检索结果-内蒙古大学图书馆

International Conference on Computational science and Technology (ICCST)

作者： R.Sharmikha Sree K. Raja Department of Computer Science and Engineering Sri Sairam Engineering College SRM University Assistant Professor Department of CSE SRM Institute of Science and Technology Ramapuram Chennai

ISBN: (纸本)9781665476560

In cloud forensics, scientific concepts, methods, and approaches are used to find, collect, retain, evaluate, and report digital data in order to reorder events. For everyone involved, including cloud service providers (CSPs), cloud consumers, researchers, and forensic practitioners, cloud forensics is getting increasingly complex. If a criminal want to conceal their dirty laundry, they can use cloud storage to conceal sexual photographs of children, documents related to terrorist groups, etc. To investigate crimes involving the cloud, forensic investigations must be undertaken in the cloud. While attempting to collect evidence, forensic investigators face significant obstacles posed by the cloud's dynamic and dispersed nature. In this paper, Cloud-based forensics professionals are only able to conduct investigations if they have access to the proper tools and techniques for retrieving relevant digital evidence from a device is discussed. It further presents the challenges associated with cloud based forensics and applications to move forward the research in current area.

关键词： Cloud computing Scientific computing Forensics Terrorism Taxonomy Faces Logistics

来源：评论

学校读者我要写书评

暂无评论

Usability Evaluation of Kids’ Learning Apps

Usability Evaluation of Kids’ Learning Apps

引用

Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Amer Ibrahim Murad Al-Rajab Khalid Hamid Muhamamd Aqeel Salman Muneer Mehvish Parveen Maryam Saleem College of Computer and Information Technology American University in the Emirates Dubai United Arab Emirates Assistant Professor Computer Scienc and IT College of Engineering Abu Dhabi University Department of Computer Science Superior University Lahore Pakistan Department of Software Engineering Superior University Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan School of Computer Science NCBAE Lahore Pakistan

The main objective of learning applications is to use modern electronic technologies to impart knowledge, communicate knowledge, and Direct learning models with their learning activities in a timely and effective manner. The preponderance of the apps were designed to up-skill the kids in the fundamentals of letters and numbers. Generally, they were grounded and practice skills in nature, based on a lack of abilities in critical thinking, favoring parrot-fashion skills, and contributing to a deep conceptual comprehension of more specific concepts are unable. By using appropriate evaluation methodologies, the purposed study observes essential characteristics and aspects that affect the usability of interfaces. An evaluation of the app's features will figure out to ensure user contentment. When a kid interacts with a learning interface, the ease of use provided by the interface is validated. Because a large number of the apps were designed to train kids’ fundamentals of alphabetic and numeric. The focus of this research is to see whether self-proclaimed learning apps for kids are built according to developmentally appropriate standards to help kids in formal and informal learning settings develop socially, emotionally, and academically.

关键词： Electronic learning User interfaces Security Usability Standards Business

来源：评论

学校读者我要写书评

暂无评论

Empirical Evaluation of Stock Market Prediction System using Intelligent Learning Scheme with Data Processing Logic

Empirical Evaluation of Stock Market Prediction System using...

引用

Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： S. Prabakar Ankit Kumar R Jayakarthik D. Venkatesh Pratheeba R S Bhola Khan Finance and Accounting ISBR Business School Bangalore Department of Computer Application Faculty of Science Swami Vivekanand Subharti University Meerut Dept of Computer science Saveetha College of Liberal Arts and Sciences SIMATS Assistant Professor of Commerce School of Commerce and Management Mohan Babu University Tirupati Department of Computer Science and Engineering Velammal Institute of Technology Panchetti Department of Regional Economics MJP Rohilkhand University Bareilly India

The Stock Market Prediction System using Intelligent Learning Scheme (SMS-ILS) presented in this study integrates advanced methodologies to enhance the accuracy and reliability of stock market predictions. The system encompasses a preprocessing phase, addressing missing data and outliers, followed by feature extraction utilizing Long Short-Term Memory (LSTM) and Recurrent Neural Networks (RNN) to capture intricate temporal dependencies. A Deep Belief Network (DBN) is employed for classification, categorizing stocks based on learned representations from historical and technical indicators. Grey Wolf Optimization (GWO) optimizes the system's parameters, ensuring adaptability to dynamic market conditions. Notably, the system achieves an impressive accuracy of 97%, emphasizing its efficacy in making correct predictions. This multi-model approach, integrating LSTM, RNN, DBN, and GWO, provides a comprehensive and adaptive framework for navigating the complexities of stock market prediction. The study emphasizes the importance of choosing metrics aligned with specific goals and conducting thorough analysis to ensure the robustness of the evaluation results in the challenging and dynamic context of financial markets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Brain tumour detection and classification from MRI images using CNN

引用

AIP Conference Proceedings 2024年第1期3134卷

作者： T. Aby Abahai Thulaseedhar Arjun S. Sabarinath Babu Jerin Associate Professor Department of Computer Science and Engineering Mar Athanasius College of Engineering Kothamangalam Kerala India Department of Computer Science and Engineering Mar Athanasius College of Engineering Kothamangalam Kerala India

This study compares different CNN architectures for identifying and categorizing brain tumors. Brain tumors are mainly of three types which are Glioma, Meningioma and pituitary adenoma. Tumors can appear in a variety of places, and the location of a tumor may reveal information about the type of cells that are responsible for it, aiding in a more accurate diagnosis. Here we will use MRI to identify and classify tumors. The main issues in MRI are illumination which can provide wrong result. To remove this the these images should be processed before training. To enhance the quality of the MRI, many image pre-processing techniques are used, such as histogram equalization, blurring and thresholding. This will help in faster classification. Six different architectures are compared in this study. These are ResNet50, VGG19, InceptionV3, MobileNet, DenseNet and NASNetMobile. By comparing this architectures we can find which one is more faster and accurate. Also maybe some architecture will be better than others for identifying certain type of tumor. That can also be identified from this. The model will be trained at different epoch to validate the result. About 20 percent of images will be used for testing and remaining are used for training. Also a part of this paper deals with calculation of brain tumor volume from MRI. Finding volume of brain tumor at two different period can help us to identify progression rate. The direction in which tumor is progressing is also identified. This will help with treatment of tumor. Volume is obtained from various slices of MRI of same brain at different locations. From each slices area of tumor is identified by segmentation. Segmentation allows us to obtain tumor part from MRI. Area will depend on number of pixels in tumor part. Two slices will be separated by a distance. This distance is multiplied by area of slice to give its volume. Summing up volume of each slice will give the approximate volume of the tumour. The main problem is eac

关键词：

来源：评论

学校读者我要写书评

暂无评论

Developing a New MapReduce Framework with SVM-based Software Solution for Lyme Lesion Impact on Alzheimer's Disease Prevention

Developing a New MapReduce Framework with SVM-based Software...

引用

International Conference on Trends in Electronics and Informatics (ICEI)

作者： Saravanan. M.S G. Sreehitha Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences and Assistant Professor Sri Padmavati Mahila Visvavidyalayam Tirupathi Andhra Pradesh India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

Alzheimer's disease has many symptoms to occur, one of the latest research studies identified that Lyme disease, caused by “Borrelia burgdorferi” also one of the reasons indirectly affect the neuroinflammation. The dataset used for this research study is supplied by many web sources, that are involved in feature extraction to apply on machine learning techniques for extracting meaningful knowledge. This work proposing a new MapReduce framework-based Support Vector Machine (SVM) model for better prediction of impact of Lyme on Alzheimer's disease. The MapReduce based framework using SVM model creates more impact on prediction of Alzheimer's disease at the earliest. The clinical data with images are collected from distributed environments and applied on preprocessing and feature extraction stages then applied to proposed MapReduce based SVM model for better accuracy and optimal classification for complex patters on Lyme image dataset. From these results the Alzheimer's risk factors are predicted for early treatment process. The results obtained by this study will give early decision making for highly available sources of treatment procedures and gives more insight on preventive care on each and every patient involved in diagnosis of Lyme disease prediction, lead to identify the Alzheimer's disease prediction.

关键词： Support vector machines Accuracy Machine learning algorithms Software algorithms Machine learning Predictive models Feature extraction Software Classification algorithms Alzheimer's disease

来源：评论

学校读者我要写书评

暂无评论

Heart Rate Anomaly Detection in Healthcare Using Elliptic Envelope and Local Forest

Heart Rate Anomaly Detection in Healthcare Using Elliptic En...

引用

3rd International Conference on Machine Learning and Data engineering, ICMLDE 2024

作者： Chandralekha, E. Vinodhini, S. Kandasamy, V. Rama, P. Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamilnadu Chennai600062 India Department of Information Technology Velammal Engineering College Tamilnadu Chennai600062 India Assistant Professor Panimalar Engineering College Tamilnadu Chennai600123 India Department of Computing Technologies College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Chennai603203 India

Medical professionals use Anomaly Detection(AD) to identify patients with potential health problems in the heart rate data (HRD), an essential metric related to cardiovascular health. In this research, the most effective AD techniques were identified in detecting unusual variations of the heart rate pattern. Synthetic HRD data with anomalous rates of 15%, 20%, and 25% was generated and standardized it using min-max scaling for consistency among the datasets. Normal HR was based on function with a mean of 70 and a standard deviation of 5 while anomalous values were generated with a mean of 120 and a standard deviation of 10. Among the evaluated models (Elliptic Envelope, one-class SVM, Local Outlier Factor, and Isolation Forest), the Elliptic Envelope (EE) and Isolation Forest (IF) models obtain the best scores in terms of recall and precision - 0.92 and 0.89, respectively. Overall, the results of this research indicate that equally robust AD models should be implemented within clinical systems and wearable devices that serve as a digital space for early cardiac risk identification, prompting adequate intervention and, as a result, health improvement. © 2025 The Author(s).

关键词： Cardiology

来源：评论

学校读者我要写书评

暂无评论

Blockchain effect on E-commerce: A framework for key research areas

Blockchain effect on E-commerce: A framework for key researc...

引用

Artificial Intelligence and Smart Communication (AISC), International Conference on

作者： Nethravathi K Jeidy Panduro-Ramirez Anita Gehlot Amit Barve Sanjay C. P R. Ponnusamy Department of BMS Jain University Bangalore India Universidad Tecnológica del Perú Uttaranchal Institute of Technology Uttaranchal University India Department of Associate Professor & HOD Parul University Department of IT& Business Analytics Sri Balaji University Pune (SBUP) Department of Computer Science & Engineering Chennai Institute of Technology

Several business applications and procedures are expected to be significantly disrupted by Blockchain-based technologies, which has significant consequences for ecommerce. In light of the potential blockchain based technology are popularly known as "trust building systems" that can be used in multiple business models and standard guidelines which evolved placed above a white period to achieve believe, serviceability, and enforcement in various domains such as cunsumers related business, business related connections have to be questioned and possibly adjusted. By enabling trustless trade interactions that work without specialized intermediaries or even central authority in the case of permission lessblock chains, Blockchain has the power to change how electronic commerce operates. Furthermore, giving universal access to immutable data across the whole supply chain may significantly alter the information and value exchange between businesses and consumers. The methodology presented in this paper are intended to motivate further study of the potential effects of Blockchain on e-commerce. Technology, law, organizational and quality challenges, as well as consumer difficulties, are the four key categories. This paper demonstrates how Blockchain may affect many Electronic commercial components in these relevant fields.

关键词： Technological innovation Law Biological system modeling Supply chains Trustless services Blockchains Cryptocurrency

来源：评论

学校读者我要写书评

暂无评论

Integration of Semantic Features for Short and Long Text Classification using Attention Based DL

Integration of Semantic Features for Short and Long Text Cla...

引用

Communications and Information Technologies (GCCIT), Global Conference on

作者： N. Thangarasu Vaibhav Kaushik Satvik Vats G. Indira M. Sudhakara Reddy Yogesh K. Sharma Department of Computer Science Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Computer Science and Engineering Graphic Era Hill University Dehradun Adjunct Professor Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Electrical and Electronics Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai School of Sciences Physics & Electronics JAIN (Deemed to be University) Bangalore Karnataka Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

The categorization of text is an essential and pivotal step in the process of natural language understanding and processing. There are a lot of different approaches to solving the problem of classifying text, but very few of them leverage the semantic integration of several views to boost the classification performance. A dual-DL attention network model, referred to as DDL, is proposed in the study. In order to address the knowledge gap, this paradigm employs semantic complementarity. For more precise extraction of textual logical semantics, DDLfirst employs transductive learning and graph structure. The next step is to use logical semantics in the attention fusion layer (Channel) to train other semantics jointly, which will gradually fix the predictions produced using unlabeled test data. Important for upcoming text mining jobs, experiments show that DDL can achieve better classification across a variety of text classification datasets.

关键词： Text mining Semantics Text categorization Natural language processing Information and communication technology

来源：评论

学校读者我要写书评

暂无评论

CPS, Sustainability and Efficiency in an Aquaponic Greenhouse

Renewable Energy and Power Quality Journal

引用

Renewable Energy and Power Quality Journal 2022年 20卷 210-215页

作者： Galvão, J. Santos, P. Aires, L. Neves, F. Department of Electrical Engineering/ESTG Polytechnic of Leiria Leiria2411-901 Portugal LSRE-LCM-Laboratory of Separation and Reaction Engineering Laboratory of Catalysis and Materials Escola Superior de Tecnologia e Gestão Instituto Politécnico de Leiria Leiria2411-901 Portugal ALiCE-Associate Laboratory in Chemical Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal R&D Unit Institute for Systems Engineering and Computers/INESC Coimbra Portugal Department of Computer Science Polytechnic of Leiria Leiria2411-901 Portugal

Nowadays the humanity needs to produce food in greater quantity and quality, in order to satisfy citizens and markets, supported by advanced technologies such as cyber-physical system (CPS) or intelligent systems where software and electronic devices and receivers of physical variables are mechanisms that control the management of multiple actions inherent to plant growth. Electronic devices and receivers of physical variables are mechanisms that involve a network of IoT components and control multiple actions inherent to plant growth in agricultural greenhouses, which in short, are intensive food production systems. In this context, this paper presents a case study that uses a monitoring and management system that considers environmental parameters measured inside a greenhouse, allowing the manager to assess the working status of an aquaponic systems, and detect critical conditions that require quick decisions in real time. It is intended to develop technology that can be used in greenhouses, close to consumer centres or cities, to mitigate the impact of transport, lowering CO2 emissions resulting from the distribution channels between the producers and consumers. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

A quantifiable framework for ‘Covid-19 exposure’ to support the Vaccine prioritization and resource allocation for resource-constraint societies

引用

Urban Governance 2021年第1期1卷 23-29页

作者： Biswas, Rathin Arya, Supreeta Arya, Kavi Project Manager Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai 400076 India Ex-Professor Radio-diagnosis Tata Memorial Hospital Mumbai Member Expert Committee National Cancer Grid India Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai 400076 India

As the pandemic COVID-19 has severely affected the entire world, it became the utmost necessity of careful prioritization and utilization of limited medical resources, especially for the resource-constraint societies. This requirement along with the asymptomatic nature of COVID-19 in a significant proportion of the population, has prompted the need for a risk assessment tool-kit that can provide a rational behind prioritization and allocation of limited available medical resources. The purpose of this study is to compose a scientific-rationale-based ‘COVID-19-Self-Assessment-Test’ (C19SAT) framework, which helps develop a basis for measuring the risk of COVID-19 exposure with self-assessment. The study comprises of two major parts- (1) identification of key components of the C19SAT framework by studying various guidelines (WHO & CDC) and relevant literature, and (2) quantification of those components by assigning weight through the analysis of survey results and opinions from medical physicians and experts. A C19SAT framework is developed to measure the risk of covid-19 exposure, comprising a set of identified components (12 parameters and their corresponding attributes) and their corresponding weights. As the scientific rationale behind such assessment framework has not been reported to date in case of available mobile applications and web-based toolkit, the present study brings the novelty and reports the construction of such a framework. The study opens up untouched research and discussion on the composition of the COVID-19 exposure-measurement framework, which can help in vaccine prioritization and resource allocation. Further studies can be carried out on refining the framework for better understanding and effectiveness towards urban health governance. © 2021 The Author(s)

关键词： COVID exposure Health Resource allocation Self-assessment Vaccine prioritization

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：