Enhancing Cybersecurity Through Fusion of Optimization With Deep Wavelet Neural Networks on Denial of Wallet Attack Detection in Serverless Computing by P. Renukadevi, Sibi Amaran, A. Vikram, T. Prabhakara Rao, Mohamad Khairi Ishak

“…Deep learning (DL) models show strong potential in detecting DoW attacks, where attackers disrupt services by exploiting system resources. …”
Get full text

RE-YOLO: An apple picking detection algorithm fusing receptive-field attention convolution and efficient multi-scale attention. by Jinxue Sui, Li Liu, Zuoxun Wang, Li Yang

“…The accuracy of current apple picking detection algorithms is still limited when the distribution is dense and occlusion exists, and there is a significant challenge in deploying current high accuracy detection models on edge devices with limited computational resources. …”
Get full text

Detection of power theft in sensitive stations based on generalized robust distance metric and multi-classification support vector machine by Wei Zhang, Qiong Cao, Shuai Yang, Hao Guo

“…Through training and optimization, the support vector machine outputs the detection results of electricity stealing behavior according to the decision function, and realizes the accurate detection of electricity stealing behavior. …”
Get full text

Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection by Yang Tian, Lisa Kelso, Yiting Xiao, Chaitanya Pallerla, Ramesh Bist, Siavash Mahmoudi, Ziyu Liu, Haizheng Xiong, Jeyam Subbiah, Terry Howell, Dongyi Wang

“…By enabling timely and accurate detection of contaminants, this technology has the potential to significantly impact public health by reducing the incidence of foodborne illnesses, safeguarding environmental resources, and enhancing overall safety and health outcomes.…”
Get full text

Redox-active sp2-c connected metal covalent organic frameworks for selective detection and reductive separation of uranium by Jin-Lan Liu, Zhi-Hai Peng, Jia-Xin Qi, Cheng-Rong Zhang, Zhen-Wen Zhang, Li Zhang, Ru-Ping Liang, Jian-Ding Qiu

Get full text

Exploratory integration of near-infrared spectroscopy with clinical data: a machine learning approach for HCV detection in serum samples by Eloy Pérez-Gómez, José Gómez, José Gómez, Jennifer Gonzalo, Sergio Salgüero, Daniel Riado, María Luisa Casas, María Luisa Gutiérrez, Elena Jaime, Enrique Pérez-Martínez, Rafael García-Carretero, Javier Ramos, Conrado Fernández-Rodríguez, Conrado Fernández-Rodríguez, Myriam Catalá, Myriam Catalá, Luca Martino, Óscar Barquero-Pérez

“…Feature importance analysis highlighted specific wavelengths near 1,150 nm, 1,410 nm, and 1,927 nm, associated with water molecular states and liver function biomarkers (GPT, GOT, GGT), reinforcing the biological relevance of this approach.ConclusionsThese findings suggest that integrating NIRS and clinical data through machine learning enhances HCV diagnostic capabilities, offering a scalable and non-invasive alternative for early detection and risk assessment.…”
Get full text

Relationship between early neurological function and motor skills in Brazilian preterm infants: a cross-sectional study by Wendy Gabrielle Franca de Sousa, Ana Luiza Righetto Greco, Maja de Medeiros, Alicia Jane Spittle, Cibelle Kayenne Roberto Formiga

“…Thus, monitoring their development is needed for early detection and targeted intervention. This study aimed to assess the correlation between neurological function and motor skills in preterm infants from 2 to 6 months of corrected age after hospital discharge in an outpatient follow-up program. …”
Get full text

Karbon dots (C-dots) dari Bahan Hayati untuk Deteksi Logam Berat by Cut Navita Rahmi, Sri Sugiarti, Alvian Dea Yuliani

“…This study aims to review carbon nanoparticles derived from natural sources for detecting heavy metals. C-dots derived from biological sources have been widely studied as selective heavy metal detection. …”
Get full text

Turning Waste into Treasure: Functionalized Biomass‐Derived Carbon Dots for Superselective Visualization and Eradication of Gram‐Positive Bacteria by Ke‐Fei Xu, Zihao Wang, Macheng Cui, Yuhan Jiang, Chengcheng Li, Zi‐Xi Wang, Ling‐Yi Li, Chenyang Jia, Lijie Zhang, Fu‐Gen Wu

Get full text

A deep learning based intrusion detection system for CAN vehicle based on combination of triple attention mechanism and GGO algorithm by Hongwei Yang, Mehdi Effatparvar

“…Within the initial phase, the major features have been extracted, and TAN functions as a descriptor of feature. Then, the discriminating categorizer classifies the current features. …”
Get full text

Upper Elevational Limit of Vegetation in the Himalayas Identified from Landsat Images by Bo Wei, Yili Zhang, Linshan Liu, Binghua Zhang, Dianqing Gong, Changjun Gu, Lanhui Li, Basanta Paudel

Get full text

Omics Multi-Layers Networks Provide Novel Mechanistic and Functional Insights Into Fat Storage and Lipid Metabolism in Poultry by Farzad Ghafouri, Abolfazl Bahrami, Abolfazl Bahrami, Mostafa Sadeghi, Seyed Reza Miraei-Ashtiani, Maryam Bakherad, Herman W. Barkema, Samantha Larose

Get full text

Unveiling the Spatial Variation in Ecosystem Services Interactions and Their Drivers Within the National Key Ecological Function Zones, China by Tingjing Zhang, Quanqin Shao, Haibo Huang

Get full text

Bio-nanoparticles sensor couple with smartphone digital image colorimetry and dispersive liquid–liquid microextraction for aflatoxin B1 detection by Mahsa Alikord, Nabi Shariatifar, Mammad Saraji, Hedayat Hosseini, Gholamreza Jahed Khaniki, Shahram Shoeibi, Toba Rezazadeh, Mohammad Fazeli

“…Abstract A novel nanobiosensor-based colorimetric method was developed by integrating ZnO nanoparticles functionalized with curcumin, dispersive liquid–liquid microextraction (DLLME), and smartphone digital image colorimetry for the sensitive detection of aflatoxin B1 (AFB1) in baby food samples. …”
Get full text

A Comprehensive Review of Detection Methods for <i>Staphylococcus aureus</i> and Its Enterotoxins in Food: From Traditional to Emerging Technologies by Assia Mairi, Nasir Adam Ibrahim, Takfarinas Idres, Abdelaziz Touati

“…Molecular methods, such as PCR and isothermal amplification, provide high specificity and speed for bacterial and toxin gene detection but cannot confirm functional toxin production. …”
Get full text

Assessment of the level of security (safety of functioning) of automated systems based on their vulnerabilities, formalized using the theory of queuing systems by A. O. Efimov, E. A. Rogozin

Get full text

Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment by Sarah A. Alzakari, Mohammad Alamgeer, Abdullah M. Alashjaee, Monir Abdullah, Khalid Nazim Abdul Sattar, Asma Alshuhail, Ahmad A. Alzahrani, Abdulwhab Alkharashi

“…Detecting DoW threats involves monitoring and analyzing the system-level resource consumption of specific bare-metal mechanisms. …”
Get full text

Glycylglycine promotes the solubility and antigenic utility of recombinant HCV structural proteins in a point-of-care immunoassay for detection of active viremia by Heba Shawky, Ashraf A. Tabll, Reem M. Elshenawy, Naiera M. Helmy, Rehab I. Moustafa, Yasser K. Elesnawy, Marwa M. Abdelghany, Yasmine S. El-Abd

Get full text

GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Given the serious economic burden that citrus diseases impose on fruit farmers and related industries, achieving rapid and accurate disease detection is particularly crucial. In response to the challenges posed by resource-limited platforms and complex backgrounds, this paper designs and proposes a lightweight method for the identification and localization of citrus diseases based on the RT-DETR-r18 model—GYS-RT-DETR. …”
Get full text

Innovative Sandia Frequency Shift Islanding Detection for Microgrids Using Interval Type-II Fuzzy Logic and VP-PSO Optimization by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Yeonwoo Lee, Sun-Kyoung Kang, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…The proposed approach further integrates a variable-parameter PSO (VP-PSO) algorithm to optimize both fuzzy membership functions and controller parameters. Comprehensive simulations demonstrate 100% detection accuracy for both PV and wind farm islanding scenarios, significantly outperforming conventional methods: standard SFS (84-86%), type-1 fuzzy SFS (89-91%), and neural network approaches (94-95%). …”
Get full text