检索结果-内蒙古大学图书馆

International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Deepa S Praveenkumar G D R Suguna Vivek Duraivelu C Jamunadevi S G Sundhar Department of Computer Technology-PG Kongu Engineering College Perundurai Erode Tamilnadu Department of computer science Vet institute of Arts and Science (Co-Education) College Erode Tamilnadu Department of Computer science and Engineering Bannari Amman Institute of Technology Sathyamangalam Department of Computer Science and Engineering B V Raju Institute of Technology Narsapur Telangana Department of Computer Technology PG Kongu Engineering College Perundurai Erode Tamilnadu Final M.Sc(Software Systems) Kongu Engineering College Perundurai Erode Tamilnadu

COVID-19, caused by the new coronavirus SARS-Co V-2, has turned into a worldwide health emergency, needing speedy and precise diagnostic techniques. This abstract provides a thorough evaluation of research works focusing on COVID-19 identification using DenseNet, a cutting-edge convolutional neural network architecture. DenseNet is notable for its innovative design, which fosters feature reuse while relieving the vanishing gradient problem and enhancing network information flow. Researchers have created novel ways for COVID-19 identification using medical imaging, such as chest X-rays and CT scans, by harnessing the capabilities of DenseNet. The analyzed studies demonstrate DenseNet's efficiency in recognizing COVID-19-specific patterns and distinguishing them from other lung diseases. These investigations have shown remarkable accuracy, sensitivity, and precision, exceeding established machine learning approaches and even professional radiologists. This research study also highlights the difficulties and constraints experienced while using DenseNet to identify COVID-19. Issues such as dataset quantity, class imbalance, and model decision-making process interpretability are addressed. Furthermore, future research paths and prospective enhancements, such as multi-modal data integration and the development of explainable AI systems, are investigated. The experimental results indicate that the proposed approach achieves high accuracy, sensitivity, and precision in the identification of COVID - 19. The proposed methodology achieved an accuracy of 89.74%, sensitivity of 87.25 % , and precision of 79.56%, which outperforms the existing state-of-the-art methods. The proposed approach is robust and can effectively differentiate between COVID-19 positive and negative cases, which is essential for early detection and prompt treatment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

QSroute : A QoS Aware Routing Scheme for software Defined Networking

QSroute : A QoS Aware Routing Scheme for Software Defined Ne...

引用

International Conference on software engineering and computer systems (ICSECS)

作者： Imran Edzereiq Kamarudin Mohamed Ariff Ameedeen Muhamad Idaham Umar Ong Azlee Zabidi Department of Computer Systems and Networking Faculty of Computing Universiti Malaysia Pahang AL-Sultan Abdullah Pekan Malaysia Department of Software Engineering Faculty of Computing Universiti Malaysia Pahang AL-Sultan Abdullah Pekan Malaysia

The increasing demand for bandwidth-intensive network applications, such as video streaming, multimedia, and Internet of Things (IoT) applications, necessitates improved resource management to protect the network without compromising Quality of Service (QoS). Meeting these challenges requires a centralized view of all available network resources. software Defined Networking (SDN), an emerging technology, provides a centralized view and control of network resources. This feature enables administrators to programmatically define and manage network behavior, including routing, making it more flexible and adaptable. This study proposes a QoS-aware routing scheme for SDN that considers available bandwidth, packet delay, and packet loss to determine the optimal routing path. Optimal paths are selected based on meeting predefined threshold criteria. The study concludes by discussing potential directions for future research in this field.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security Controls

arXiv

引用

arXiv 2024年

作者： Gupta, Deepti Elluri, Lavanya Jain, Avi Moni, Shafika Showkat Aslan, Omer Dept. of Computer Information Systems Texas A&M University - Central Texas TX United States College of Business University of Tampa Florida United States Dept. of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Florida United States Department of Software Engineering Bandırma Onyedi Eylül University Bandırma Turkey

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamper-proof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls—such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture—this approach strengthens an organization’s defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth’s transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, enab

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

NESec: A Modified-UI Honeyword Generation Strategy for Mitigating Targeted Guessing Attacks

NESec: A Modified-UI Honeyword Generation Strategy for Mitig...

引用

Cyber Security in Networking Conference (CSNet)

作者： Nilesh Chakraborty Mohammad Shojafar Zhuangzhuang Chen Victor C. M. Leung Jianqiang Li Mohammad Zulkernine School of Computing Queen's University Canada 5GIC & 6GIC Institute for Communication Systems University of Surrey United Kingdom College of Computer Science and Software Engineering Shenzhen University China

By harnessing Graphics Processing Unit (GPU), Field-programmable Gate Array (FPGA), and advanced cracking techniques, the success rates of server-side threats on passwords have reached unprecedented levels. Honeywords, also known as decoy passwords, have emerged as a promising detection strategy against this threat scenario. However, existing work falls short in creating a trap to counter targeted guessing attackers $(\mathbf{TgA})$ who exploit users' personal information to bypass honeyword-based traps. In this paper, we introduce two fundamental honeyword generation modules, namely NSecure-modifiedUI and ESecure-modifiedUI. Building upon these primary modules, we propose a hybrid honeyword-based strategy named NESec, which significantly enhances the ability to detect $\mathbf{TgA}$ 's activities. A comparative analysis showcases the usability advantages and security benefits of the proposed NESec approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Career Aura-Smart Resume and Employment Recommender 3

Career Aura-Smart Resume and Employment Recommender

引用

3rd International Conference on Advancements in Computing, ICAC 2021

作者： Dissanayake, Kavindi Mendis, Senidu Subasinghe, Randula Geethanjana, Dineth Lunugalage, Dilani Kasthurirathna, Dharshana Sri Lanka Institute of Information Technology Computer Systems Engineering Department Malabe Sri Lanka Sri Lanka Institute of Information Technology Information Technology Department Malabe Sri Lanka Sri Lanka Institute of Information Technology Computer Science and Software Engineering Department Malabe Sri Lanka

ISBN: (纸本)9781665408622

Recruitment and Job seeking are two major factors that are directly proportional to each other. Due to the competitive nature of the present world, the process of acquiring the best resource effectively and efficiently has become a challenging aspect for the companies. As a result, modern job portals have become increasingly popular to address the challenges identified in the early recruitment and job search process. The purpose of this research is to introduce an optimal solution to address the ineffective areas identified in the job and recruitment domain which can further enhance the recruitment and job seeking decisions by utilizing deep learning and sentiment analytic approach along with descriptive analysis. The proposed system recommends the relevant job opportunities by omitting the irrelevant job advertisements for job hunters who are interested in the IT job domain while they input their resume to the system and additionally, they can improve their career decisions by adhering to the prediction schemes. Moreover, the system facilitates recruiters to headhunt top talents efficiently once they input job requirements to the system and candidate suggestions are not only made depending on their resume information but also analyzing their LinkedIn endorsements. © 2021 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

An Investigation Method Incorporates with Contextual Information and Transformer Residual BiLSTM to Improve the Accuracy of Detecting Sensitive Content in Various Contexts

An Investigation Method Incorporates with Contextual Informa...

引用

International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Niharika Karne Chandra Shekar Ramagundam Ranga Rao Patnala Shashishekhar Ramagundam Sai Nitisha Tadiboina Department of Electrical Engineering Masters in Electrical Engineering Sr. Principal Systems Engineer in C&RS Platform Services DT Amtrak University of South Alabama USA Senior Software Engineer in Cloud Platform Services City Of Philadelphia Pennsylvania USA Vice President US AL. Department of Computer Science Masters In Computer Science Software Development & Engineering in Content Discovery & AI Comcast Troy University Montgomery Campus USA Department of Information Technology GEICO - Chevy Chase MD United States

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

In the modern era, the internet is an emerging technology with a rapidly growing user. Sensitive content uploaders consider this platform as a way to transmit disturbing visual content, such as animated cartoon videos to circulate unsuitable content among youngsters. Previous researches show that the interaction of online sensitive information has substantial offline effects on historically impoverished communities. As a result, it is strongly recommended that social media platforms have an automatic real-time sensitive content filtering method for detecting contextual information. In this proposed model, a novel deep-learning framework is developed for detecting sensitive content from contextual information. For this, the suggested architecture performs under three stages (i) text collection, (ii) preprocessing, and (iii) detection. Initially, the required texts from the contextual information are gathered from the standard available data resource. The collected text is subjected to text preprocessing, where the text is cleaned and prepared for further analysis. Finally, in the detection phase, the developed Transformer Residual Bidirectional Long Short-Term Memory (TR-BiLSTM) is employed to learn the effective representation from the preprocessed text and perform the sensitive content detection. Furthermore, performance comparisons are carried out between the proposed frameworks with other standard approaches. The developed architecture achieved better results in detecting the sensitive content from the text.

关键词： Visualization Accuracy Recurrent neural networks Noise Transformers Real-time systems Long short term memory Standards Context modeling Videos

来源：评论

学校读者我要写书评

暂无评论

Quantifying Information Exposure by Web Browsers

Quantifying Information Exposure by Web Browsers

引用

Future Technologies Conference, FTC 2020

作者： Mohsen, Fadi Shehab, Mohamed Lange, Maxamilliano Karastoyanova, Dimka Department of Computer Science Bernoulli Institute University of Groningen Groningen Netherlands Department of Software and Information Systems University of North Carloina at Charlotte Charlotte United States Department of Computer Science Engineering and Physics University of Michigan-Flint Flint United States

ISBN: (纸本)9783030630911

Internet surfing entails exchanging numerous HTTP requests between clients and servers. Attached with each request is a string containing plenty of information about the client called User-Agent string. There have been numerous researches that showed the privacy and security risks of User-Agent strings. In this work we aim to minimize those risks by directing users towards using less exposing browsers. In doing so, we propose and test a new method for calculating an exposure score for web browsers based mainly on their User-Agent strings besides other attributes. We then apply this method on a dataset of over a million browsers to infer and compare their exposure scores. Finally, we present a demo web tool that shows how the resulting scores can be leveraged to aid end users. Our results reveal a variation in the exposure scores of these browsers, which creates prospect for safe Internet surfing. © 2021, Springer Nature Switzerland AG.

关键词： Web browsers

来源：评论

学校读者我要写书评

暂无评论

MIMO-Terahertz in 6G Nano-Communications:Channel Modeling and Analysis

引用

computers, Materials & Continua 2021年第1期66卷 263-274页

作者： Shahid Bashir Mohammed H.Alsharif Imran Khan Mahmoud A.Albreem Aduwati Sali Borhanuddin Mohd Ali Wonjong Noh Business Studies Department Namal InstituteMianwali42250Pakistan Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006South Korea Department of Electrical Engineering University of Engineering and Technology PeshawarPeshawar814Pakistan Department of Electronics and Communications Engineering College of EngineeringA’Sharqiyah UniversityIbraOman Wireless and Photonics Networks Research Centre of Excellence Department of Computer and Communication Systems EngineeringUnversiti Putra MalaysiaSelangor43400Malaysia School of Software Hallym UniversityHallymdaehak-gilChunchoen-si24252South Korea

With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by *** wireless mobile communication frequency tends to be saturated,which demands for new ***(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information *** communication has great application prospects in military-civilian integration and coordinated *** China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the ***,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond *** paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel ***,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the *** results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.

关键词： Wireless communication 6G mobile communication terahertz communication MIMO channel modeling

来源：评论

学校读者我要写书评

暂无评论

The software Complex for the Selection and Analysis of Algorithms Predicting Key Quality Indicators of Polymer Film Materials of Industrial Production

The Software Complex for the Selection and Analysis of Algor...

引用

International Conference on Control systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Tamara B. Chistyakova Anton Damrin Nikita D. Grishchenkov CAD&C Department St. Petersburg State Institute of Technology (Technical University) St. Petersburg Russia Faculty of Software Engineering and Computer Systems ITMO University St. Petersburg Russia

The following algorithms for constructing predictive models of key quality indicators of polymer film materials are considered and implemented: adaptive boosting of decision trees (AdaBoost), recurrent neural network of long short-term memory (LSTM). The characteristics of production data and the stages of their preparation for the construction of predictive models are presented. The comparison of trained predictive models for the defect by the number of black dots per m2 of the film web is carried out by various algorithms according to the main metrics: precision, recall, f1-score, to identify the best depending on the production data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Dental Caries Identification with Deep Learning: A Study of Convolutional Neural Networks and Transfer Learning Approaches

SSRN

引用

SSRN 2024年

作者： Mannan, Fayqa Adeel, Muhammad Arif, Erssa Li, Jianqiang Ullah, Amin Nawazish, Samra Mahmood, Tariq Rehman, Amjad Shoukat, Ijaz Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Government College University Faisalabad38000 Pakistan Department of Computer Science School of Science National Textile University Faisalabad37610 Pakistan Department of Computer Science Faculty of Computing Riphah International University Faisalabad38000 Pakistan Beijing Engineering Research Center for IoT Software and Systems 100124 China Department of Computer Science Faculty of IT and Computer Science University of Central Punjab Lahore Pakistan School of Computer Science and Engineering Southeast University Nanjing China Software Engineering Department University of Engineering and Technology Taxila Pakistan Artificial Intelligence & Data Analytics Lab CCIS Prince Sultan University Riyadh11586 Saudi Arabia Faculty of information Sciences University of Education Vehari Campus Vehari61100 Pakistan

Various deep learning techniques have been employed to diagnose dental caries using X-ray images. In this study, we utilized deep learning models, including Convolutional Neural Networks (CNNs) and transfer learning models such as Visual Geometry Group (VGG16), VGG19, ResNet50, and Inception V3, to identify dental caries in periapical radiographs. The traditional CNN model comprises three sets of 2D convolutional layers, followed by an activation layer, a max-pooling layer, a flatten layer, one dense layer, another activation layer, dropout, another dense layer, and a final activation layer. For the VGG models, ResNet50, and Inception V3, the top convolutional layers were frozen to prevent retraining of the model, with only the last layers trained to produce the required output. The accuracy achieved by CNN, VGG16, VGG19, ResNet50, and Inception V3 was 90%, 96%, 73%, 70%, and 73%, respectively. VGG16 exhibited the highest accuracy among the models. Hyperparameters were carefully selected using a grid search approach, and the results were validated using the Shuffle-Split-Cross (SSC) validation method. These findings underscore the effectiveness of transfer learning in analyzing medical images, particularly in the diagnosis of dental caries. © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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：