Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

“…An SCR case study for brown tree snakes showed identical estimates of density and σ under models accounting for or ignoring temporal variation in detection. …”
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First molecular detection of Eimeria spp. in domestic goats from Java Island, Indonesia by Dias Aprita Dewi, Yudhi Ratna Nugraheni, Aan Awaludin, Vika Ichsania Ninditya, Dwi Priyowidodo, Raden Wisnu Nurcahyo, Fitrine Ekawasti, Joko Prastowo

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Molecular characterization of VP1 gene during the foot and mouth disease virus outbreak in East Java, Indonesia, in 2022 by Zayyin Dinana, Suwarno Suwarno, Imam Mustofa, Jola Rahmahani, Kusnoto Kusnoto, Aussie Tahta Maharani, Anisa Lailatul Fitria, Adiana Mutamsari Witaningrum, Firdausy Kurnia Maulana, Nur Saidah Said, Deka Uli Fahrodi, Fedik Abdul Rantam

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Development of a Multiplex RT-PCR for the Simultaneous Detection of Five Viruses and Viroids in Peach by Jeong-Eun Kim, Boram Kwon, Eun Jung Heo, Eunhae Baek, Gahyun Son, Hyun Joo Shin

“…A multiplex reverse transcription-polymerase chain reaction (mRT-PCR) assay was developed for the simultaneous detection of three viruses and two viroids infecting peach trees, including apple chlorotic leaf spot virus, plum bark necrosis stem pitting-associated virus, peach-associated luteovirus, peach latent mosaic viroid, and hop stunt viroid, which have been reported in peach trees in Korea. …”
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ACCDW-YOLO: an effective detection method for small-sized pests and diseases in navel oranges by Kai Wang, Youliang Chen, Hanzheng Sun

“…The incorporation of the DCNv3 module into the design creates the DCNv3-E-ELAN module, which enhances the model’s proficiency in detecting objects of varying sizes. The Wise Intersection over Union version 3 (WIoUv3) loss function was used to reduce the competitiveness of high-quality anchor boxes, reduce the harmful gradients generated by low-quality samples, and improve the overall performance of the model. …”
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Comparing Classification Algorithms to Recognize Selected Gestures Based on Microsoft Azure Kinect Joint Data by Marc Funken, Thomas Hanne

“…The compared models performed well on the recorded sample data, with the recurrent neural networks outperforming feedforward neural networks and decision trees on the captured motions. …”
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Obtaining the Highest Quality from a Low-Cost Mobile Scanner: A Comparison of Several Pipelines with a New Scanning Device by Marek Hrdina, Juan Alberto Molina-Valero, Karel Kuželka, Shinichi Tatsumi, Keiji Yamaguchi, Zlatica Melichová, Martin Mokroš, Peter Surový

“…The tested low-cost device produced moderate results, achieving a tree detection rate of up to 78% and a relative root mean square error (rRMSE) of 19.7% in diameter at breast height (DBH) estimation. …”
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The application of deep learning technology in smart agriculture: Lightweight apple leaf disease detection model by Luo Man

“…Current models for disease detection in fruit tree leaves suffer from limitations such as low recognition precision, high frequencies of missed and false detections. …”
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Utilization of Stockwell Transform and Random Forest Algorithm for Efficient Detection and Classification of Power Quality Disturbances by T. Ravi, K. Sathish Kumar, C. Dhanamjayulu, Baseem Khan

“…Each training set is used to construct a decision tree by recursively partitioning the data based on significant features. …”
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Skeletal Muscle Ultrasound Radiomics and Machine Learning for the Earlier Detection of Type 2 Diabetes Mellitus by Sameed Khan, Chad L. Klochko, Sydney Cooper, Brendan Franz, Lauren Wolf, Adam Alessio, Steven B. Soliman

“…Background: Studies have demonstrated that a qualitatively and quantitatively assessed hyperechoic deltoid muscle on ultrasound (US) was accurate for the earlier detection of type 2 diabetes (T2D). We aim to demonstrate the utility of automated skeletal muscle US radiomics and machine learning for the earlier detection of T2D and prediabetes (PreD) as a supplement to traditional hemoglobin A1c (HbA1c) testing. …”
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Secure sensitive data deduplication schemes based on deterministic/probabilistic proof of file ownership by Yue CHEN, Chao-ling LI, Ju-long LAN, Kai-chun JIN, Zhong-hui WANG

“…To solve the difficult problems of sensitive data deduplication in cloud storage,such as detection and PoW (proofs of ownership) of the duplicated ciphertext,the attacks aiming at data sensitivity,etc,a Merkle hash tree based scheme called MHT-Dedup and a homomorphic MAC based scheme called hMAC-Dedup were proposed.Both schemes provided PoW of the ciphertext file to find duplicated files on cross-user file level and check the hash of block plaintext to find duplicated blocks on local block-level,which avoided the security flaws of the hash-as-a-proof method in the cross-user file-level client-side duplication detection.MHT-Dedup provided the deterministic PoW of file with an authen-ticating binary tree generated from the tags of encrypted blocks,which had lower computing and transferring cost,and hMAC-Dedup provided the probabilistic PoW of file by verifying some sampled blocks and their homomorphic MAC tags,which had lower additional storage cost.Analyses and comparisons show that proposed schemes are preferable in many as-pects such as supporting secure two-level client-side sensitive data deduplication and resisting to brute force attack to blocks.…”
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Fusarium Wilt of Banana Latency and Onset Detection Based on Visible/Near Infrared Spectral Technology by Cuiling Li, Dandan Xiang, Shuo Yang, Xiu Wang, Chunyu Li

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Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…Abstract This study presents a comprehensive approach to predicting solubility of recombinant protein in four E. coli samples by employing machine learning techniques and optimization algorithms. …”
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Improving performance of defect detection by setting skewed tolerance and joint tolerances in crimp force monitor by Liancheng Zeng, Dali Qin

“…Abstract A Crimp Force Monitor (CFM) detects defects by whether the crimp force curve of the force sensor exceeds the set tolerance, with the goal of low defect miss rate and false alarm rate. …”
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A novel approach based on XGBoost classifier and Bayesian optimization for credit card fraud detection by Mohammed Tayebi, Said El Kafhali

“…Researchers have explored a lot of machine learning classifiers, such as random forest, decision tree, support vector machine, logistic regression, artificial neural network, and recurrent neural network, to secure these systems. …”
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Detection and Genetic Analysis of Songling Virus in Haemaphysalis concinna near the China-North Korea Border by De Li, Jixu Li, Ruichen Wang, Weijia Zhang, Kai Nie, Qikai Yin, Shihong Fu, Qianqian Cui, Songtao Xu, Fan Li, Xingzhou Li, Huanyu Wang

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Evaluating war-induced damage to agricultural land in the Gaza Strip since October 2023 using PlanetScope and SkySat imagery by He Yin, Lina Eklund, Dimah Habash, Mazin B. Qumsiyeh, Jamon Van Den Hoek

“…We performed accuracy assessments on a generated tree crop fields damage map using 1,200 randomly sampled 3 × 3-m areas, and we generated error-adjusted area estimates with a 95% confidence interval. …”
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Change Detection Based on Image Standardization and Improved Residual Network for Single-Polarization SAR Images by Mengmeng Wang, Jixian Zhang, Guoman Huang, Lijun Lu, Fenfen Hua

“…Deep-learning-based change detection (CD) methods have become an important means of synthetic aperture radar (SAR) images to identify changes. …”
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An FPGA Prototype for Parkinson’s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

“…This paper proposes an efficient machine learning model for PD detection using voice-based features, which offer a non-invasive, cost-effective, and accessible alternative to complex imaging methods. …”
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An AutoEncoder enhanced light gradient boosting machine method for credit card fraud detection by Lianhong Ding, Luqi Liu, Yangchuan Wang, Peng Shi, Jianye Yu

“…This paper proposes an AutoEncoder enhanced LightGBM method for credit card detection. The method inherits the advantages of each component, using an AutoEncoder for feature reconstruction on the dataset, and integrating the LightGBM algorithm for improving the GBDT (Gradient Boosting Decison Tree) to detect abnormal data more accurately and efficiently. …”
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