Network security traffic detection and legal supervision based on adaptive metric learning algorithm by Liu Zhen

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App-DDoS detection method using partial binary tree based SVM algorithm by Bin ZHANG, Zihao LIU, Shuqin DONG, Lixun LI

“…As it ignored the detection of ramp-up and pulsing type of application layer DDoS (App-DDoS) attacks in existing flow-based App-DDoS detection methods,an effective detection method for multi-type App-DDoS was proposed.Firstly,in order to fast count the number of HTTP GET for users and further support the calculation of feature parameters applied in detection method,the indexes of source IP address in multiple time windows were constructed by the approach of Hash function.Then the feature parameters by combining SVM classifiers with the structure of partial binary tree were trained hierarchically,and the App-DDoS detection method was proposed with the idea of traversing binary tree and feedback learning to distinguish non-burst normal flow,burst normal flow and multi-type App-DDoS flows.The experimental results show that compared with the conventional SVM-based and naïve-Bayes-based detection methods,the proposed method has more excellent detection performance and can distinguish specific App-DDoS types through subdividing attack types and training detection model layer by layer.…”
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Design and investigation of charge plasma-based TMD heterojunction TFET biosensor for ultrasensitive detection by Monika Kumari, Niraj Kumar Singh, Vinay Kantipudi, Manodipan Sahoo

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Self-Powered Microsystem for Ultra-Fast Crash Detection via Prestressed Triboelectric Sensing by Yiqun Wang, Yuhan Wang, Xinzhi Liu, Xiaofeng Wang, Keren Dai, Zheng You

“…We further developed a self-powered, compact (<4.5 cm3) microsystem that integrates the shock sensor, a signal processing module, airbag triggering circuitry, and a high-g-resistant supercapacitor as a backup power source. The microsystem achieves ultra-fast shock detection and airbag activation with a delay of less than 0.2 ms. …”
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Comparison of genotyping assays for detection of targeted CRISPR/Cas mutagenesis in highly polyploid sugarcane by Eleanor J. Brant, Eleanor J. Brant, David May, David May, Ayman Eid, Ayman Eid, Fredy Altpeter, Fredy Altpeter

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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…Finally, the Variable Minimum Point Distance Intersection over Union (VMPDIoU) loss is proposed to optimize the model’s loss function. This method employs variable input parameters to directly calculate key point distances between predicted and ground-truth boxes, more accurately reflecting positional differences between detection results and reference targets, thus effectively improving the model’s mean Average Precision (mAP). …”
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A diagnosis method based on graph neural networks embedded with multirelationships of intrinsic mode functions for multiple mechanical faults by Bin Wang, Manyi Wang, Yadong Xu, Liangkuan Wang, Shiyu Chen, Xuanshi Chen

“…Additionally, a graph-level based fault diagnosis network model is designed to enhance feature learning capabilities for graph samples and enable flexible application across diverse signal sources and devices. Experimental validation with datasets including independent vibration signals for gear fault detection, mixed vibration signals for concurrent gear and bearing faults, and pressure signals for hydraulic cylinder leakage characterization demonstrates the model's adaptability and superior diagnostic accuracy across various types of signals and mechanical systems.…”
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Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning by Ali Altalbe

“…To address this problem, machine learning (ML) based intrusion detection systems (IDSs) have been proposed. However, existing IDSs suffer from low detection accuracy, limited real-time response, and high resource requirements. …”
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Development and validation of microwave-assisted extraction for phenolic compound profiling in diverse oyster mushrooms (Pleurotus spp.) sourced from various geographical regions by M Umar Harun, Miguel Palma, Widiastuti Setyaningsih

“…Seven phenolic compounds—p-coumaric acid, t-cinnamic acid, p-hydroxybenzaldehyde, p-hydroxybenzoic acid, quercetin-3-glucoside, gallic acid, and vanillic acid—were effectively extracted and quantified using ultra-performance liquid chromatography with photodiode array detection. Application of this method across oyster mushroom samples from different geographical sources revealed significant variation in phenolic compound concentrations, with Pleurotus pulmonarius exhibiting the highest level of gallic acid at 433.90 ± 7.77 μg g−1 (DM) and Pleurotus ostreatus var. …”
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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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The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review by Khadiza Tun Suha, Hugh Lubenow, Stefania Soria-Zurita, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

“…We envision that, through the combination of tele-echocardiography and AI, low-resource medical facilities may gain access to the effective detection of CHD at the prenatal stage.…”
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Spatiotemporal differences induced changes in the structure and function of the gut microbiota in an endangered ungulate by Xiaofan Ma, Xiaoyu Hu, Kai Liu, Wei Wang, Wei Jia, Huayao Gao, Ming Lu, Jie Liu, Yunfeng Chen, Yingjie Ma, Yumei Li, Yonggang Nie

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Two-photon excitation fluorescence in ophthalmology: safety and improved imaging for functional diagnostics by Vineeta Kaushik, Michał Dąbrowski, Michał Dąbrowski, Luca Gessa, Nelam Kumar, Humberto Fernandes

“…Recent advances in laser-source manufacturing have made it possible to minimize the exposure of in vivo measurements within safety, while achieving sufficient signals to detect for functional images, making TPEF a viable option for human application. …”
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Analysis of physicochemical, functional, and antioxidant properties of four different Indian seaweed species by Radheshyam B. Bajad, Meenatai G. Kamble, Sumit R. Gawai, Irshaan Syed, Mrinmoy Roy

“…Thus, the selected four marine seaweeds act as a good source of functional components and can be utilized for the development of functional food products such as bread, biscuits, cookies, tea, snacks, soups and beverages.…”
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Evaluation of the retinal morphological and functional findings in optic neuritis related to multiple sclerosis by Katanić-Pasovski Katarina, Rančić Nemanja, Pasovski Viktor, Sajić Marija, Resan Mirko, Dinčić Evica

“…The aim of the study was to determine the diagnostic and prognostic value of structural and functional examination using novel ‘swept-source’ optical coherence tomography (SS-OCT) and OCT angiography (OCTA) techniques in patients with MS who experienced RBN. …”
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Advancements in Nanostructured Functional Constituent Materials for Gas Sensing Applications: A Comprehensive Review by Ivana Panžić, Arijeta Bafti, Floren Radovanović-Perić, Davor Gašparić, Zhen Shi, Arie Borenstein, Vilko Mandić

“…High-end detection values may reach around a few ppb for most gases. …”
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Conscious and unconscious perception of pitch shifts in auditory feedback during vocalization: Behavioral functions and event-related potential correlates by Daniel Suchý, Roozbeh Behroozmand, Henry Railo

“…Source localization of the ERPs suggested that conscious pitch shift detection was associated with increased neural activity within the temporal, frontal and parietal cortical networks known to be involved in speech motor control. …”
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Energy-Efficiency using Critical Nodes Detection Problem in Industrial Wireless Sensor Networks (IWSNs) by Karima MOULEY, Mohamed Amin TAHRAOUI, Abdelaziz KELLA

“…Experiments simulation validates our proposed approach, approving its efficiency in reducing significant energy consumption while preserving connectivity and functionality for industrial systems. Furthermore, the results highlight the potential of using critical node analysis to support sustainable and efficient operations in resource-constrained industrial environments. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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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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