2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)最新文献_第2页

An Efficient Fashion Recommendation System using a Deep CNN Model 基于深度CNN模型的高效时尚推荐系统

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029063

B. Suvarna, Sivadi Balakrishna

引用次数: 0

Traffic Sign Detection using HOG and GLCM with Decision Tree and Random Forest 基于决策树和随机森林的HOG和GLCM交通标志检测

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029118

A. J, Giridhran R, Agalya K, Sathya R

引用次数: 0

Breast Cancer Segmentation by K-Means and Classification by Machine Learning 基于K-Means的乳腺癌分割和基于机器学习的分类

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029301

K. Priya, V. Senthilkumar, J. Samson Isaac, Sreekanth Kottu, V. S. Ramakrishna, M. Jogendra Kumar

{"title":"Breast Cancer Segmentation by K-Means and Classification by Machine Learning","authors":"K. Priya, V. Senthilkumar, J. Samson Isaac, Sreekanth Kottu, V. S. Ramakrishna, M. Jogendra Kumar","doi":"10.1109/ICACRS55517.2022.10029301","DOIUrl":"https://doi.org/10.1109/ICACRS55517.2022.10029301","url":null,"abstract":"Breast Cancer (BC) progression is currently a common health problem among modern women. It is the cause of death for a significant number of women. BC is the growth of malignant cells in the breast tissue. Adipose or connective tissue can also develop BC. Because of developments in medical technology, ultrasonography is one of many procedures utilised for the early identification of cancer. Ultrasound is a technique that uses high-frequency sound wave technology to create images of inside body structures such as organs and soft tissues. Because of the poor quality of the information, there is a lot of possibility for interpretational mistakes when diagnosing cancer based on ultrasound images. As a result of these concerns, this paper uses the idea of Machine Learning (ML) is employed for the classification and segmentation of BC. The K-means clustering approach is used as part of the segmentation procedure to detect where the cancer is present. A recent study has demonstrated that machine learning produces reliable findings, allowing specialists to make better decisions. Using standard BC datasets, the performance of three different Machine Learning algorithms—Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbors (KNN)—is tested in this work. In terms of accuracy, RF outperformed the other algorithms, according to the finding. Future BC researchers will be able to utilise the findings of this study to guide their investigations and influence their efforts to improve the efficiency of specific algorithms.","PeriodicalId":407202,"journal":{"name":"2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124413289","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

Classification of WBC based on Deep Learning using Microscopic Images 基于微观图像的深度学习WBC分类

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029231

R. T, S. C

引用次数: 0

Real-Time Face Mask Detection from CCTV Video Frames using Deep Neural Networks 基于深度神经网络的CCTV视频帧实时人脸检测

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029096

V. Natarajan, P. Vishnu Vardhan, Nayakula Murahara Sai Priya, Nunna Vineeth, Parthu V

{"title":"Real-Time Face Mask Detection from CCTV Video Frames using Deep Neural Networks","authors":"V. Natarajan, P. Vishnu Vardhan, Nayakula Murahara Sai Priya, Nunna Vineeth, Parthu V","doi":"10.1109/ICACRS55517.2022.10029096","DOIUrl":"https://doi.org/10.1109/ICACRS55517.2022.10029096","url":null,"abstract":"The coronavirus, commonly known as SARS COVID-19, is causing a pandemic that is affecting individuals all over the world. The spread of the virus compelled the authorities to impose a rigorous lockdown on its citizens. Every person in society may experience a variety of issues as a result of this. According to WHO (World Health Organization) regulations, the sole method to halt the virus's spread is to wear a face mask. Therefore, the suggested approach makes sure that everyone appropriately wears a face mask in public locations. The objective of this approach is to detect people without face masks and people who wear facemasks incorrectly in social environments. This system consists of multiple face detection modules to find the area of interest within the video frames. In the next level, using the trained Deep Learning model, the presence of a mask is detected and faces without mask and faces wearing masks incorrectly are highlighted. The dataset for face mask identification comprises of 8190 photos with unique facial annotations from the Kaggle and RMFD datasets that come into two categories: \"with mask\" and \"without mask\".","PeriodicalId":407202,"journal":{"name":"2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133881011","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

Experimental Setup of Apache Spark Application Execution in a Standalone Cluster Environment using Default Scheduling Mode 使用默认调度模式在独立集群环境下执行Apache Spark应用程序的实验设置

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029155

M. Jayanthi, K. R. M. Rao

{"title":"Experimental Setup of Apache Spark Application Execution in a Standalone Cluster Environment using Default Scheduling Mode","authors":"M. Jayanthi, K. R. M. Rao","doi":"10.1109/ICACRS55517.2022.10029155","DOIUrl":"https://doi.org/10.1109/ICACRS55517.2022.10029155","url":null,"abstract":"This paper proposes the Apache Spark application execution on a local machine using covid dataset with the standalone cluster environment using default scheduling mode. Cloud computing has been widely used in various fields of organization due to its flexibility and scalability. Efficient job scheduling technique can apply in the cloud to increases the profit of Cloud Service Provider and also reduces various optimization technique was recently applied to increases the performance of cloud computing. Experimental setup of apache spark done on a local machine in a standalone cluster environment using FIFO default scheduling mode. Existing techniques have limitations of local optimal trap, lower convergence and over fitting in prediction. This research applies First In First Out (FIFO) technique to increases the efficiency of cloud, reduce the cost, easy to configure with simplest standalone cluster manager. In this proposed framework, the first phase configure the local machine with apache spark second phase launch master node and worker node and the final phase launch the history server and run the application. The FIFO technique has a cost value of 2.5 $ based on the results recorded with two parameters execution time and resources utilized (CPU cores and memory).","PeriodicalId":407202,"journal":{"name":"2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130744606","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

Privacy Preserving Encryption with Optimal Key Generation Technique on Deduplication for Cloud Computing Environment 云计算环境下基于重复数据删除最优密钥生成技术的隐私保护加密

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029045

Sanjeeva Polepaka, B. Gayathri, Shahnawaz Ayoub, Himanshu Sharma, Yudhveer Singh Moudgil, S. Kannan

{"title":"Privacy Preserving Encryption with Optimal Key Generation Technique on Deduplication for Cloud Computing Environment","authors":"Sanjeeva Polepaka, B. Gayathri, Shahnawaz Ayoub, Himanshu Sharma, Yudhveer Singh Moudgil, S. Kannan","doi":"10.1109/ICACRS55517.2022.10029045","DOIUrl":"https://doi.org/10.1109/ICACRS55517.2022.10029045","url":null,"abstract":"Cloud computing performs a significant part in sharing resources and data with other devices via data outsourcing. The data collaboration services, as a potential service given by the cloud service provider (CSP), is to assist the consistency and availability of the shared data amongst users. At the time of sharing resources, it is a complicated process for providing secure writing and access control operations. This study develops a Privacy Preserving Encryption with Optimal Key Generation Technique (PPE-OKGT) for CC environment. The presented PPE-OKGT technique secures the data prior to storing in the cloud sever via encryption process. For accomplishing this, the presented PPE-OKGT technique employs data encryption technology to secure the input data into a hidden format. Besides, in order to improve secrecy, the presented PPE-OKGT technique designs a chaotic search and rescue optimization (CSRO) algorithm for optimal generation of keys. The promising performance of the PPE-OKGT technique can be verified using a set of experimentations. A comprehensive comparison study reported the enhancements of the PPE-OKGT technique over other models.","PeriodicalId":407202,"journal":{"name":"2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131900740","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

Data Extraction Approach using Natural Language Processing for Sentiment Analysis 基于自然语言处理的情感分析数据提取方法

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029216

Shreyash Mishra, Siddhartha Choubey, Abha Choubey, N. Yogeesh, J. Durga Prasad Rao, P. William

引用次数: 27

Ensuring Safety for School Children using IoT 使用物联网确保学童的安全

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029188

Daniel NareshKumar. M, Aneeshraj P B, Balaji A, D. Dhanush

引用次数: 0

Machine Learning Techniques for Detecting DDoS Attacks in SDN SDN中检测DDoS攻击的机器学习技术

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) Pub Date : 2022-12-13 DOI: 10.1109/ICACRS55517.2022.10029110

M. Kavitha, M. Suganthy, Aniket Biswas, R. Srinivsan, R. Kavitha, A. Rathesh

{"title":"Machine Learning Techniques for Detecting DDoS Attacks in SDN","authors":"M. Kavitha, M. Suganthy, Aniket Biswas, R. Srinivsan, R. Kavitha, A. Rathesh","doi":"10.1109/ICACRS55517.2022.10029110","DOIUrl":"https://doi.org/10.1109/ICACRS55517.2022.10029110","url":null,"abstract":"Future internet is increasingly reliant on Software Defined Networking (SDN). With SDN, networks can be dynamically controlled, providing a global network. Compared to traditional networks, SDN offers the advantage of better security provisioning due to centralized management. However, SDN architecture manifests several new network security problems that need to be handled to improve the security of SDN networks. Information security and data analysis systems for Big Data have become more essential due to the increasing volume of data and its incremental growth. Monitoring and analyzing data is needed to detect any intrusion into a system or network via an intrusion detection system (IDS). By using traditional methods, traditional data analysis techniques are unable to detect attacks caused by high volumes, a wide variety and high speeds of network data. For an accurate and efficient data analysis process, IDS employs Big Data techniques. The paper uses machine learning models to detect Distributed Denial of Service (DDoS) attacks. The machine learning model is trained using data from KDD Cup 99.K Nearest Neighbor Classifier, Logistic Regression, and Decision Tree have been used to train and test the datasets. It can be concluded that machine learning methods can be more effective at detecting DDoS attacks than traditional methods, that can be applied to software defined networks. Several experiments demonstrate the potential of our proposal to detect intrusion in SDN environments after extensive evaluation.","PeriodicalId":407202,"journal":{"name":"2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125879743","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