Distributed denial-of-service (DDoS) on the smart grids based on VGG19 deep neural network and Harris Hawks optimization algorithm by Abdurahim Alhashmi, H. Idwaib, Selçuk Alparslan Avci, Javad Rahebi, Raheleh Ghadami

“…This paper presents an effective method for identifying smart grid DDoS attacks by introducing the use of the deep neural network VGG19 combined with the Harris Hawks Optimization Algorithm (HHO). The suggested approach uses the robust feature extraction capability of VGG19-DNN for network traffic pattern analysis to detect abnormal traffic flows indicative of DDoS attacks. …”
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Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model by Elhoucine Ouassam, Yassine Dabachine, Nabil Hmina, Belaid Bouikhalene

“…To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. …”
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Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations by Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

“…We further refine the super-resolution map by employing a KDTree algorithm for efficient MB tracking across consecutive frames. …”
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Self-Sensing of Piezoelectric Micropumps: Gas Bubble Detection by Artificial Intelligence Methods on Limited Embedded Systems by Kristjan Axelsson, Mohammadhossien Sheikhsarraf, Christoph Kutter, Martin Richter

“…The training and hyper-parameter optimization of artificial intelligence algorithms from the TensorFlow and scikit-learn libraries are conducted using a grid search approach. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…The Concat module in Neck is replaced by a two-way weighted feature fusion mechanism, which constructs a top-down and bottom-up two-way information flow, reduces the loss of cross-layer information, and significantly enhances the model’s ability to detect multi-scale defects, such as insulator cracks and fouling, and especially improves the resolution of details of small targets in long-distance shooting scenarios. …”
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DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium by Anichur Rahman, Md. Jahidul Islam, Ziaur Rahman, Md. Mahfuz Reza, Adnan Anwar, M. A. Parvez Mahmud, Mostofa Kamal Nasir, Rafidah Md. Noor

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Adaptive strategies for the deployment of rapid diagnostic tests for COVID-19: a modelling study [version 2; peer review: 2 approved, 1 approved with reservations] by Emily Kendall, Lucia Cilloni, Nimalan Arinaminpathy, David Dowdy

“…Background Lateral flow assays (LFAs) for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provide an affordable, rapid and decentralised mean for diagnosing coronavirus disease 2019 (COVID-19). …”
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Tunnel Traffic Enforcement Using Visual Computing and Field-Programmable Gate Array-Based Vehicle Detection and Tracking by Yi-Chen Lin, Rey-Sern Lin

“…We developed a foreground detection algorithm based on the K-nearest neighbor (KNN) and Gaussian mixture model and 400 collected images. …”
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Vibration Analysis of a Centrifugal Pump with Healthy and Defective Impellers and Fault Detection Using Multi-Layer Perceptron by Masoud Hatami Garousi, Mahdi Karimi, Paolo Casoli, Massimo Rundo, Rasoul Fallahzadeh

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The Complex Alarming Event Detecting and Disposal Processing Approach for Coal Mine Safety Using Wireless Sensor Network by Cheng Bo, Zhou Peng, Zhu Da, Chen Junliang

“…Firstly, we introduce the event and complex events model, offer fully customizable policies for event selection and consumption, and also describe the state-automata-based complex event detection algorithm. Then, we describe an event-driven service coordination pattern for the behavioral model, which is based on event-condition-action triggering with BPEL control flow realized using decoupled publish/subscribe semantics. …”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…To overcome these challenges, this paper presents a specialized dataset created from 1983 pavement images. A deep learning detection algorithm named YOLO-CS (You Only Look Once Crack Sealant) is proposed. …”
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A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks. by Shaowei Sun, Mingzhou Liu

“…To address these limitations, we propose a framework based on multimodal deep fusion and heterogeneous graph neural networks (HGNNs), incorporating an Ensemble Contrastive Pessimistic Likelihood Estimation (CPLE) algorithm to optimize performance. The framework integrates static and dynamic traffic data, such as video images, traffic flow, vehicle speed, and tunnel weather conditions. …”
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StaEn-IDS: An Explainable Stacking Ensemble Deep Neural Network-Based Intrusion Detection System for IoT by Monika Vishwakarma, Nishtha Kesswani

“…The model also addresses the challenge of detecting minority-class attacks in IoT traffic. We evaluate the approach on data derived from the CIC IoT 2022 dataset (pcap files converted to flow records using CICFlowMeter), and demonstrate real-time deployment on a resource-constrained edge device. …”
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Efficient Vehicle Detection and Optimization in Multi-Graph Mode Considering Multi-Section Tracking Based on Geographic Similarity by Yue Chen, Jian Lu

“…At present, complex deep learning algorithms are often used for vehicle detection and tracking, but high-precision detection results are often obtained at the cost of time, and the existing research rarely considers optimization algorithms for vehicle information. …”
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Hybrid Deep Learning Approach for Accurate Detection and Multiclass Classification of Broken Conductor Faults in Power Distribution Systems by Firas Saadoon Mohammed Al-Jumaili, Mustafa Onat

“…Our method refines input using the Proportional Topology Optimization (PPTO) algorithm that enhances the signal quality of unbalanced three-phased current signals for fault identification. …”
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Design of an Electronic Nose System with Automatic End-Tidal Breath Gas Collection for Enhanced Breath Detection Performance by Dongfu Xu, Pu Liu, Xiangming Meng, Yizhou Chen, Lei Du, Yan Zhang, Lixin Qiao, Wei Zhang, Jiale Kuang, Jingjing Liu

“…Therefore, accurate collection of end-tidal breath gases is crucial to enhance electronic noses’ performance in breath detection. Regarding this issue, this study proposes a novel electronic nose system and employs a threshold control method based on exhaled gas flow characteristics to design a gas collection module. …”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

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Toward lightweight intrusion detection systems using the optimal and efficient feature pairs of the Bot-IoT 2018 dataset by Erman Özer, Murat İskefiyeli, Jahongir Azimjonov

“…Intrusion detection systems play a vital role in traffic flow monitoring on Internet of Things networks by providing a secure network traffic environment and blocking unwanted traffic packets. …”
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WPD-ResNeSt: Substation Station Level Network Anomaly Traffic Detection Based on Deep Transfer Learning by Ting Yang, Yucheng Hou, Yachuang Liu, Feng Zhai, Rongze Niu

“…The existing substation network analyzers and flow anomaly detection algorithms are usually based on threshold determination, which cannot reflect the inherent characteristics of substation automation flow based on IEC 61850 and have low detection accuracy. …”
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Advanced video anomaly detection using 2D CNN and stacked LSTM with deep active learning-based model by ANOOPA S, Dr Salim A, Dr Nadera Beevi S

“…The model combines the use of 2DCNN and Stacked LSTM to extract frame-level features through an improved anisotropic Gunnar Farneback Optical Flow algorithm. The system is evaluated on the benchmarked datasets namely UCSD Ped1 UCSD Ped2 and achieves an AUC of 95% and 94% respectively. …”
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