The interference of baicalein with uric acid detected by the enzymatic method and its correction method by Jiuyan Li, Zichen Zhang, Jia Li, Wei Li, Liqiang Wang, Yumei Pei, Jing Huang

“…The interferences of baicalein during the detection of these five analytes were investigated on the Hitachi 7600 system. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…Automated video anomaly detection (VAD) is a challenging task due to its context-dependent and sporadic nature. …”
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AI-Powered Object Detection in Radiology: Current Models, Challenges, and Future Direction by Abdussalam Elhanashi, Sergio Saponara, Qinghe Zheng, Nawal Almutairi, Yashbir Singh, Shiba Kuanar, Farzana Ali, Orhan Unal, Shahriar Faghani

“…Artificial intelligence (AI)-based object detection in radiology can assist in clinical diagnosis and treatment planning. …”
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Hybrid CNN-Ensemble Framework for Intelligent Optical Fiber Fault Detection and Diagnosis by Salem Titouni, Idris Messaoudene, Yassine Himeur, Omar Alnaseri, Farouk Chetouah, Boualem Hammache, Massinissa Belazzoug, Shadi Atalla, Wathiq Mansoor

“…Additionally, existing machine learning approaches often struggle with generalization across diverse fault types and imbalanced datasets. …”
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Oximation reaction induced reduced graphene oxide gas sensor for formaldehyde detection by Lei Zhou, Rong Qian, Shangjun Zhuo, Qiao Chen, Zhaoyin Wen, Guorong Li

“…The gas-sensing performance test results suggested that the RGO hydroxylamine hydrochloride (RGO/HA-HCl) sensor presented a high response of 75% at 16 ppm HCHO at room temperature, and a high selectivity for HCHO suffering little interference with high concentrations of volatile organic compounds, including methanol, ethanol, and methylbenzene, dichloromethane and water. Additionally, the RGO/HA-HCl sensor also showed a good long-term stability with RSD of 5.83% for a 15-day continuous sensing test, and the detection limit (DL) could reach 0.023 ppm under ambient conditions. …”
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Outlier Detection of Photovoltaic Power Generation System Data Based on GMM-IF Algorithm by Xin Li, Guoxin Du, Yuman Li, Zengqiang Ma, Lihu Liu, Minglong Jiang, Feiyu Liu, Tianming Mu

“…In this method, the decision tree segmentation modeling strategy is used to structure the data to construct a local Gaussian-like distribution dataset to overcome the prior assumptions. Additionally, it integrates an Isolation Forest (IF) as the decision-making mechanism for detailed detection, further enhancing detection accuracy. …”
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CP-YOLO: An Algorithm for Cigarette Pack Defects Detection Based on CCD Images by Peng Dong, Weihua Feng, Rui Wang, Mingyan Zhang, Qunye Hong, Yongsheng Wang, Di Wang, Guohao Zong

“…In cigarette production, detecting cigarette pack defects is crucial for ensuring that products meet quality standards. …”
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Innovative fast and low-cost method for the detection of living bacteria based on trajectory by Paul Perronno, Julie Claudinon, Carmen Senin, Serap Elçin-Guinot, Lena Wolter, Olga N. Makshakova, Norbert Dumas, Dimitri Klockenbring, Joseph Lam-Weil, Vincent Noblet, Siegfried Steltenkamp, Winfried Römer, Morgan Madec

“…Abstract Detection of pathogens is a major concern in many fields like medicine, pharmaceuticals, or agri-food. …”
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Recent advances in aptamer-based biosensing technology for isolation and detection of extracellular vesicles by Osama Alnaser-Almusa, Mohammed Mahmoud, Mohammed Ilyas, Raghda Adwan, Farah Abul Rub, Noha Alnaser-Almusa, Fayrouz Mustafa, Sana Ahmed, Alaa Alzhrani, Alaa Alzhrani, Alaa Alzhrani, Tanveer Ahmad Mir, Tanveer Ahmad Mir, Mubarak. Alabudahash, Raja Chinnappan, Raja Chinnappan, Ahmed Yaqinuddin

“…Researchers have developed numerous isolation and detection methods for EVs, including ultracentrifugation, immunoaffinity capture, and antibody-based biosensors. …”
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MEViT: Generalization of Deepfake Detection With Meta-Learning EfficientNet Vision Transformer by Van-Nhan Tran, Hoanh-Su Le, Piljoo Choi, Suk-Hwan Lee, Ki-Ryong Kwon

“…With the rapid advances in deep generative models, the accessibility and sophistication of such manipulation technologies are increasing, making it more challenging to detect fake content. Different facial forgery techniques result in complex data distributions, and most existing deepfake detection approaches rely on convolutional neural networks (CNNs) that treat the task as a binary classification problem. …”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…Change detection in synthetic aperture radar imagery is challenging due to noise, complex nonlinear features, and variations in underlying data distributions. …”
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Targeted next-generation sequencing for antimicrobial resistance detection in ventilator-associated pneumonia by Yuting Li, Yanfang Jiang, Hao Liu, Yao Fu, Junying Lu, Hongyan Li, Lulu Sheng, Dejian Gu, Dong Zhang

“…While the sensitivity rate of microbial culture was just 66.84%. Additionally, tNGS performed almost half the turnaround time of microbial culture (1.66 days vs 3.00 days). …”
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CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals by Ugur Ince, Yunus Talu, Aleyna Duz, Suat Tas, Dahiru Tanko, Irem Tasci, Sengul Dogan, Abdul Hafeez Baig, Emrah Aydemir, Turker Tuncer

“…Classification results were obtained using the cumulative weighted iterative neighborhood component analysis (CWINCA) feature selector and the t-algorithm-based k-nearest neighbors (tkNN) classifier. Additionally, explainable results were generated using the CWINCA selector and Directed Lobish (DLob). …”
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Computer Vision-Based Obstacle Detection Mobile System for Visually Impaired Individuals by Gisel Katerine Bastidas-Guacho, Mario Alejandro Paguay Alvarado, Patricio Xavier Moreno-Vallejo, Patricio Rene Moreno-Costales, Nayely Samanta Ocaña Yanza, Jhon Carlos Troya Cuestas

“…Therefore, technological solutions based on computer vision tasks are presented as promising alternatives to help detect obstacles. Object detection models are easy to couple to mobile systems, do not require a large consumption of resources on mobile phones, and act in real-time to alert users of the presence of obstacles. …”
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YOLO-v4 Small Object Detection Algorithm Fused With L-α by ZHANG Ning, YU Ming, REN Honge, AO Rui, ZHAO Long

“… The detection ability for small object is still need to be improved urgently in spite of the rapidly developing object detection technology based on deep learning at present.Compared with large objects, small object detection tasks hold drawbacks of low resolution and feature loss which leads to that many general algorithms cannot be directly applied to small object detection.The feature pyramid fusion can effectively combine the features of deep and shallow layers to enhance the performance.To solve the problem most models existing ignoring the imbalance of information during the feature fusion between adjacent layers, it is proposed to integrate the idea of fusion factor into the PANet of YOLOv4, use the fusion factor L-αto control the amount of information transmitted from the deep layer to the shallow, so as to effectively improve the efficiency of information fusion and enhance the ability of YOLO-v4 for small objects detection.With the addition of L-αin YOLO- V4 model, the experiment results show that the APtiny50and APsmall50on the TinyPerson are improved by 2.14% and 1.85% respectively, while the AP and APS on the MS COCO are separately increased by 1.4% and 2.7%.It is proved that this improved method is effective for small object detection with the evidence of better result than other small object detection algorithms.…”
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SwinSegFormer: Advancing Aerial Image Semantic Segmentation for Flood Detection by Muhammad Tariq Shaheen, Hafsa Iqbal, Numan Khurshid, Haleema Sadia, Nasir Saeed

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Detecting Foci of Malaria Transmission with School Surveys: A Pilot Study in the Gambia. by Ebako N Takem, Muna Affara, Alfred Amambua-Ngwa, Joseph Okebe, Serign J Ceesay, Musa Jawara, Eniyou Oriero, Davis Nwakanma, Margaret Pinder, Caitlin Clifford, Makie Taal, Momodou Sowe, Penda Suso, Alphonse Mendy, Amicoleh Mbaye, Chris Drakeley, Umberto D'Alessandro

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FedSW-TSAD: SWGAN-Based Federated Time Series Anomaly Detection by Xiuxian Zhang, Hongwei Zhao, Weishan Zhang, Shaohua Cao, Haoyun Sun, Baoyu Zhang

“…However, federated anomaly detection experiences issues with unstable training and poor generalization due to client heterogeneity and the limited expressiveness of single-path detection methods. …”
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Research on plasma arc flame length detection technology based on region of interest. by Jie Li, Wei Jiang, Jian Lei, Xiaoxiao Xing

“…Additionally, real-time monitoring of the detection site is enabled through KingView. …”
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The Induction and Detection Method of Angry Driving: Evidences from EEG and Physiological Signals by Lixin Yan, Ping Wan, Lingqiao Qin, Dunyao Zhu

“…Due to possible crash and injury from the on-road experiments, the proposed approach of driving anger induction using a driving simulator is effective in exploring the causal relationship between angry driving, unsafe driving behavior, and traffic accident. In addition, angry driving detection approach can provide theoretical foundation for the development of driving anger warning products.…”
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