2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)最新文献_第8页

Computational Intelligence Approach to Improve The Classification Accuracy of Brain Tumor Detection 提高脑肿瘤检测分类准确率的计算智能方法

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047792

S. K. UmaMaheswaran, S. Deivasigamani, Kapil Joshi, Devvret Verma, Santhosh Kumar Rajamani, Dhyana Sharon Ross

{"title":"Computational Intelligence Approach to Improve The Classification Accuracy of Brain Tumor Detection","authors":"S. K. UmaMaheswaran, S. Deivasigamani, Kapil Joshi, Devvret Verma, Santhosh Kumar Rajamani, Dhyana Sharon Ross","doi":"10.1109/SMART55829.2022.10047792","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047792","url":null,"abstract":"One of its most serious diseases that may affect kids and teens is a cancerous tumor. Gliomas account for 85% to 90% of all recurrent System (CNS) cancers. An estimated 11,700 individuals get a glioma diagnosis per year. When a person has a benign brains or CNS cancer, their five - year survival is around 36% for women and approximately 34% for men. There are several distinct types of brain cancers, including benign, aggressive, endocrine, and other types. The average lifespan of people should really be increased by using appropriate treatment, scheduling, and precise diagnosis. Mri scan is the most effective method for finding tumour (MRI). An large quantity of picture data is produced by scanners. The surgeon looks over these pictures. Algorithms (ML) and intelligent systems (AI)-based automation classification systems have repeatedly beaten hand categorisation in high accuracy. Therefore., offering a system can perform classification and tracking using Deep Learning Techniques such as Fully Convolutional Systems (CNN), Knn (ANN), (Template matching), and Transfer Learning (TL) would be helpful to physicians everywhere.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124546557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Study on the Applications of Supply Chain Management 供应链管理的应用研究

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047167

C. Gupta, Vipin Kumar, K. Kumar

引用次数: 0

Groundwater Delineation Using RS and GIS for Gurgaon Region 基于RS和GIS的古尔冈地区地下水圈定

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047572

R. Jain

引用次数: 0

Identification and Analysis of Log4j Vulnerability Log4j漏洞的识别与分析

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047372

Hritik Gupta, A. Chaudhary, Anil Kumar

引用次数: 2

A Survey of Machine Learning Based Approaches for Neurological Disorder Predictions 基于机器学习的神经系统疾病预测方法综述

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10046944

Atul Mathur, R. Dwivedi, Rajul Rastogi

引用次数: 0

Scheduling Cloudlets in a Cloud Computing Environment: A Priority-based Cloudlet Scheduling Algorithm (PBCSA) 云计算环境下的云调度:基于优先级的云调度算法(PBCSA)

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047622

D. Gritto, P. Muthulakshmi

{"title":"Scheduling Cloudlets in a Cloud Computing Environment: A Priority-based Cloudlet Scheduling Algorithm (PBCSA)","authors":"D. Gritto, P. Muthulakshmi","doi":"10.1109/SMART55829.2022.10047622","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047622","url":null,"abstract":"Cloud computing is a service model that has evolved in its stature beyond its traditional bounds of infrastructure, platform and software as a service. As the surge in resource demand may hit the cloud service provider at any time, a ceaseless monitoring system is vital. The allocation of an appropriate virtual machine for the cloudlet i.e., the user workload and maintaining the work load equilibrium among the resources is the most challenging operation in the cloud environment. The proper utilization of the cloud resources can be ensured by selecting the right cloudlet scheduling and load balancing algorithm(s). The cloudlet scheduling algorithm selection is based on the combination of two or more Quality of Service (QoS) and performance metrics like makespan, throughput, cost, power consumption, virtual machine or resource utilization and load balancing etc. The load balancer module takes the responsibility of dispersing the cloudlets evenly among the virtual machines by considering various features like CPU utilization, number of processing elements, bandwidth, memory and the load limit of the virtual machines. In this paper, an effort has been made to comprehend the most persisting cloudlet scheduling and load balancing algorithms that have been proposed by the researchers. Compiling the load balancing technologies that are integrated with the contemporary cloud platforms such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) has also been prioritized. This study suggests a Priority Based Cloudlet Scheduling Algorithm (PBCSA) that schedules the cloudlet according to the user priority. The Min-Min scheduler is used to schedule the high priority cloudlets and the Max-Min scheduler is used to schedule the low priority cloudlets. The experimental findings reveals that, in the majority of scenarios, the proposed algorithm outperforms the Min-Min and Max-Min scheduling in terms of makespan and virtual machine utilization ratio.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130696354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

“Secure Architecture for Providing Data Authenticity in IoT Enabled Devices” “在物联网设备中提供数据真实性的安全架构”

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047067

Shivangi, Gulishta Khan, S. Ninoria

引用次数: 0

Detection of Skin Diseases via Deep Learning using SVM Method 基于SVM方法的深度学习皮肤病检测

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047402

A. K. Moharana, Daxa Vekariya

{"title":"Detection of Skin Diseases via Deep Learning using SVM Method","authors":"A. K. Moharana, Daxa Vekariya","doi":"10.1109/SMART55829.2022.10047402","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047402","url":null,"abstract":"Dermatological issues are one of the most preventable diseases in the world. Although it is widespread, studying it is challenging because of the many layers of complexity introduced by the presence of colour, concealment, and hair. Diagnosing skin problems early is essential for effective therapy. The method for identifying and treating skin injury is based on the specialist's level of competence and experience. There needs to be pinpoint accuracy in the analysis. Success rates for clinical diagnostic and clinical therapeutic frameworks are improving with time as a result of cutting-edge developments in medicine and data science. Skin disease diagnosis has benefited from the application of AI calculations and the utilisation of the large quantity of information available in hospitals and clinics. For this study, we collated a large number of previous studies that analysed skin illnesses via the lens of AI-based classification strategies. In their previous studies, the specialists employed numerous frameworks, instruments, and calculations. A small number of frameworks have been developed that are capable of correctly identifying skin diseases with varying degrees of suggestive precision. Multiple models have used image processing and component extraction methods to","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131200433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Shared Cycle and Vehicle Sharing and Monitoring System 共享单车及车辆共享监控系统

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10047734

Lakshmaiah Alluri, Hemant Jeevan Magadum

{"title":"Shared Cycle and Vehicle Sharing and Monitoring System","authors":"Lakshmaiah Alluri, Hemant Jeevan Magadum","doi":"10.1109/SMART55829.2022.10047734","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047734","url":null,"abstract":"Cycle sharing and vehicle sharing and monitoring system is the solutions for managing and monitoring shared cycles or vehicle remotely for pollution free operation and facility available to public to travel in Smart City. Cycle or vehicle sharing is a kind of personal or public transport. Cycle or vehicle can be parked at the place provided nearer to the network of stations. With an IoT application on mobile phone, a user can find the availability of a Cycle or vehicle from a station, if it is available user can use it for a short ride, later it can be return to the any other nearby station. So developments of Cycle or vehicle sharing stations are more useful for common public transport through which connectivity can be established between the smart stations so that last minute rush can be avoided. Traffic density can be reduced and also provide last-mile connectivity. The paper proposes development of highly efficient integrated Shared cycles or vehicle monitoring system with GPRS remote control and remotely locking and unlocking based on user request. The project proposes usage of solar powered locking system with low carbon footprint.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Just Use a Perceptron to Anticipate Dry 只需使用感知器来预测干燥

2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART) Pub Date : 2022-12-16 DOI: 10.1109/SMART55829.2022.10046805

D. K. Sinha, S. Reddy

{"title":"Just Use a Perceptron to Anticipate Dry","authors":"D. K. Sinha, S. Reddy","doi":"10.1109/SMART55829.2022.10046805","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046805","url":null,"abstract":"Drought is considered one of the most terrifying disasters that humanity have ever experienced, and farmers all over the globe often deal with it. It may happen anywhere outside of the globe and is referred to as a “slow catastrophe” since it lasts for a long time, and perhaps even further if it chooses to be more severe. Drought affects also human lives but also crops, global economy, and power that farmers have ingested. During a disaster, seems to be at risk. Basic necessities like food are difficult to get, and market forces imbalance causes irritation to reach its height. There are a variety of things that may be done to prevent the dry, such as desalinating water, crop planning, rainfall gathering, and sprinkler, which can all help preserve water during dry spells. The primary answer to this problem would have been to analyse the environment and the potential results of it, that could aid in planning for the worst-case scenario. Soil predictions may also be very helpful in forecasting this scenario. In order to forecast how floods might be averted, the article combines meteorological and soil data. Deep learning methods will make it possible to determine with remarkable accuracy if the droughts will occur or not.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121623440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0