Pub Date : 2022-04-08DOI: 10.5815/ijitcs.2022.02.02
Sajid Bin-Faisal, Dip Nandi, Mashiour Rahman
In modern communication scenario of the 5G era, the service quality is the greatest concern for the users. Also, the concept of security can’t be neglected in this case. In the IoT oriented services like vehicle and VANET systems, the security in the presentation layer of the network is required. This work is over the security mechanism of the service storage and fetching the files for service. A new scheme of multi layered file and content encryption has been produced in order to strengthen the security of the file and data to maintain integrity and confidentiality of the IoT enabled services implemented in 5G. The encryption scheme is designed for the password encryption through asymmetric key cryptography (RSA) along with an enhanced concern of internal content or data security with symmetric key (AES-128) cryptography. This encryption system of double layer for a file makes the study unique and differentiable than other security schemes.
{"title":"Dual Layer Encryption for IoT based Vehicle Systems over 5G Communication","authors":"Sajid Bin-Faisal, Dip Nandi, Mashiour Rahman","doi":"10.5815/ijitcs.2022.02.02","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.02.02","url":null,"abstract":"In modern communication scenario of the 5G era, the service quality is the greatest concern for the users. Also, the concept of security can’t be neglected in this case. In the IoT oriented services like vehicle and VANET systems, the security in the presentation layer of the network is required. This work is over the security mechanism of the service storage and fetching the files for service. A new scheme of multi layered file and content encryption has been produced in order to strengthen the security of the file and data to maintain integrity and confidentiality of the IoT enabled services implemented in 5G. The encryption scheme is designed for the password encryption through asymmetric key cryptography (RSA) along with an enhanced concern of internal content or data security with symmetric key (AES-128) cryptography. This encryption system of double layer for a file makes the study unique and differentiable than other security schemes.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131663320","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 : 2022-04-08DOI: 10.5815/ijitcs.2022.02.04
Rohit Verma, Jyoti Dhiman
A network is an interconnected group of independent computing devices which uses a different set of protocols to communicate with each other independently and meaningfully. This communication should be carried out securely. Due to different attacks, this security sometimes gets compromised. So, to communicate securely different cryptography algorithms are used i.e., symmetric and asymmetric algorithms. Cryptography helps to achieve authentication, confidentiality, integrity, non-repudiation, and availability of data. Nowadays many algorithms provide security to data but these algorithms have various security flaws. To improve the strength of these algorithms, a new security protocol is designed using features of symmetric key and asymmetric key algorithms. The security principles can be achieved by AES and RSA algorithms. The main purpose of designing this algorithm is to provide better security to data in transit against passive as well as from active attacks. The new proposed hybrid algorithm is implemented in MATLAB R2019a. This algorithm will be analysed and compared on three parameters like avalanche effect, performance, and security against attacks. The proposed model will contribute towards improving the excellence of educators and academics, as well as increase competitiveness of educational programmes on cybersecurity among similar institutions in the EU countries.
{"title":"Implementation of Improved Cryptography Algorithm","authors":"Rohit Verma, Jyoti Dhiman","doi":"10.5815/ijitcs.2022.02.04","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.02.04","url":null,"abstract":"A network is an interconnected group of independent computing devices which uses a different set of protocols to communicate with each other independently and meaningfully. This communication should be carried out securely. Due to different attacks, this security sometimes gets compromised. So, to communicate securely different cryptography algorithms are used i.e., symmetric and asymmetric algorithms. Cryptography helps to achieve authentication, confidentiality, integrity, non-repudiation, and availability of data. Nowadays many algorithms provide security to data but these algorithms have various security flaws. To improve the strength of these algorithms, a new security protocol is designed using features of symmetric key and asymmetric key algorithms. The security principles can be achieved by AES and RSA algorithms. The main purpose of designing this algorithm is to provide better security to data in transit against passive as well as from active attacks. The new proposed hybrid algorithm is implemented in MATLAB R2019a. This algorithm will be analysed and compared on three parameters like avalanche effect, performance, and security against attacks. The proposed model will contribute towards improving the excellence of educators and academics, as well as increase competitiveness of educational programmes on cybersecurity among similar institutions in the EU countries.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123576575","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 : 2022-04-08DOI: 10.5815/ijitcs.2022.02.05
Kaniz Fatema Fomy, Ashik Mahmud, Musabbir Islam, Shamsur Rahim
Road traffic congestion is a recurring occurrence causing enormous loss of valuable working hours around the world. It is impossible to eradicate such a problem overnight. Rather it could be handled intelligently with the help of modern technologies. Researchers and practitioners have introduced several algorithms, frameworks, systems to mitigate traffic congestion. This paper presents a systematic literature review on existing research and critically analyze the applications on traffic analytics systems. After designing a review protocol, each work was evaluated based on the five research questions and criteria. After critically and carefully analyzing the existing works, this paper also identified the advantages as well as the limitations of the existing approaches towards solving traffic congestion. Based on the findings, a prototype of a mobile application is proposed that can be considered as an improved alternative to the existing works. Finally, this study provides future research directions and improvement scopes in this field.
{"title":"Road Rush: A Review on Road Traffic Analytics Systems and A Proposed Alternative","authors":"Kaniz Fatema Fomy, Ashik Mahmud, Musabbir Islam, Shamsur Rahim","doi":"10.5815/ijitcs.2022.02.05","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.02.05","url":null,"abstract":"Road traffic congestion is a recurring occurrence causing enormous loss of valuable working hours around the world. It is impossible to eradicate such a problem overnight. Rather it could be handled intelligently with the help of modern technologies. Researchers and practitioners have introduced several algorithms, frameworks, systems to mitigate traffic congestion. This paper presents a systematic literature review on existing research and critically analyze the applications on traffic analytics systems. After designing a review protocol, each work was evaluated based on the five research questions and criteria. After critically and carefully analyzing the existing works, this paper also identified the advantages as well as the limitations of the existing approaches towards solving traffic congestion. Based on the findings, a prototype of a mobile application is proposed that can be considered as an improved alternative to the existing works. Finally, this study provides future research directions and improvement scopes in this field.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"376 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122346388","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 : 2022-04-08DOI: 10.5815/ijitcs.2022.02.03
O. S. Adebayo, Bashir Sulaimon Adebayo, Monday Jubril Abdullah, Omale Samuel Enemona, Lateefah Abdulazeez
This research developed a secured student industrial work experience scheme (SIWES) placement system to take care of the security challenges of the existing automated systems. There are attempts by researchers to ameliorate the challenges associated with the scheme by developing various systems. However, the developed systems are subjected to security vulnerabilities. This research, in an attempt to avert the security challenges associated with the existing automated systems, designed a new scheme which includes security architectures in the kernel and application layers. This new system was able to achieve two important tasks; first, the system automation and second, the inclusion of security architectures to cubs the application’s vulnerabilities. The present process involves students manually seeking placement to undergo the program, and due to this, students end up applying at organizations that are not relevant to what they are studying. Despite the fact there are no much existing systems that digitally caters for this component of the scheme, the available existing systems are subjected to security vulnerability. Therefore, leveraging on secure web application technologies using Unified Modelling Languages for design, HTML, CSS, JavaScript, PHP for its implementation and user privilege and password hash to ensure its security, this project developed a secure solution to this pertinent challenge. The system is tested using unit testing component of each design, integration testing and general system testing. The implementation shows the system works according to the design, by ensuring all units of the development perform necessary functions of data storage, data retrieval, error alerting, and interface/server appropriate communication. In addition, the security architecture, design and implementation of the system’s design are better than the existing ones.
{"title":"Development of an Electronic Secure Students’ Industrial Works Experience Scheme Placement System","authors":"O. S. Adebayo, Bashir Sulaimon Adebayo, Monday Jubril Abdullah, Omale Samuel Enemona, Lateefah Abdulazeez","doi":"10.5815/ijitcs.2022.02.03","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.02.03","url":null,"abstract":"This research developed a secured student industrial work experience scheme (SIWES) placement system to take care of the security challenges of the existing automated systems. There are attempts by researchers to ameliorate the challenges associated with the scheme by developing various systems. However, the developed systems are subjected to security vulnerabilities. This research, in an attempt to avert the security challenges associated with the existing automated systems, designed a new scheme which includes security architectures in the kernel and application layers. This new system was able to achieve two important tasks; first, the system automation and second, the inclusion of security architectures to cubs the application’s vulnerabilities. The present process involves students manually seeking placement to undergo the program, and due to this, students end up applying at organizations that are not relevant to what they are studying. Despite the fact there are no much existing systems that digitally caters for this component of the scheme, the available existing systems are subjected to security vulnerability. Therefore, leveraging on secure web application technologies using Unified Modelling Languages for design, HTML, CSS, JavaScript, PHP for its implementation and user privilege and password hash to ensure its security, this project developed a secure solution to this pertinent challenge. The system is tested using unit testing component of each design, integration testing and general system testing. The implementation shows the system works according to the design, by ensuring all units of the development perform necessary functions of data storage, data retrieval, error alerting, and interface/server appropriate communication. In addition, the security architecture, design and implementation of the system’s design are better than the existing ones.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115214799","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 : 2022-04-08DOI: 10.5815/ijitcs.2022.02.01
Talal Almutiri, F. Nadeem
Markov models are one of the widely used techniques in machine learning to process natural language. Markov Chains and Hidden Markov Models are stochastic techniques employed for modeling systems that are dynamic and where the future state relies on the current state. The Markov chain, which generates a sequence of words to create a complete sentence, is frequently used in generating natural language. The hidden Markov model is employed in named-entity recognition and the tagging of parts of speech, which tries to predict hidden tags based on observed words. This paper reviews Markov models' use in three applications of natural language processing (NLP): natural language generation, named-entity recognition, and parts of speech tagging. Nowadays, researchers try to reduce dependence on lexicon or annotation tasks in NLP. In this paper, we have focused on Markov Models as a stochastic approach to process NLP. A literature review was conducted to summarize research attempts with focusing on methods/techniques that used Markov Models to process NLP, their advantages, and disadvantages. Most NLP research studies apply supervised models with the improvement of using Markov models to decrease the dependency on annotation tasks. Some others employed unsupervised solutions for reducing dependence on a lexicon or labeled datasets.
{"title":"Markov Models Applications in Natural Language Processing: A Survey","authors":"Talal Almutiri, F. Nadeem","doi":"10.5815/ijitcs.2022.02.01","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.02.01","url":null,"abstract":"Markov models are one of the widely used techniques in machine learning to process natural language. Markov Chains and Hidden Markov Models are stochastic techniques employed for modeling systems that are dynamic and where the future state relies on the current state. The Markov chain, which generates a sequence of words to create a complete sentence, is frequently used in generating natural language. The hidden Markov model is employed in named-entity recognition and the tagging of parts of speech, which tries to predict hidden tags based on observed words. This paper reviews Markov models' use in three applications of natural language processing (NLP): natural language generation, named-entity recognition, and parts of speech tagging. Nowadays, researchers try to reduce dependence on lexicon or annotation tasks in NLP. In this paper, we have focused on Markov Models as a stochastic approach to process NLP. A literature review was conducted to summarize research attempts with focusing on methods/techniques that used Markov Models to process NLP, their advantages, and disadvantages. Most NLP research studies apply supervised models with the improvement of using Markov models to decrease the dependency on annotation tasks. Some others employed unsupervised solutions for reducing dependence on a lexicon or labeled datasets.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129593029","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 : 2022-02-08DOI: 10.5815/ijitcs.2022.01.04
M. M. Khan, Waqas Mahmood
The success of any software product could be measured by its uses and adoption of that technology by the end-users. In this study, we investigate the factors on which bank user intents to adopt internet banking in Pakistan. A survey was conducted on Pakistani banking industry customers using the unified theory of acceptance and use of technology (UTAUT) model which explains the intention of bank users to use the banking systems. The four predictors of UTAUT which were facilitating conditions, social influence, effort expectancy and performance expectancy were significant in predicting the intention of bank users to adopt the banking systems. Finally, we discuss the results, restrictions, implications and future recommendations. The findings of the study may help to provide insights into a better approach to promote e-banking acceptance.
{"title":"Technology Adoption in Pakistani Banking Industry using UTAUT","authors":"M. M. Khan, Waqas Mahmood","doi":"10.5815/ijitcs.2022.01.04","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.01.04","url":null,"abstract":"The success of any software product could be measured by its uses and adoption of that technology by the end-users. In this study, we investigate the factors on which bank user intents to adopt internet banking in Pakistan. A survey was conducted on Pakistani banking industry customers using the unified theory of acceptance and use of technology (UTAUT) model which explains the intention of bank users to use the banking systems. The four predictors of UTAUT which were facilitating conditions, social influence, effort expectancy and performance expectancy were significant in predicting the intention of bank users to adopt the banking systems. Finally, we discuss the results, restrictions, implications and future recommendations. The findings of the study may help to provide insights into a better approach to promote e-banking acceptance.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131916849","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 : 2022-02-08DOI: 10.5815/ijitcs.2022.01.02
Kishan Kumar Ganguly, Moumita Asad, K. Sakib
Decentralized self-adaptive systems consist of multiple control loops that adapt some local and system-level global goals of each locally managed system or component in a decentralized setting. As each component works together in a decentralized environment, a control loop cannot take adaptation decisions independently. Therefore, all the control loops need to exchange their adaptation decisions to infer a global knowledge about the system. Decentralized self-adaptation approaches in the literature uses the global knowledge to take decisions that optimize both local and global goals. However, coordinating in such an unbounded manner impairs scalability. This paper proposes a decentralized self-adaptation technique using reinforcement learning that incorporates partial knowledge in order to reduce coordination overhead. The Q-learning algorithm based on Interaction Driven Markov Games is utilized to take adaptation decisions as it enables coordination only when it is beneficial. Rather than using unbounded number of peers, the adaptation control loop coordinates with a single peer control loop. The proposed approach was evaluated on a service-based Tele Assistance System. It was compared to random, independent and multiagent learners that assume global knowledge. It was observed that, in all cases, the proposed approach conformed to both local and global goals while maintaining comparatively lower coordination overhead.
{"title":"Decentralized Self-adaptation in the Presence of Partial Knowledge with Reduced Coordination Overhead","authors":"Kishan Kumar Ganguly, Moumita Asad, K. Sakib","doi":"10.5815/ijitcs.2022.01.02","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.01.02","url":null,"abstract":"Decentralized self-adaptive systems consist of multiple control loops that adapt some local and system-level global goals of each locally managed system or component in a decentralized setting. As each component works together in a decentralized environment, a control loop cannot take adaptation decisions independently. Therefore, all the control loops need to exchange their adaptation decisions to infer a global knowledge about the system. Decentralized self-adaptation approaches in the literature uses the global knowledge to take decisions that optimize both local and global goals. However, coordinating in such an unbounded manner impairs scalability. This paper proposes a decentralized self-adaptation technique using reinforcement learning that incorporates partial knowledge in order to reduce coordination overhead. The Q-learning algorithm based on Interaction Driven Markov Games is utilized to take adaptation decisions as it enables coordination only when it is beneficial. Rather than using unbounded number of peers, the adaptation control loop coordinates with a single peer control loop. The proposed approach was evaluated on a service-based Tele Assistance System. It was compared to random, independent and multiagent learners that assume global knowledge. It was observed that, in all cases, the proposed approach conformed to both local and global goals while maintaining comparatively lower coordination overhead.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123456989","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 : 2022-02-08DOI: 10.5815/ijitcs.2022.01.03
Winanti, F. Goestjahjanti
Informal education will be successful as an alternative for the community because not all people are able to receive formal education. This study uses a qualitative method with a systematic literature review (SLR) technique to look for learning community components in informal education to support learning in the culinary community in the new normal era of Covid-19. The author collects, studies, and analyzes reference sources according to the specified keywords. Found 53 papers from 2002 to 2021 with background authors from academia, industry, and the public sector with reference sources from journals, conferences, white papers, and research reports. Systematic literature review results obtained 6 components of learning community in informal education, namely content, forum, method, technology, figure/layout, and human/social resources. The six components as a reference and the author's first step in the next research through searching for the characteristics of the learning community in the culinary field, then making a learning model of the culinary community. Because of the importance of the learning community component in informal education to help community members share knowledge, solve problems, share common goals and interests among community members.
{"title":"Component Learning Community for Informal Education to Support Culinary Community at Era New Normal Covid-19: A Systematic Literature Review","authors":"Winanti, F. Goestjahjanti","doi":"10.5815/ijitcs.2022.01.03","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.01.03","url":null,"abstract":"Informal education will be successful as an alternative for the community because not all people are able to receive formal education. This study uses a qualitative method with a systematic literature review (SLR) technique to look for learning community components in informal education to support learning in the culinary community in the new normal era of Covid-19. The author collects, studies, and analyzes reference sources according to the specified keywords. Found 53 papers from 2002 to 2021 with background authors from academia, industry, and the public sector with reference sources from journals, conferences, white papers, and research reports. Systematic literature review results obtained 6 components of learning community in informal education, namely content, forum, method, technology, figure/layout, and human/social resources. The six components as a reference and the author's first step in the next research through searching for the characteristics of the learning community in the culinary field, then making a learning model of the culinary community. Because of the importance of the learning community component in informal education to help community members share knowledge, solve problems, share common goals and interests among community members.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116959526","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}
Leaf disease of plants causes great loss in productivity of crops. So proper take care of plants is mandatory. Plants can be affected by various diseases. So Early diagnosis of leaf disease is a good practice. Computer vision-based classification of leaf disease can be a great way in diagnosing diseases early. Early detection of diseases can lead to better treatment. Vision based technology can identify disease quickly. Though deep learning is trending and using vastly for recognition task, but it needs very large dataset and also consumes much time. This paper introduced a method to classify leaf diseases using Gist and LBP (Local Binary Pattern) feature. These manual feature extraction process need less time. Combination of gist and LBP features shows significant result in classification of leaf diseases. Gist is used as global feature and LBP as local feature. Gist can describe an image very well as a scene. LBP is robust to illumination changes and occlusions and computationally simple. Various diseases of different plants are considered in this study. Gist and LBP features from images are extracted separately. Images are pre-processed before feature extraction. Then both feature matrix is combined using concatenation method. Training and testing is done on different plants separately. Different machine learning model is applied on the feature vector. Result from different machine learning algorithms is also compared. SVM performs better in classifying plant's leaf dataset.
{"title":"Classification of Leaf Disease Using Global and Local Features","authors":"Prashengit Dhar, Md. Shohelur Rahman, Zainal Abedin","doi":"10.5815/ijitcs.2022.01.05","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.01.05","url":null,"abstract":"Leaf disease of plants causes great loss in productivity of crops. So proper take care of plants is mandatory. Plants can be affected by various diseases. So Early diagnosis of leaf disease is a good practice. Computer vision-based classification of leaf disease can be a great way in diagnosing diseases early. Early detection of diseases can lead to better treatment. Vision based technology can identify disease quickly. Though deep learning is trending and using vastly for recognition task, but it needs very large dataset and also consumes much time. This paper introduced a method to classify leaf diseases using Gist and LBP (Local Binary Pattern) feature. These manual feature extraction process need less time. Combination of gist and LBP features shows significant result in classification of leaf diseases. Gist is used as global feature and LBP as local feature. Gist can describe an image very well as a scene. LBP is robust to illumination changes and occlusions and computationally simple. Various diseases of different plants are considered in this study. Gist and LBP features from images are extracted separately. Images are pre-processed before feature extraction. Then both feature matrix is combined using concatenation method. Training and testing is done on different plants separately. Different machine learning model is applied on the feature vector. Result from different machine learning algorithms is also compared. SVM performs better in classifying plant's leaf dataset.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132058921","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 : 2022-02-08DOI: 10.5815/ijitcs.2022.01.01
Mesut Polatgil
Machine learning and artificial intelligence techniques are more and more in our lives and studies in this field are increasing day by day. Data is vital for these studies. In order to draw meaningful conclusions from the available data, new methods are proposed and successful results are obtained. The preparation of the obtained data is very important in the studies to be carried out. Data preprocessing is very important in the preparation of data. The most critical stage of the data preprocessing process is the scaling or normalization of the data. Machine learning libraries such as scikit-learn and programming languages such as R provide the necessary libraries to scale data. However, it is not known exactly which normalization method will be applied and which will yield more successful results. The success of these normalization methods has been investigated on many different methods, but such a study has not been done on the adaptive neural fuzzy inference system (ANFIS). The aim of this study is to examine the success of normalization methods on ANFIS in terms of both classification and regression problems. So, for studies using the Anfis method, guidance will be provided on which normalization process will give better results in the data preprocessing stage. Four different normalization methods in the scikit-learn library were applied on the Diabets and Forestfire datasets in the UCI database. The results are presented separately for both classification and regression. It has been determined that min-max normalization in classification problems and working with original data in regression problems are more successful.
{"title":"Investigation of the Effect of Normalization Methods on ANFIS Success: Forestfire and Diabets Datasets","authors":"Mesut Polatgil","doi":"10.5815/ijitcs.2022.01.01","DOIUrl":"https://doi.org/10.5815/ijitcs.2022.01.01","url":null,"abstract":"Machine learning and artificial intelligence techniques are more and more in our lives and studies in this field are increasing day by day. Data is vital for these studies. In order to draw meaningful conclusions from the available data, new methods are proposed and successful results are obtained. The preparation of the obtained data is very important in the studies to be carried out. Data preprocessing is very important in the preparation of data. The most critical stage of the data preprocessing process is the scaling or normalization of the data. Machine learning libraries such as scikit-learn and programming languages such as R provide the necessary libraries to scale data. However, it is not known exactly which normalization method will be applied and which will yield more successful results. The success of these normalization methods has been investigated on many different methods, but such a study has not been done on the adaptive neural fuzzy inference system (ANFIS). The aim of this study is to examine the success of normalization methods on ANFIS in terms of both classification and regression problems. So, for studies using the Anfis method, guidance will be provided on which normalization process will give better results in the data preprocessing stage. Four different normalization methods in the scikit-learn library were applied on the Diabets and Forestfire datasets in the UCI database. The results are presented separately for both classification and regression. It has been determined that min-max normalization in classification problems and working with original data in regression problems are more successful.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131935807","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：