检索结果-内蒙古大学图书馆

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Kumar, C.Siva Vasantha, Lebaku Siroshini, Pacha Jagruthi, Pullaiahgari Pavithra, Nellore Supriya, Thumati Sree Vidyanikethan Engineering College Dept.of Computer Science and Systems Engineering Tirupati India

ISBN: (纸本)9798350348217

Cloud technology is the distribution of physical servers in such processors, memory, networks, connectivity, applications, statistics, as well as smartness only via Online platform so,in addition to allow greater innovative technology, better versatile facilities, plus scalable *** this mechanism, the data owner's maintenance and storage costs can be reduced. Simultaneously, when the data owner loses procurity and physical authority over the data, a security threat arises. As a result, data inspection is required to ensure data integrity over a *** concern is now difficult for information owners because data authority must have been validated thereby preserving confidentiality. In the process of labelling these issues, this paradigm provides secure data acquisition as well as efficient privacy-preserving ***, it now supports multipleownership, data complexities, also an unit identification. A majority intriguing aspect for the process in which examiner will validate ownership of data having little maintenance cost. The system demonstrates that a malware platform will present evidence that is adequate to carry third-party auditors authentication of the user. The scheme's security is analysed and demonstrated at this system to protect data privacy from third-party public auditing while making it impossible for cloud service providers avoids saving the necessary blocks to ignore the *** proposed scheme's best intriguing feature is that it supports all of its crucial elements, such as blocking-free validation, security, process monitoring, as well as information behaviour. © 2023 IEEE.

关键词： Cloud storage

来源：评论

学校读者我要写书评

暂无评论

Pharmacy Location and Recommendation Services

Pharmacy Location and Recommendation Services

引用

2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Dhanalakshmi, R. Vijayaraghavan, N. Valli, R. Prathiba, Sahaya Beni School of Computer Science and Engineering Vellore Institute of Technology Centre for Cyber Physical Systems Chennai India Kcg College of Technology Dept.of Mathematics Chennai India Manakula Vinayagar Institute of Technology Dept.of Electronics and Communication Puducherry India

ISBN: (纸本)9798350315127

The medical sector has continually advanced in recent years. The integration of medical services with a centralized system, on the other hand, is effective in enhancing people's lives thanks to the technology that is currently available. This system will help people to make out their medicinal requirements in their nearby location. If the exact medicine is not available alternative medicines are recommended based on user searched medicine combination it is achieved by using the rank-based algorithm to find similar medicine. This approach will computerize all pharmacy records so that customers and pharmacists can access them whenever and wherever they choose. The proposed system is to lay out a plan of action to the consumers plus pharmacist and do the representation of web services between them. This system intensifies the engagement of unorganized pharmacies into the computerized system to lift medical assistance. In such a way, the system will become the forthcoming way of e-medicinal services and advances the approach of medicinal assistance that are given to the patients by hospitals and doctors. It also helps to get drug availability in every locality © 2023 IEEE.

关键词： Medicine

来源：评论

学校读者我要写书评

暂无评论

Transport Service Scheduling in Remote Regions by the Application of Machine Learning

Transport Service Scheduling in Remote Regions by the Applic...

引用

2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Usha, V. Abhinash, Nalagarla Chiru Sathya, V. Kujani, T. Rao, P. S. Omkara Eswara Kishore, Koneti Leela Vel Tech Rangarajan Dr. Sagunthala R&d Institute Of Science And Technology Dept.of Cse Chennai India Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Dept Of Computer Science And Business Systems Chennai India

ISBN: (纸本)9798350352689

Transportation operations in sparsely populated or rural areas are planned and organized in an efficient manner. The objective is to maximize the efficiency of transport service scheduling in order to cater to the movement requirements of the inhabitants in these regions. The aim is to optimize the functionality and efficiency of transportation services in rural regions by coordinating the available vehicles in a manner that satisfies the needs and preferences of the local populace while also taking into account logistical limitations. The implementation of machine learning incorporates a theoretical and data-driven strategy to enhance the transit timetable decision-making process. A dataset including vehicle capacities, available vehicle counts, and desired travel hours for people is essential to the project code. This project use unsupervised machine learning methods since the data does not have any labels. Clustering is a popular unsupervised machine learning technique because it groups similar data into meaningful categories. Among the clustering techniques that were used were K-Medoids, DBSCAN, Mini-Batch K-Means, and K-Means. Hierarchical clustering is chosen because it can keep the total number of clusters and the number of nodes within each cluster at a constant value. Once the data points have been aggregated using the algorithms, the silhouette score is used to choose the approach that is most suited for vehicle scheduling. The relevance of cluster centers determines the final scheduling of the vehicles. © 2024 IEEE.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Secure and Proficient Provable Data Procurity With Privacy Protection in Cloud Storage

Secure and Proficient Provable Data Procurity With Privacy P...

引用

International Conference on computer Communication and Informatics (ICCCI)

作者： Dr.C.Siva Kumar Lebaku Vasantha Pacha Siroshini Pullaiahgari Jagruthi Nellore Pavithra Thumati Supriya Dept.of computer science and systems engineering Sree vidyanikethan engineering college Tirupati

Cloud technology is the distribution of physical servers in such processors, memory, networks, connectivity, applications, statistics, as well as smartness only via Online platform so,in addition to allow greater innovative technology, better versatile facilities, plus scalable *** this mechanism, the data owner’s maintenance and storage costs can be reduced. Simultaneously, when the data owner loses procurity and physical authority over the data, a security threat arises. As a result, data inspection is required to ensure data integrity over a *** concern is now difficult for information owners because data authority must have been validated thereby preserving confidentiality. In the process of labelling these issues, this paradigm provides secure data acquisition as well as efficient privacy-preserving ***, it now supports multipleownership, data complexities, also an unit identification. A majority intriguing aspect for the process in which examiner will validate ownership of data having little maintenance cost. The system demonstrates that a malware platform will present evidence that is adequate to carry third-party auditors authentication of the user. The scheme’s security is analysed and demonstrated at this system to protect data privacy from third-party public auditing while making it impossible for cloud service providers avoids saving the necessary blocks to ignore the *** proposed scheme’s best intriguing feature is that it supports all of its crucial elements, such as blocking-free validation, security, process monitoring, as well as information behaviour.

关键词： Process monitoring Cloud computing Data privacy Costs Program processors Authentication Maintenance engineering

来源：评论

学校读者我要写书评

暂无评论

Improving E-commerce Fraud Detection via Machine Learning: Comparative Evaluation of Model Effectiveness

Improving E-commerce Fraud Detection via Machine Learning: C...

引用

2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Gangalakshmi, T. Sathya, V. Vinodhini, S. Chandralekha, E. Usha, V. Ravikumar, S. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Dept.of CSE Chennai India Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Dept.of Computer Science and Business Systems Chennai India Velammal Engineering College Dept. of Information Technology Chennai India

ISBN: (纸本)9798350319200

In the fast-growing E-commerce world, fraud has become a major concern, causing economic losses and eroding consumer trust. This work aimed to detect E-commerce fraud using machine learning on a customer dataset. The dataset contained transactional and customer data, requiring preprocessing to handle missing values and categorical features. Four models - Logistic Regression, Random Forest, Gradient Boosting, and Support Vector Classifier - were trained and evaluated for fraud detection accuracy using metrics like Accuracy, Precision, Recall, and F1-Score. Results revealed distinct model strengths and weaknesses. Logistic Regression achieved balanced performance, while Random Forest and Gradient Boosting excelled in certain aspects. Support Vector Classifier also demonstrated competitive results. This work highlights the potential of machine learning in E-commerce fraud prevention, enhancing transaction security and trust. Further research could refine and advance fraud detection techniques for online platforms. © 2023 IEEE.

关键词： E-commerce fraud Fraud detection Hybrid approach Machine learning

来源：评论

学校读者我要写书评

暂无评论

Pharmacy Location and Recommendation Services

Pharmacy Location and Recommendation Services

引用

IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： R. Dhanalakshmi N. Vijayaraghavan R Valli Sahaya Beni Prathiba Centre for Cyber Physical Systems School of Computer Science and Engineering Vellore Institute of Technology Chennai Dept.of Mathematics KCG College of Technology Chennai India Dept.of Electronics and Communication Manakula Vinayagar Institute of Technology Puducherry India

关键词：

来源：评论

学校读者我要写书评

暂无评论

Transport Service Scheduling in Remote Regions by the Application of Machine Learning

Transport Service Scheduling in Remote Regions by the Applic...

引用

International Conference on Communication, Computing and Internet of Things (IC3IoT)

作者： V. Usha Nalagarla Chiru Abhinash V. Sathya T. Kujani P S Omkara Eswara Rao Koneti Leela Kishore Dept.of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Dept of Computer Science and Business Systems Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

关键词： Schedules Machine learning algorithms Systematics Transportation Clustering algorithms Machine learning Scheduling

来源：评论

学校读者我要写书评

暂无评论

Improving E-commerce Fraud Detection via Machine Learning: Comparative Evaluation of Model Effectiveness

Improving E-commerce Fraud Detection via Machine Learning: C...

引用

Innovative Computing, Intelligent Communication and Smart Electrical systems (ICSES), International Conference on

作者： Gangalakshmi T V. Sathya S. Vinodhini E. Chandralekha V. Usha Ravikumar S Dept.of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Dept.of Computer Science and Business Systems Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India Dept. of Information Technology Velammal Engineering College Chennai India

In the fast-growing E-commerce world, fraud has become a major concern, causing economic losses and eroding consumer trust. This work aimed to detect E-commerce fraud using machine learning on a customer dataset. The dataset contained transactional and customer data, requiring preprocessing to handle missing values and categorical features. Four models—Logistic Regression, Random Forest, Gradient Boosting, and Support Vector Classifier—were trained and evaluated for fraud detection accuracy using metrics like Accuracy, Precision, Recall, and F1-Score. Results revealed distinct model strengths and weaknesses. Logistic Regression achieved balanced performance, while Random Forest and Gradient Boosting excelled in certain aspects. Support Vector Classifier also demonstrated competitive results. This work highlights the potential of machine learning in E-commerce fraud prevention, enhancing transaction security and trust. Further research could refine and advance fraud detection techniques for online platforms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Cost Benefit Analysis for Distribution of Threatened Species Based on Climate Change

Research Square

引用

Research Square 2021年

作者： Nandhi Kesavan, R. Latha, K. Anna University Chennai India Dept.of Computer Science& Engineering Anna University BIT Campus Tiruchirappalli India

Among all the threats to global diversity, climate change is the most severe cause. According to the world’s biodiversity conservation organization, reptile species are affected mostly because the biological and ecological traits of the reptiles are strongly linked with climate. To prevent species extinction, we tried to develop a decision support system that incurs the costs and benefits of reintroducing a taxon from its origin to adapt environmental conditions to conserve it from its extinction. The model was developed by applying multiple linear regressions that take the climatic variables and species traits to determine the cost and benefits for the distribution of species. The effectiveness of the model was evaluated by applying it to the Indian Black Turtle, which is an endangered species list in India evaluated by the International Union for Conservation of Nature list. The model recommends moving the species, which is endangered, to the location where it can save itself from climate change. However, the framework demonstrates huge differences in the estimated significance of climate change, and the model strategy helps to recognize the probable risk of increased revelation to critically endangered species. © 2021, CC BY.

关键词： Climate change

来源：评论

学校读者我要写书评

暂无评论

Certain Investigation on IoT Based Cotton Dust Pollution Monitoring in Textile Plants

Certain Investigation on IoT Based Cotton Dust Pollution Mon...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： P Sivanesan Anand J V Trilok Sai Vaddanam Shaik Mohammad Irfan Department of Information Communication Technology School of Computing SASTRA University Thanjavur Tamilnadu India Sri Ramachandra Faculty of Engineering and Technology Sri Ramachandra Institute of Higher Education and Research Chennai Tamil Nadu India Dept. of Computer science and Business Systems SASTRA University Thanjavur Tamilnadu India Dept.of ECE Siddhartha Academy of Higher Education Vijayawada Andhra Pradesh India

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

The objective of the work is to track the level of cotton dust in the textile sector. The IoT-enabled cotton dust monitoring system deploys three sensors: Sharp GP2Y1010AU0F; Shinyei PPD42NS; and Honeywell HPMA115S0-XXX measuring the dust levels. The Optical dust sensor GP2Y1010AU0F has a threshold of 1 mg/mS, which is placed inside the mask and when that threshold is crossed, buzzer alerts the worker with the air contaminants. It measures inhaled cotton dust and sends data to IoT, real-time concentration height of dust into the mobile devices. Experimental results show that Sharp GP2Y1010AU0F sensor has achieved award for acquiring the highest mean dust concentration of 95.167 mg/mS with a standard deviation of 3.014 among the three sensors, while Honeywell HPMA115S0-XXX and Shinyei PPD42NS recorded a mean of 87.833 mg/mS and 77.500 mg/mS, respectively. The observed response times of the sensors as follows for GP2Y1010AU0F-8s, HPMA115S0-XXX-6s, and PPD42NS- 5s, recording the fastest response by Honeywell HPMA115S0-XXX. A comparative study in accuracy, precision and sensitivity, with a response time, shows the merits and demerits for each sensor. Results emphasize the effectiveness of the system proposed for monitoring in terms of airborne cotton dust exposure in improving safety in textile workplaces. A meta-analysis is performed with Bayesian framework using JASP software.

关键词： Sensor phenomena and characterization Software Real-time systems Sensors Safety Bayes methods Pollution measurement Cotton Time factors Monitoring

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：