检索结果-内蒙古大学图书馆

Cognitive Robotics and Intelligent Systems (ICC - RObINS), International Conference on

作者： S. Alvin Jesuraj S. V. Evangelin Sonia C. P. Shirley B.Tech Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

This research investigates the application of DenseNet-201, a deep convolutional neural network architecture, in the RSNA-MICCAI brain Tumor Radiogenomic Classification aimed at predicting the genetic subtype of glioblastoma using MRI imaging data. This study demonstrates the effectiveness of DenseNet-201 in accurately classifying glioblastoma cases based on MGMT promoter methylation status, a critical biomarker influencing treatment outcomes. Through comprehensive experimental evaluations, including training, validation, and testing phases, DenseNet-201 exhibits robust performance metrics such as high accuracy, precision, recall, F1-score, and AUC-ROC values. These results highlight the model's ability to effectively distinguish between MGMT promoter methylation-positive and negative glioblastoma cases, offering valuable support for clinical decision-making in treatment planning and prognosis assessment. Leveraging deep learning techniques and MRI imaging data, DenseNet-201 holds promise as a powerful tool for enhancing the understanding of glioblastoma genetics and guiding personalized therapeutic interventions, ultimately contributing to improved patient outcomes in brain cancer management.

关键词： Deep learning Training Magnetic resonance imaging Medical services Genetics Planning Prognostics and health management

来源：评论

学校读者我要写书评

暂无评论

EASYDIAGNOS: A FRAMEWORK FOR ACCURATE FEATURE SELECTION FOR AUTOMATIC DIAGNOSIS IN SMART HEALTHCARE

arXiv

引用

arXiv 2024年

作者： Maji, Prasenjit Mondal, Amit Kumar Mondal, Hemanta Kumar Mahanty, Saraju P. Computer Science and Design Dr. B. C. Roy Engineering College WB 713206 India Computer Science and Engineering Bengal College of Engg. and Tech. WB 713212 India Electronics and Communication Engg. National Institute of Technology WB Durgapur713209 India Dept. of Computer Science and Engineering University of North Texas United States

The rapid advancements in artificial intelligence (AI) have revolutionized smart healthcare, driving innovations in wearable technologies, continuous monitoring devices, and intelligent diagnostic systems. However, security, explainability, robustness, and performance optimization challenges remain critical barriers to widespread adoption in clinical environments. This research presents an innovative algorithmic method using the Adaptive Feature Evaluator (AFE) algorithm to improve feature selection in healthcare datasets and overcome problems. AFE integrating Genetic Algorithms (GA), Explainable Artificial Intelligence (XAI), and Permutation and Combination techniques (PCT), the algorithm optimizes Clinical Decision Support Systems (CDSS), thereby enhancing predictive accuracy and interpretability. The proposed method is validated across three diverse healthcare datasets using six distinct machine learning algorithms, demonstrating its robustness and superiority over conventional feature selection techniques. The results underscore the transformative potential of AFE in smart healthcare, enabling personalized and transparent patient care. Notably, the AFE algorithm, when combined with a Multi-layer Perceptron (MLP), achieved an accuracy of up to 98.5%, highlighting its capability to improve clinical decision-making processes in real-world healthcare applications. © 2024, CC bY.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Enhanced Monitoring and Security Measures with Video Analysis

Enhanced Monitoring and Security Measures with Video Analysi...

引用

Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： V. Esther Jyothi G. Rakesh Vipparla Aruna Shobana Gorintla Yalanati Ayyappa U Ganesh Naidu Department of Computer Applications Velagapudi Ramakrishna Siddhartha Engineering College Deemed to be University Vijayawada A.P. India Department of Computer Science and Engineering NRI Institute of Technology (Autonomous) Pothavarapadu A.P India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Tamilnadu India B V Raju Institute of Technology Narsapur Telangana India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

In modern surveillance, activities have increasingly become dependent on the continuous observation offered by CCTV systems. Still, with massive amounts of video data generated in a minute, sifting through this information manually to pick up any anomalies would be extremely burdensome and nearly impossible without significant human labor and vigilant watchfulness. CNN and CLIP models changed everything with regards to the working of surveillance systems. It makes use of CNN's capability for video frame processing and analysis to detect and classify these activities in the frames as either normal or suspicious. At the same time, it improves this by adding the CLIP model's capability of understanding textual descriptions and visual content together for better nuance detection in suspicious activities. This methodology transforms video surveillance by breaking video streams into frames and analyzing the behavior and interactions of persons in those frames. The synergy of CNN and CLIP models not only ensures real-time, efficient, and accurate surveillance but also minimizes dependency on extensive manual labor for monitoring. This paper aims to provide a contribution toward developing better security infrastructures in public spaces, transportation hubs, and private facilities. The introduction of this anomaly-detection mechanism can hugely improve the capability of implemented surveillance systems with a proactive response based on real-time detection and response capabilities against suspicious activities.

关键词： Visualization Transportation Transforms Manuals Streaming media Video surveillance Real-time systems Security Feeds Streams

来源：评论

学校读者我要写书评

暂无评论

A comprehensive evaluation of polygon-based hologram algorithms 14

A comprehensive evaluation of polygon-based hologram algorit...

引用

Holography, Diffractive Optics, and Applications XIV 2024

作者： Wang, Fan Wang, Pin Zhang, Yaping blinder, David Gupta, Anuj Poon, Ting-Chung Ito, Tomoyoshi Shimobaba, Tomoyoshi Graduate School of Engineering Chiba University 1-33 Yayoi-cho Inage-ku Chiba Japan Yunnan Provincial Key Laboratory of Modern Information Optics Kunming University of Science and Technology Kunming Yunnan650500 China Pleinlaan 2 BrusselB-1050 Belgium IMEC Kapeldreef 75 LeuvenB-3001 Belgium CSIR-Central Scientific Instruments Organisation Chandigarh160030 India Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

ISBN: (纸本)9781510682085

Polygon-based computer-generated holography algorithms can achieve high realism at low computational cost. Many recent contributions improve the hologram generation efficiency and solve many issues of 3D realistic rendering. This manuscript provides a comprehensive evaluation of their performance and potential through a detailed classification and comparison. Although the numerical-based algorithms using spectral interpolation offer greater flexibility in achieving realistic 3D displays, further phase-optimization algorithms are needed to render 3D reconstructions with higher definition, reduced noise, and faster updates. © 2024 SPIE. All rights reserved.

关键词： computer generated holography

来源：评论

学校读者我要写书评

暂无评论

IoT-Genomics Analysis for Personal Health with Cybergenomics and Cloud technology

IoT-Genomics Analysis for Personal Health with Cybergenomics...

引用

International Conference on Communications and Signal Processing

作者： T. Prabakaran A. Ramesh babu S. Hemalatha Jayabharathi Ramasamy Rajesh Kambattan Kovarasan b Elango Department of Computer Science and Engineering Joginpally B.R. Engineering College Hyderabad Telangana India School of Computer Applications Vidya Vikas Institute of Engineering And Technology Mysore Karnataka India Department of Artificial Intelligence and Data Science Tagore Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering RMK College of Engineering and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Adhiparasakthi Engineering College Melmaruvathur Tamil Nadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

Recent innovations at the convergence of genomics and the Internet of Things (IoT) have opened the way for an innovative strategy for administering individualized health care. This research study combines the potential of wearable health monitoring technologies with genetic insights to analyze the personal healthcare. A comprehensive knowledge of health dynamics may be achieved by seamlessly integrating real-time health data collected from IoT-enabled wearables with individual genetic profiles. Using algorithms for machine learning, connections between genetic differences and instantaneous health responses may be uncovered, paving the way for the development of individualized therapies and lifestyle recommendations. The suggested framework allows people to improve their health and gives medical professionals access to data-driven insights that can be used for the early diagnosis of diseases and the development of individualized treatment plans. The work that has been done sheds light on the revolutionary potential of merging genetics with the Internet of Things to establish a new paradigm of preventative and individualized medical treatment.

关键词： technological innovation Merging Medical treatment Genomics Real-time systems Internet of Things bioinformatics

来源：评论

学校读者我要写书评

暂无评论

Method of Text Summarization Using Lsa and Sentence based Topic Modelling with bert

Method of Text Summarization Using Lsa and Sentence Based To...

引用

2021 International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021

作者： Gupta, Hritvik Patel, Mayank Geetanjali Institute of Technical Studies 5th Sem B. Tech Computer Science and Engineering Udaipur Rajasthan India

ISBN: (纸本)9781728195377

Document summarization is one such task of the natural language processing which deals with the long textual data to make its concise and fluent summaries that contains all of document relevant information. The branch of NLP that deals with it, is automatic text summarizer. Automatic text summarizer does the task of converting the long textual document into short fluent summaries. There are generally two ways of summarizing text using automatic text summarizer, first is using extractive text summarizer and another abstractive text summarizer. This paper has demonstrated an experiment in contrast with the extractive text summarizer for summarizing the text. On the other hand topic modelling is a NLP task that extracts the relevant topic from the textual document. One such method is Latent semantic Analysis (LSA) using truncated SVD which extracts all the relevant topics from the text. This paper has demonstrated the experiment in which the proposed research work will be summarizing the long textual document using LSA topic modelling along with TFIDF keyword extractor for each sentence in a text document and also using bERT encoder model for encoding the sentences from textual document in order to retrieve the positional embedding of topics word vectors. The algorithm proposed algorithm in this paper is able to achieve the score greater than that of text summarization using Latent Dirichlet Allocation (LDA) topic modelling. © 2021 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

A Statistical Analysis of Impact of COVID19 on the Global Economy and Stock Index Returns

引用

SN computer science 2021年第1期2卷 27页

作者： Verma, Parag Dumka, Ankur bhardwaj, Anuj Ashok, Alaknanda Kestwal, Mukesh Chandra Kumar, Praveen Computer Science and Engineering Uttaranchal University Dehradun India Computer Science and Engineering Women Institute of Technology (Govt.) Dehradun India Computer Science and Engineering Chandigarh University Punjab India Computer Science and Engineering College of Technology G.B. Pant University of Agriculture and Technology Pantnagar India Atal Incubation Center EMPI New Delhi India Yuvayana Tech and Craft (P) Ltd. Uttar Pradesh Bilaspur India

The outbreak of pandemic COVID-19 across the world has completely disrupted the political, social, economic, religious, and financial structures of the world. According to the data of April 22nd, 2020, more than 4.6 million people have been screened, in which the infection has made more than 2.7 million people positive, in which 182,740 people have died due to infection. More than 80 countries have closed their borders from transitioning countries, ordered businesses to close, instructed their populations to self-quarantine, and closed schools to an estimated 1.5 billion children. The world’s top ten economies such as the United States, China, Japan, Germany, United Kingdom, France, India, Italy, brazil, and Canada stand on the verge of complete collapse. In addition, stock markets around the world have been pounded, and tax revenue sources have fallen off a cliff. The epidemic due to infection is having a noticeable impact on global economic development. It is estimated that by now the virus could exceed global economic growth by more than 2.0% per month if the current situation persists. Global trade may also fall from 13 to 32% depending on the depth and extent of the global economic slowdown. The full impact will not be known until the effects of the epidemic occurred. This research analyses the impact of COVID-19 on the economic growth and stock market as well. The aim of this research is to present how well COVID-19 correlated with economic growth through gross domestic products (GDP). In addition, the research considers the top five other tax revenue sources like S&P500 (GPSC), Crude oil (CL = F), Gold (GC = F), Silver (SI = F), Natural Gas (NG = F), iShares 20 + Year Treasury bond (TLT), and correlate with the COVID-19. To fulfill the statistical analysis purpose this research uses publically available data from yahoo finance, IMF, and John Hopkins COVID-19 map with regression models that revealed a moderated positive correlation between them. The model was

关键词： COVID19 Crude oil revenue Gold revenue Gross domestic products (GDP) iShares 20 + year treasury bond revenue Natural gas revenue Regression model S&P500 revenue Silver revenue World economy growth

来源：评论

学校读者我要写书评

暂无评论

A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography

A Secure Data Encryption Mechanism in Cloud Using Elliptic C...

引用

Intelligent and Innovative technologies in Computing, Electrical and Electronics (IITCEE), International Conference

作者： I. Sudha Cecil Donald S. Navya G. Nithya Manivannan balamurugan S. Saravanan Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences – SIMATS Chennai India Department of Computer Science CHRIST (Deemed to be University) Bengaluru India Department of Computer Science Engineering Raghu Engineering College Visakhapatnam India Department of CSE V. S. B College of Engineering Technical Campus Coimbatore India Department of Mathematics Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Tamil Nadu India

Cloud computing is undergoing continuous evolution and is widely regarded as the next generation architecture for computing. Cloud computing technology allows users to store their data and applications on a remote server infrastructure known as the cloud. Cloud service providers, such Amazon, Rackspace, VMware, iCloud, Dropbox, Google's Application, and Microsoft Azure, provide customers the opportunity to create and deploy their own applications inside a cloud-based environment. These providers also grant users the ability to access and use these applications from any location worldwide. The subject of security poses significant challenges in contemporary times. The primary objective of cloud security is to establish a sense of confidence between cloud service providers and data owners inside the cloud environment. The cloud service provider is responsible for ensuring user data's security and integrity. Therefore, the use of several encryption techniques may effectively ensure cloud security. Data encryption is a commonly used procedure utilised to ensure the security of data. This study analyses the Elliptic Curve Cryptography method, focusing on its implementation in the context of encryption and digital signature processes. The objective is to enhance the security of cloud applications. Elliptic curve cryptography is a very effective and robust encryption system due to its ability to provide reduced key sizes, decreased CPU time requirements, and lower memory utilisation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Lung Cancer Detecting using Radiomics Features and Machine Learning Algorithm

Lung Cancer Detecting using Radiomics Features and Machine L...

引用

technological Advancements in Computational sciences (ICTACS), International Conference on

作者： M.N. Rajesh Nikita Tanni Z. Tanveer baig Electronics and Communication Engineering Jain (Deemed-to be-University) Bengaluru India B.Tech in Computer Science and Engineering (Data Science) Christ (Deemed to be University) Bengaluru India Dept of IT Amity University Taskent Uzbekistan

Lung Cancer Incidence across the globe is the second leading cancer type tallying to about 2,206,771 during 2020 and is estimated to rise to about 3,503,378 by 2040 for both male and female sexes and for all ages accounting to 11.4% as per Globocan 2020 [1]. It is the leading death-causing cancer. Lung Cancer [2] in broad terms encompasses Trachea, bronchus as well as lungs. Purpose: The study is aimed to understand Radiomics based approach in the identification as well as classification of CT Images with Lung Cancer when Machine Learning (ML) algorithms are applied. Method: CT Image from LIDC-IDRI [4] Dataset has been chosen. CT Image Dataset was balanced and image features by PyRadiomics library were collected. Various ML features classification algorithms are utilized to create models and matrices adopted in judging their accuracies. The models, distinctive capacity is assessed by receiver operating characteristics (ROC) analysis. Result: The Accuracy scores and ROC-AUC values obtained for various Classification Model are as follows, for Ada boosting, the accuracy score was 0.9993 ROC-AUC was 0.9993 and followed by GbM, the accuracy score was 0.9993, was 0.9992. Conclusion: Extracting texture parameters on CT images as well as linking the Radiomics method with ML would categorize Lung Cancer commendably.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Digital Cottage Hub for Empowering Artisans, Fostering Connectivity, and Promoting ‘Make in India’

Digital Cottage Hub for Empowering Artisans, Fostering Conne...

引用

International Conference on Advances in Information technology (ICAIT)

作者： Vani Hiremani Praveen Gujjar J Sumit Shinde Raghavendra M Devadas Anser Pasha C A Lubna Ambreen Symbiosis Institute of Technology Pune Campus Symbiosis International (Deemed University) (SIU) Lavale Pune Faculty of Management Studies JAIN (Deemed-to-be University) Bengaluru India B. Tech Computer Science and Engineering ITM Skills University Navi Mumbai Department of Computer Science and Engineering Gitam School of Technology Gitam (Deemed-to-be University) Bengaluru India Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

Aims to redefine the landscape of the cottage industry with an innovative social web application designed to simplify the exchange of handcrafted items. At its heart, the platform aims to bridge the gap between producers and customers by providing a thriving marketplace for one-of-a-kind, handcrafted things. With a focus on encouraging job possibilities, particularly for women, the application corresponds with the wider purpose of supporting “women empowerment” and contributing to national efforts such as “Make in India.”The system study highlights the existing holes in present systems, emphasizing the necessity for a complete platform tailored exclusively to the cottage sector. An architecture diagram and extensive use case overviews for customers, producers, and administrators are included in the system design. Implementation specifics include login, identity, purchasing, and administrative operations, among others. The initiative aims to promote not just economic activity in the cottage industry, but also social issues like as empowering women and inclusive employment. The dedication to ongoing development is obvious in the plans for the future, which include tightening security measures, notably for online financial transactions. Finally, the social web application aspires to build a dynamic and safe digital area for artisans, producers, and customers, therefore leaving a lasting impression on the cottage industry in the age of technology. The chatbot is implemented using the rasa open-source framework along with the digital platform. The results of the chatbot are discussed in detail in the results and discussion section.

关键词： Industries Economics Heart Employment Chatbots Remote working Security Information technology System analysis and design business

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：