2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)最新文献_第5页

A Novel Simplified Approach for Text Line Extraction of Handwritten Malayalam Document 一种新的马来语手写文本行提取简化方法

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213218

P. V. Pearlsy, D. Sankar

{"title":"A Novel Simplified Approach for Text Line Extraction of Handwritten Malayalam Document","authors":"P. V. Pearlsy, D. Sankar","doi":"10.1109/ACCTHPA49271.2020.9213218","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213218","url":null,"abstract":"This paper presents a novel and simple method for extracting individual lines from handwritten Malayalam documents.The challenge involved in text line extraction of handwritten document is segmentation of touching lines. As far as Malayalam language is considered, symbols like chandrakkala will be classified into separate line due to the small gap between the Malayalam alphabet and the symbol chandrakkala. This paper addresses the possibility of touching lines and misclassification of character like chandrakkala into a separate line. In the proposed method, the scanned handwritten document is divided into vertical stripes. Using horizontal projection method lines are extracted in each vertical stripe separately. Touching lines, segmentation of character like chandrakkala into separate line and extra lines due to noise are addressed using the median values of the height of lines in each vertical stripe separately. The handwritten document image is divided into vertical stripes prior to line segmentation to account for the possibility of skewed lines. When the document is divided into vertical stripe, the characters will be cut in between. This paper also presents a solution to join the characters cut in between when the document is divided into vertical stripes. This is done by compensating for the distance of characters from the top of the line at the joining edge of the vertical stripe.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128715781","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

A study on using private-permissioned blockchain for securely sharing farmers data 关于使用私人许可的区块链安全地共享农民数据的研究

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213237

Alfin Abraham, M. B. Santosh Kumar

{"title":"A study on using private-permissioned blockchain for securely sharing farmers data","authors":"Alfin Abraham, M. B. Santosh Kumar","doi":"10.1109/ACCTHPA49271.2020.9213237","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213237","url":null,"abstract":"In agriculture, farmers are the most important entity. For supporting farmers in increasing productivity and efficiency, the government offers subsidies, loans, insurances, and so on. This paper explores the usage of Blockchain technology for securing farmer’s data in the Indian scenario. The farmer needs to register through the multiple official registration systems for availing different schemes and information provided by the country. The personnel and crop-based details of each farmer are collected at the time of registration. The filing also helps in providing better services to farmers like connecting farmers and traders to ensure a fair price for quality crops, advice to farmers of agricultural practices and location. In this paper, a blockchain-based farmer’s data securing system is proposed to provide data provenance and transparency of the information entered in the system. While registering, the data is collected, and it is verified. A single verified record of farmers accessed by various government agriculture departments were designed using the Hyperledger fabric framework.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133820391","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: 5

Predicting Human Activity from Mobile Sensor Data Using CNN Architecture 利用CNN架构从移动传感器数据预测人类活动

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213225

K. K. Krishnaprabha, C. Raju

{"title":"Predicting Human Activity from Mobile Sensor Data Using CNN Architecture","authors":"K. K. Krishnaprabha, C. Raju","doi":"10.1109/ACCTHPA49271.2020.9213225","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213225","url":null,"abstract":"Having a model for predicting motion related activities of humans have tremendous applications. Quite often a simple smartphone is enough for monitoring the liveliness of a person. This can be achieved by using Activity Recognition (AR). Smartphones are employed in a wider manner and it becomes one amongst the ways to spot the human’s environmental changes by using the sensors in smart mobile. A variety of sensors are embedded in a smartphone - for instance gyroscope, accelerometer. The contraption is demonstrated to look at the state of a person. Here, a framework Human Activity Recognition (HAR) collects the raw data from sensors and movements of humans observed using a deep learning approach. Deep learning models are proposed to spot motions of humans with plausible high accuracy by using sensed data. The performance of a framework is analyzed using Convolutional Neural Network. The act of the model is analyzed in terms of exactness and efficiency. The designed activity recognition model is manipulated to detect the activities of elderly humans at home and it can detect the activities of persons in a crowded area when the area is authorized.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130942936","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: 2

Multi-Soft Set Based Approach for Rule based Classification Using Sequential Covering Algorithm 基于顺序覆盖算法的多软集规则分类方法

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213229

Santhosh Kottam, V. Paul

{"title":"Multi-Soft Set Based Approach for Rule based Classification Using Sequential Covering Algorithm","authors":"Santhosh Kottam, V. Paul","doi":"10.1109/ACCTHPA49271.2020.9213229","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213229","url":null,"abstract":"Rule-based classification is a popular and adaptable method for determining the class of an object. Two accepted rule based classification methods are decision tree induction and sequential covering algorithms. Now a days, soft computing tools are widely used in all areas of knowledge discovery. Soft set theory that has wide application in data mining, is a novel soft computing tool. One of its branches is multi soft set theory. In the research, we have brought out applications of multi soft set theory in rule-based classification using a sequential covering algorithm. Conventional sequential covering algorithm for implementing rule based classification has certain limitations. The proposed research is supposed to overcome those problems. The beginning part is an introduction and the second part, details the applications of multi-soft set theory. Towards the end, we are contributing a new algorithm using multi soft set theory which can be implemented in python programming language. This new method has wide applications in different areas like business, health, sports, education etc.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131997640","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

A University Admission Prediction System using Stacked Ensemble Learning 基于堆叠集成学习的大学录取预测系统

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213205

S. Sridhar, Siddartha Mootha, Santosh Kolagati

{"title":"A University Admission Prediction System using Stacked Ensemble Learning","authors":"S. Sridhar, Siddartha Mootha, Santosh Kolagati","doi":"10.1109/ACCTHPA49271.2020.9213205","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213205","url":null,"abstract":"For an aspiring graduate student, shortlisting the universities to apply to is a difficult problem. Since an application is extremely dynamic, students often tend to wonder if their profile matches the requirement of a certain university. Moreover, the cost of applying to a university is extremely high making it critical that students shortlist universities based on their profile. A university admission prediction system is quite useful for students to determine their chances of acceptance to a specific university. The system could make use of data related to previous applicants to various universities and their admit or reject status. Earlier models of such prediction systems suffer from several drawbacks such as not considering important parameters like GRE (Graduate Record Exam) scores or research experience. Further, the accuracy reported by earlier models is also not sufficiently high. In this paper, a stacked ensemble model that predicts the chances of admit of a student to a particular university has been proposed. The proposed model takes into consideration various factors related to the student including their research experience, industry experience etc. Further, the system proposed has been evaluated against various other machine learning algorithms including other deep learning methods. It is observed that the proposed model easily outperforms all other models and provides a very high accuracy.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"62 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128453522","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: 9

A study on the significance of smart IoT sensors and Data science in Digital agriculture 智能物联网传感器与数据科学在数字农业中的意义研究

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213207

Neenu Johnson, M. B. Santosh Kumar, T. Dhannia

引用次数: 10

Evaluation of Inpainting in Speckled and Despeckled 2D Ultrasound Medical Images 斑点和去斑点二维超声医学图像补色的评价

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213203

D. M. Alex, D. Chandy

引用次数: 2

Face Depth Estimation and 3D Reconstruction 人脸深度估计和三维重建

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-04-20 DOI: 10.1109/ACCTHPA49271.2020.9213233

A. Baby, A. Andrews, A. Dinesh, Amal Joseph, V. Anjusree

引用次数: 5