检索结果-内蒙古大学图书馆

Enhancing the Security in Group Message Communication Using Multi-Party Key Distribution Technique

Journal of Mobile Multimedia 2024年第5期20卷 961-996页

作者： Haldar, Bilas Sinha, Rohit Paul, Pranam Department of Computer Science and Engineering The Neotia University Sarisha Diamond Harbour Road West Bengal South 24 Parganas 743368 India AI Labs Academy Pvt. Ltd. West Bengal Kolkata 700091 India Department of Computer Science and Engineering Global Institute of Engineering and Management Palpara More NH-34 Krishnanagar West Bengal Nadia 741102 India

Authentication and authorization techniques are essential for any kind of secure transaction over the Internet. It enables and empowers mechanisms to implement highly secure systems such as digital financial transition systems, hospitality management systems, and defence organizations. Most of the work on these techniques has been done based on single-user authorization. It is less secure than the multi-user authorization technique. Multi-party settings require the authorization of the majority user pool, the work is still in its nascent stage. Hence the presented work includes a multi-user authentication technique based on the approach of arithmetic greatest common divisor. This method aims to significantly enhance the security and reliability of the authorization process. Additionally, the proposed work also presented innovative encryption and decryption techniques for the security of data transformation using a modified N prime RSA algorithm. Furthermore, this work also discussed the application of the proposed methodology in the hospitality industry to ensure the security of customer data. The results of this work indicate that the suggested techniques enhance the security of data transformation and improve the time efficiency of key generation, encryption, and decryption techniques. © 2024 River Publishers.

关键词： authentication decryption encryption hospitality industry Key generation N prime RSA security analysis

来源：评论

学校读者我要写书评

暂无评论

Cancer Diseases Diagnosis Using Deep Transfer Learning Architectures 1st

Cancer Diseases Diagnosis Using Deep Transfer Learning Archi...

引用

1st International Conference on Machine Intelligence and Emerging Technologies, MIET 2022

作者： Promy, Tania Ferdousey Joya, Nadia Islam Turna, Tasfia Haque Sukhi, Zinia Nawrin Ashraf, Faisal Bin Uddin, Jia Department of Computer Science and Engineering School of Data Science Brac University Dhaka Bangladesh AI and Big Data Department Endicott College Woosong University Daejeon Korea Republic of

ISBN: (纸本)9783031346187

Cancer is a lethal disease among the diseases in the world. It is clinically known as ‘Malignant Neoplasm’ which is a vast group of diseases that encompasses unmonitored cell expansion. It can begin anywhere in the body such as the breast, skin, liver, lungs, brain, and so on. As reported by the National Institutes of Health (NIH), the projected growth of new cancer cases is forecast at 29.5 million and cancer-related deaths at 16.4 million through 2040. There are many medical procedures to identify the cancer cell, such as mammography, MRI, CT scan, which are common methods for cancer diagnosis. The methods used above have been found to be ineffective and necessitate the development of new and smarter cancer diagnostic technologies. Persuaded by the phenomena of medical image classification using deep learning, our recommended initiative targets to analyze the performance of different deep transfer learning models for cancer cell diagnosis. In this paper, we have used VGG16, Inception V3 and MobileNet V2 deep architectures to diagnosis the breast cancer (KAU-BCMD dataset), lung cancer (IQ-OTH/NCCD dataset) and skin cancerHam10000). Experimental results demonstrate that VGG16 architecture shows comparatively higher accuracy by exhibiting 98.5% of accuracy for breast cancer, 99.90% for lung cancer and 93% for skin cancer dataset. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Two-dimensional Parameter Relationships for W UMa-type Systems Revisited

引用

Research in Astronomy and Astrophysics 2024年第1期24卷 51-58页

作者： Atila Poro Ehsan Paki ailar Alizadehsabegh Mehdi Khodadadilori Selda Ranjbar Salehian Mahya Hedayatjoo Fatemeh Hashemi Yasaman Dashti Fatemeh Mohammadizadeh Astronomy Department of the Raderon AI Lab. BurnabyBCCanada Faculty of Electrical and Computer Engineering Department of PhotonicsUniversity of TabrizTabriz 51664Iran Department of Electrical Engineering Amirkabir University of TechnologyTehranIran Astronomy Students'Scientific Association University of TabrizTabriz 51664Iran Department of Physics Iran University of Science and TechnologyTehranIran Institute for the Intellectual Development(Kanoon) Astronomy GroupBojnordIran Department of Mechanical Engineering Amirkabir University of TechnologyTehranIran Aerospace Engineering Department Science and Research Branch of Islamic Azad UniversityTehranIran

Reviewing the empirical and theoretical parameter relationships between various parameters is a good way to understand more about contact binary *** this investigation,two-dimensional(2D)relationships for P–MV(system),P–L1,2,M1,2–L1,2,and q–Lratiowere *** sample used is related to 118 contact binary systems with an orbital period shorter than 0.6 days whose absolute parameters were estimated based on the Gaia Data Release 3 *** reviewed previous studies on 2D relationships and updated six parameter ***,Markov chain Monte Carlo and Machine Learning methods were used,and the outcomes were *** selected 22 contact binary systems from eight previous studies for comparison,which had light curve solutions using spectroscopic *** results show that the systems are in good agreement with the results of this study.

关键词： (stars:)binaries(including multiple):close stars:fundamental parameters methods:data analysis

来源：评论

学校读者我要写书评

暂无评论

Convolutional Neural Network Based Glaucoma Detection and Classification using Optic Disc Localization 2

Convolutional Neural Network Based Glaucoma Detection and Cl...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Neelagar, Mahesh B Manjunath, T.C. Patra, Raj Kumar Jagadish, Sripelli Mazumder, Debarshi Visvesvaraya Technological University Dayanand College of Engineering Bengaluru Department of ECE Karnataka Belgavi India CMR Technical Campus Department of Computer Science and Engineering Hyderabad India SR University School of Computer Science and Artificial Intelligence Warangal India Nitte Meenakshi Institute of Technology Department of AI and DS Bengaluru India

ISBN: (纸本)9798350317558

Glaucoma in the retina is considered a significant cause of irreparable vision loss, and automated glaucoma detection on fundus images has seen the development of several approaches recently. Although early diagnosis and treatment can prevent possible blindness, manually segmenting the optic disc depends on the availability of a large number of labeled samples for the training phase. The proposed method utilizes U-Net for segmentation based on labeled and unlabeled data for prediction and data enhancement with a large number of feature channels in up sampling. This approach can improve overall performance by considering pixel-level and image-level labels during network training and encoding the data train, differentiating U-Net from Convolutional Neural Network (CNN). Classification is performed using CNN for diagnosing glaucoma, evaluated on a large training dataset. The obtained results demonstrate that the proposed U-Net model achieves better accuracy, reaching 0.99 on the Drishti dataset. These results ensure accurate segmentation and classification performance compared to other existing methods such as CNN and Multi-layer Neural Network. © 2024 IEEE.

关键词： Convolutional Neural Network Deep Learning Deep Neural Network Glaucoma Detection ResNet-50 and U-Net

来源：评论

学校读者我要写书评

暂无评论

Multi-Task Learning for Sarcasm Detection and Sentiment Analsysis Using BERT

Multi-Task Learning for Sarcasm Detection and Sentiment Anal...

引用

International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： B. Jyothsna Swathi Gowroju V. Sahithi Fahd Khadri B. Sri Vinny P. Vardhan Raj Dept of CSE (AI & ML) Sreyas Institute of Engineering and Technology Telangana India Computer Science Engineering Sreyas Institute of Engineering and Technology Telangana India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

This paper proposes a Multi –Task Learning Model approach to detect Sarcasm and to analyze Sentiment within the given text. Sarcasm detection is important for enhancing natural language understanding particularly in customer reviews and social media where sarcastic sentences are mostly used. This system uses BERT (Bi-directional Encoder Representations from Transformers) to processes both tasks concurrently. It uses separate layers to handle each task individually. The text processing pipeline includes techniques such as text normalization, tokenization, and lemmatization and then followed by encoding using BERT’s tokenizer before using it for model training. BERT can understand the complex patterns of language which helps in easily recognize the small clues present in sarcastic statements. The architecture of the model incorporates specific layers for sarcasm and sentiment classification which optimizes prediction with loss functions for each task. If there is imbalance in class distributions class weighting is applied and model evaluation is performed using K-Fold cross validation to ensure robustness. To measure the model effectiveness performance metrics such as ROC-AUC curves, confusion matrix and detailed classification reports are used. Therefore, including MTL and BERT improves the performance and effectiveness in sarcasm detection and sentiment analysis.

关键词： Analytical models Sentiment analysis Social networking (online) Computational modeling Transfer learning Bidirectional control Predictive models Transformers Encoding Tokenization

来源：评论

学校读者我要写书评

暂无评论

ai-Powered Drone to Address Smart City Security Issues 37th

AI-Powered Drone to Address Smart City Security Issues

引用

37th International Conference on Advanced Information Networking and Applications, aiNA 2023

作者： Salama, Ramiz Al-Turjman, Fadi Culmone, Rosario Department of Computer Engineering Research Center for AI and IoT AI and Robotics Institute Near East University Nicosia Mersin 10 Nicosia Turkey Artificial Intelligence Engineering Department AI and Robotics Institute Near East University Mersin 10 Nicosia Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Mersin 10 Kyrenia Turkey Computer Science Division School of Science and Technology University of Camerino Camerino62032 Italy

ISBN: (纸本)9783031286933

The idea of a dazzling metropolis has drawn interest from all across the world. New innovations like blockchain, IoT, artificial intelligence, robots, and many other things were added to it. Security is one of the top issues for people living in big cities, and everyone wants to feel completely secure when traveling around every single day. In this research, we will look into how CEOs in affluent cities use and value robots, especially in terms of security. To understand the robot security the board stream, some approaches and intricacies are used. Following that is a discussion of issues with urban security and the application of artificial intelligence to drones as a management tool. The use of cutting-edge technology, such as blockchain, to support smart urban community management is covered in the last part. The smart city idea and all of its benefits for local inspection are supported by robotic use. The idea of thriving urban areas is spreading around the world and is crucial in the context of developing economies. We examined how to leverage cutting-edge technologies in this project to make it feasible. Artificial intelligence, robotics breakthroughs, and blockchain technologies all have significant effects. This research highlights their significance to analysts and how they consider them when assessing prospects. This project will be very beneficial for analysts and experts in a relevant subject. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

SlowFast Based Real-Time Human Motion Recognition with Action Localization

引用

computer Systems science & engineering 2023年第11期47卷 2135-2152页

作者： Gyu-Il Kim Hyun Yoo Kyungyong Chung Department of Computer Science Kyonggi UniversitySuwon16227Korea Contents Convergence Software Research Institute Kyonggi UniversitySuwon16227Korea Division of AI Computer Science and Engineering Kyonggi UniversitySuwon16227Korea

Artificial intelligence is increasingly being applied in the field of video analysis,particularly in the area of public safety where video surveillance equipment such as closed-circuit television(CCTV)is used and automated analysis of video information is ***,various issues such as data size limitations and low processing speeds make real-time extraction of video data *** analysis technology applies object classification,detection,and relationship analysis to continuous 2D frame data,and the various meanings within the video are thus analyzed based on the extracted basic *** recognition is key in this *** recognition is a challenging field that analyzes human body movements,requiring the interpretation of complex movements of human joints and the relationships between various *** deep learning-based human skeleton detection algorithm is a representative motion recognition ***,motion analysis models such as the SlowFast network algorithm,have also been developed with excellent ***,these models do not operate properly in most wide-angle video environments outdoors,displaying low response speed,as expected from motion classification extraction in environments associated with high-resolution *** proposed method achieves high level of extraction and accuracy by improving SlowFast’s input data preprocessing and data structure *** input data are preprocessed through object tracking and background removal using YOLO and DeepSORT.A higher performance than that of a single model is achieved by improving the existing SlowFast’s data structure into a frame unit *** on the confusion matrix,accuracies of 70.16%and 70.74%were obtained for the existing SlowFast and proposed model,respectively,indicating a 0.58%increase in *** detection,based on behavioral classification,the existing SlowFast detected 2,341,164 cases,whereas the proposed model detected 3,11

关键词： Artificial intelligence convolutional neural network video analysis human action recognition skeleton extraction

来源：评论

学校读者我要写书评

暂无评论

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

引用

computer Modeling in engineering & sciences 2024年第7期140卷 409-430页

作者： Zhuoqun Xia Hangyu Hu Wenjing Li Qisheng Jiang Lan Pu Yicong Shu Arun Kumar Sangaiah School of Computer and Communication Engineering Changsha University of Science and TechnologyChangshaChina Hunan Province People’s Hospital(The First Affiliated Hospital of Hunan Normal University) ChangshaChina The First Affiliated Hospital of Guangxi Medical University NanningChina International Graduate Institute of AI National Yunlin University of Science and TechnologyYunlinChina Department of Electrical and Computer Engineering Lebanese American UniversityBayrutLebanon

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible *** research has failed to fully explore effective DR lesion information in fundus ***,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion ***,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis ***,the LLM generates a global attention map based on ***,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion *** paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

关键词： DDR dataset diabetic retinopathy lesion localization multi-level patch attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Machine Learning In Sustainable Development-An Overview 1

Machine Learning In Sustainable Development-An Overview

引用

1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Altrjman, Chadi Gupta, Richa Near East University Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Nicosia Turkey Near East University Ai and Robotics Institute Artificial Intelligence Engineering Dept. Turkey University of Kyrenia Faculty of Engineering Kyrenia Turkey Waterloo University Canada Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350338027

I have studied how artificial intelligence (ai) or machine learning (ml) is applied in a sustainable system called "Eugenie"for my work, project, and thesis. In this project, I get to discuss Eugenie's role in ensuring the sustainability of large environmental business organizations. I also get to discuss how it aids operation managers in making predictions about when their machines will break down days, weeks, and months in advance, allowing them to schedule maintenance cycles more effectively. In other words, Eugenie provides plant operators with data so they can prioritize repairs. Eugenie executes this process by utilizing real-time data from numerous sensors attached to large machinery and equipment in the process industry, metals and mining, oil and gas, and smart cities industries. Two products make up this program;the first is named RAY-FINN and the second is called PAPILLON. Eugenie assists businesses in a variety of ways, including:•aids in the attainment of operational excellence by process organizations•Always raise overall profitability.•Contributes to a greener and safer future. © 2023 IEEE.

关键词： Sustainable development

来源：评论

学校读者我要写书评

暂无评论

FAT-HuBERT: Front-End Adaptive Training of Hidden-Unit BERT For Distortion-Invariant Robust Speech Recognition

FAT-HuBERT: Front-End Adaptive Training of Hidden-Unit BERT ...

引用

2023 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2023

作者： Yang, Dongning Wang, Wei Qian, Yanmin Shanghai Jiao Tong University MoE Key Lab of Artificial Intelligence Ai Institute Department of Computer Science and Engineering Shanghai China

ISBN: (纸本)9798350306897

Advancements in monaural speech enhancement (SE) techniques have greatly improved the perceptual quality of speech. However, integrating these techniques into automatic speech recognition (ASR) systems has not yielded the expected performance gains, primarily due to the introduction of distortions during the SE process. In this paper, we propose a novel approach called FAT-HuBERT, which leverages distortion-invariant self-supervised learning (SSL) to enhance the robustness of ASR. To address the distortions introduced by the SE frontends, we introduce layer-wise fusion modules that incorporate features extracted from both observed noisy signals and enhanced signals. During training, the SE frontend is randomly selected from a pool of models. We evaluate the performance of FAT-HuBERT on simulated noisy speech generated from LIBRISPEECH as well as real-world noisy speech from the CHIME-4 1-channel dataset. The experimental results demonstrate a significant relative reduction in word error rate (WER). © 2023 IEEE.

关键词： Speech enhancement

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：