Pub Date : 2021-05-30DOI: 10.37622/IJAER/16.5.2021.400-405
R. Kalpana, R. Kumar
{"title":"Investigation of speed control of Three phase Induction Motor fed through Direct Matrix Converter using Generalized Scalar Pulse Width Modulation (GSPWM) Technique","authors":"R. Kalpana, R. Kumar","doi":"10.37622/IJAER/16.5.2021.400-405","DOIUrl":"https://doi.org/10.37622/IJAER/16.5.2021.400-405","url":null,"abstract":"","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"43 1","pages":"400"},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90497939","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}
Pub Date : 2021-05-30DOI: 10.37622/ijaer/16.5.2021.416-423
A. Sudhakaraiah, T. Visalakshi, T. Venkateswarlu, K. Narayana
{"title":"Some Properties on Degrees of Dominating Sets for Circular-Arc Graph","authors":"A. Sudhakaraiah, T. Visalakshi, T. Venkateswarlu, K. Narayana","doi":"10.37622/ijaer/16.5.2021.416-423","DOIUrl":"https://doi.org/10.37622/ijaer/16.5.2021.416-423","url":null,"abstract":"","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75421214","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}
Pub Date : 2021-05-30DOI: 10.37622/ijaer/16.5.2021.346-351
Khushi Talesra, G. Nagaraja
In today’s digital world, with a rapid growth in number of companies and ever-changing market requirements, the benefit of low-code solutions can be an important step in providing the technology required to automate the creation and deployment of essential business applications and encourage digital transformation. The interest towards these platforms has significantly augmented in business industry since past few years as more research is conducted towards them. Low code development platforms (LCDPs) provide user friendly visual environments to create software applications with attractive UI, responsive designs, and minimal programming skills. This paper discusses how low-code platforms can facilitate the building of secure and scalable applications with outstanding features. It discusses the challenges addressed by low-code solutions. Also, the use of Oracle APEX low-code platform in Application development is discussed with respect to building of User Access Audit and control automation application.
{"title":"Low-Code Platform for Application Development","authors":"Khushi Talesra, G. Nagaraja","doi":"10.37622/ijaer/16.5.2021.346-351","DOIUrl":"https://doi.org/10.37622/ijaer/16.5.2021.346-351","url":null,"abstract":"In today’s digital world, with a rapid growth in number of companies and ever-changing market requirements, the benefit of low-code solutions can be an important step in providing the technology required to automate the creation and deployment of essential business applications and encourage digital transformation. The interest towards these platforms has significantly augmented in business industry since past few years as more research is conducted towards them. Low code development platforms (LCDPs) provide user friendly visual environments to create software applications with attractive UI, responsive designs, and minimal programming skills. This paper discusses how low-code platforms can facilitate the building of secure and scalable applications with outstanding features. It discusses the challenges addressed by low-code solutions. Also, the use of Oracle APEX low-code platform in Application development is discussed with respect to building of User Access Audit and control automation application.","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82128526","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}
Pub Date : 2021-04-30DOI: 10.37622/ijaer/13.8.2018.6056-6062
Sheerin Sitara N., K. S., Raghuraman. G
In real time scenario, cracks are very common in building, bridge, road, pavement, railway track, automobile, tunnel and aircraft. The presence of crack diminishes the value of the civil infrastructure and hence it is necessary to estimate the severity of crack. Crack detection and classification techniques with quantitative analysis play a major role in finding the severity of crack. The various quantitative metrics are length, width and area. Due to the rapid development in technology, number of images acquired for analysis is growing enormously. Therefore, automatic crack detection and classification techniques for civil infrastructure are essential. This paper focuses on three objectives: (i) Analysis of various crack detection and classification techniques based on crack types (ii) Implementation of Otsu’s based thresholding method for crack detection (iii) Design of proposed system.
{"title":"Review and Analysis of Crack Detection and Classification Techniques based on Crack Types","authors":"Sheerin Sitara N., K. S., Raghuraman. G","doi":"10.37622/ijaer/13.8.2018.6056-6062","DOIUrl":"https://doi.org/10.37622/ijaer/13.8.2018.6056-6062","url":null,"abstract":"In real time scenario, cracks are very common in building, bridge, road, pavement, railway track, automobile, tunnel and aircraft. The presence of crack diminishes the value of the civil infrastructure and hence it is necessary to estimate the severity of crack. Crack detection and classification techniques with quantitative analysis play a major role in finding the severity of crack. The various quantitative metrics are length, width and area. Due to the rapid development in technology, number of images acquired for analysis is growing enormously. Therefore, automatic crack detection and classification techniques for civil infrastructure are essential. This paper focuses on three objectives: (i) Analysis of various crack detection and classification techniques based on crack types (ii) Implementation of Otsu’s based thresholding method for crack detection (iii) Design of proposed system.","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84794751","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}
Pub Date : 2021-02-28DOI: 10.37622/ijaar/16.2.2021.161-165
H. Joshi, P. P. Raval, K. Patel
{"title":"Smart Irrigation System for Optimized Use of Water and Energy","authors":"H. Joshi, P. P. Raval, K. Patel","doi":"10.37622/ijaar/16.2.2021.161-165","DOIUrl":"https://doi.org/10.37622/ijaar/16.2.2021.161-165","url":null,"abstract":"","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84202321","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}
Pub Date : 2021-02-26DOI: 10.37622/IJAER/16.1.2021.75-84
A. Chaudhary, L. Sapkota, Vijay Kumar
Here, a new distribution using the Poisson generating family with Gompertz distribution as baseline distribution have been generated called Poisson Gompertz (PGZ) distribution. Some distributional features of the PGZ distribution are presented. For the parameter estimates of the presented model, Maximum likelihood Estimation (MLE) is applied along with Cramer-Von-Mises estimation (CVME) and least-square estimation (LSE) methods. We have constructed the asymptotic confidence intervals based on maximum likelihood estimates. R software platform was used to perform the computations. The application of the proposed model has been illustrated by considering the data set obtained from real life and investigated the goodness of fit attained by the observed model via different test statistics and graphical methods. We have found that the distribution that is introduced provides better fit to the dataset taken with more flexibility as compared to other models in consideration
{"title":"Poisson Gompertz Distribution with Properties and Applications","authors":"A. Chaudhary, L. Sapkota, Vijay Kumar","doi":"10.37622/IJAER/16.1.2021.75-84","DOIUrl":"https://doi.org/10.37622/IJAER/16.1.2021.75-84","url":null,"abstract":"Here, a new distribution using the Poisson generating family with Gompertz distribution as baseline distribution have been generated called Poisson Gompertz (PGZ) distribution. Some distributional features of the PGZ distribution are presented. For the parameter estimates of the presented model, Maximum likelihood Estimation (MLE) is applied along with Cramer-Von-Mises estimation (CVME) and least-square estimation (LSE) methods. We have constructed the asymptotic confidence intervals based on maximum likelihood estimates. R software platform was used to perform the computations. The application of the proposed model has been illustrated by considering the data set obtained from real life and investigated the goodness of fit attained by the observed model via different test statistics and graphical methods. We have found that the distribution that is introduced provides better fit to the dataset taken with more flexibility as compared to other models in consideration","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"62 10 1","pages":"75-84"},"PeriodicalIF":0.0,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73257601","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}
Pub Date : 2021-02-26DOI: 10.37622/IJAER/16.2.2021.85-88
H. Singh, R. Das, D. Mishra
{"title":"A Multi-Dimensional Flow Which Satisfies the Equation of Continuity","authors":"H. Singh, R. Das, D. Mishra","doi":"10.37622/IJAER/16.2.2021.85-88","DOIUrl":"https://doi.org/10.37622/IJAER/16.2.2021.85-88","url":null,"abstract":"","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"40 1","pages":"85-88"},"PeriodicalIF":0.0,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84554139","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}
Pub Date : 2021-01-30DOI: 10.37622/IJAER/16.1.2021.67-74
K. Sridevi
In this paper, we introduce the notion of partial sub-basic sequence on the sub set of square-free odd integers and using convolution definition of arithmetic functions from the set of square free positive integers to real numbers and obtain some basic algebraic properties of convolution. We also define partial multiplicative functions with respect to partial basic sequences and obtain their properties. These results are extended the results given in Sridevi [7] relating to the arithmetic functions, thus this paper is a sequel to Sridevi [7].
{"title":"Algebraic Properties of Convolution of Arithmetic Functions on the Partial Sub-Basic Sequence of Square-Free Odd Integers","authors":"K. Sridevi","doi":"10.37622/IJAER/16.1.2021.67-74","DOIUrl":"https://doi.org/10.37622/IJAER/16.1.2021.67-74","url":null,"abstract":"In this paper, we introduce the notion of partial sub-basic sequence on the sub set of square-free odd integers and using convolution definition of arithmetic functions from the set of square free positive integers to real numbers and obtain some basic algebraic properties of convolution. We also define partial multiplicative functions with respect to partial basic sequences and obtain their properties. These results are extended the results given in Sridevi [7] relating to the arithmetic functions, thus this paper is a sequel to Sridevi [7].","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"06 1","pages":"67-74"},"PeriodicalIF":0.0,"publicationDate":"2021-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86134305","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}
Pub Date : 2021-01-01DOI: 10.37622/ijaer/15.8.2020.827-834
J. R. L., A. M.
Feature extraction plays the key role in pattern recognition systems. With the invent of Deep learning algorithms it is believed that the importance of feature extraction methods has been reduced. But the cost of implementing deep algorithms is very high. Deep neural networks rely on GPU architecture and requires large amount of data for achieving high recognition efficiency. It is computationally expensive to train the deep architecture and more over the learning procedure and factors for training is not easy to realize. Therefore having inspired by the structure of Deep Convolutional Neural Network a new feature extraction method based on conventional feature extraction system for recognition is proposed. In this method a multilayer architecture is designed with convolution layer based on gabor filter and classification layer based on Artificial Neural Network.Only the classification layer is subjected to learning by backpropogation and all other layers acts as the part of feature extraction system.The input image without applying any pre-processing can be subjected to the proposed system which in turn predicts the class of image as output. The proposed method is compared with some of the existing efficient feature extraction methods like discrete meyer wavelet, zernike moment, curvelet , legendre moments, gaussian hermite(GH) moment and Histogram of gradient(HOG). The recognition efficiency produced by the method without applying any pre-processing on input images is much higher than existing efficient feature extraction methods with preprocessing applied.The proposed method works effectively invariant to noise, translation and rotation. Experimental analyses were carried out in two datasets. First dataset is the standard HPL dataset of isolated Tamil characters. The second dataset consists of Grantha characters extracted from ancient palm leaves.
{"title":"Handwritten Character Recognition from Ancient Palm Leaves using Gabor based MultiLayer Architecture:GMA","authors":"J. R. L., A. M.","doi":"10.37622/ijaer/15.8.2020.827-834","DOIUrl":"https://doi.org/10.37622/ijaer/15.8.2020.827-834","url":null,"abstract":"Feature extraction plays the key role in pattern recognition systems. With the invent of Deep learning algorithms it is believed that the importance of feature extraction methods has been reduced. But the cost of implementing deep algorithms is very high. Deep neural networks rely on GPU architecture and requires large amount of data for achieving high recognition efficiency. It is computationally expensive to train the deep architecture and more over the learning procedure and factors for training is not easy to realize. Therefore having inspired by the structure of Deep Convolutional Neural Network a new feature extraction method based on conventional feature extraction system for recognition is proposed. In this method a multilayer architecture is designed with convolution layer based on gabor filter and classification layer based on Artificial Neural Network.Only the classification layer is subjected to learning by backpropogation and all other layers acts as the part of feature extraction system.The input image without applying any pre-processing can be subjected to the proposed system which in turn predicts the class of image as output. The proposed method is compared with some of the existing efficient feature extraction methods like discrete meyer wavelet, zernike moment, curvelet , legendre moments, gaussian hermite(GH) moment and Histogram of gradient(HOG). The recognition efficiency produced by the method without applying any pre-processing on input images is much higher than existing efficient feature extraction methods with preprocessing applied.The proposed method works effectively invariant to noise, translation and rotation. Experimental analyses were carried out in two datasets. First dataset is the standard HPL dataset of isolated Tamil characters. The second dataset consists of Grantha characters extracted from ancient palm leaves.","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"47 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79103276","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}
Pub Date : 2020-12-30DOI: 10.37622/IJAER/15.12.2020.1116-1121
Nidhi Bansal, S. Sridhar, P. L. D. Priya
Melanoma is the greatest carcinogenic skin cancer. In the last years, the prevalence degree of melanoma has risen by 50 percent. There is a necessity to provide an onscreen system for the diagnosis of skin lesions. The system will reduce the unnecessary biopsy and the cancer can be diagnosed at an early stage. In this paper a framework is proposed for the automated skin lesion detection in an input image. A segmentation algorithm based on texture is used to classify normal skin class or lesion class. Also, fusion of texture and geometric features is presented in this work. SVM classifier is trained to identify lesions as malignant melanoma or benign lesion. The system yielded an efficiency of 84.7%, 89.4% and 83.5% for Haralick features, features given by Soh and Clausi and Histogram based features respectively. The fusion based on texture and geometric features enhanced the performance of the system. The evaluated performance metrics are better than the previous methods. The improved system helps diagnose at an early stage reducing the mortality rate.
{"title":"Improved Skin Lesion Detection and Segmentation by Fusing Texture and Geometric Features","authors":"Nidhi Bansal, S. Sridhar, P. L. D. Priya","doi":"10.37622/IJAER/15.12.2020.1116-1121","DOIUrl":"https://doi.org/10.37622/IJAER/15.12.2020.1116-1121","url":null,"abstract":"Melanoma is the greatest carcinogenic skin cancer. In the last years, the prevalence degree of melanoma has risen by 50 percent. There is a necessity to provide an onscreen system for the diagnosis of skin lesions. The system will reduce the unnecessary biopsy and the cancer can be diagnosed at an early stage. In this paper a framework is proposed for the automated skin lesion detection in an input image. A segmentation algorithm based on texture is used to classify normal skin class or lesion class. Also, fusion of texture and geometric features is presented in this work. SVM classifier is trained to identify lesions as malignant melanoma or benign lesion. The system yielded an efficiency of 84.7%, 89.4% and 83.5% for Haralick features, features given by Soh and Clausi and Histogram based features respectively. The fusion based on texture and geometric features enhanced the performance of the system. The evaluated performance metrics are better than the previous methods. The improved system helps diagnose at an early stage reducing the mortality rate.","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78359469","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}
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