing Bayesian-Optimized Grad-CAM-Driven Deep Learning by Osman Tayfun Bişkin, Cemre Candemir, Mustafa Alper Selver

“…Building on its success in other domains, including autism spectrum disorder and Alzheimer’s disease, DL models have demonstrated the potential to detect subtle structural changes in BD and SCH. Recent advancements suggest that DL can outperform traditional statistical methods, offering higher classification accuracy and enabling the differentiation of complex psychiatric disorders. …”
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A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation by Dong Miao, Ying Zhao, Xue Ren, Meng Dou, Yu Yao, Yiran Xu, Yingchao Cui, Ailian Liu

“…By correlating landmark detection with segmentation, we enhance surgical planning precision. …”
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Electrochemical detection of simple alkanes by utilizing a solid-state zirconia-based gas sensor by Anatoly S. Kalyakin, Alexander N. Volkov

“…While relatively simple gas mixtures (H2O+N2, O2+N2) have been successfully studied by means of ZrO2-based sensors, the precise detection of more complex compounds represents a challenging task. …”
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An IoT intrusion detection framework based on feature selection and large language models fine-tuning by Huan Ma, Wan Zhang, Dalong Zhang, Baozhan Chen

“…Therefore, we propose a Feature Selection and Large Language Models (LLMs)-based IoT intrusion detection framework (FSLLM). At its core is a multi-stage feature selection algorithm combining Minimum Redundancy Maximum Relevance algorithm (mRMR) and a Pearson Correlation Coefficient (PCC)-improved Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES). …”
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Enhanced BDS four-frequency cycle slip detection and repair using fuzzy clustering analysis by Jinfeng Yuan, Xiaoning Su, Yuzhao Li

“…It is worth noting that during the repair process, the coefficients of the combined observation values are integers, preserving the integer cycle characteristic of the observation values, which allows cycle slips to be fixed directly, eliminating the need for complex searching procedures. …”
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Development of a New Indirect ELISA Test for the Detection of Anti-Feline Coronavirus Antibodies in Cats by Irene Ferrero, Sarah Dewilde, Paolo Poletti, Barbara Canepa, Enrica Giachino, Paola Dall’Ara, Joel Filipe

“…The diagnosis of FIP is complex and requires different examinations. Among serological tests, the indirect immunofluorescent antibody test (IFAT), considered the gold standard, and the enzyme-linked immunosorbent assay (ELISA) are the most widely used to detect FCoV antibodies. …”
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A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…The results of the computer-based experiments show acceptable performance for all methods for the test case of bearings but the potential to detect more complex faults and change detection in the behavior of the machines, in general. …”
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