Wireless Sensor Networks Energy Effectively Distributed Target Detection by Xiaogang Qi, Peng Wei, Lifang Liu, Mande Xie, Guoyong Cai

“…In this paper, we propose an energy effective distributed multisensor target detection method, which is different from the existing single sensor target detection methods, and target is detected by multisensor cooperation scheme. …”
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Optimal azimuth positioning algorithm for base station antenna based on Gaussian distribution by Songbai LIANG, Feng CHEN, Haiping SONG, Wensheng LI

“…In order to improve the accuracy and efficiency of the discovery of the antenna-feeder problem,an optimal direction angle solution based on Gaussian distribution was proposed to diagnose the antenna-feeder coverage problems of operators.First of all,the location direction information between each MR sampling point reported by the UE and the base station was calculated,and then the proportion of MR sampling points in each interval was calculated,Based on the Gaussian distribution feature,the angle range with the largest proportion of MR sampling points was the appropriate azimuth,which was based on the user hotspot distribution of the sector.Finally,the date of optimal azimuth was compared with the base station azimuth in the background antenna database to detect antenna feeder problems,such as cross feeder,improper antenna coverage direction and incorrect background antenna database,and so on.The field verification shows that,the cost,accuracy and efficiency of the antenna-feeder problems are obviously improved compared with the existing methods.…”
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Overcoming Fairness and Latency Challenges in BBR With an Adaptive Delay Detection by Zewei Han, Go Hasegawa

“…BBR aims to set the data-sending rate of flows to operate at an optimal operating point—maximizing throughput, minimizing delay, and reducing packet loss. …”
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Optimal Zero-Defect Solution for Multiple Inspection Items in Incoming Quality Control by Wenqing Zhou, Yufeng Chen

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Case of granulomatosis with polyangiitis: optimal possibilities for rapid diagnosis in a multidisciplinary hospital by A. V. Novikova, N. G. Pravdyuk, E. I. Shmidt, A. P. Raksha, M. R. Mazra, A. R. Yunyaev, J. S. Zhulina

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Deep learning in defects detection of PV modules: A review by Katleho Masita, Ali Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…Traditional manual inspection methods are time-consuming, labor-intensive, and subject to human error, necessitating the development of automated, efficient detection techniques. …”
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Machine learning-driven strategies for enhanced pediatric wheezing detection by Hye Jeong Moon, Hyunmin Ji, Hyunmin Ji, Baek Seung Kim, Beom Joon Kim, Kyunghoon Kim, Kyunghoon Kim

“…To overcome these limitations, artificial intelligence models have been developed.MethodsIn this prospective study, we aimed to compare respiratory sound feature extraction methods to develop an optimal machine learning model for detecting wheezing in children. …”
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Detecting Software Anomalies in Robots by Means of One-class Classifiers by Héctor Quintián, Esteban Jove, Francisco Zayas-Gato, Nuño Basurto, Carlos Cambra, Álvaro Herrero

“…The results show that Principal Component Analysis outperforms other methods in most scenarios, although the optimal performance varies depending on the anomaly type. …”
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A method for calculating the coverage area of radar network based on Monte Carlo method and its simulation by WANG Yinlong, WANG Dan, MA Juntao, ZHAO Deyong

“…Since the probability of detecting a target by the radar network is the result of the joint action of various radars, the graph of its coverage area is very complex and difficult to obtain an analytical solution by conventional methods. …”
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Hyperspectral Wavelength Selection and Integration for Bruise Detection of Korla Pears by Yiming Fang, Fan Yang, Zhu Zhou, Lujun Lin, Xiaoqin Li

“…Experimental results demonstrated that the feature wavelength integration resulted in lower detection errors. The proposed method is simple and promising for bruise detection of Korla pears, and it can be utilized for other types of defects on fruits.…”
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Establishment and application of TAS-ELISA for the detection of M. rosenbergii Nodavirus by QIAN Dong, LIU Wen, PAN Xiao-yi, CAO Zheng, YU Lian

“…The sensitivity of TAS-ELISA to purified MrNV was 0.98 ng, without cross reaction to WSSV, TSV and other dead prawn postlarvae caused by bacterial infection. The positive detection rate as well as coincident rate were compared with different methods and showed that TAS-ELISA was better than indirect ELISA and RNA characterization with electrophoresis, when the diseased and suspicious prawn samples were analysed. …”
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Actuator Fault Detection and Identification Using H-Infinity Filter by Ndabarushimana Egone, Ma Lei

“…Performance metrics indicate a significant improvement in detection reliability compared to conventional methods. …”
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Application of Infrared Thermography in the Detection of Hoof Disease and Lameness in Cattle by Tina Bobić, Nikola Raguž, Mihaela Oroz, Marko Oroz, Maja Gregić, Pero Mijić, David Kranjac, Boris Lukić

“…However, further research is needed to develop optimal combinations of different diagnostic methods to improve the accuracy and efficiency of detecting hoof disease and lameness.…”
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DeepPolyp: an artificial intelligence framework for polyp detection and segmentation by Marco Mameli, Sepideh Shiralizadeh, Massimiliano Papi, Iulian Gabriel Coltea

“…Aim: Colorectal cancer is a leading cause of cancer-related mortality, emphasising the need for accurate polyp segmentation during colonoscopy for early detection. Existing methods often struggle to generalize effectively across diverse clinical scenarios. …”
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Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection by Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo

“…The Cumulative Sum (CUSUM) method, based on calculating the cumulative values within a time series, is commonly used for change detection due to its early detection of small drifts, simplicity, low computational cost, and robustness to noise. …”
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Explainable correlation-based anomaly detection for Industrial Control Systems by Ermiyas Birihanu, Imre Lendák

“…This study proposes an explainable correlation-based anomaly detection method for ICS. The optimal window size of the data is determined using Long Short-Term Memory Networks—Autoencoder (LSTM-AE) and the correlation parameter set is extracted using the Pearson correlation. …”
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Toward Causal and Evidential Open-Set Temporal Action Detection by Zhuoyao Wang, Rui-Wei Zhao, Rui Feng, Cheng Jin

“…Experimental results show that our proposed method achieves state-of-the-art open-set temporal action detection performance on the THUMOS14 and ActivityNet1.3 benchmarks. …”
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Pig Detection Algorithm Based on Sliding Windows and PCA Convolution by Longqing Sun, Yan Liu, Shuaihua Chen, Bing Luo, Yiyang Li, Chunhong Liu

“…By calculating the omission detection rate, the misdetection rate, and the average detection time, it can be seen that in the detection methods of the proposed algorithm, BING + PCANet, faster rcnn and yolo, the performance of the proposed algorithm was optimal.…”
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An indirect ELISA for the detection of antibodies against Dirofilaria spp. in cats by Lívia Perles, Mariaelisa Carbonara, Jairo Alfonso Mendoza-Roldan, Luigi Venco, Simona Gabrielli, Domenico Otranto

“…Results The optimized ELISA showed 89% Se and 98% Sp in detecting D. immitis infections, presenting a cross-reactivity with D. repens. …”
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Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…This study aims to evaluate and compare the performance of five widely used deep learning-based edge detection methods to identify the most effective approach specifically tailored for natural images. …”
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