Pub Date : 2019-11-01DOI: 10.1109/SMART46866.2019.9117284
Md. Rahmat Ullah, Nagifa Anjum Dola, A. Sattar, Abir Hasnat
The way a doctor can predict what kind of diseases a patient is suffering from, similarly, the fastest stratagem of predicting plant diseases is to analyze leaf's physiognomy changes and compare them with their actual color, shape, structure, etc. Plant disease recognition on the basis of leaf's physiognomy changes is the fundamental purpose of our project. We have used Convolutional Neural Network as a training method. CNN works via 3 dimensions of layers where neurons of every layer aren't fully connected to the next layer rather only a small portion is connected and the output will be decreased to a single dimension. For this, even with big datasets CNN works faster than any other networks. That's why we have used it for achieving a satisfying accuracy outcome. The program will exert plant images as input and detaching them to predict plant diseases. So it will help to identify and differentiate various types of plant diseases like aster yellows, bacterial wilt, scab, etc. quite easily & correctly.
{"title":"Plant Diseases Recognition Using Machine Learning","authors":"Md. Rahmat Ullah, Nagifa Anjum Dola, A. Sattar, Abir Hasnat","doi":"10.1109/SMART46866.2019.9117284","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117284","url":null,"abstract":"The way a doctor can predict what kind of diseases a patient is suffering from, similarly, the fastest stratagem of predicting plant diseases is to analyze leaf's physiognomy changes and compare them with their actual color, shape, structure, etc. Plant disease recognition on the basis of leaf's physiognomy changes is the fundamental purpose of our project. We have used Convolutional Neural Network as a training method. CNN works via 3 dimensions of layers where neurons of every layer aren't fully connected to the next layer rather only a small portion is connected and the output will be decreased to a single dimension. For this, even with big datasets CNN works faster than any other networks. That's why we have used it for achieving a satisfying accuracy outcome. The program will exert plant images as input and detaching them to predict plant diseases. So it will help to identify and differentiate various types of plant diseases like aster yellows, bacterial wilt, scab, etc. quite easily & correctly.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114858362","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117443
Pushpendra Singh, A. K. Dubey, P. Shrivastava
The high grinding ratio (GR) is one of the most desirable quality parameter in any grinding process. People are trying to improve the performance of grinding by combining it with other processes. Electrical discharge machining (EDM) is a process that has been adopted to develop hybrid variant of grinding. In the present research a combined process of grinding and EDM has been performed in high speed steel. The GR has been evaluated by varying different EDM and grinding parameters. Further, the process prediction and optimization of GR has been done by applying advanced artificial intelligence based technique. Optimization result elucidates significant improvement in GR.
{"title":"Performance Evaluation of Electrical Discharge Abrasive Grinding Process using Grinding Ratio","authors":"Pushpendra Singh, A. K. Dubey, P. Shrivastava","doi":"10.1109/SMART46866.2019.9117443","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117443","url":null,"abstract":"The high grinding ratio (GR) is one of the most desirable quality parameter in any grinding process. People are trying to improve the performance of grinding by combining it with other processes. Electrical discharge machining (EDM) is a process that has been adopted to develop hybrid variant of grinding. In the present research a combined process of grinding and EDM has been performed in high speed steel. The GR has been evaluated by varying different EDM and grinding parameters. Further, the process prediction and optimization of GR has been done by applying advanced artificial intelligence based technique. Optimization result elucidates significant improvement in GR.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123963542","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 : 2019-11-01DOI: 10.1109/smart46866.2019.9117361
{"title":"Track VII: System Modelling and Design Implementation","authors":"","doi":"10.1109/smart46866.2019.9117361","DOIUrl":"https://doi.org/10.1109/smart46866.2019.9117361","url":null,"abstract":"","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122162995","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}
The approaches to detecting Parkinson's disease in the human body from voice data by using Classification techniques apply three different algorithms for finding the growth rate of this disease. Unified Parkinson's disease rating scale deals with motor fluctuations and changes over voice after a certain period and that can measure the people affected by this disease and the difference with healthy people. Hoehn & Yahr scale measures the symptoms which are being working through the improvement of Parkinson's disease in the human body. Classifier algorithms used to detect the factors and symptoms which are involved in the advancement of this disease in the human body using voice data. From the distinctions of all algorithms measures the growth rate and find out which algorithm gives the best result for several approaches to diagnosis Parkinson's disease and chances of had this disease in the human body.
{"title":"A Knowledge Base Data Mining based on Parkinson's Disease","authors":"Md. Redone Hassan, S. Kadir, Md. Aminul Islam, Sheikh Abujar, Raihana Zannat, Ohidujjaman","doi":"10.1109/SMART46866.2019.9117450","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117450","url":null,"abstract":"The approaches to detecting Parkinson's disease in the human body from voice data by using Classification techniques apply three different algorithms for finding the growth rate of this disease. Unified Parkinson's disease rating scale deals with motor fluctuations and changes over voice after a certain period and that can measure the people affected by this disease and the difference with healthy people. Hoehn & Yahr scale measures the symptoms which are being working through the improvement of Parkinson's disease in the human body. Classifier algorithms used to detect the factors and symptoms which are involved in the advancement of this disease in the human body using voice data. From the distinctions of all algorithms measures the growth rate and find out which algorithm gives the best result for several approaches to diagnosis Parkinson's disease and chances of had this disease in the human body.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124745451","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117373
S. Manocha, Akanksha Upadhyaya
Information Technology is the combination of two words - “Information” and “Technology”. The above term is very easy to pronounce but having deep inside to elaborate and involutes about the insights of the given term is very vast and include an ocean of “information” when synthesizing with the “technology”. This is the reason that the people nowadays have named this ERA or generation as “The Era of Information Technology”. The Higher Education Institutes are not unaware of the requirement and importance of IT in the working area with respect to both the faculty and the students. As a result maximum amount of the money is being invested by these HEI's on the IT and the other allied resources to digitalize the entire routine working of the institute, from a small task to the bigger volumes of transactions, irrespective of its nature. The present paper basically focuses on the identification of crucial factors that led HEIs to adopt the technology. Further, the study has been carry forwarded to identify the significant difference between technology adoption factors and gender as demographic variables. To conduct the study online questionnaire was designed and 70 useful responses analysis was done. The analysis of the responses was done on IBM SPSS software using Exploratory Factor Analysis and Independent T-test. The study identified 5 factors that influence HEIs to adopt the technology. Furthermore, it is also revealed from the study that there is no significant difference between technology adoption factors and gender.
{"title":"Investigating Critical Factors Affecting the Adoption of Technology for Overall Development of HEI","authors":"S. Manocha, Akanksha Upadhyaya","doi":"10.1109/SMART46866.2019.9117373","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117373","url":null,"abstract":"Information Technology is the combination of two words - “Information” and “Technology”. The above term is very easy to pronounce but having deep inside to elaborate and involutes about the insights of the given term is very vast and include an ocean of “information” when synthesizing with the “technology”. This is the reason that the people nowadays have named this ERA or generation as “The Era of Information Technology”. The Higher Education Institutes are not unaware of the requirement and importance of IT in the working area with respect to both the faculty and the students. As a result maximum amount of the money is being invested by these HEI's on the IT and the other allied resources to digitalize the entire routine working of the institute, from a small task to the bigger volumes of transactions, irrespective of its nature. The present paper basically focuses on the identification of crucial factors that led HEIs to adopt the technology. Further, the study has been carry forwarded to identify the significant difference between technology adoption factors and gender as demographic variables. To conduct the study online questionnaire was designed and 70 useful responses analysis was done. The analysis of the responses was done on IBM SPSS software using Exploratory Factor Analysis and Independent T-test. The study identified 5 factors that influence HEIs to adopt the technology. Furthermore, it is also revealed from the study that there is no significant difference between technology adoption factors and gender.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129014375","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117225
D. Parygin, A. Golubev, I. Korneev, A. Gurtyakov, V. Tsyganov, Yury Zatuliveter
The paper considers the development of modules that allow to work with data using automated methods for processing and analyzing information on urban infrastructure with use of a single work procedure. The main contribution of this paper is the proposed methods for collecting and initial processing of information on infrastructure and real estate objects using different resources and technologies for extracting information. Also, the paper deals with the algorithm of interaction with the API of the Russian state site “ReformaGKH” and management of obtained data. Key software solutions for building the multiservice informational and analytical online platform of integrated geospatial data processing to support decision-making on urban areas development are described.
{"title":"Multiservice Online Platform for Integrated Geospatial Data Processing","authors":"D. Parygin, A. Golubev, I. Korneev, A. Gurtyakov, V. Tsyganov, Yury Zatuliveter","doi":"10.1109/SMART46866.2019.9117225","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117225","url":null,"abstract":"The paper considers the development of modules that allow to work with data using automated methods for processing and analyzing information on urban infrastructure with use of a single work procedure. The main contribution of this paper is the proposed methods for collecting and initial processing of information on infrastructure and real estate objects using different resources and technologies for extracting information. Also, the paper deals with the algorithm of interaction with the API of the Russian state site “ReformaGKH” and management of obtained data. Key software solutions for building the multiservice informational and analytical online platform of integrated geospatial data processing to support decision-making on urban areas development are described.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130212106","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}
To speaks to the potential answers for the particles where every last molecule has two vectors: position vector and speed vector, A Particle Swarm Optimization calculation presented. In this paper we presented another idea for the estimation of the speed with the idea of Euclidian Distance. The presented idea will help in finding the closeness of molecule with Gbest (Global best) and Pbest (Personal best). Our mean to acquaint this idea is with simply locate the ideal arrangement inside a sensible number of ages.
{"title":"Modified HPSO using TVAC and Analysis using CEC Benchmark Functions","authors":"Deepak Kumar, Er. Surbhi Madan, Er. Avneeshwar Singh","doi":"10.1109/SMART46866.2019.9117542","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117542","url":null,"abstract":"To speaks to the potential answers for the particles where every last molecule has two vectors: position vector and speed vector, A Particle Swarm Optimization calculation presented. In this paper we presented another idea for the estimation of the speed with the idea of Euclidian Distance. The presented idea will help in finding the closeness of molecule with Gbest (Global best) and Pbest (Personal best). Our mean to acquaint this idea is with simply locate the ideal arrangement inside a sensible number of ages.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115986008","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117480
M. K. Mahto, K. Bhatia, R.K. Sharma
Segmentation of words into isolated characters is the essential component in handwritten character recognition systems. In this paper, the segmentation of Gurmukhi handwritten words into characters is presented. For this, horizontal and vertical projection features have been used to segment the characters from words. Simple words without upper and lower modifier of Gurmukhi handwritten text having three and four characters are considered in the present work. An overall accuracy of 91.4 % on a dataset of 550 handwritten Gurmukhi words has been achieved in this work.
{"title":"Segmentation of Offline Handwritten Gurmukhi Words Using Projection Features","authors":"M. K. Mahto, K. Bhatia, R.K. Sharma","doi":"10.1109/SMART46866.2019.9117480","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117480","url":null,"abstract":"Segmentation of words into isolated characters is the essential component in handwritten character recognition systems. In this paper, the segmentation of Gurmukhi handwritten words into characters is presented. For this, horizontal and vertical projection features have been used to segment the characters from words. Simple words without upper and lower modifier of Gurmukhi handwritten text having three and four characters are considered in the present work. An overall accuracy of 91.4 % on a dataset of 550 handwritten Gurmukhi words has been achieved in this work.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127185050","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117371
A. Yakovlev, S. Postupaeva, V. Grebennikov, E.I. Sutulov
The paper considers an algorithm for constructing a model of the physical operating principle for cooling systems. The substantiation of this mathematical model is presented, graphic representations of the basic physical processes realized in cooling systems are developed. The proposed method allows to increase the productivity of designers at the first stages of work and is a methodological basis for the creation of CAD cooling systems with liquid and gaseous working fluid.
{"title":"Development of Cooling and Refrigerating Systems by the Search Design","authors":"A. Yakovlev, S. Postupaeva, V. Grebennikov, E.I. Sutulov","doi":"10.1109/SMART46866.2019.9117371","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117371","url":null,"abstract":"The paper considers an algorithm for constructing a model of the physical operating principle for cooling systems. The substantiation of this mathematical model is presented, graphic representations of the basic physical processes realized in cooling systems are developed. The proposed method allows to increase the productivity of designers at the first stages of work and is a methodological basis for the creation of CAD cooling systems with liquid and gaseous working fluid.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134038761","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117224
S. Chowdhury, Mushfiqur Rahman, M. T. Oyshi, Md. Arid Hasan
Automated text extraction from video data through lip reading can overcome the language barrier and open the door of opportunities in terms of security, connectivity and physical challenges. The conversion is possible by analyzing facial expression using deep learning method. But this conversion is a challenging task due to the varieties of pronunciation and accents of the same word causing different countenance. In this research, a method of converting video data to text data through lip reading has been proposed. The proposed method includes test dataset, image frame analysis and having text output from identified words. In the proposed technique, the test dataset will be organized by combining all the possible facial expressions of different words.
{"title":"Text Extraction through Video Lip Reading Using Deep Learning","authors":"S. Chowdhury, Mushfiqur Rahman, M. T. Oyshi, Md. Arid Hasan","doi":"10.1109/SMART46866.2019.9117224","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117224","url":null,"abstract":"Automated text extraction from video data through lip reading can overcome the language barrier and open the door of opportunities in terms of security, connectivity and physical challenges. The conversion is possible by analyzing facial expression using deep learning method. But this conversion is a challenging task due to the varieties of pronunciation and accents of the same word causing different countenance. In this research, a method of converting video data to text data through lip reading has been proposed. The proposed method includes test dataset, image frame analysis and having text output from identified words. In the proposed technique, the test dataset will be organized by combining all the possible facial expressions of different words.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122340347","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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