Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading by Katarzyna PANASIUK, Krzysztof DUDZIK, Grzegorz HAJDUKIEWICZ

“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
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DNA-Based Nanobiosensor for the Colorimetric Detection of Dengue Virus Serotype 2 Synthetic Target Oligonucleotide by Michael Sandino C. Flores, Evangelyn C. Alocilja, Divina M. Amalin, Mae Joanne B. Aguila, Marynold V. Purificacion, Florinia E. Merca, Ma. Carmina C. Manuel, Mark Pierre S. Dimamay, Ma. Anita M. Bautista, Lilia M. Fernando

“…Being a developing country, most of the high-risk areas in the Philippines are resource-limited and cannot afford equipment for detection and monitoring. …”
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YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping by Huijiao Yu, Xuehui Zhang, Jun Yan, Xianyong Meng

“…The Focaler-IoU loss function is employed to improve keypoint localization accuracy. …”
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From fish to fiber: 3D-nanoprinted optical neuromast for multi-integrated underwater detection by Liangye Li, Xuhao Fan, Geng Chen, Yueqi Liu, Fujun Zhang, Zhuolin Chen, Zhi Zhang, Wangyang Xu, Shixiong Zhang, Yuncheng Liu, Zongjing Li, Hui Gao, Zhijun Yan, Wei Xiong, Qizhen Sun

“…Abstract Fish possess high sensitivity to acoustic, vibrational, and hydrodynamic stimuli through unique sensing cells, providing unparalleled paradigms for developing underwater detection methods. However, artificial perception devices face challenges in replicating comparable sensitivity and multi-dimensional integration of fish in function and scale. …”
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Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

“…Although various technologies with wearables and vision systems that utilize artificial intelligence (AI) have been developed to detect falls, many AI models are complex and resource-intensive. …”
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LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning by Xu Liu, Yuewen Liu, Miaomiao Wei, Peng Xu

“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
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Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
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Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture by Bekir Eray Katı, Ecir Uğur Küçüksille, Güncel Sarıman

“…The model’s performance was compared with other methods evaluated on the DFDC dataset, highlighting its efficiency in resource utilization and overall effectiveness. The findings reveal that the proposed QTL-CaiT-based system provides a strong foundation for deepfake detection and contributes significantly to the academic literature. …”
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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

“…The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. …”
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Automated Artery Detection and Stenosis Classification in CTA Using Deep Learning for Peripheral Arterial Disease by Ali M. O. A. Anwer, Hacer Karacan, Muhammed Rabee, Levent Enver, Gonca Cabuk

“…We use Faster R-CNN with a ResNet-101 backbone driven by a custom loss function to achieve good artery localization and reduce false positives. …”
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Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices by Hikaru Sugimoto, Ken-ichi Hironaka, Tomoaki Nakamura, Tomoko Yamada, Hiroshi Miura, Natsu Otowa-Suematsu, Masashi Fujii, Yushi Hirota, Kazuhiko Sakaguchi, Wataru Ogawa, Shinya Kuroda

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GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

“…It provides an invaluable resource for developing machine learning models aimed at the automatic diagnosis, classification, and detection of GERD and polyps, potentially improving the speed and accuracy of clinical decision-making. …”
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Deception mechanisms of FDA‒AWACS against passive monopulse angle measurements by Bo Wang, Gang Wang, Yonglin Li, Rennong Yang, Yu Zhao

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Survey of gut microbial biogeography and their functional niche in the grow-finishing swine of ordinary feeding by Lili Cao, Lili Cao, Wei Guo, Shiyu Yang, Shiyu Yang, Anum Ali Ahmad, Yuntao Dong, Cen Gong, Shuoqi Wang, Xuemin Yang, Zhentao Cheng, Zhihong Yan, Zhihong Yan, Weiwei Wang

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A Heterogeneity-Aware Semi-Decentralized Model for a Lightweight Intrusion Detection System for IoT Networks Based on Federated Learning and BiLSTM by Shuroog Alsaleh, Mohamed El Bachir Menai, Saad Al-Ahmadi

“…Most IoT devices have limited resource capabilities (e.g., memory capacity, processing power, and energy consumption) to function as conventional intrusion detection systems (IDSs). …”
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Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium by Sandra Hoyek, Eleni Konstantinou, Francesco Romano, Darren Chen, Celine Chaaya, Magdalena G. Krzystolik, Daniel Hu, Rachel Huckfeldt, Demetrios G. Vavvas, Leo A. Kim, Jason Lee, Elise De, John B. Miller, Nimesh A. Patel

“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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Enhancing Human Detection in Occlusion-Heavy Disaster Scenarios: A Visibility-Enhanced DINO (VE-DINO) Model with Reassembled Occlusion Dataset by Zi-An Zhao, Shidan Wang, Min-Xin Chen, Ye-Jiao Mao, Andy Chi-Ho Chan, Derek Ka-Hei Lai, Duo Wai-Chi Wong, James Chung-Wai Cheung

“…VE-DINO enhances detection accuracy by incorporating body part key point information and employing a specialized loss function. …”
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Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

“…Compared to various lightweight architectures and advanced detection models, this method demonstrates excellent accuracy, lower computational costs, and better real-time performance, providing a feasible coal mine pedestrian-vehicle detection method for resource-constrained coal mine scenarios, meeting the deployment requirements of coal mine video surveillance and enabling real-time alerts for intelligent inspection of coal mine pedestrian-vehicles.…”
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Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

“…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
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