Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model by Md. Siddikur Rahman, Miftahuzzannat Amrin, Md. Abu Bokkor Shiddik

“…Results Our study findings detected a nonlinear effect of climatic parameters on dengue at different thresholds such as mean (27°C), minimum (22°C), maximum temperatures (32°C), and relative humidity (82%). …”
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High-throughput phenotyping tools for blueberry count, weight, and size estimation based on modified YOLOv5s by Xingjian Li, Sushan Ru, Zixuan He, James D. Spiers, Lirong Xiang

“…The first pipeline used traditional algorithms such as Hough Transform, Watershed, and filtering. …”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…We train more than 900 different combination of feature selector, models and hyperparameters. At last, we assess the performance of the models on multiple performance measures (accuracy, sensitivity, specificity and area under the ROC curve (AUC)). …”
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Machine learning reveals the dynamic importance of accessory sequences for Salmonella outbreak clustering by Chao Chun Liu, William W. L. Hsiao

“…Annotating the genomic features important for cluster classification revealed functional enrichment of molecular fingerprints in genes involved in membrane transportation, trafficking, and carbohydrate metabolism. …”
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MRI-based habitat analysis of vascular and nerve invasion in the tumor microenvironment: an advanced approach for prostate cancer diagnosis by Bo Guan, Cong Huang, Yalei Wang, Jialong Zhang, Xiaowei Li, Zongyao Hao, Zongyao Hao

“…PurposeThis study aims to detect vascular and neural invasion in prostate cancer through MRI, utilize habitat analysis of the tumor microenvironment, construct a radiomic feature model, thereby enhancing diagnostic accuracy and prognostic assessment for prostate cancer, ultimately improving patients’ quality of life.MethodsWe retrospectively collected records of 400 patients with pathologically verified prostate cancer from January to December 2023. …”
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FinSafeNet: securing digital transactions using optimized deep learning and multi-kernel PCA(MKPCA) with Nyström approximation by Ahmad Raza Khan, Shaik Shakeel Ahamad, Shailendra Mishra, Mohd Abdul Rahim Khan, Sunil Kumar Sharma, Abdullah AlEnizi, Osama Alfarraj, Majed Alowaidi, Manoj Kumar

“…These improvements further help the model to detect the relevant features in transaction data that may present a threat to the security of the system. …”
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A machine vision approach for classification and dimensional design of furniture panels using GMM-SVM by Yuan Tian, Li Zhao, Haoxin Li

“…Meanwhile, in the comparative experiments with Bayesian classification algorithm (BC) and artificial neural network algorithm (ANN), the suggested GMM-SVM combination algorithm provides the greatest recognition effect, with the maximum accuracy rate of 0.948. …”
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A Robust Approach to Vision-Based Terrain-Aided Localization by Dan Navon, Ehud Rivlin, Hector Rotstein

“…The SFM problem can be solved using existing techniques such as feature detection, matching, and triangulation wrapped with a bundle adjustment algorithm. …”
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Real-Time Recognition of Loading Cycles’ Process Based on Electric Mining Shovel Monitoring by Bonan Wang, Yun Duan, Wei Xu

“…An automatic recognition algorithm based on the feature extraction of working parameters to recognize each state in the loading cycle process of an electric mining shovel was proposed. …”
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Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays. by Ankit Srivastava, Qinlu Wang, Christina D Orrù, Manel Fernandez, Yaroslau Compta, Bernardino Ghetti, Gianluigi Zanusso, Wen-Quan Zou, Byron Caughey, Catherine A A Beauchemin

“…Seed amplification assays (SAAs) such as real-time quaking-induced conversion (RT-QuIC) have shown high diagnostic sensitivity and specificity for detecting proteopathic αSynD seeds in a variety of biospecimens from PD and DLB patients. …”
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Research on Measurement and Statistical Characteristics of Air-to-Ground Bidirectional Links Channels by Yang Yuxin, Lei Taiya, Hua Boyu, Chen Xiaomin, Liu Yuchao, Li Hanpeng, Zhu Qiuming

“…A method for capturing the channel impulse response is presented, employing constant false alarm rate detection for multipath extraction and channel feature analysis. …”
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A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…The prediction of underwater acoustic signal is the basis of underwater acoustic signal processing, which can be applied to underwater target signal noise reduction, detection, and feature extraction. Therefore, it is of great significance to improve the prediction accuracy of underwater acoustic signal. …”
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Identification of sweetpotato virus disease-infected leaves from field images using deep learning by Ziyu Ding, Fanguo Zeng, Haifeng Li, Jianyu Zheng, Junzhi Chen, Biao Chen, Wenshan Zhong, Xuantian Li, Zhangying Wang, Lifei Huang, Xuejun Yue, Xuejun Yue

“…The APF module combines a channel attention mechanism with multi-scale feature fusion to enhance the model’s performance in disease pixel segmentation. …”
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3D Reconstruction and Measurement Analysis of a Dense Point Cloud Fused with a Depth Image by Yujing Qiao, Ning Lv, Siyuan Zhang

“…Our method provides technical support for complex surface topography detection and has industrial practical significance.…”
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Fast Spectral Correlation Based on Sparse Representation Self-Learning Dictionary and Its Application in Fault Diagnosis of Rotating Machinery by Hongchao Wang, Wenliao Du

“…However, the fault feature such as impulsive characteristic component is often interfered by other background noise, and the situation is serious especially in early weak fault stage. …”
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Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database by Lin Xu, Xuejing Li, Na Zhang, Chunmei Guo, Pan Wang, Min Gao, Yanhui Zhang, Lixin Zhao

“…Utilizing the formula ln[(triglycerides mg/dl) × (glucose mg/dl)/2], the TyG index was calculated. The Boruta algorithm and Xgboost model were used for feature selection in order to pinpoint the important variables affecting results. …”
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Research review of digital modeling technologies with 3D spatial visualization for pipelines by Xin LIU, Shengwen TU, Yanfang HOU, Dong LIN, Jie SHU, Yu TANG

“…MethodsFrom the perspective of software and algorithm characteristics, this paper classifies visual modeling technologies for pipelines into three categories: 3D modeling software, secondary development based on existing components, and underlying development. …”
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Mobile direct-sequence spread-spectrum underwater acoustic communication based on improved differential energy detector by Peng-yu DU, Long-xiang GUO, Jing-wei YIN, Gang QIAO

“…A Doppler estimation method based on the structural features of spread spectrum signal was proposed,which could achieve real-time Doppler estimation for received spread spectrum signals by energy detecting the result of matching correlation calculation of adjacent received spreading symbols.In addition,this method made full use of the spread spectrum processing gain and could do Doppler estimation under low SNR condition.Improved differential energy detector was further proposed,which can effectively deal with the rapid carrier phase fluctuation interference caused by Doppler effect and time-varying multi-path interference by detecting the output energy of two correlators.Simulation verified the robustness of improved differential energy detector algorithm and the Doppler estimation method based on spread spectrum signal.At-sea data shows that improved differential energy detector combined with the proposed Doppler estimation method can achieve low bit error rate communication for direct-sequence spread spectrum underwater acoustic communication with large time-varying Doppler interference when SNR is −10 dB.…”
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Position Normalization of Propellant Grain Point Clouds by Junchao Wang, Fengnian Tian, Renfu Li, Zhihui Li, Bin Zhang, Xuelong Si

“…In the coarse normalization stage, a layer-by-layer feature points detection scheme based on k-dimensional trees (KD-tree) and k-means clustering (k-means) is designed to extract feature points from the propellant grain point cloud. …”
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Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models by Deok-Hee Kim-Dufor, Michel Walter, Marie-Odile Krebs, Yannis Haralambous, Philippe Lenca, Christophe Lemey, Christophe Lemey

“…IntroductionPeculiar use of language and even language deficits are one of the well-known signs of schizophrenia. Different language features analyzed using natural language processing and machine learning have been reported to differentiate patients at ultra-high risk for psychosis. …”
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