Predictions for the Detectability of Milky Way Satellite Galaxies and Outer-Halo Star Clusters with the Vera C. Rubin Observatory by Kabelo Tsiane, Sidney Mau, Alex Drlica-Wagner, Jeffrey L. Carlin, Peter S. Ferguson, Keith Bechtol, Ethan O. Nadler, Annika H. G. Peter, Yao-Yuan Mao, Adam J. Thornton, LSST Dark Energy Science Collaboration

“…When assuming perfect star/galaxy classification and a model for the galaxy-halo connection fit to current data, we predict that 89 +/- 20 Milky Way satellite galaxies will be detectable with a simple matched-filter algorithm applied to the LSST wide-fast-deep data set. …”
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Multi-Scale Feature Fusion GANomaly with Dilated Neighborhood Attention for Oil and Gas Pipeline Sound Anomaly Detection by Yizhuo Zhang, Zhengfeng Sun, Shen Shi, Huiling Yu

“…Anomaly detection in oil and gas pipelines based on acoustic signals currently faces challenges, including limited anomalous samples, varying audio data distributions across different operating conditions, and interference from background noise. …”
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What makes a microsaccade? A review of 70 years research prompts a new detection method by Anna-Katharina Hauperich, Laura K. Young, Hannah E. Smithson

“…Our new microsaccade detection method is easy to implement and intuitive to understand, and affords researchers flexibility in adjusting it to their experimental set-up.…”
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Classification and analysis of quantitative and qualitative variables in fluoride monitoring data collected from animal feed products by Andrea Trossi, Paola Brizio, Maria Leogrande, Caterina Stella, Chiara Marchese, Giulia Mastellone, Maria Cesarina Abete, Stefania Squadrone

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Assessing geographic polarisation in Britain’s digital landscape through stable dynamic embedding of spatial web data by Emerald Dilworth, Emmanouil Tranos, Daniel J. Lawson

“…We show how the methodology can be made robust to the problems of large-scale real-world data, used to detect changes over time, and identify their characteristics. …”
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Bayesian identification of differentially expressed isoforms using a novel joint model of RNA-seq data. by Xu Shi, Xiao Wang, Lu Jin, Leena Halakivi-Clarke, Robert Clarke, Andrew F Neuwald, Jianhua Xuan

“…We applied the approach to breast cancer RNA-seq data and uncovered a unique set of isoforms that form key pathways associated with breast cancer recurrence. …”
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Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network by Gang Zhao, Changyu Han, Zhongxiang Yu, Zhipan Li, Guoao Yu, Hongmei Zhang, Dadong Zhao, Zhengyi Jiang

“…The pressed rigging defect data set is constructed, and the region of broken wire defect and stress in the image is calibrated. …”
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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…This study aims to identify non-invasive biomarkers for detecting bronchogenic carcinoma and its various stages by analyzing gene expression data using bioinformatics and machine learning techniques. …”
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Detection of the origin of wolfberry based on electronic nose and electronic tongue combined with LSTM-AM-M1DCNN by MA Zeliang, LIU Yaqian, CHENG Qifeng, WANG Pingping, YANG Tianxing, DU Gang

“…First, an electronic nose and tongue were used to detect wolfberries from five different origins. Then, the collected data were fused, and finally, the LSTM-AM-M1DCNN was employed to classify and discriminate the fused data.ResultsCompared with traditional LSTM and CNN methods, the LSTM-AM-M1DCNN effectively extracted deep feature information from the electronic tongue and nose signals. …”
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Exploring home-based reminder systems for daily routine support: usability, data insights, and future directions by Alyssia A. Sanchez, Joy Lai, Alexander Tighe, Alex Mihailidis

“…Methods: Data were collected by logging reminder interactions from two dyads of PLwDs and caregivers to assess system usability in real-world settings. …”
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Improving Multi-Label Emotion Classification on Imbalanced Social Media Data With BERT and Clipped Asymmetric Loss by Sandhya Ramakrishnan, L. D. Dhinesh Babu

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GSD-YOLO: A Lightweight Decoupled Wheat Scab Spore Detection Network Based on Yolov7-Tiny by Dongyan Zhang, Wenfeng Tao, Tao Cheng, Xingen Zhou, Gensheng Hu, Hongbo Qiao, Wei Guo, Ziheng Wang, Chunyan Gu

“…In addition, we utilize an improved Spore–Copy data augmentation strategy to improve the detection performance and generalization ability of the algorithm to fit the large numbers, morphology, and variety of wheat disease spores in the actual field and to improve the efficiency of constructing a large data set of diverse spores. …”
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An innovative full-size pathogenic tandem duplication mutation precise detection system based on next-generation sequencing by Li-Li Zhang, Zhe Wang, Ying Zhou, Dai-Yang Li, Xiao-Nian Tu, Yu-Xia Li, Ke-Ming Du, Zhong-Zheng Zheng

“…During performance validation, the lower detection limit was set to a parameter close to capillary electrophoresis (“gold standard”) by adjusting reference values (sensitivity 3–5%). …”
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The "Low Slow and Small" UAV target detection and tracking algorithm based on improved YOLOv7 and DeepSort by JIAN Yuhong, YANG Huiyue, WANG Xinggang, RONG Yisheng, ZHU Yukun

“…A "low slow small" human-machine data set is constructed with four types of backgrounds: sky, trees, buildings, and dark conditions. …”
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Improved Iterative CD-Spline Approach for Building Boundary Regularization Using Airborne LiDAR Data by Renato Cesar dos Santos, Ayman F. Habib, Mauricio Galo

“…In the ICDS strategy, CPs are detected using Douglas–Peucker algorithm followed by an angle-based constraint; then, a single set of CPs is used in a regularization process, not being possible to guarantee that the derived result corresponds to the best contour model. …”
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ZFD-Net: Zinc flower defect detection model of galvanized steel surface based on improved YOLOV5. by Yang Gao, Hanquan Zhang, Lifu Zhu, Feitong Xie, Dong Xiao

“…ZFD-Net is compared with state-of-the-art (SOTA) methods on the self-built data set, and its performance indicators are better than all methods.…”
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The probability of detecting host-specific microbial source tracking markers in surface waters was strongly associated with method and season by Claire M. Murphy, Daniel L. Weller, Tanzy M. T. Love, Michelle D. Danyluk, Laura K. Strawn

“…To understand how to best employ MST marker data for managing fecal contamination risks, the present study compiled previously collected MST marker data (N = 12,878 samples) from across North America; each sample in the data set had been tested for fecal contamination from one or more of five sources (avian, canine, human, ruminant, swine). …”
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From pixels to letters: A high-accuracy CPU-real-time American Sign Language detection pipeline by Jonas Rheiner, Daniel Kerger, Matthias Drüppel

“…For this we calculate accuracy as a function of validation set size, and thus ensure sufficient data is allocated for evaluation. …”
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Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data by Ailing Zhang, Haobo Zhang

“…The best-performing model achieved an accuracy of 0.85 and an AUC of 0.80, highlighting the potential of combining sMRI and rs-fMRI features with ML for early depression detection while revealing the potential of overfitting in small-sample and high-dimensional settings. …”
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Integrating human biomonitoring exposure data into a primary care morbidity database: a feasibility study by Pieter Jansen, Elly Den Hond, Katleen De Brouwere, Endale Alemayehu Ali, Hamid Yimam Hassen, Ilona Gabaret, Gijs Van Pottelbergh

“…Aim We assessed the feasibility of linking exposure data from HBM programs to health outcomes from the Intego registry, which collects data from general practitioners’ electronic health records. …”
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