Research on machine vision online monitoring system for egg production and quality in cage environment by Zhenlong Wu, Hengyuan Zhang, Cheng Fang

“…To diverse operational needs, two distinct post-processing algorithms were developed: one for counting eggs and detecting abnormalities during robotic patrols, and another for assessing egg quality through fixed video streams, which measured crucial parameters such as egg dimensions and shape indexes. …”
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STUDY OF COMPATIBILITY OF METHODS AND TECHNOLOGIES OF HIGH-LEVEL PROTOCOLS AND ERROR-CORRECTING CODES by Vladyslav Sharov, Olena Nikulina

“…This period saw groundbreaking contributions from researchers like David MacKay and Radford Neal, who refined LDPC algorithms, and Erdal Arıkan, who introduced polar codes in 2008. …”
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Snake-DETR: a lightweight and efficient model for fine-grained snake detection in complex natural environments by Heng Wang, Shuai Zhang, Cong Zhang, Zheng Liu, Qiuxian Huang, Xinyi Ma, Yiming Jiang

“…Compared to other state-of-the-art models, Snake-DETR achieved an accuracy of 97.66%, a recall rate of 93.92%, mAP@0.5 of 95.23%, and mAP@0.5:0.95 of 72.15%, all outperforming other algorithms in the comparative tests. Furthermore, the computational load and parameter count of the model are reduced by 47.2 and 52.2%, respectively, compared to the benchmark model. …”
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A Survey on Adversarial Attacks for Malware Analysis by Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam, Pradip Kunwar, Bhavani Thuraisingham

“…We systematically analyze adversarial generation algorithms from broader domains adapted to malware evasion attacks, proposing a taxonomy of adversarial evasion attacks within malware detection based on target domains(Windows, Android and PDF). …”
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Intraocular Pressure Measurement Using Ocular Response Analyzer, Dynamic Contour Tonometer, and Scheimpflug Analyzer Corvis ST by Lisa Ramm, Robert Herber, Eberhard Spoerl, Frederik Raiskup, Lutz E. Pillunat, Naim Terai

“…As no influence of CCT on IOPcc, DCT-IOP, and bIOP was detectable, the used correction algorithms appear to be appropriate in these tonometers in the clinical setting. …”
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Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
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Efficient evidence selection for systematic reviews in traditional Chinese medicine by Yizhen Li, Zhe Huang, Zhongzhi Luan, Shujing Xu, Yunan Zhang, Lin Wu, Darong Wu, Dongran Han, Yixing Liu

“…Methods We integrated an established deep learning model (Evi-BERT combined rule-based method) with Boolean logic algorithms and an expanded retrieval strategy to automatically and accurately select potential evidence with minimal human intervention. …”
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Application of Solenoid Valves for Tram Hydraulic Braking Force Control by ZHANG Yanwei, MAO Jinglu, WANG Cong, WANG Zhongxiang, HAO Xinxin

“…A test bench for the tram hydraulic braking force control is set up, and pressure following tests with 0.5 Hz and 1.0 Hz sinusoidal waves are carried out on the two types of valves respectively by using closed-loop control algorithms. The following situations of the actual pressure curves and the target pressure curves are compared. …”
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New probabilistic methods for quantitative climate reconstructions applied to palynological data from Lake Kinneret by T. Netzel, A. Miebach, T. Litt, A. Hense

“…This includes consideration of various machine learning (ML) algorithms for solving the classification problem of biome presence and absence, taking into account uncertainties in the proxy–climate relationship. …”
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Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis by Fei Zuo, Lei Zhong, Jie Min, Jinyu Zhang, Longping Yao

“…Using these features, four machine learning (ML) algorithms were developed. The optimal model was visualized and clarified using SHapley Additive exPlanations (SHAP) and presented as a nomogram. …”
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Morphological analysis of sigmoid sinus anatomy: clinical applications to neurotological surgery by Kylen Van Osch, Daniel Allen, Bradley Gare, Thomas J. Hudson, Hanif Ladak, Sumit K. Agrawal

“…The secondary objective was to create a statistical shape model (SSM) of a dominant and non-dominant sigmoid sinus (SS) to provide a template for automated segmentation algorithms. Methods A free image processing software, 3D Slicer, was utilized to create three-dimensional reconstructions of the SS, jugular bulb (JB), facial nerve (FN), and external auditory canal (EAC) from micro-CT scans. …”
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Post-Marketing Pharmacovigilance of Canakinumab from the FDA Adverse Event Reporting System (FAERS) by Weidong Zhang, Yunzhou Chen, Zeyu Yao, Mengling Ouyang, Minghui Sun, Shupeng Zou

“…<b>Methods:</b> We used a disproportionate analysis to quantify canakinumab-related adverse events (AEs) using four algorithms. Clinical prioritization of the detected signals was assessed with a semiquantitative score method. …”
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Integrating microplastic research in sustainable agriculture: Challenges and future directions for food production by Marcelo Illanes, María-Trinidad Toro, Mauricio Schoebitz, Nelson Zapata, Diego A. Moreno, María Dolores López-Belchí

“…Furthermore, machine learning algorithms can be employed to analyze complex datasets, enhancing our ability to predict the impacts of MPs on plant health and crop performance under different environmental conditions. …”
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Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning by Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang

“…Multiple logistic regression (MLR) and machine learning algorithms were adopted to construct the prediction models.Results A total of 976 patients were included, with 349 patients successfully weaned off RRT. …”
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Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China by Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

“…., lipid lowering medication prescription) using self-designed algorithms. While the encounter-based measures included number or rate of visits for HL, currently-noticed hyperlipidemia (CNHL, or HL noticed during the current consultation), and ever-diagnosed hyperlipidemia (EDHL). …”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. Consequently, we propose the shuffle attention for you only look once version eight (SA-YOLOv8) model, which is based on an enhanced framework. …”
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Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study by Femke Wouters, Henri Gruwez, Christophe Smeets, Anessa Pijalovic, Wouter Wilms, Julie Vranken, Zoë Pieters, Hugo Van Herendael, Dieter Nuyens, Maximo Rivero-Ayerza, Pieter Vandervoort, Peter Haemers, Laurent Pison

“… Abstract BackgroundConsumer-oriented wearable devices (CWDs) such as smartphones and smartwatches have gained prominence for their ability to detect atrial fibrillation (AF) through proprietary algorithms using electrocardiography or photoplethysmography (PPG)–based digital recordings. …”
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Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke by Yanan Lin, Yan Li, Yayin Luo, Jie Han

“…We utilized the Random Forest (RF), Multilayer Perceptron (MLP), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GauNB) algorithms to develop ML-HT models. The models' predictive performance was evaluated using confusion matrix (including accuracy, precision, recall, and F1 score), and discriminative analysis (area under the receiver-operating-characteristic curve, ROC-AUC) in the original cohort, followed by validation in an independent external cohort. …”
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Association of Plasma Levels of Nitric Oxide Oxidative Metabolites with Acute Stroke in Patients Presenting to the Emergency Department of a Low-Middle Income Country by Shahan Waheed, Ayaz Ghouse Kalsekar, Ayeesha Kamran Kamal, Nathan S. Bryan, Asad I. Mian

“…Clinical demographic information, ancillary blood, and diagnostic specimens were collected as per standard of care since the center follows stroke algorithmic guidelines. Plasma NOx analysis was performed using high performance liquid chromatography. …”
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Analysis of spatio-temporal fungal growth dynamics under different environmental conditions by Liselotte De Ligne, Guillermo Vidal-Diez de Ulzurrun, Jan M. Baetens, Jan Van den Bulcke, Joris Van Acker, Bernard De Baets

“…Fortunately, more automated ways of measurement are gaining momentum due to the availability of cheap imaging and processing equipment and the development of dedicated image analysis algorithms. In this paper, we use image analysis to assess the impact of environmental conditions on the growth dynamics of two economically important fungal species, Coniophora puteana and Rhizoctonia solani. …”
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