检索结果-内蒙古大学图书馆

2024 International Conference on E-Mobility, Power Control and Smart Systems, ICEMPS 2024

作者： Temara, Sheetal Samanthapudi, Sagar Varma Rohella, Piyush Gupta, Ketan Ashokkumar, S.R. University of The Cumberlands Dept of Computer & Information Sciences WilliamsburgKY United States The Polis Center Indiana University Purdue University Indianapolis Applied Data Science IndianapolisIN United States Payments & Commerce GoDaddy EdmondsWA United States University of The Cumberlands Dept. of Information Technology WilliamsburgKY United States Sri Eshwar College of Engineering Centre For Blockchain and Cyber Security Department of Computer and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350394399

This technical summary outlines the use of Artificial Intelligence (AI) and Natural Language Processing (NLP) to beautify patron banking decision-making. AI-based banking systems can autonomously identify patterns in consumer information and generate insights from a number of sources, including but not restricted to purchaser 360 profiles, 1/3-party statistics, and transactional statistics. With the assistance of AI and NLP, this gadget can answer customer questions relating to their banking wishes and offer personalized recommendations. AI-based monetary decision-making systems also permit banks to offer computerized customer service with information on clients' needs, respond speedily to purchaser requests, and offer quick acclaim for loans and other banking merchandise. Moreover, AI and NLP enhance patron engagement via chatbot-like solutions and purchaser sentiment analysis. The extraordinary AI and NLP-based services being presented by using banks are mentioned in this technical abstract. In conclusion, AI and NLP technology are giving banks the capacity to meet the desires of their customers and improve typical purchaser pleasure. © 2024 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach with Particle Swarm Optimization and Genetic Algorithm.

引用

IEEE Access 2025年 13卷 98639-98655页

作者： Elwahsh, Haitham Bakhiet, Ali Alirr, Omar Ibrahim Khalifa, Tarek Alsabaan, Maazen Ibrahem, Mohamed I. El-Shafeiy, Engy Applied Science Private University Faculty of Information Technology Amman 11931 Jordan Kafrelsheikh University Faculty of Computers and Information Department of Computer Science Kafrelsheikh 33516 Egypt Badya University Faculty of Computing and Data Science Egypt American University of the Middle East College of Engineering and Technology Egaila 54200 Kuwait King Saud University College of Computer and Information Sciences Department of Computer Engineering P.O.Box 51178 Riyadh 11543 Saudi Arabia Augusta University School of Computer and Cyber Sciences Augusta 30912 GA United States University of Sadat City Faculty of Computers and Artificial Intelligence Department of Computer Science Sadat City 32897 Egypt

One of the forms of cancerous tumors that can be fatal is malignant lymphoma. Histopathological examination of lymphoma tissue images is a diagnostic technique for detecting malignant lymphomas. Differentiating lymphoma subtypes manually is challenging due to their similar morphological features. This paper introduces a cutting-edge methodology for classifying malignant lymphoma using Hematoxylin and Eosin (H&E)-stained biopsy images. It integrates feature reduction using Particle Swarm Optimization (PSO) and model optimization through a Genetic Algorithm (GA) in conjunction with DenseNet121 architecture. The DenseNet121 model, which employs four distinct freezing strategies, extracts features from the images, generating an initial 4096 features per image. These features are subsequently reduced by more than 54.4% using PSO, thereby enhancing the computational efficiency without sacrificing classification accuracy. The trained GA Deep Neural Network (DNN) model achieved a significant score of 96.77% testing accuracy with high precision, recall and F1 scores as well. The results after comparison with other existing state-of-the-art models showed the usefulness of the proposed approach in terms of performance as well as the consumption of resources for medical imaging classification. It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. This technique is expected to be further developed and applied in different tasks of computer aided diagnosis of malignant lymphoma in particular the tasks with requirements for explainable artificial intelligence. © 2013 IEEE.

关键词： Artificial intelligent deep learning genetic algorithm malignant lymphoma optimized DenseNet121 particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

A review of DNA cryptograhic approaches 2

A review of DNA cryptograhic approaches

引用

2nd IEEE International Conference on cyberspace, cyber NIGERIA 2020

作者： Iliyasu, Mohammed Awwal Abisoye, Opeyemi Aderiike Bashir, Sulaimon Adebayo Ojeniyi, Joseph Adebayo Department of Computer Science Federal University of Technology Minna Nigeria Department of Cyber Security Federal University of Technology Minna Nigeria

ISBN: (纸本)9781665444095

Cryptography is described as the encryption analysis of data or secret data writing using logical and mathematical data protection principles. It is an information technology for banking, medical systems, transportation and other Internet of things applications. Cryptography has become more important, and it is subjected to growing security concerns. Each system is built with its own strength in cryptography;symmetric encryption provides an economical data protection solution without compromise but it is important to share or distribute the secret key during encryption and decryption process. In comparison, the asymmetric encryption addresses the issue of secret key distribution;however, the stand-alone technique is slow and needs more computing resources than the symmetric encryption approach. In this context, a study of papers relating to DNA cryptographic approaches are presented and the research was centered from 2015 to 2020. The primary sources of information are Science Direct and Research Gate publication platforms. The existing shortcomings of DNA cryptographic approaches were established and analysis was performed on the most frequently used encryption technique based on the literature. The significant findings of this research reviewed that DNA digital coding is the most adopted cryptographic technique used to improve information security and the most common limitations of the DNA cryptographic approaches are high time complexity and algorithm complexity which is possible to infer from the literature. © 2021 IEEE.

关键词： DNA

来源：评论

学校读者我要写书评

暂无评论

An Adaptive User Service Deployment Strategy for Mobile Edge Computing

引用

China Communications 2022年第10期19卷 238-249页

作者： Gang Li Jingbo Miao Zihou Wang Yanni Han Hongyan Tan Yanwei Liu Kun Zhai Institute of Information Engineering Chinese Academy of SciencesBeijing 100093China School of Cyber Security University of Chinese Academy of SciencesBeijing 101408China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029China Sunwise Intelligent Technology Company Beijing 100190China

Mobile edge computing(MEC) is a cloud server running at the edge of a mobile network, which can effectively reduce network communication delay. However, due to the numerous edge servers and devices in the MEC, there may be multiple servers and devices that can provide services to the same user simultaneously. This paper proposes a userside adaptive user service deployment algorithm ASD(Adaptive Service Deployment) based on reinforcement learning algorithms. Without relying on complex system information, it can master only a few tasks and users. In the case of attributes, perform effective service deployment decisions, analyze and redefine the key parameters of existing algorithms, and dynamically adjust strategies according to task types and available node types to optimize user experience delay. Experiments show that the ASD algorithm can implement user-side decision-making for service deployment. While effectively improving parameter settings in the traditional Multi-Armed Bandit algorithm,it can reduce user-perceived delay and enhance service quality compared with other strategies.

关键词： edge computing adaptive algorithm reinforcement learning computing unloading service deployment

来源：评论

学校读者我要写书评

暂无评论

Secure Deduplication and Cloud Storage Auditing with Efficient Dynamic Ownership Management and Data Dynamics

引用

IEEE Transactions on Network and Service Management 2025年

作者： Peng, Xueqi Shen, Wenting Yang, Yang Zhang, Xi Qingdao University College of Computer Science and Technology Qingdao266071 China Zhongnan University of Economics and Law School of Information Engineering Wuhan430073 China Hebei Normal University College of Computer and Cyber Security Shijiazhuang050024 China

To verify the integrity of data stored in the cloud and improve storage efficiency, numerous cloud storage auditing schemes with deduplication have been proposed. In cloud storage, when users perform data dynamic operations, they should lose ownership of original data. However, existing schemes require re-encrypting the entire ciphertext when ownership changes and recalculating the authenticators for the blocks following the updated blocks when insertion or deletion operations are performed. These processes lead to high computation overhead. To address the above issues, we construct a secure deduplication and cloud storage auditing scheme with efficient dynamic ownership management and data dynamics. We adopt CAONT encryption method, where only a portion of the updated block is required to be re-encrypted during the ownership management phase, significantly reducing computation overhead. We also implement index switch sets to maintain the mapping between block indexes and cloud storage indexes of ciphertext blocks. By embedding cloud storage indexes within the authenticators, our scheme avoids the need to recalculate authenticators when users perform dynamic operations. Additionally, our scheme supports block-level deduplication, further improving efficiency. Through comprehensive security analysis and experiments, we validate the security and effectiveness of the proposed scheme. © 2004-2012 IEEE.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

An overview Scientific Cloud computing Web-based cloud services issues and challenges 23

An overview Scientific Cloud computing Web-based cloud servi...

引用

Proceedings of the 5th International Conference on Information Management & Machine Intelligence

作者： Sayan Majumder Kommisetti Murthy Raju Nancy Arya Nazeer Shaik Sanjay Tiwari Akanksha Singh Department of cyber security The Heritage Academy India Department of Electronics and Communication Engineering Shri Vishnu Engineering College For Women India Department of Computer Science and Engineering Shree Guru Gobind Singh Tricentenary University India Department Of Computer Science and Engineering Srinivasa Ramanujan Institute Of Technology-- Autonomous- India Department of Computer Science and Engineering ARYA Institute of Engineering Technology and Management India Computer Science and Engineering Babu Banarasi Das University India

ISBN: (纸本)9798400709418

This research investigates the crucial role of cloud computing services in web development for creating scalable applications. Our study explores the benefits, challenges, and best practices associated with leveraging these services. Real-world case studies will be examined to showcase their significance. Additionally, we examine the integration of blockchain technologies in cloud-based web development and their potential impact on scalability. This paper presents a comprehensive analysis of the indispensability of cloud computing services in building scalable applications for the web. This research project delves into the transformative impact of cloud computing services on the field of web development. By providing scalable and flexible infrastructure, these services have revolutionized the way applications are built. Through an in-depth analysis of benefits, challenges, and best practices, along with real- world case studies, the project highlights the indispensable nature of cloud computing in creating scalable web applications. Furthermore, the exploration of blockchain integration within cloud-based web development offers insights into potential advancements in scalability and opens new avenues for innovation in the field. Additionally, the integration of blockchain technologies in cloud-based web development is investigated, providing insights into its potential impact on scalability and fostering innovation in the field. The research presents a comprehensive analysis of the indispensability of cloud computing services in creating scalable web applications and highlights their transformative impact on the development process.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Product Quality Evaluation using Hybrid LSTM-FCNN Model and GWO Algorithm for Social Media Sentiment Analysis

An Enhanced Product Quality Evaluation using Hybrid LSTM-FCN...

引用

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

作者： V. S. Raj Kumar T. Kumaresan P. Rajesh Kanna S. Jagadeesan P. Showmiya P. Nithin Department of Artificial Intelligence and Data Science Bannari Amman Institute of Technology Erode India Department of Computer Science and Engineering Bannari Amman Institute of Technology Erode India Department of Computer Science and Engineering Nandha Engineering College Erode India Department of Computer Science – Cyber Security Nehru Institute of Technology Coimbatore India Department of Artificial Intelligence and Machine Learning Bannari Amman Institute of Technology Erode India

ISBN: (数字)9798350367904

ISBN: (纸本)9798350367911

Sentiment analysis is still in its developing era, and sometimes, struggles are faced in evaluating user sentiment due to the use of traditional models to analyze the relationship structures in social media interactions. To tackle the issue, we proposed an innovative approach Hybrid LSTM neural network and a fully connected neural network (FCNN) integrated with the Grey Wolf Optimization (GWO) algorithm. The objective of this proposed method is to improve sentiment analysis by employing the LSTM to capture the sequence of data and improve the ability of FCNNs to improve feature extraction and the analysis process. The proposed system process initiated with the data preprocessing of input Twitter sentiment dataset transformed into a suitable input to the Hybrid LSTM-FCNN neural network. Then, temporal dependency of the data captured by LSTM and FCNN is used to extract the features. The GWO method mimics the grey wolf hunting behaviour, for optimizing the proposed Hybrid LSTM-FCNN model’s parameters to enhance the classification accuracy. The system models start with the initialization of the model, parameters, and training the models using the dataset to reduce the cross-entropy loss, estimating the testing dataset from unseen data and fine-tuning using GWO as necessary. Results demonstrate significant improvements in sentiment categorization compared to traditional methods. The Hybrid LSTM-FCNN model, enhanced with GWO, effectively captures nuanced sentiment patterns, leading to more accurate classification. Additionally, GWO’s computational efficiency contributes to scalability. In conclusion, our proposed approach offers a promising solution for enhancing product quality evaluation through advanced neural network architectures and optimization algorithms applied to social media sentiment analysis.

关键词： Sentiment analysis Analytical models Accuracy Social networking (online) Neural networks Blogs Feature extraction Data models Optimization Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Insect Identification in Pulsed Lidar Images Using Changepoint Detection Algorithms

Insect Identification in Pulsed Lidar Images Using Changepoi...

引用

2023 Annual Intermountain engineering, technology and Computing, IETC 2023

作者： Sweeney, Nathaniel Xu, Caroline Shaw, Joseph A. Hocking, Toby D. Whitaker, Bradley M. Montana State University Electrical and Computer Engineering Department United States University of Michigan Electrical Engineering and Computer Science Department United States Montana State University Optical Technology Center United States School of Informatics Computing and Cyber Systems Northern Arizona University United States

ISBN: (纸本)9798350335903

Noninvasive entomological insect monitoring often utilizes a variety of tools such as LiDAR to gather information without interfering with the insects in their habitat. These collection methods often result in large amounts of data that can be te-dious and lengthy to interpret and analyze. Machine learning has been previously used in the past in order to analyze Li-DAR images to detect insects, but often suffers from pitfalls such as long training times and large computational power requirements. In an attempt to offer an alternative that takes little to no training on the data and much less computational power, this paper looks at the use of changepoint detection algorithms to analyze LiDAR images containing insects. By analyzing the rows or columns of a LiDAR image, the algorithms should be able to detect abrupt changes in the image that would represent the insects. While not as accurate, the changepoint detection algorithms give comparable results to a machine learning algorithm tested on the same dataset without the need for supervised training. © 2023 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Building a Large-Scale and Wide-Area Quantum Internet Based on an OSI-Alike Model

引用

China Communications 2021年第10期18卷 1-14页

作者： Zhonghui Li Kaiping Xue Jian Li Nenghai Yu Jianqing Liu David S.L.Wei Qibin Sun Jun Lu School of Cyber Security University of Science and Technology of ChinaHefeiAnhui 230027China School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhui 230027China Department of Electrical and Computer Engineering University of Alabama in HuntsvilleHuntsvilleAL 35899USA Department of Computer and Information Science Fordham UniversityBronxNY 10458USA

The theory and experiment of quantum information have been studied extensively in recent years,and the feasibility of quantum communication has been *** the fundamental technology is not yet mature,research on quantum internet should be *** implement quantum internet,an architecture that describes how quantum nodes are linked to form networks and how protocol functions are vertically composed need to be developed *** this paper,we present a novel design of a clusterbased structure to describe how quantum nodes are interconnected,and how the structure can improve the performance of qubit transmission and reduce the network *** idea of the quantum local area network(QLAN)is proposed as an essential component of the quantum ***,each quantum repeater links to neighboring repeaters to form a core network,and multiple QLANs are connected through the core *** core network can be grouped into different hierarchical quantum repeater networks according to needed service *** the sake of interoperability and fast prototyping,we adopt the idea of OSI layering model of the current Internet in the design of quantum ***,we elaborate on the composition of quantum nodes and the realization of end-to-end communication.

关键词： quantum internet entanglement swapping quantum repeater teleportation

来源：评论

学校读者我要写书评

暂无评论

An Automated Platform for Gathering and Managing Open-Source cyber Threat Intelligence 2

An Automated Platform for Gathering and Managing Open-Source...

引用

2nd International Conference on Business Analytics for technology and security, ICBATS 2023

作者： Al-Dmour, Nidal A. Kamrul Hasan, Mohammad Ajmal, Masood Ali, Muhammad Naseer, Iftikhar Ali, Atif Hamadi, Hussam Al Ali, Nasir Mutah University College of Engineering Department of Computer Engineering Jordan Center for Cyber Security Malaysia Riphah International University Islamabad Pakistan University of Central Punjab Pakistan The Superior University Faculty of Computer Science & Information Technology Lahore Pakistan Cyberjaya Malaysia College of Engineering and IT University of Dubai United Arab Emirates School of Computer Science NCBA&E Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

The community has begun paying more attention to source OSCTI cyber Threat Intelligence to stay informed about the rapidly changing cyber threat landscape. Numerous reports from the OSCTI frequently provide Information about dangers. However, current OSCTI gathering and management tools have mainly concentrated on individual minor compromise indicators, despite the urgent need for high-quality OSCTI. The relationship between higher-level notions (including the strategies, methods, and processes) and the connections between them, which hold crucial Information about dangerous behaviors and are crucial to revealing the full dangerous situation, have been disregarded. Therefore, we present securityKG, an automated OSCTI collection and administration system. securityKG collects OSCTI to extract high-fidelity knowledge about threat behaviours to address the void. Using a mixture of AI and NLP approaches, a security know-how graph is then constructed from a wide variety of sources. To facilitate knowledge graph exploration, securityKG provides a user interface (UI) that supports multiple forms of interactivity. © 2023 IEEE.

关键词： User interfaces

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：