AI-based orchard monitoring at night: Enhancing sustainable fruit production through real-time apple detection by Kutyrev Alexey, Khort Dmitry, Smirnov Igor, Zubina Valeria

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Hybrid Time Series Methods and Machine Learning for Seismic Analysis and Volcano Eruption Predict by Fridy Mandita, Ahmad Ashari, Moh. Edi Wibowo, Wiwit Suryanto

“…Ultimately, the method enhances hybrid methods and machine learning for seismic event analysis and volcano monitoring.   …”
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AI-driven discovery of minimal sepsis biomarkers for disease detection and progression: precision medicine across diverse populations by Qiyuan Su, Jingtao Huang, Yunlong Zhang, Zhou Liu, Zhihua Lv, Chunming Zhang, Chengxiu Ling, Hanwen Su, Liying Zhan, Zhengjun Zhang, Zhengjun Zhang, Zhengjun Zhang

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Establishment and preliminary application of PCR-RFLP genotyping method for Giardia duodenalis in goats by Xuanru Mu, Jianchao Guo, Hongcai Wang, Yilong Li, Kaijian Yuan, Hui Xu, Wenjing Zeng, Qiaoyu Li, Xingang Yu, Yang Hong

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Combining Endpoint Detection and One-Dimensional CNN-Based Classifier for Non-Technical Loss Screening in Smart Grids by Ping-Tzan Huang, Feng-Chang Gu, Chia-Hung Lin, Chao-Lin Kuo, Neng-Sheng Pai, Yung-Chang Luo, Wen-Cheng Pu

“…The EPD method is employed to preliminarily detect discrepancies between metering data and historical records, focusing on the time-domain variations in electricity consumption. …”
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Ship behavior prediction and anomaly detection using LSTM-DCross model based on AIS and remote sensing data by Wanrong Wu, Dongmei Yan, Jun Yan, Xiaowei Wang

“…The study addresses two critical scenarios: GPS failure and complete AIS failure, utilizing two prediction methods – joint prediction and historical data-based prediction – to forecast the target ship behaviour. …”
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Developing a Prediction Model for Real-Time Incident Detection Leveraging User-Oriented Participatory Sensing Data by Md Tufajjal Hossain, Joyoung Lee, Dejan Besenski, Branislav Dimitrijevic, Lazar Spasovic

“…Effective incident detection is essential for emergency response and transportation management. …”
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Research on Long-Distance Snow Depth Measurement Method Based on Improved YOLOv8 by Jia-Wen Wang, Yu Cao, Zong-Kai Guo, Cheng Xu

“…To address these issues, this paper proposes a snow depth detection method based on an improved YOLOv8-seg model, named YOLOv8-AE. …”
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Towards Automated Real-Time Detection and Location of Large-Scale Landslides through Seismic Waveform Back Projection by En-Jui Lee, Wu-Yu Liao, Guan-Wei Lin, Po Chen, Dawei Mu, Ching-Weei Lin

“…Compared to local earthquake recordings, the recordings of landslides usually show longer durations and lack distinctive P and S wave arrivals; therefore, the back projection method is adopted for the landslide detection and location. …”
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A machine learning-based detection, classification, and quantification of marine litter along the central east coast of India by Mallela Pruthvi Raju, Subramanian Veerasingam, V. Suneel, Fahad Syed Asim, Hana Ahmed Khalil, Mark Chatting, P. Suneetha, P. Vethamony

“…This study aims to understand the spatial distribution of marine litter along the central east coast of India using the conventional method and AI based object detection approach. From the field survey, a total of 4588 marine litter items could be identified, with an average of 1.147 ± 0.375 items/m2. …”
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Optimization Method for Transit Signal Priority considering Multirequest under Connected Vehicle Environment by Song Xianmin, Yuan Mili, Liang Di, Ma Lin

“…Finally, the paper combines the COM interface of VISSIM and Matlab to achieve the proposed method under connected vehicle environment. Four control methods were tested when the VCR was 0.5, 0.7, and 0.9. …”
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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…The convolutional neural network and bi-directional gated recurrent unit with attention (CNN-BiGRU-A) method is employed to classify and detect haematologic disorders. …”
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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

“…The proposed method provides a viable alternative for secure and efficient credit card fraud detection in the contemporary digital economy, characterized by high accuracy and real-time scalability.…”
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A comprehensive evaluation of a novel targeted-sequencing workflow for Mycobacterium species identification and anti-tuberculosis drug-resistance detection by Xichao Ou, Shaojun Pei, Shaojun Pei, Hongru Li, Zhonghua Qin, Richard Anthony, Jichun Wang, Zexuan Song, Ruida Xing, Lixia Zhang, Chong Teng, Hui Xia, Yang Zhou, Yuanyuan Song, Yang Zheng, Shengfen Wang, Bing Zhao, Yanlin Zhao

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Precise irrigation of dryland cotton under canal irrigation system constraints based on the CERES-CROPGRO-Cotton model by Lei Wang, Liang He, Weihong Sun, Chen Gao, Zhenxiang Han, Meiwei Lin

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Exploring Machine Learning Methods for Aflatoxin M1 Prediction in Jordanian Breast Milk Samples by Abdullah Aref, Eman Omar, Eman Alseidi, Nour Elhuda A. Alqudah, Sharaf Omar

“…The presence of aflatoxin M1 in breast milk poses a serious risk to the health of infants because of its potential to cause cancer and have negative effects on development. Detecting AFM1 in milk samples using conventional methods is often time-consuming and may not provide real-time monitoring capabilities. …”
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A machine learning method to monitor China's AIDS epidemics with data from Baidu trends. by Yongqing Nan, Yanyan Gao

“…This paper uses search engine data to monitor and forecast AIDS in China.<h4>Methods</h4>A machine learning method, artificial neural networks (ANNs), is used to forecast AIDS incidences and deaths. …”
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A Bootstrapping Convolutional Neural Network Technique for Optimizing Automated Detection of Equatorial Plasma Bubbles by Optical All‐Sky Imagers by Daniel Okoh, Claudio Cesaroni, Babatunde Rabiu, Kazuo Shiokawa, Yuichi Otsuka, Samuel Ogunjo, Aderonke Akerele, John Bosco Habarulema, Bruno Nava, Yenca Migoya‐Orué, Punyawi Jamjareegulgarn, Adeniran Seun, Ogechi Adama, George Ochieng, James Ameh, Adero Awuor, Paul Baki

“…Abstract Equatorial plasma bubbles (EPBs) disrupt satellite‐based communication and navigation systems, particularly in equatorial regions. Reliable detection and classification of EPBs from all‐sky imager (ASI) images are essential for accurate space weather monitoring and forecasting. …”
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Exploring Different Dynamics of Recurrent Neural Network Methods for Stock Market Prediction - A Comparative Study by Ajit Mohan Pattanayak, Aleena Swetapadma, Biswajit Sahoo

“…The intricate and unpredictable nature of stock markets underscores the importance of precise forecasting for timely detection of downturns and subsequent rebounds. …”
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Detecting and classifying metabolic activity of Staphylococcus aureus by D2O-probed single-cell Raman spectroscopy and machine learning by Li Liu, Bing Feng, Yang Song, Taijie Zhan, Dongxin Liu, Jia Ding, Xiaohui Song, Jian Xu, Duochun Wang, Qiang Wei

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