Evaluation of Touchdown Loop-Mediated Isothermal Amplification for the Detection of <i>Giardia duodenalis</i> by Márton Hartdégen, András József Laki, Kolos Farkasvölgyi, Kristóf Iván, Judit Plutzer

“…Based on the results of this study, the 66–60 °C range touchdown LAMP with the use of betaine, 90 °C denaturation step, Bst 2.0 WarmStart^® DNA Polymerase, and the primer set of Momoda et al. were the optimal conditions. We increased the analytical sensitivity of the LAMP reaction to 7.8- and 8-fold higher than the previously published methods for <i>G. duodenalis</i> assemblages A and B, with detection limits of 20 and 19.5 fg/assay, respectively, instead of 156 fg/assay. …”
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The Fruit Recognition and Evaluation Method Based on Multi-Model Collaboration by Mingzheng Huang, Dejin Chen, Dewang Feng

“…Finally, the classification results were optimized by the feature matching network. In the method, the detection model was based on YOLOv8, and the model was improved by introducing a TripletAttention structure and an Attention Mechanism-Based Feature Fusion (AFM) structure. …”
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Evaluation of The Utilization of The iPosyandu Application in Enhancing Midwives&amp;rsquo; Competence in Early Pregnancy Detection Services: Mixed Methods Study by Susanti AI, Nuraini A, Rinawan FR, Adnani QES, Wirakusumah FF

“…Consequently, mobile health (mHealth) solutions, such as the iPosyandu application, are essential to assist midwive’s in delivering maternal and child health services and enhancing their competence for early detection in pregnant women.Purpose: This study seeks to examine the evaluation of the iPosyandu application on midwive’s proficiency in early pregnancy identification.Patients and Methods: The research employed a convergent mixed-method approach, incorporating quantitative analysis involving 120 village midwives in Purwakarta Regency, divided into intervention (n = 60) and control (n = 60) groups. …”
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Research on Arc Fault Detection Based on Conditional Batch Normalization Convolutional Neural Network with Cost-Sensitive Multi-Feature Extraction by Xin Ning, Tianli Ding, Hongwei Zhu

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Research on the Method of Crop Pest and Disease Recognition Based on the Improved YOLOv7-U-Net Combined Network by Wenchao Xiang, Zitao Du, Xinran Liu, Zehui Lu, Yuna Yin

“…This paper proposes an improved YOLOv7-U-Net combined network for crop pest and disease recognition, aiming to address the issue of insufficient accuracy in existing methods. For the YOLOv7 network, a self-attention mechanism is integrated into the SPPCSPC module to dynamically adjust channel weights and suppress redundant information while optimizing the PAFPN structure to enhance cross-scale feature fusion and improve small-object detection capabilities. …”
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Standardization and validation of a novel reverse transcriptase polymerase chain reaction method for detecting virulent strains of the infectious bursal disease virus by Vladimir Longa-Bobadilla, Phillip Ormeño-Vásquez, Manuel Criollo-Orozco, Luis Tataje-Lavanda, Katherine Huamán-Gutierrez, Ángela Montalván, Mirko Zimic, Manolo Fernández-Sanchez, Manolo Fernández-Díaz

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Maximum likelihood DOA estimation based on improved ant colony optimization algorithm by JIAO Yameng, LI Wenping, WU Yue, CUI Lin

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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

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LGN-YOLO: A Leaf-Oriented Region-of-Interest Generation Method for Cotton Top Buds in Fields by Yufei Xie, Liping Chen

“…Using the ROI output by this method as the detection region can address the problem of feature sparsity in small targets during traditional detection, achieve pre-detection region optimization, and thus reduce the cost of mining detailed features.…”
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Microwave Foreign Object Detection in a Lossy Medium Using a Planar Array Antenna by Longzheng Yu, Peng Xu, Wenbo Li, Xiao Cai

“…The excitation distribution of the transmitting array is optimized by using the method of maximum power transmission efficiency based on the differential scattering parameter matrices with the absence and presence of the foreign object. …”
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A Diffusion-Based Detection Model for Accurate Soybean Disease Identification in Smart Agricultural Environments by Jiaxin Yin, Weixia Li, Junhong Shen, Chaoyu Zhou, Siqi Li, Jingchao Suo, Jujing Yang, Ruiqi Jia, Chunli Lv

“…This paper proposes a diffusion-based object detection model that integrates the endogenous diffusion sub-network and the endogenous diffusion loss function to progressively optimize feature distributions, significantly enhancing detection performance for complex backgrounds and diverse disease regions. …”
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YOLOv9-Based Human Face Detection and Counting Under Human-Animal Faces, Complex Imaging Environments, and Image Qualities by Sivaranjini Perikamana Narayanan, M. Sabarimalai Manikandan, Linga Reddy Cenkeramaddi

“…Evaluation results demonstrate that the YOLOv9-based face counting outperforms most of the state-of-the-art face detection and people counting methods with a mean absolute error (MAE) of 3.36 and root mean square error (RMSE) of 22.38. …”
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Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale by Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak

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Rapid detection of volatile fatty acids in biogas slurry using near-infrared spectroscopy combined with optimized wavelength selection and partial least squares regression by Honglin Wang, Jinming Liu, Pengfei Li, Chong Tan

“…Model validation yielded determination coefficients of 0.9882, 0.9452, and 0.9483, and root mean square errors of prediction of 0.1193, 0.1178, and 0.5492 for acetic acid, propionic acid, and total acid, respectively, representing reductions of approximately 40 %, 18 %, and 30 % compared to full-spectrum modeling. This method significantly enhances detection accuracy and stability, providing an efficient strategy for optimizing anaerobic fermentation processes.…”
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PFAS residue analysis in fish and fish feed by applying a modified QuEChERS method in combination with LC-HRMS detection by Ourania Koloka, Vasiliki Boti, Dimitra Hela, Triantafyllos Albanis, Ioannis Konstantinou

“…A targeted method for the quantitative determination of PFAS residues in fish feed and marine aquaculture fish species was developed and validated in the current study. …”
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Water Body Detection Using Sentinel-2 Imagery Through Particle Swarm Intelligence: A Novel Framework for Optimizing Spectral Multi-Band Index by Baydaa Ismail Abrahim, Ammar Abd Jasim, Mohammed Riyadh Mahmood, Hassanein Riyadh Mahmood, Hayder A. Alalwan, Malik M. Mohammed

“…This paper proposes a new approach by incorporating Particle Swarm Optimization with a Spectral Multi-Band Water Index for the enhanced detection of water bodies using Sentinel-2 imagery. …”
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Comparative analysis of deep learning and traditional methods for IoT botnet detection using a multi-model framework across diverse datasets by Saeed Ullah, Junsheng Wu, Zhijun Lin, Mian Muhammad Kamal, Hala Mostafa, Muhammad Sheraz, Teong Chee Chuah

“…These contributions advance IoT security by enabling scalable, high-performance detection adaptable to diverse network scenarios, with practical optimizations for real-world deployment.…”
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COMPARATIVE ANALYSIS OF STANDARD AND ENHANCED SWARM INTELLIGENT DEEP BELIEF NETWORK ON MAIZE DISEASE DETECTION by Kehinde Sotonwa, Adebisi Oluwatosin, Adesesan Adeyemo, Micheal Adenibuyan

“…The PSO was applied to DBN to select its optimal weight parameters. The system was implemented using a language app designer, trained and tested using k-fold cross-validation method, where k is 10-fold. …”
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Efficient deep learning based rail fastener screw detection method for fastener screw maintenance robot under complex lighting conditions by Yijie Cai, Ming He, Bin Chen

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CrossGraphNet: a cross-spatiotemporal graph-based method for traffic speed reconstruction using remote sensing vehicle detection by Yan Zhang, Mei-Po Kwan, Jiannan Cai, Jianying Wang, Peifeng Ma

“…The method is designed to address the challenges of traffic modeling in the absence of ground observation data. …”
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