检索结果-内蒙古大学图书馆

1st International Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Kiran Kumar, M. Amalanathan, Anthoniraj Vellore Institute of Technology School of Computer Science & Engineering Tamilnadu Vellore India

ISBN: (纸本)9798350328042

Lung cancer remains a leading cause of cancer-related deaths globally. Timely identification and categorization of lung nodules are crucial for improving prognoses and survival rates. This review explores various optimization algorithms applied to the detection and classification of lung nodules, analyzing their effectiveness in computed tomography (CT) scans. The study delves into evolutionary, swarm-based, and gradient-based algorithms, evaluating their impact on sensitivity, specificity, accuracy, and computational efficiency. It also compares traditional machine learning, deep learning, and hybrid models while addressing associated challenges and proposing potential solutions. © 2023 IEEE.

关键词： Evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

E-voting system using cloud-based hybrid blockchain technology

引用

Journal of Safety science and Resilience 2024年第1期5卷 102-109页

作者： Beulah Jayakumari S Lilly Sheeba Maya Eapen Jani Anbarasi Vinayakumar Ravi A.Suganya Malathy Jawahar Department of Information Technology Tagore Engineering College Chennai India School of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram ChennaiIndia Department of Information Technology Jerusalem College of Engineering ChennaiIndia School of Computer Science and Engineering Vellore Institute of Technology Chennai India Center for Artificial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia Leather Process Technology Division CSIR-Central Leather Research Institute ChennaiIndia

With the invention of Internet-enabled devices,cloud and blockchain-based technologies,an online voting system can smoothly carry out election *** pandemic situations,citizens tend to develop panic about mass gatherings,which may influence the decrease in the number of *** urges a reliable,flexible,transparent,secure,and cost-effective voting *** proposed online voting system using cloud-based hybrid blockchain technology eradicates the flaws that persist in the existing voting system,and it is carried out in three phases:the registration phase,vote casting phase and vote counting phase.A timestamp-based authentication protocol with digital signature validates voters and candidates during the registration and vote casting *** smart contracts,third-party interventions are eliminated,and the transactions are secured in the blockchain ***,to provide accurate voting results,the practical Byzantine fault tolerance(PBFT)consensus mechanism is adopted to ensure that the vote has not been modified or ***,the overall performance of the proposed system is significantly better than that of the existing *** performance was analyzed based on authentication delay,vote alteration,response time,and latency.

关键词： E-voting Cloud Blockchain Smart contract Consensus mechanism

来源：评论

学校读者我要写书评

暂无评论

AquaVision Dehaze and Enhancement: A Robust Algorithm for Improving Underwater Image Quality in Aquatic Environments 2

AquaVision Dehaze and Enhancement: A Robust Algorithm for Im...

引用

2nd International Conference on computer Vision and Internet of Things, ICCVIoT 2024

作者： Vijayalakshmi, M. Sasithradevi, A. Spoorthi, J.S. Prakash, P. School of Electronics Engineering Vellore Institute of Technology Chennai India Centre for Advanced Data Science Vellore Institute of Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Electronics Engineering Madras Institute of Technology Chennai India

ISBN: (数字)9781837242535

ISBN: (纸本)9781837242672

Underwater imaging is frequently challenged by light scattering, leading to haze, color distortion, and visibility loss. To address these issues, we introduce the AquaVision Dehaze and Enhancement algorithm to improve underwater image quality. Extensive testing on a dataset from an aquaculture environment demonstrates that the algorithm significantly enhances image clarity. Quantitative evaluations reveal high performance across various image quality metrics, with scores of UICM (19.6463), UISM (18.1490), UIConM (26.7463), and UIQM (13.3312). Furthermore, the algorithm delivers competitive results in no-reference image quality metrics, including NIQE (3.6780), Entropy (7.5942), PIQE (52.1444), and BRISQUE (35.9847). These results highlight the algorithm's effectiveness in addressing the challenges of underwater imaging and illustrate the effectiveness through an ablation study. The AquaVision Dehaze and Enhancement algorithm offers a robust solution for improving the quality making it a valuable tool for advancing research in aquatic environments. © The Institution of engineering & technology 2024.

关键词： Aquaculture

来源：评论

学校读者我要写书评

暂无评论

Heart Disease Prediction Using Machine Learning Algorithms

Heart Disease Prediction Using Machine Learning Algorithms

引用

2023 Innovations in Power and Advanced Computing Technologies, i-PACT 2023

作者： Priya, M. Anitha, A. Nallakaruppan, M.K. Raju, J. Raghavan, R. Srivastava, Divyansh School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India School of Electrical Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350325188

Heart disease is one of the destructive infections that an enormous populace of individuals all over the planet grieves. The prediction of heart disease is very much urged because of increasing death rates. The conventional method of prediction isn't adequate for such a disease. Evolving a clinical determination framework based on machine learning concepts gives more exact conclusions than the conventional way for the prediction of such illness. In this paper, we have used different machine learning algorithms to accurately foresee whether an individual has a heart illness or not. The concepts of machine learning like linear prediction KNN, SVM, and, ANN to predict the probability of heart disease in an individual are used. The medical and general details of the person like BMI, alcohol and tobacco consumption, etc. are used to make the prediction. © 2023 IEEE.

关键词： ANN Heart Disease KNN Machine Learning Neural Network SVM

来源：评论

学校读者我要写书评

暂无评论

Detection of Fake Reviews on Products Using Machine Learning 7th

Detection of Fake Reviews on Products Using Machine Learning

引用

7th International Conference on Information and Communication technology for Competitive Strategies, ICTCS 2022

作者： Narayana Royal, M. Reddy, Rajula Pavan Kalyan Sangathya, Gokina Sri Sai Madesh Pretam, B. Kaliappan, Jayakumar Suganthan, C. School of Computer Science and Engineering Vellore Institute of Technology Vellore India Institute of Industry and International Programme Vellore Institute of Technology Vellore India

ISBN: (纸本)9789811993039

It is hard to exaggerate how crucial user reviews are in figuring out an organization’s e-commerce income. Before purchasing any goods or service, online customers rely on product and service reviews. As a result, firms must consider how reliable Internet reviews are because they might directly affect their reputation and bottom line. Because of this, some businesses pay spammers to post false reviews. These false reviews profit from consumer buying choices. As a result, during the past twelve years, there has been substantial study into techniques for spotting false reviews. However, there is still a need for a survey that can analyze and summarize the diverse techniques. In this paper, we are going to put the SVM and Naive Bayesian machine learning model system into place that can spot false reviews with an accuracy of 0.801 and 0.687. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electronic commerce

来源：评论

学校读者我要写书评

暂无评论

Personal Safety and Health Monitoring System for Emergency Assistance using IOT 3

Personal Safety and Health Monitoring System for Emergency A...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Poovanna, K.B. Rai, Arjun Roy, Sritama Vellore Institute of Technology Department of Computer Science Chennai600127 India Vellore Institute of Technology School of Electronics Engineering Chennai600127 India

ISBN: (纸本)9798350372120

Internet of Things (IoT) has the potential to transform how we live and work. One of the most promising applications of IoT is in the area of emergency response. In this research work, we have presented a smart medical application through IoT environment that combines a pulse rate sensor, a geographic sensor, and an SMS sender using SIM800L and Arduino microcontroller. The work has designed to help people in distress by sending their location and pulse rate to the police or a concerned person. The work has the potential to be used to help people in a variety of situations, such as when they are lost, injured, or being attacked. It is significant because it demonstrates the potential of IoT to be used to improve emergency responses. It also highlights the importance of using open source hardware and software in IoT domain. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing

引用

IEEE Access 2025年 13卷 92816-92832页

作者： Slathia, Ashwin Singh Sharma, Abhiram Krishna, P.B. Anand, Saksham Rathi, Ayush Joseph, Linda Gao, Xiao-Zhi Vellore Institute of Technology School of Computer Science and Engineering Chennai600127 India University of Eastern Finland School of Computing Kuopio Finland

Cloud computing plays a crucial role in modern technology, providing scalable and on-demand computing resources. However, excessive resource use can result in higher energy demand, higher operating expenses, and a more significant adverse effect on the environment as per study by A. Berl et al. [1]. In order to forecast and maximize the energy efficiency in cloud systems, this paper presents a machine learning based methodology. Using the Cloud Efficiency Dataset from Google Cloud, key performance indicators such as CPU usage, memory consumption, network traffic, and power consumption were analyzed. Three machine learning models—Random Forest, Naïve Bayes, and Support Vector Machine (SVM) were trained and assessed based on Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and an Equivalent Accuracy metric. Among them Random Forest model performed the best, achieving an RMSE of 0.16 and an accuracy of 96.8 %. To improve the interpretability of the model Explainable Artificial Intelligence (XAI) techniques were applied, specifically SHapley Additive exPlanations (SHAP), to evaluate feature importance. The findings demonstrated that the most important variables which influence energy efficiency are CPU usage and memory consumption. This research develops A novel algorithm based on the XAI results. Unlike static thresholding or heuristic schedulers, our SHAP-driven approach dynamically adapts VMplacement decisions with built-in interpretability. It is capable to efficiently schedule and allocateVirtual Machines on the cloud in a live environment. The proposed framework demonstrates tthe high scalability and real time applicability, making it suitable for the deployment in live cloud environments. While the integration of XAI methods like SHAP enhances interpretability, it introduces additional computational overhead—a trade-off that is justified by the improved transparency and decision making support. © 2013 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Histopathological Analysis for Colon Cancer Diagnosis: A Comparative Study of CNN and Transformer Models with Image Preprocessing Techniques 23th

Deep Learning-Based Histopathological Analysis for Colon Can...

引用

23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Karthik, R. Thalanki, Vaibhav Yadav, Preyash Centre for Cyber Physical Systems Vellore Institute of Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9783031648120

Colon cancer is a serious life-threatening type of cancer that affects the colon and rectum. Manual diagnosis of this disease is time-consuming and la-bor-intensive, requiring pathologists to carefully examine multiple tissue sections and slides per patient. Deep learning techniques offer promising solutions to these challenges. This research investigates the performance of various deep learning architectures, including ResNet50, InceptionResnetV2, NasNet, EfficientNetB0, DenseNet169, ViT, and MobileViT, in histopathology. Four stain normalization methods (Vahadane, Macenko, Reinhard, and ITK) and four image-denoising techniques (Wavelet-based denoising, Gaussian Filtering, Bilateral Filtering, and Median Filtering) were employed to ad-dress staining and noise issues. An ensemble is developed integrating a CNN and a transformer. CNNs excel at extracting local features from images through the use of convolutional layers and pooling operations, while the transformer can capture long-range dependencies. This allows the ensemble to capture intricate local patterns while also considering the relationships be-tween objects, regions, or features that may span the entire image. A quantitative comparative study on the ‘EBHI’ dataset was conducted, resulting in the development of an ensemble model achieving an accuracy of up to 92.02%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Image denoising

来源：评论

学校读者我要写书评

暂无评论

Design and fabrication of a mobile robot for weed removal applications in agricultural fields 3

Design and fabrication of a mobile robot for weed removal ap...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Natesan, Nandan Arunkumar, V. Sathiyavathi, S. Kalaiarassan, G. Vellore Institute of Technology School of Computer Science and Engineering Chennai India Kongu Engineering College Perundurai Department of Mechatronics Engineering Erode India Vellore Institute of Technology School of Mechanical Engineering Vellore India

ISBN: (纸本)9798350372120

Agriculture is one of the most important aspects across the globe which is also a primary task for any country to lead their economic growth and to be a healthy country. The objective of agriculture is to produce various food materials, vegetables and fruits as an outcome of the process. But to provide the outcome from agriculture is not as simple as it looks, Farmers face many issues while making the outcome and they need to work separately to overcome this problem. One of the issues faced by the farmer is the weed management. Weed Management is that the method of dominant that the expansion and removal of the weeds in timely manner. The weeds present in the fields have a major impact on the farmers in terms of their reduction in yield and loss in the capital income. In all recent surveys, it is stated that Weeds present in the field causes almost 60 to 75 percentage loss in agriculture. In order to solve this problem and to give a tentative visioned solution, this project focuses on the development of a mobile robot which can identify the weeds in the field while traversing the field and also capable of differentiating the weeds with crops and other small plants and after the identification, weeds are removed by the weed remover. Apart from removing the weeds this project can also give the small summary of the traversed agricultural land. © 2024 IEEE.

关键词： Machine design

来源：评论

学校读者我要写书评

暂无评论

MIRA: An Affordable Design and engineering of an Autonomous Underwater Vehicle 6

MIRA: An Affordable Design and Engineering of an Autonomous ...

引用

6th International Conference on Control and Robotics, ICCR 2024

作者： Shrote, Sumukh Karunamurthy, K. Gunturu, Shasank Srivatsa, Puvvala Shyam Ganesan, Suganya School of Computer Science and Engineering Vellore Institute of Technology Chennai Chennai India School of Mechanical Engineering Vellore Institute of Technology Chennai Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai Chennai India

ISBN: (纸本)9798331518158

Autonomous underwater vehicles (AUVs) are be-coming crucial for complex subsea tasks such as pipeline in-spection, subsea valve manipulation, and autonomous docking. This paper presents the design and development of an AUV system with Level 4 autonomy, aimed at performing these tasks with high precision and efficiency in challenging underwater environments. To maintain a balance between performance and cost, the AUV relies solely on visual-inertial sensors, eliminating the need for expensive sonar systems. The key features of the proposed system include a low-light multi-sensor vision system for enhanced perception, a robust pressure hull with multiple compartments to protect critical electronics, a static mechanical gripper for subsea manipulation, and an eight-thruster configuration that provides superior maneuverability and stability. These advancements make the AUV a reliable and cost-effective solution for subsea operations, particularly in regions where low-cost alternatives are critical, such as the growing offshore energy sectors of developing nations. © 2024 IEEE.

关键词： Autonomous underwater vehicles

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：