检索结果-内蒙古大学图书馆

International Journal of Interactive Mobile Technologies 2023年第5期17卷 71-83页

作者： Aljammal, Ashraf H. taamneh, Salah Qawasmeh, Ahmad Salameh, Hani Bani Department of Computer Science and Applications The Hashemite University Zarqa Jordan Department of Software Engineering The Hashemite University Zarqa Jordan

Nowadays, individuals and organizations are increasingly targeted by phishing attacks, so an accurate phishing detection system is required. Therefore, many phishing detection techniques have been proposed as well as phishing datasets have been collected. In this paper, three datasets have been used to train and test machine learning classifiers. The datasets have been archived by Phish-Tank and UCI Machine Learning Repository. Furthermore, Information Gain algorithm have been used for features reduction and selection purpose. In addition, six machine learning classifiers have been evaluated, namely NaiveBayes, ANN, DecisionStump, KNN, J48 and RandomForest. However, the classifiers have been trained and tested over the three datasets in two stages. The first stage is using all features included in each dataset while the second stage using selected features by IG algorithm. At the first stage RandomForest classifier has shown the best performance over Dataset-1 and Dataset-2, while J48 has shown the best performance over Dataset-3. On the other hand, after features selection, the RandomForest classifier was the superior among the other five classifiers over Dataset-1 and Dataset-2 with accuracy of 98% and 93.66% respectively. While ANN classifier has shown the best performance with accuracy of 88.92% over Dataset-3. Because of the few number of instances as well as features in Dataset-3 comparing to the other two dataset;the performance of the classifiers has been affected © 2023, International Journal of Interactive Mobile *** Rights Reserved.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

DC Fault Detection Using Time Derivative of High-Pass Filter Response in MTDC Systems 50

DC Fault Detection Using Time Derivative of High-Pass Filter...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Khan, Saad Ahmed Ukil, Abhisek Nair, Nirmal-Kumar C. Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (纸本)9781665464543

In the DC fault event, DC link capacitors immediately discharge a colossal current of high frequency. These large currents of high frequencies can instantly damage the components attached to the DC transmission system. Therefore, a rapid and robust DC fault detection topology is necessary, facilitating protection coordination in forthcoming Multi-Terminal Direct Current (MTDC) systems. This study introduces a novel fault detection technique using the time derivative of the High Pass Filter (HPF) response to identify fault currents in just a few microseconds (µs). This topology enables protection coordination for modern MTDC systems. Furthermore, this technique can identify different types of DC faults and remains unaffected by AC faults and load variation. © 2024 IEEE.

关键词： Chebyshev filters

来源：评论

学校读者我要写书评

暂无评论

Integrating Blockchain and SDN for Centrality-Aware Virtual Multicast Tree Embedding 9

Integrating Blockchain and SDN for Centrality-Aware Virtual ...

引用

9th International Conference on computer Science and engineering, UBMK 2024

作者： Ayaz, Furkan Guler, Evrim Karakus, Murat Hanbay, Davut Bartin University Department of Computer Engineering Bartin Turkey Ankara University Department of Software Engineering Ankara Turkey

ISBN: (纸本)9798350365887

Recent innovations in network virtualization have made it possible to support multiple tenants, or 'virtual net-works;' on a single physical infrastructure. This is feasible due to the decoupling of network services from the actual hardware design. The intricate NP-Hard problem known as Virtual Network Embedding (VNE) requires the simultaneous avail-ability of certain network resources (e.g., bandwidth, computing capacity) and the mapping of virtual network components (e.g., virtual nodes and links) onto an existing Substrate Network (SN). In contrast to the classic VNE problem, which is centered on unicast communication, this research aims to efficiently map Virtual Networks (VNs) with one-to-many (multicast) interactions onto an SN using Virtual Multicast Trees (VMTs). To embed VMTs onto a shared SN, we provide a Centrality-Aware Blockchain Infrastructure for Virtual Multicast Tree Embedding (CBI-VMTE). This approach uses a blockchain-based centrality-aware path-finding mechanism. The goal of the CBI-VMTE architecture is to satisfy the processing needs of virtual nodes while minimizing the SN's use of network resources, especially bandwidth. In a wide range of network topologies, including NSFNET, US Backbone, Random-14, and Random-24-nodes, our approach outperforms dynamic node ranking and traditional greedy-based VMTE approaches in terms of bandwidth efficiency. © 2024 IEEE.

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Experimental Design and Teaching Research of a MPLS VPN Network Based on BGP 12

Experimental Design and Teaching Research of a MPLS VPN Netw...

引用

12th IEEE International Conference on Educational and Information Technology, ICEIT 2023

作者： Tao, Jun Chen, Huan Liu, Huamin She, Xingxing Anhui Institute of Information Engineering School of Computer and Software Engineering WuHu China

ISBN: (纸本)9781665475518

after expounding the concepts of MPLS VPN and BGP, the advantage of MPLS VPN is described, subsequently a computer network experiment based on MPLS VPN and BGP is designed. The experiment includes three parts: network topology design, IP address planning and configuration implementation. First, the experiment is simulated through the simulator, and then the network is constructed with real physical equipment. After the experiment, the corresponding evaluation can be obtained immediately, and all network parameters are tested normally. Through the completion of this experiment, the teaching has achieved good results. © 2023 IEEE.

关键词： Border Gateway Protocol

来源：评论

学校读者我要写书评

暂无评论

Comparative Evaluation of DNA Encryption and Henon Chaotic Map in Image Encryption: Correlation Coefficient, Entropy, Mean Square Error and NIST SP800-22 Test

Comparative Evaluation of DNA Encryption and Henon Chaotic M...

引用

2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Savasturk, Pinar Yerlikaya, Tarık Software Engineering Kırklareli University Kırklareli Turkey Computer Engineering Trakya University Edirne Turkey

ISBN: (纸本)9798350379433

This research presents comparative analyzes of Henon chaotic map and Deoxyribonucleic Acid (DNA) image encryption. These image encryption techniques examined with these metrics: Correlation Coefficient, Entropy, Mean Square Error (MSE) and NIST SP800-22 statistical tests which is among Frequency (Monobit), Test. The results of the review indicate the effectiveness of chaotic maps and DNA encryption in image encryption. The comparative analyzes revealed by this study highlight the weak and strong features of the methods. The analysis results obtained guide the selection of encryption techniques suitable for image security. © 2024 IEEE.

关键词： Image correlation

来源：评论

学校读者我要写书评

暂无评论

Application of optimized deformable convolution in underwater biological detection algorithm 3

Application of optimized deformable convolution in underwate...

引用

3rd International Symposium on computer Applications and Information Systems, ISCAIS 2024

作者： Zhuang, Hongwei Liu, Weisheng School of Computer and Software Engineering Liaoning University of Science and Technology Liaoning Anshan China

ISBN: (纸本)9781510681316

Underwater target detection is an important method for marine life detection. However, the accuracy of target detection and recognition is affected by the problems of image occlusion, blurred water quality and complex background of underwater targets. An improved YOLOV7 underwater biological target detection method is proposed to address the above problems. Firstly, the DCN structure is improved by incorporating the residual structure into the DCN, with new jump connections and 1×1 convolutional branches, so that the network can learn the residual information between the input and the output. It can improve the expressive ability of the model, reduce the number of parameters, and enhance the adaptability to the shape of the object. Finally, COT3 is integrated, which utilises a self-attention mechanism to weight the input feature maps so that the model can focus on important contextual information around the target and improve the model's ability to handle complex scenes. The experimental results show that the improved YOLOv7 model achieves an average detection accuracy mAP value of 80.4%, which is 2.8% higher than the original algorithm, and the algorithm is better than the original YOLOv7 algorithm in terms of detection accuracy and speed, which is more suitable for the detection of underwater targets. © 2024 SPIE.

关键词： Water quality

来源：评论

学校读者我要写书评

暂无评论

Uvcgan-Dehaze: a dehazing method for unpaired images

引用

Soft Computing 2024年第20期28卷 12217-12226页

作者： Li, Canlin Zhang, Xiangfei Zhang, Wenjiao Su, Haowen Bi, Lihua School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou China School of Software Engineering Zhengzhou University of Light Industry Zhengzhou China

To solve the problems of feature loss and color difference after image dehazing and poor dehazing effect in real hazy images, a method UVCGAN-Dehaze is proposed for unpaired image dehazing. In the proposed model, the generator learns the relationship between image features and low-frequency features at multiple scales by combining the U-Net with the transformer. We strengthen the connection between spatial and channel features by adding Convolutional Block Attention Module(CBAM) before the skip connection of each layer of U-Net of the generator and adaptively adjusting the weight allocation of the feature map, so that the image after dehazing can better retain the detailed information of the image. Simultaneously, in order to reduce the feature loss and color difference after image dehazing, we propose a loss function named Feature Laplacian Perception (FLP) loss, which jointly constrains the generator by fusing the perception loss and Laplacian loss, so that the generated image reduces the feature loss and color difference. The method not only generates dehazing images with high perceptual quality in terms of important regions and details, but also avoids content and color loss. Extensive experiments verify the effectiveness of the method on synthetic images and real hazy images, and the proposed method achieves better dehazing results when compared with the experimental results of previous typical methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Rotating target detection algorithm in remote sensing images based on improved YOLOv5s 4

Rotating target detection algorithm in remote sensing images...

引用

4th International Conference on computer Vision, Image and Deep Learning, CVIDL 2023

作者： Chen, Lunfeng Luo, Chengzhi Li, Xiao Xiao, Jixiang School of Computer and Software Engineering Xihua University Chengdu China

ISBN: (纸本)9798350326444

Aiming at the problem of low target detection accuracy and easily missed detection in remote sensing images, a rotating target detection method based on YOLOv5s is proposed with YOLOv5s as the basic framework. First of all, the circular smooth label CSL (Circular Smooth Label, CSL) is used to realize the conversion of angle regression prediction to classification prediction to overcome the problems of regression prediction angle periodicity and variable boundary and improve the detection accuracy. Secondly, the densely coded label (Densely Coded Label, DCL) replaces the sparsely coded label, dramatically reducing the thickness of the prediction layer and improving the training speed. Finally, in the C3 module of the original YOLOv5s feature extraction and feature fusion network, a lightweight channel attention mechanism is introduced into the module, thereby improving the network's local feature capture and fusion capabilities. The experimental results show that on the public DOTA remote sensing image dataset, the map results of the improved YOLOv5s-obb reach 0.78, respectively. Compared with the original YOLOv5s, this method can be improved by 1.7%, and compared with other typical remote sensing target detection methods, the accuracy has also been improved, which proves the effectiveness of the improved YOLOv5s-obb method. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Towards Cache-Assisted Hierarchical Detection for Real-Time Health Data Monitoring in IoHT

引用

computers, Materials & Continua 2023年第11期77卷 2529-2544页

作者： Muhammad Tahir Mingchu Li Irfan Khan Salman AAl Qahtani Rubia Fatima Javed Ali Khan Muhammad Shahid Anwar School of Software Technology Dalian University of Technology(DUT)Dalian116621China School of Software Technology Key Laboratory for Ubiquitous Network and Service Software of Liaoning ProvinceDalian116650China Department of Computer Engineering King Saud UniversityRiyadh11543Saudi Arabia School of Software Tsinghua UniversityBeijing100084China Department of Software Engineering University of Science and TechnologyBanu28100Pakistan Department of AI and Software Gachon UniversitySeongnamsi13120Korea

Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)***,delays in data retrieval can markedly hinder the efficacy of big data awareness detection *** advocate for a collaborative caching approach involving edge devices and cloud networks to combat *** strategy is devised to streamline the data retrieval path,subsequently diminishing network *** an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation *** paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge *** system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health *** the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during *** system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response ***,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize *** the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a *** reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark *** empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring *** encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection *** methodology yields enh

关键词： Real-time health data monitoring Cache-Assisted Real-Time Detection(CARD) edge-cloud collaborative caching scheme hierarchical detection Internet of Health Things(IoHT)

来源：评论

学校读者我要写书评

暂无评论

A Novel Two-Stage Net for Human Body Region Segmentation via Centimeter-Wave Radar 3

A Novel Two-Stage Net for Human Body Region Segmentation via...

引用

3rd International Conference on Neural Networks, Information and Communication engineering, NNICE 2023

作者： Xiao, Jiaren Chen, Zhiguo Luo, Bing The School of Computer and Software Engineering Xihua University Chengdu China

ISBN: (纸本)9798350335972

Human body region segmentation is a sub-task in semantic segmentation. Due to the size, complexity, abstraction of radar signal and the lack of open source datasets of radar signal data, the radar signal is rarely used for human body segmentation in past. In recent years, with the development of deep learning, some radar signal data from unmanned drive has been used for research on classification, target detection and semantic segmentation. In this paper, a novel two-stage neural network model based on centimeter-wave radar sensor is designed for human body region segmentation. In the first stage, radar signals are encoded and compressed, in the second stage, decode the spatial feature information of the human body extracted by the encoder to output the segmentation results. The network adopts the design idea of teacher-student network, which use the teacher network to annotate radar signal data and provide cross-modal supervision for the student network. We collected human body data in different scenes, and input the radar signal into the model, performs human body region segmentation. The effectiveness of this human segmentation model is experimentally verified for single and multi-person scenes, especially for occlusion scenes. © 2023 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：