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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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
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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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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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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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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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The Advanced Role of Carbon Quantum Dots in Nano-Food Science: Applications, Bibliographic Analysis, Safety Concerns, and Perspectives by Abdul Majid, Khurshid Ahmad, Liju Tan, Waqas Niaz, Wang Na, Li Huiru, Jiangtao Wang

“…This article discussed the sources, fabrication methods, advantages, and limitations of CQDs as a sensing for the detection of food contaminants. …”
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Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

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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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A Method for Extracting Features of the Intrinsic Mode Function’s Energy Arrangement Entropy in the Shaft Frequency Electric Field of Vessels by Xiaoguang Ma, Zhaolong Sun, Runxiang Jiang, Xinquan Yue, Qi Liu

“…To address the challenge of detecting low-frequency electric field signals from vessels in complex marine environments, a vessel shaft frequency electric field feature extraction method based on intrinsic mode function energy arrangement entropy values is proposed, building upon a scaled model. …”
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An Ultrathin Optoelectronic Memristor with Dual‐Functional Photodetector and Optical Synapse Behaviors for Neuromorphic Vision by Lilan Zou, Junru An, Haonan Xu, Guizhen Wang, Shiwei Lin

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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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Thermonuclear Superburst of MAXI J1752−457 Observed with NinjaSat and MAXI by Amira Aoyama, Teruaki Enoto, Takuya Takahashi, Sota Watanabe, Tomoshi Takeda, Wataru Iwakiri, Kaede Yamasaki, Satoko Iwata, Naoyuki Ota, Arata Jujo, Toru Tamagawa, Tatehiro Mihara, Chin-Ping Hu, Akira Dohi, Nobuya Nishimura, Motoko Serino, Motoki Nakajima, Takao Kitaguchi, Yo Kato, Nobuyuki Kawai, (NinjaSat collaboration)

“…An uncatalogued bright X-ray transient was detected with MAXI on 2024 November 9, named MAXI J1752−457. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…The Industrial Internet of Things (IIoT) faces significant cybersecurity threats due to its ever-changing network structures, diverse data sources, and inherent uncertainties, making robust intrusion detection crucial. …”
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