检索结果-内蒙古大学图书馆

International Journal of Systematic Innovation 2025年第1期9卷 116-128页

作者： Kavitha, P. Shakkeera, L. School of Computer Science Engineering & Information Science Presidency University Bangalore India

Machine and deep learning methods have gained significant prominence in the healthcare industry, particularly for the prediction of cardiac diseases. The increasing prevalence of heart-related diseases underscores the necessity for proactive and accurate healthcare interventions. Machine learning, a data-driven approach, can play a crucial role in recognizing and addressing cardiovascular risks. To achieve this, researchers have utilized a range of classification techniques, such as Support Vector Machines, Random Forests, and Naive Bayes, to unravel the intricate aspects of heart disease prediction. Additionally, ensemble learning techniques, especially Stacking Technique, is employed to further enhance predictive accuracy. However, the ensemble approach has certain limitations. Therefore, confusion matrices are utilized for thorough evaluation and validation, offering better classifier performance. As research advances, prediction models aim to achieve higher accuracy and generalizability. Insights from confusion matrices can help researchers to make more robust and dependable predictions. Future research will investigate the deep learning models to detect subtle patterns in electrocardiogram data, with the aim of enabling earlier identification of cardiovascular conditions. Additionally, the integration of wearable sensor technologies holds promise for continuous risk monitoring and the development of personalized healthcare interventions. These technological advancements possess the potential to fundamentally transform the field of cardiac care, facilitating earlier disease diagnosis and substantially enhancing patient prognosis. In conclusion, the convergence of machine learning and deep learning models heralds a novel era for precision medicine, where data-driven insights empower stakeholders to tackle formidable challenges with unparalleled effectiveness. © (2025), (Society of Sytematic Innovation). All rights reserved.

关键词： Artificial Neural Network Cardiovascular Diseases Data Analysis Pattern Classification Data Mining Heart Disease Prediction Support Vector Machine

来源：评论

学校读者我要写书评

暂无评论

Enhanced Triple Layered Approach for Mitigating Security Risks in Cloud

引用

computers, Materials & Continua 2025年第4期83卷 719-738页

作者： Tajinder Kumar Purushottam Sharma Xiaochun Cheng Sachin Lalar Shubham Kumar Sandhya Bansal Computer Science&Engineering Department Jai Parkash Mukand Lal Innovative Engineering&Technology InstituteRadaur135133HaryanaIndia School of Computer Science&Engineering Galgotias UniversityGreater Noida203201Uttar PradeshIndia Computer Science Department Bay Campus Fabian WaySwansea UniversitySwanseaSA18ENUK Department of Engineering and Technology Gurugram UniversityGurugram122003India Presidency School of Computer Science Presidency UniversityBangalore560089India Maharishi Markendeshwar Engineering College Maharishi Markandeshwar(Deemed to be)UniversityMullanaAmbala133203India

With cloud computing,large chunks of data can be handled at a small ***,there are some reservations regarding the security and privacy of cloud data *** solving these issues and enhancing cloud computing security,this research provides a Three-Layered Security Access model(TLSA)aligned to an intrusion detection mechanism,access control mechanism,and data encryption *** TLSA underlines the need for the protection of sensitive *** proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard(AES).For data transfer and storage,this encryption guarantees the data’s authenticity and ***,the solution employs the AES encryption algorithm to secure essential data before storing them in the Cloud to minimize unauthorized ***-based access control(RBAC)implements the second strategic level,which ensures specific personnel access certain data and *** RBAC,each user is allowed a specific role and *** implies that permitted users can access some data stored in the *** layer assists in filtering granular access to data,reducing the risk that undesired data will be discovered during the *** 3 deals with intrusion detection systems(IDS),which detect and quickly deal with malicious actions and intrusion *** proposed TLSA security model of e-commerce includes conventional levels of security,such as encryption and access control,and encloses an insight intrusion detection *** method offers integrated solutions for most typical security issues of cloud computing,including data secrecy,method of access,and *** extensive performance test was carried out to confirm the efficiency of the proposed three-tier security *** have been made with state-of-art techniques,including DES,RSA,and DUAL-RSA,keeping into account Accuracy,QILV,F-Measure,Sensitivity,MSE,PSNR,SSIM,and computation time,encryption time,and decryption *** proposed

关键词： Cloud security:data encryption AES access control intrusion detection systems(IDS) role-based access control(RBAC)

来源：评论

学校读者我要写书评

暂无评论

Automatic lung cancer detection and classification using Modified Golf Optimization with densenet classifier

引用

International Journal of Information Technology (Singapore) 2025年第3期17卷 1551-1559页

作者： Shanthi, S. Smitha, J.A. Saradha, S. School of Computer Science & amp Engineering Presidency University Bengaluru India Department of CSE Sri Sairam College of Engineering Bangalore India Department of CSE Sri Eshwar College of Engineering Coimbatore India

One of the most common diseases in recent years has been lung cancer. In the US, around 200,000 new instances are reported annually, based on studies in this area. Malignant tumors are created when lung cells proliferate and expand out of control. Convolutional Neural Networks (CNN), in particular, are deep learning algorithms that have emerged as the best method for autonomously diagnosing illness in recent times. In the literature, some methods are reviewed, but they do not provide efficient detection. A few techniques are evaluated in the literature, however, they don't offer effective detection. To classify lung cancer, the Optimal DenseNet is therefore built in this study. DenseNet and Modified Golf Optimization (MGO) were used in the creation of this structure. The MGO selects the best hyperparameters for fully connected layers (number of hidden units, number of fully connected layers) and convolution layers (size and number of filters). Initially, lung cancer images were gathered and taken into consideration for the data analysis procedure. The next step is feature extraction, which uses wavelet, texture, and histogram characteristics to extract the important information from the enhanced images. The categorization stage receives the features. Using the image, lung cancer is classified as either malignant or non-cancerous at the classification step. MATLAB is used to implement the suggested approach, and metrics are calculated for validation. The method's performance is justified by drawing comparisons with conventional approaches. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： DenseNet Histogram features Lung cancer Modified Golf Optimization Textural features Wavelet features

来源：评论

学校读者我要写书评

暂无评论

Secure mobile cloud data using federated learning and blockchain technology

International Journal of Systematic Innovation

引用

International Journal of Systematic Innovation 2025年第2期9卷 26-36页

作者： Matheen Fathima, G. Shakkeera, L. Sharmasth Vali, Y. School of Computer Science Engineering and Information Science Presidency University Karnataka Bengaluru India

In the current era, mobile cloud (MC) transactions raise concerns over the data stored in the MC. These data can be tampered with by third parties, leading to data loss and information misplacement. Such security breaches can be mitigated by implementing federated learning (FL). FL refers to a distributed data learning approach that trains data without revealing the information to the server or coordinator. It uses the current model data for training and then sends the updated model to the coordinator or server. The server collects the updated trained models from all clients and aggregates them into a single global model. This updated model is then communicated back to the clients. FL, when implemented with MC, protects user privacy, ensures efficient learning, and achieves higher accuracy compared to traditional machine learning algorithms. We propose the implementation of MC FL using blockchain, a model designed to protect user data by maintaining it on edge devices and sending the updated model to the server after training. Finally, the data-generated model will be stored in the blockchain network, preventing data tampering and providing a higher level of security and privacy for the data. © (2025), (Society of Sytematic Innovation). All rights reserved.

关键词： Blockchain Data Security and Integrity Federated Learning Mobile Cloud Computing

来源：评论

学校读者我要写书评

暂无评论

Real-Time Classification of Defects During Automated Valve Testing and Inspection 5th

Real-Time Classification of Defects During Automated Valve T...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Singh, Shweta Agarwal, Trapty Haripriya Hemlata School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India

ISBN: (纸本)9789819780426

This paper offers a singular method for actual-time type of defects at some point of computerized valve testing and inspection. Mainly, an image processing gadget is developed to discover and classify various defects which includes cracks, dents, foreign items, and different floor irregularities. The machine includes a high-decision digital camera, LED lighting fixtures, processing unit, and defect reputation algorithm. The image processing system captures the picture and methods it to pick out the illness regions. The gadget then extracts the features from every of the detected regions and classifies them the usage of a guide Vector device. The model is demonstrated with manually received pics, and the outcomes show true overall performance in terms of accuracy and speed. Similarly, the system can alert the consumer whilst a potential disorder is identified and the defects can then be in addition inspected and repaired. This approach has the ability to lessen inspection time, enhance manufacturing efficiency, and reduce charges. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lighting fixtures

来源：评论

学校读者我要写书评

暂无评论

Early Detection of Amyotrophic Lateral Sclerosis with Time Collection Evaluation 5th

Early Detection of Amyotrophic Lateral Sclerosis with Time C...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Mehar, Palavancha Tirumala Krishna Agarwal, Trapty Suneetha, K. Ahmad, Naseem School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India

ISBN: (纸本)9789819780426

This paper discusses the usage of time series analysis for the early detection of Amyotrophic Lateral Sclerosis (ALS). A time series approach was used to expand a set of rules that may detect the early stages of ALS via analyzing symptomatic changes in signs and symptoms consisting of muscle energy, taking walks potential, speech, swallowing, and different bodily motion. This technique become examined on a retrospective dataset, and proven if you want to come across changes in the circumstance of ALS in a well-timed way. The outcomes suggest that this technique has ability as a tool for early detection in ALS sufferers. The proposed algorithm ought to potentially be used to improve the present day standard of care and help lead to in advance analysis and higher scientific effects. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Motion Potential Swallowing

来源：评论

学校读者我要写书评

暂无评论

Utilizing Support Vector Machines for Signal Processing in Telecommunications 5th

Utilizing Support Vector Machines for Signal Processing in T...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Mishra, Awakash Mehta, Deepak Arya, Rakesh Prasad, P.S. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

SVMs had been effectively applied to various signal processing tasks in Telecommunications, along with goal detection and category in cognitive radio networks, channel estimation, exploiting spatial variety for multipath wireless conversation channels, interference cancellation, and era of feature vectors for sign type. In goal detection and category in Wi-Fi conversation networks, SVMs may be used to come across and classify specific types of wireless signals with an excessive diploma of accuracy. The input characteristic vectors are comprised of the signal’s spectrum and temporal features, and they are used for the education of the SVM classifier. In channel estimation, SVMs may be used to estimate the unknown channel parameters in Wi-Fi conversation channels with a low but suitable suggest-squared-blunders charge. That is viable via exploiting the diversity of more than one received signal replicas and the usage of the predicted channel parameters to improve signal reception. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wi-Fi

来源：评论

学校读者我要写书评

暂无评论

Innovative Image Processing Techniques for Automating Cosmetic Inspection 5th

Innovative Image Processing Techniques for Automating Cosmet...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Panwar, Govind Singh Murthy, D.H.R. Agarwal, Trapty Jaison, Feon Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Progressive photograph processing techniques were developed for automating the technique of beauty inspection. These techniques make use of the wealthy, unique image records of the inspected objects to hastily become aware of diverse product defects. Specifically, object features including coloration, texture, size, shape, and location are first extracted from the photograph, and every function is then evaluated to come across cosmetic defects. Following the detection technique, the extracted capabilities are used to at once alter the manufacturing technique, enabling faster production turnaround times and progressed product quality. The strategies are designed to make certain rapid and accurate product inspection and also provide a bendy adjustment of parameters for various types of cosmetic merchandise. With these techniques, producers are capable of reduce cosmetically based totally product defects and supply improved great merchandise in a shorter time frame. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inspection

来源：评论

学校读者我要写书评

暂无评论

Detecting Electromagnetic Vulnerabilities in Networking Topologies 5th

Detecting Electromagnetic Vulnerabilities in Networking Topo...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Preethi, D. Verma, Upendra K. Arumugam, Jayachandran Alam, Intekhab Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

This paper describes a technique of detecting electromagnetic vulnerabilities in networking topologies, consisting of Wi-Fi communications. A green approach is offered which entails the mixture of electromagnetic measurements from multiple antennae, and the utility of parameterization, optimization and clustering algorithms. Effects are generated to offer a complete breakdown of the electromagnetic residences of a community topology, permitting identity of weaknesses or regions of vulnerability. The resulting vulnerabilities may be used to guide layout changes, or as a first indicator of potential security problems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Analyzing the Role of Time Series Analysis in Early Detection of Pancreatic Cancer 5th

Analyzing the Role of Time Series Analysis in Early Detectio...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Kavitha, R. Singh, Yudhveer Madhusudhan, M.V. Mishra, Awakash Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Pancreatic cancer is a vital disorder that is still the number one motive of lack of lifestyle, with a five-12 months survival fee of only 9. Early detection of pancreatic cancers is fundamental to beautifying outcomes. However, it could be tough to stumble on based totally on scientific and imaging outcomes myself. Time collection evaluation offers a progressive technique to sources in the early detection of pancreatic cancer. This paper proposes to research time series analysis for analysis and early detection of pancreatic cancers. Time series evaluation is a powerful series of techniques for analyzing statistics and temporal records, biological alerts, or healthcare facts. It uses a sequence of observations taken through the years to assess patterns and traits in facts, which could tell osteoporotic fracture hazards or provide early sickness signs and symptoms. Previous research has assessed time series evaluation's efficacy in detecting cardiovascular ailments and influenza. However, there may be a shortage of research examining the application of time series evaluation for pancreatic cancer detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

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：