Applying Grey Relational Analysis to Detect Change Points in Time Series by Yi-Chung Hu, Shu-hen Chiang, Yu-Jing Chiu

“…The goal of detecting change points is to recognize abrupt changes in time series data. …”
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Linear and Nonlinear Damage Detection Using a Scanning Laser Vibrometer by Steve Vanlanduit, Patrick Guillaume, Johan Schoukens, Eli Parloo

“…Unfortunately, the use of linear damage detection features, as for instance FRFs or modal parameters, does not always lead to a successful identification of the damage location. …”
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Detecting ROM changes using KINOVEA after muscle decontracture technique by Popa Vlad, Sandor Iosif, Ciocoi-Pop Dumitru Rareș

“…After assessing the mobility of the cervical region in a longitudinal axistwice,we used paired T tests to check in every instance what the statistical significance would be.We can conclude that Kinovea was in fact a software that could easily detect ROM alteration. …”
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Double balloon enteroscopy in the detection and removal of jejunal anisakiasis: Case report by Erika Abe, Tsukasa Ishida, Tatsuya Osuga, Saori Kakuyama, Hirofumi Ogawa, Katsutoshi Nabeshima

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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…Aiming at the problems of large workload and low intelligence of the current infrared image-based overheating defect detection techniques for composite insulators, and the poor accuracy and poor generalization performance of the traditional image segmentation methods in complex backgrounds, an overheating defect detection method is proposed for composite insulators based on instance segmentation network Mask R-CNN. …”
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A Hardware-Aware Failure-Detection Method for GPU Control-Logic by Hiroaki Itsuji, Takumi Uezono, Tadanobu Toba, Kojiro Ito, Masanori Hashimoto

“…This paper assumes three types of control-logic failures for a general GPU architecture and proposes efficient failure detection methods for each type. For instance, the proposed method efficiently detects GPU-specific control-logic failures caused by program counter faults with a detection rate of 99.5% and can be implemented with a runtime overhead of 5.3% and a memory-resource overhead of 4.2% for a matrix multiplication application. …”
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Deformability-Based Grasp Pose Detection From a Visible Image by Koshi Makihara, Yukiyasu Domae, Ryo Hanai, Ixchel G. Ramirez-Alpizar, Hirokatsu Kataoka, Kensuke Harada

“…Unlike previous approaches that synthesize the entire image in one step and struggle with accuracy in complex scenarios, such as cluttered environments with multiple objects, our method advances the field by employing an encoder-decoder model for simultaneous deformability estimation and instance segmentation from depth images, as well as by enhancing grasp pose detection for deformable objects under specific conditions using the outcomes of our deformability assessments. …”
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Online Machine Learning for Intrusion Detection in Electric Vehicle Charging Systems by Fazliddin Makhmudov, Dusmurod Kilichev, Ulugbek Giyosov, Farkhod Akhmedov

“…Electric vehicle (EV) charging systems are now integral to smart grids, increasing the need for robust and scalable cyberattack detection. This study presents an online intrusion detection system that leverages an Adaptive Random Forest classifier with Adaptive Windowing drift detection to identify real-time and evolving threats in EV charging infrastructures. …”
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Handling Class Imbalanced Data in Sarcasm Detection with Ensemble Oversampling Techniques by Ya-Han Hu, Ting-Hsuan Liu, Chih-Fong Tsai, Yu-Jung Lin

“…We work with two imbalanced sarcasm detection datasets, iSarcasmEval and SARC-reduced, collected from Twitter and Reddit. …”
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An Adapter and Segmentation Network-Based Approach for Automated Atmospheric Front Detection by Xinya Ding, Xuan Peng, Yanguang Xue, Liang Zhang, Tianying Wang, Yunpeng Zhang

“…This study presents AD-MRCNN, an advanced deep learning framework for automated atmospheric front detection that addresses two critical limitations in existing methods. …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Abstract The ever-growing number of complex cyber attacks requires the need for high-level intrusion detection systems (IDS). While the available research deals with traditional, hybrid, and ensemble methods for network data analysis, serious challenges are still being met in terms of producing robust and highly accurate detection systems. …”
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Evaluating knowledge fusion models on detecting adverse drug events in text. by Philipp Wegner, Holger Fröhlich, Sumit Madan

“…Detecting adverse drug events (ADE) of drugs that are already available on the market is an essential part of the pharmacovigilance work conducted by both medical regulatory bodies and the pharmaceutical industry. …”
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YOLO deep learning algorithm for object detection in agriculture: a review by Kamalesh Kanna S, Kumaraperumal Ramalingam, Pazhanivelan P, Jagadeeswaran R, Prabu P.C.

“… YOLO represents the one-stage object detection also called regression-based object detection. …”
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Improving Moving Insect Detection with Difference of Features Maps in YOLO Architecture by Angel Gomez-Canales, Javier Gomez-Avila, Jesus Hernandez-Barragan, Carlos Lopez-Franco, Carlos Villaseñor, Nancy Arana-Daniel

“…Insect detection under real-field conditions remains a challenging task due to factors such as lighting variations and the small size of insects that often lack sufficient visual features for reliable identification by deep learning models. …”
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Plasma metabolite biomarker identification study for the early detection of gastric cancer by Juan Zhu, Yida Huang, Bin Liu, Xue Li, Li Yuan, Le Wang, Kun Qian, Yingying Mao, Lingbin Du, Xiangdong Cheng

“…Background: Gastric cancer (GC) is the fifth most prevalent and the fifth deadliest cancer worldwide, and timely diagnosis of GC contributes to an increased survival rate. However, current detection methods for GC mainly rely on gastroscopy examination, limited by relatively low compliance. …”
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Novel shortcut strategies in copositivity detection: Decomposition for quicker positive certificates by Johannes Zischg, Immanuel Bomze

“…First empirical results on carefully orchestrated randomly generated instances seem to corroborate our approach.…”
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Leveraging Bias in Pre-trained Word Embeddings for Unsupervised Microaggression Detection by Tolúlọpẹ́ Ògúnrẹ̀mí, Valerio Basile, Tommaso Caselli

“…The algorithm relies on pre-trained word-embeddings, leveraging the bias encoded in the model in order to detect microaggressions in unseen textual instances. …”
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Concept Drift Detection in Data Stream Mining : A literature review by Supriya Agrahari, Anil Kumar Singh

“…Classifier classifies incoming instances using past training instances of the data stream. …”
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Detecting the Limitations of Performance: Performance Art as a Neo-Shamanistic Ritual by Elif Dastarlı, İlkay Canan Okkalı

“…Whilst numerous instances of performance art since the 1960s have propelled it into the realm of contemporary expression, articulating a precise academic definition for this art form rooted in its actions rather than in how the art is performed proves challenging. …”
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Fraud Detection and Providing Mitigation Solutions in Iran Health Insurance Organization by Milad Mehri, Mohammad Efatpanah, Ebrahim Jaafaripooyan, Mohammad Arab

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