检索结果-内蒙古大学图书馆

2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Deshpande, Sonali Kulkarni, Nilima Mit Art Design and Technology University Mit SoC Computer Science & Engineering Department Pune India

ISBN: (纸本)9798331528713

Neuroimaging and deep learning have become the focus of much research for diagnosing Alzheimer's disease (AD) in recent years. Nevertheless, the limited availability of neuroimaging training data has resulted in significant overfitting issues for several deep learning models. However, the dataset was very imbalanced. To address this issue, we employed several augmentation techniques such as flipping, rotating, and zooming to balance the dataset. The ADNI dataset consisted of four classes: mild demented, moderate demented, very mild demented, and non-demented. In this work, we have proposed an ensemble of EfficientNetB2, DenseNet121, VGG16, and Xception for the diagnosis of Alzheimer at early stage. Experiment results shows that EfficientNetB2 ensemble with Xception and VGG16 performed extremely well with 99.1% and 99.4% respectively. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Establishing a Secure Mobile Online Banking System using AES 3

Establishing a Secure Mobile Online Banking System using AES

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Karpagalakshmi, R.C. Lenin, J. Robin Rohit, V. Saravanan, K. Rajesh Sharma, R. Banshal, Sumit Kumar Alliance College of Engineering and Design Alliance University Department of Computer Science and Information Technology Bangalore India School of Computer Science & Engineering and Information Science Presidency University Bangalore India New Horizon College of Engineering Department of Information Science Engineering Bangalore India

ISBN: (纸本)9798331518592

Using a mobile phone or other portable device to conduct financial transactions online is known as 'mobile banking.' Activities such as verifying one's account balance, transferring funds to another account, making bill payments, and finding a local automated teller machine (ATM) are included under this classification. Due to the significant expenses associated with implementing this technology, Authentication of users, data privacy, non-repudiation, data integrity, and obtainability of services are all areas where people have voiced concerns. The analysis described in this paper introduces a more advantageous and convenient framework for addressing these issues. The proposed approach effectively accomplishes its intended goals via the use of a widely adopted technique known as salting, which involves the application of the Secure Hash Algorithm (SHA512) to obfuscate sensitive information such as user IDs and passwords. The encoding and decoding procedures used the Advanced Encoding Standard (AES) technique while implementing one-time passwords (OTPs) was implemented to enhance user authentication. The design approach used PHP, JScript, CSS, and a MySQL database. The password recovery technique was used to assess the model's credibility and reliability and acquire the outcomes. This program enhances the process of recovering passwords across various scenarios. It intercepts network traffic using dictionary attacks, brute-force assaults, and cryptanalytics attacks to decrypt encrypted passwords. Additionally, it uncovers password bins, retrieves secreted passwords and analyses routing protocols. The gathered findings support the idea's feasibility since the encrypted and hashed data demonstrates resistance to unauthorized access. © 2024 IEEE.

关键词： Automatic teller machines

来源：评论

学校读者我要写书评

暂无评论

Addressing Challenges and Opportunities in Precision Medicine Using Deep Learning and Personalized Cancer Treatment 3

Addressing Challenges and Opportunities in Precision Medicin...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Ghantasala, G. S. Pradeep Kumari, Nalli Vinaya Rajesh Sharma, R. Vidyullatha, Pellakuri Sungheetha, Akey Bathool, Saliha Alliance College of Engineering and Design Alliance University Department of Computer Science and Engineering Bengaluru India Malla Reddy Engineering College for Women Jntuh Department of Computer Science and Engineering Hyderabad India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaddeswaram Andhra Pradesh Guntur India

ISBN: (纸本)9798331518592

The primary aim of personalized cancer treatment is to increase effectiveness and reduce side effects by tailoring therapies based on a patient's unique genetic and molecular characteristics. This research investigates how deep learning is transforming personalized cancer care through its ability to process and analyze complex, high-dimensional data. The study explores the use of deep learning techniques in predicting tumor classifications, genetic mutations, and treatment responses by integrating clinical data, genomic profiles, and medical imaging. It reviews recent advancements in deep learning applications for cancer, such as targeted therapy through genetic profiling, tumor identification from histopathology images, and optimization of treatment protocols. Additionally, the paper discusses challenges including model transparency, clinical integration, and data security. The study demonstrates how deep learning can enhance patient outcomes and outlines future opportunities for this evolving area of cancer care. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Data Mining and Identification of Influencing Factors for Effective Load Forecasting of A Substation Using Machine Learning Regressors 8

Data Mining and Identification of Influencing Factors for Ef...

引用

8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Kamath, Anantha Krishna Rajalakshmi Samaga, B.L. Canara Engineering College Visvesvaraya Technological University Department of Computer Science and Design Mangalore India India

ISBN: (纸本)9798350350593

Electric load forecasting (ELF), which is a fundamental step in the planning of the energy industry and is important for managing power systems and electric capacity scheduling, has drawn growing academic interest. Therefore, for the planning of energy generating capacity and for power system management, the accuracy of electric load forecasting is crucial. Recently, Load forecasting using Machine learning algorithms are the area of interest. Model designed based on featured data provides better result compared to that of based on raw data. Thus, data mining and feature extraction of raw data is the trending area for researcher. This paper deals with Data mining of historical data of Talapady substation through graphical approach and identifies the influencing factors such as season, month etc. Moreover, this work provides a brief idea to research scholars on how to analyze historical data and to identify the influencing factors through analysis. Proposed work validated using random forest regressor model. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Bridging the Modality Gap: Generative Adversarial Networks for T1-T2 MRI Image Translation 15

Bridging the Modality Gap: Generative Adversarial Networks f...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Pandey, Mayank Kunda, Naga Sai Shreya Pranave, K.C. Singh, Tripty Nair, Rekha R. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India Alliance University Alliance College of Engineering and Design Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

CycleGAN, a significant deep learning model, has transformed medical imaging by providing a remedy for translating MRI images between different modalities. Its ability to transform T1-weighted to T2-weighted images is crucial in healthcare environments where obtaining multiple scans can be time-consuming and burdensome for patients. This can be achieved by utilizing CycleGAN, which generates images that contains vital information that will help the healthcare professionals to diagnose the patient without exposing them to further radiations. This unleashes an effective and safer way of diagnosing patients. The adaptability of CycleGAN also allows scalability and the ability to customize it for different types of medical images, where scanning can be achieved with less exposure to radiation, without loosing or compromising any important information. © 2024 IEEE.

关键词： Discriminator GAN Generator Magnetic Resonance Image T1 T2

来源：评论

学校读者我要写书评

暂无评论

A novel approach to detect, analyze and block adversarial web pages

引用

International Journal of Information Technology (Singapore) 2024年第6期16卷 3617-3622页

作者： Kumar, M. Ranjith Naik, Darshana A. Kapila, Neha Mohan, Chinnem Rama Prasad, Ch Raghava Shelke, Chetan Rao, C. V. Guru School of Computer Science and Engineering Vellore Institute of Technology Department of Computer Science and Engineering M S Ramaiah Institute of Technology Department of Electronics and Electrical Engineering Lovely Professional University Department of Computer Science and Engineering Narayana Engineering College Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Alliance College of Engineering and Design Alliance University School of CS & amp AI SR Universtity

The phenomenon of distraction is very common, and its adverse effects are seen among people. The major cause underlying this issue is the ease with which adversarial web sites and web pages can be accessed. It is of utmost importance to locate, evaluate, and actively block such web pages in an effort to comprehensively and globally solve this societal issue. Thus, the given paper proposes an extension or plug-in to detect, analyze, and block websites smartly. The proposed approach takes keywords entered by the user as input into consideration, which eventually leads to the generation of web pages and web links. The filtering of web links is done by the proposed extension, followed by the extraction of features, the utilization of support vector machines (SVM) for binary classification, and the summarization of textual data using natural language processing (NLP). Lastly, the precise results corresponding to relevant web links are presented to the users, which will increase their productivity, thereby reducing their distraction levels under all working circumstances. The performance of the proposed approach is validated against existing recent studies based on evaluation metrics such as adversarial website detection time (ms) and accuracy (%). © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Adversarial web pages Distraction Natural language processing (NLP) Support vector machine (SVM) Text summarization

来源：评论

学校读者我要写书评

暂无评论

Attention Based CNN to Improve Identification of Ischaemia and Infection in DFU

Attention Based CNN to Improve Identification of Ischaemia a...

引用

2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Bhowmick, Priya Revanth, K. Lakshmi, Parlapalli Das, Sujit Kumar Babu, Tina Alliance University Alliance College of Engineering and Design Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350317060

Diabetic foot ulcers (DFUs) frequently occur as complications of diabetes. Identifying infection and ischaemia in DFUs is crucial for wound assessment and treatment planning. Recent advancements in deep learning have shown promise in classifying infection and ischaemia in DFUs using computerized methods. Many modern systems for classifying DFU images rely on deep neural networks, particularly convolutional neural networks. These networks analyze distinctive features and predict class probabilities based on these features. During testing, predictions are made using individual input images and trained parameters. To harness the information in training data more effectively, this study introduces the concept of an attention layer. This layer aids neural networks in memorizing long sequences of data, mitigates issues like exploding gradients, and enhances model accuracy. Experimental results demonstrate that this proposed approach significantly improves the accuracy of DFU infection and ischaemia detection. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Gauging Deep Learning Archetypal Effectiveness in Haematological Reclamation

引用

SN computer science 2024年第7期5卷 963页

作者： Pradeep kumar, B.P. Ravikumar, J. Dept. of Computer Science and Design Atria Institute of Technology VTU Karnataka Bangalore India Dept. of Computer Science and Engineering Atria Institute of Technology VTU Karnataka Bangalore India

This paper project an system for reclamation of medical images in an effective way for the extraction and retrieving of data from large archives is critical. This study aims to improve haematological image reclamation by combining visual-based image reclamation (VBIR) approaches with the GLCM algorithm, specifically for characteristics related to the prostate gland. While previous research has focused on computer-aided methods for Gleason grading, our technique focuses on early-stage feature reclamation across 14 paired glands. The experimental findings, including Bicubic Interpolation The resolution Enrichment with a standard deviation of 12.37, kurtosis of 122.83, and skewness of 2.92, demonstrate improved reclamation performance. Our suggested methodology uses a handmade learning approach that includes critical components such as GLCM contrast and correlation. This extensive feature extraction step includes descriptors for morphology, texture, fractals, and contextual information, which are then subjected to in-depth statistical analysis to identify significant features. Using an RNN, our technique improves performance somewhat but significantly when compared to alternatives, with time required for execution offering insights into the intricate interaction of stages and the effect of sample variability. These findings not only encourage more research, but also help to advance standard reviews in haematological analysis of images. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Gland reclamation Gray-level co-occurrence matrix (GLCM) Haematological Haematological image Prostate gland

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Consumer Behavior Regarding Food Delivery Applications in India 4

Evaluation of Consumer Behavior Regarding Food Delivery Appl...

引用

4th International Conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Titus, Ray Babu, Tina Nair, Rekha R Sharma R, Rajesh Chinnaiyan, R. Sungheetha, Akey Alliance University Bengaluru India Alliance University Alliance School of Engineering and Design Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350307757

This article investigates customer behaviour towards meal delivery apps, focusing on factors such as restaurant diversity, food packaging quality, application design, and user interface. According to the study, having a varied choice of eateries increases consumer happiness, which leads to more app usage. However, the quality of food packaging has no meaningful impact on overall satisfaction. Fortunately the study emphasises the importance of application design and user interface in influencing consumer behaviour. Both factors have a substantial impact on overall happiness, with user-friendly interfaces attracting new users and encouraging frequent app usage. The findings highlight the necessity of organisations addressing these characteristics in order to improve customer satisfaction, increase app engagement, and create long-term client loyalty. Understanding and adapting to client preferences in these areas can help food delivery applications compete successfully. © 2024 IEEE.

关键词： Consumer behavior

来源：评论

学校读者我要写书评

暂无评论

Drawing Order Diagrams Through Two-Dimension Extension

引用

Journal of Graph Algorithms and Applications 2023年第9期27卷 783-802页

作者： Dürrschnabel, Dominik Hanika, Tom Stumme, Gerd Knowledge & Data Engineering Group Research Center for Information System Design & Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Computer Science University of Hildesheim Germany Berlin School of Library and Information Science Humboldt-Universität zu Berlin Germany

Ordinal real-world data such as concept hierarchies, ontologies, genealogies, or task dependencies in scheduling often has the property to not only contain pairwise comparable, but also incomparable elements. Order diagrams provide an important tool for understanding and thus discovering knowledge in such data. Easily readable drawings of such order diagrams are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work, we present the novel algorithm DimDraw to decompose an ordered set (e.g., a concept hierarchy) in linear orders and to produce a corresponding order diagram. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of its transitive incompatibility graph. To evaluate the quality of the algorithm, a user study was conducted where generated drawings were compared with ones from state-of-the-art drawing algorithms. © 2023 Brown University. All rights reserved.

关键词： Set theory

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：