Article
Automation & Control Systems
Xinlei Wang, Xiaojuan Wang, Mingshu He, Min Zhang, Zikui Lu
Summary: This article proposes an attention-weighted model to enhance the detection capabilities in the widely used message queuing telemetry transport protocol in the Internet of Things. The model extracts spatial-temporal features by constructing perception node collection graphs, utilizing message-passing mechanism, bidirectional long short-term memory model, and self-attention mechanism. Experimental results demonstrate its effectiveness and high accuracy on multiple datasets.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Mechanical
Xiaoming Lei, Ye Xia, Ao Wang, Xudong Jian, Huaqiang Zhong, Limin Sun
Summary: This study proposes a residual attention network (RAN) that employs the attention mechanism and residual learning to improve classification efficiency and accuracy, aiming to address the impact of abnormal monitoring data on structural assessment. The hourly segmented measured data is transformed into matrix form through mutual information correlation analysis for training a deep learning model. The proposed RAN model shows excellent classification performance in identifying most anomaly data types in the test dataset and demonstrates good generalization performance with another cable-stayed bridge dataset, outperforming existing preprocessing and deep learning models in multi-classification and classification accuracy.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Physics, Multidisciplinary
Mingfeng Zha, Wenbin Qian, Wenlong Yi, Jing Hua
Summary: In this study, the YOLOv4_MF model was proposed to improve pest detection accuracy in complex forestry environments. By using techniques such as MobileNetv2 and depth-wise separated convolution, the model achieved higher performance compared to YOLOv4 while reducing the model parameters. The experimental results demonstrated superior mAP, precision, and recall, as well as a significant reduction in model size.
Article
Biology
Samir Jain, Ayan Seal, Aparajita Ojha, Anis Yazidi, Jan Bures, Ilja Tacheci, Ondrej Krejcar
Summary: The study presents a deep learning model WCENet for anomaly detection and localization in WCE images. The model processes images in two phases and achieves high accuracy and area under receiver operating characteristic.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Ying Zheng, Hong Bao, Chaochao Meng, Nan Ma
Summary: This paper discusses the importance of traffic police gesture recognition in driverless technology, and proposes a real-time detection method based on an attention mechanism. The author collected and organized a large amount of traffic police data sets, providing important data support for the research.
Article
Computer Science, Artificial Intelligence
Hironori Takimoto, Junya Seki, Sulfayanti F. Situju, Akihiro Kanagawa
Summary: This study proposes an anomaly detection method based on the Siamese network with an attention mechanism for a small dataset, addressing the problem of insufficient abnormal product data in practical application.
APPLIED ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Information Systems
Qianqing Cheng, Xiuhe Li, Bin Zhu, Yingchun Shi, Bo Xie
Summary: In this study, a novel drone detection method called YOLOv4-MCA is proposed to address the issues of large model parameters and false and missing detections of multi-scale drone targets. The approach utilizes the lightweight MobileViT and Coordinate Attention to extract features, obtain positional information, and optimize the detection efficiency. Experimental results demonstrate that the proposed method achieves high accuracy in multi-scale drone target detection with a low number of parameters.
Article
Plant Sciences
Weijun Cheng, Tengfei Ma, Xiaoting Wang, Gang Wang
Summary: This article proposes a new anomaly detection model based on generative adversarial networks (GAN) for processing multidimensional time series data generated by smart agricultural IoT. The model utilizes an encoder-decoder structure with attention mechanism to improve the learning of normal data. Experimental results show that the proposed model accurately achieves anomaly detection and outperforms the counterpart models.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
Summary: This article proposes a method called ResGCN for effectively detecting anomalous nodes in attributed networks. The method utilizes deep residual modeling, captures sparsity and nonlinearity through GCN modeling of attributed networks, and reduces the impact of anomalous nodes and prevents over-smoothing through a residual-based attention mechanism.
Article
Engineering, Electrical & Electronic
Zhiyu Wang, Linheng Li, Xu Qu, Peipei Mao, Bin Ran
Summary: This paper proposes a new traffic flow prediction model that considers the probability of anomaly detection and integrates the anomaly detection outcomes into the traffic flow prediction framework. Through simulation studies using actual measured traffic flow data, the real-time and accurate nature of the proposed model is demonstrated.
IET INTELLIGENT TRANSPORT SYSTEMS
(2023)
Article
Computer Science, Theory & Methods
Jian Hou, Fangai Liu, Hui Lu, Zhiyuan Tan, Xuqiang Zhuang, Zhihong Tian
Summary: Malicious traffic detection is crucial for cyber security, and using flow as the detection object is deemed effective. This paper proposes a novel approach for detecting malicious traffic by utilizing only the packet header fields in the raw traffic to generate characteristic representations and employing a two-layer attention network to generate flow vectors. Experimental results demonstrate high accuracy rates and AUC-ROC values for binary and multi-class classification tasks.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Article
Mathematical & Computational Biology
Yuanyao Lu, Kexin Li
Summary: This paper introduces the application of deep learning technology in lip recognition and proposes a deep learning-based lip recognition application system. The system improves recognition rate by extracting spatial and temporal features, utilizing attention mechanism, and assists hearing-impaired individuals in learning and pronunciation correction through a lip similarity matching system.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Zhenwei Li, Wei Zhang, Xiaoli Yang
Summary: An improved deep learning model based on YOLOv5 is proposed in this paper to achieve more accurate and faster recognition of different obstacles and traffic lights. The model incorporates features such as a coordinate attention layer, a weighted bidirectional feature pyramid structure, and a SIoU loss function to enhance detection performance. Testing and evaluation using the BDD100K dataset demonstrate that the improved model outperforms existing methods, particularly for small targets.
Article
Chemistry, Multidisciplinary
Zeeshan Ahmad, Adnan Shahid Khan, Kashif Nisar, Iram Haider, Rosilah Hassan, Muhammad Reazul Haque, Seleviawati Tarmizi, Joel J. P. C. Rodrigues
Summary: The revolutionary concept of Internet of Things (IoT) has led to exponential growth in IoT networks, connected devices, and data, raising concerns about security. This paper introduces an efficient anomaly detection mechanism for IoT networks using mutual information (MI) and deep neural network (DNN). Comparative analysis of various deep learning models shows that the DNN-based NIDS model outperforms other models in terms of accuracy and false alarm rate reduction.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Civil
Shen Fang, Veronique Prinet, Jianlong Chang, Michael Werman, Chunxia Zhang, Shiming Xiang, Chunhong Pan
Summary: The article introduces a new model for predicting urban traffic flow, which can consider the complex spatio-temporal dependencies in traffic networks and utilizes multi-source data for prediction. In various experiments, the model performs well on different types of traffic networks, particularly showing significant results in handling large-scale traffic networks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Editorial Material
Computer Science, Information Systems
Al-Sakib Khan Pathan, Zubair Md. Fadlullah, Salimur Choudhury, Mohamed Guerroumi
Article
Computer Science, Artificial Intelligence
Shaik Shakeel Ahamad, Al-Sakib Khan Pathan
Summary: Existing mobile healthcare schemes based on cloud and IoMT lack end-to-end security and HIPAA compliance. Our proposed community cloud framework utilizing TPM ensures security while reducing costs.
CONNECTION SCIENCE
(2021)
Article
Chemistry, Analytical
A. N. M. Bazlur Rashid, Mohiuddin Ahmed, Al-Sakib Khan Pathan
Summary: Detection of rare anomalies and infrequent patterns in cybersecurity datasets is computationally expensive. Feature selection is essential for improving classification performance, and cooperative co-evolution (CC)-based feature selection methods are more suitable for this purpose. Experimental results show that using CC-based feature selection can significantly improve the detection of both rare anomalies and infrequent patterns in cybersecurity data preprocessing.
Article
Computer Science, Hardware & Architecture
Mounya Smara, Makhlouf Aliouat, Saad Harous, Al-Sakib Khan Pathan
Summary: With the increasing popularity of Cloud computing systems, the demand for highly dependable Cloud applications has significantly increased. Ensuring reliability and availability of Cloud applications is challenging due to the dynamic nature of Cloud computing paradigm. This paper proposes a formal framework for constructing reliable and available Cloud components using the DRB scheme to enhance Cloud dependability through fault-masking nodes.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Physics, Multidisciplinary
A. F. M. Suaib Akhter, Tawsif Zaman Arnob, Ekra Binta Noor, Selman Hizal, Al-Sakib Khan Pathan
Summary: The popularity of electric vehicles is rising and a peer-to-peer charging system utilizing blockchain technology has been proposed to address the insufficient charging stations. A cryptocurrency-based payment system is employed for secure transactions, and a reputation management system is implemented to ensure the quality of service.
Article
Computer Science, Information Systems
A. F. M. Shahen Shah, Muhammet Ali Karabulut, A. F. M. Suaib Akhter, Nazifa Mustari, Al-Sakib Khan Pathan, Khaled M. Rabie, Thokozani Shongwe
Summary: Cryptocurrencies gain user confidence through transparent creation and transaction history, guaranteeing transaction security and privacy. The growing trend of financial institutions investing in cryptocurrencies has increased the importance of synthesizing previous research. This paper analyzes the use of data mining in Bitcoin transactions, addresses the challenges and applications of electronic currencies, and highlights methods to enhance user privacy. It also identifies security threats in existing cryptocurrency systems and highlights research gaps and future trends that need further exploration.
Editorial Material
Computer Science, Information Systems
Uttam Ghosh, Deepak Tosh, Nawab Muhammad Faseeh Qureshi, Ali Kashif Bashir, Al-Sakib Khan Pathan, Zhaolong Ning
Review
Environmental Sciences
Md. Al-Masrur Khan, Seong-Hoon Kee, Al-Sakib Khan Pathan, Abdullah-Al Nahid
Summary: Cracks in concrete structures can cause degradation, so early detection is crucial for inspecting structural health. Image Processing Techniques (IPTs) based on Deep Learning (DL) have been investigated to overcome the limitations of manual inspection. However, a comprehensive systematic review of the research trends and prominent IPTs for crack detection in concrete structures is currently lacking.
Review
Computer Science, Information Systems
Muhammet Ali Karabulut, A. F. M. Shahen Shah, Haci Ilhan, Al-Sakib Khan Pathan, Mohammed Atiquzzaman
Summary: Vehicular Ad Hoc Networks (VANETs) have become popular in the area of smart transportation due to their strategic significance. However, the rapid development of VANETs faces challenges in meeting the strict requirements of low latency, high mobility, top security, and massive connectivity of the 5G network. This paper provides a comprehensive taxonomy of VANETs and discusses various issues including applications, Quality of Service (QoS), security, physical layer fading, Artificial Intelligence (AI) techniques, Medium Access Control (MAC), and routing protocols.
Article
Computer Science, Hardware & Architecture
Mohiuddin Ahmed, A. F. M. Suaib Akhter, A. N. M. Bazlur Rashid, Al-Sakib Khan Pathan
Summary: Microservices are an important component in the design and development of IoT. They are small, independent services that communicate through well-defined APIs. Ensuring data integrity and availability is a challenge in microservice architectures, and blockchain technology can be utilized to solve these challenges. This paper proposes a Trustworthy Consensus Algorithm (TCA) that uses consensus algorithms from blockchain to address the data integrity and availability issues in microservice architectures. The proposed algorithm has been evaluated against alternative solutions and shows good efficiency.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Computer Science, Information Systems
Chahrazed Benrebbouh, Houssem Mansouri, Sarra Cherbal, Al-Sakib Khan Pathan
Summary: This paper proposes an enhanced mutual authentication protocol for IoT-based Energy Internet using blockchain technology. It utilizes blockchain-based security mechanisms to ensure secure communication between IoT devices, and the performance and security were evaluated through experimental results.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Chahrazed Benrebbouh, Houssem Mansouri, Sarra Cherbal, Al-Sakib Khan Pathan
Summary: This paper proposes a mechanism to defend against quantum computer attacks in IoT-based EI using the GGH cryptosystem and quantum key distribution.
INTERNATIONAL JOURNAL OF SENSOR NETWORKS
(2023)
Review
Engineering, Multidisciplinary
Saifur Rahman Sabuj, Mohammad Saadman Alam, Majumder Haider, Md Akbar Hossain, Al-Sakib Khan Pathan
Summary: This paper discusses the significance and prospects of low altitude small satellite aerial vehicles in ensuring smooth aerial-ground communications for next-generation broadband networks. It explores the architecture and resource management challenges of low altitude aerial networks, as well as the coordination between communication technologies and such networks. The paper also highlights techniques for user-friendly control and monitoring, and presents future research directions in aerial-ground communications.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2022)
Proceedings Paper
Computer Science, Information Systems
Mohiuddin Ahmed, A. F. M. Suaib Akhter, A. N. M. Bazlur Rashid, Mahdi Fahmideh, Al-Sakib Khan Pathan, Adnan Anwar
Summary: This paper discusses how blockchain technology can address the challenge of data integrity in microservice architectures, proposing a reliable consensus algorithm and demonstrating its effectiveness through evaluation.
WINSYS : PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON WIRELESS NETWORKS AND MOBILE SYSTEMS
(2022)