This paper explores the proposed solutions based on blockchain technology's potential to solve supply chain management issues. The problems include lack of traceability and transparency, scalability and cost issues, sustainability, efficiency, patchwork logistics, and bullwhip effect issues. In this paper, we have suggested some solutions with the help of blockchain technology. The solutions can solve multiple significant issues in supply chain management. Our blockchain-based solutions can provide a secure and visible record of all transactions and data along the supply chain, which can improve traceability and transparency, a decentralized and efficient method of data processing and exchange that can also increase scalability and reduce cost, a transparent and accountable way to track and verify sustainability-related data. Our method can enable more streamlined and automated tracking and data sharing, helping to reduce the risk of delays and inefficiencies while mitigating the risk of the bullwhip effect by providing real-time visibility and enabling better communication and collaboration between parties. The paper discusses the implications and challenges of implementing blockchain in supply chain management.
{"title":"Beyond the Hype: A Proposed Model Based on Critical Analysis of Blockchain Technology’s Potential to Address Supply Chain Issues","authors":"A.S.M. Fazle Rabbi, T.M. Ragib Shahrier, Mushfiqur Rahman Miraz, Sazia Rahman, Dip Nandi","doi":"10.5815/ijitcs.2023.06.05","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.06.05","url":null,"abstract":"This paper explores the proposed solutions based on blockchain technology's potential to solve supply chain management issues. The problems include lack of traceability and transparency, scalability and cost issues, sustainability, efficiency, patchwork logistics, and bullwhip effect issues. In this paper, we have suggested some solutions with the help of blockchain technology. The solutions can solve multiple significant issues in supply chain management. Our blockchain-based solutions can provide a secure and visible record of all transactions and data along the supply chain, which can improve traceability and transparency, a decentralized and efficient method of data processing and exchange that can also increase scalability and reduce cost, a transparent and accountable way to track and verify sustainability-related data. Our method can enable more streamlined and automated tracking and data sharing, helping to reduce the risk of delays and inefficiencies while mitigating the risk of the bullwhip effect by providing real-time visibility and enabling better communication and collaboration between parties. The paper discusses the implications and challenges of implementing blockchain in supply chain management.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"8 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138586446","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 : 2023-08-08DOI: 10.5815/ijitcs.2023.04.03
Utsha Das, Hasan Sanjary Islam, Kakon Paul Avi, Ajmayeen Adil, Dipannyta Nandi
Predicting crop yields is one of the more difficult tasks in the agriculture sector. A fascinating area of research to estimate agricultural productivity has emerged from recent advancements in information technology for agriculture. Crop yield prediction is a technique for estimating crop production based on a variety of factors, including weather conditions and parameters such as temperature, rainfall, fertilizer, and pesticide use. In the world of agriculture, Data mining techniques are extremely popular. In order to predict the crop production for the following year, data mining techniques are employed and evaluated in the agricultural sector. In this paper, we carried out the comparison between Naive Bayes, K-nearest neighbor, Decision Tree, Random Forest, and K-Means clustering algorithms to predict crop yield in order to determine which method is most effective at doing so. The results show which algorithm is better suitable for this particular purpose by comparing these data mining algorithms for agricultural crop production and determining which algorithm is more successful for this outcome.
{"title":"Comparative Analysis of Data Mining Techniques for Predicting the Yield of Agricultural Crops","authors":"Utsha Das, Hasan Sanjary Islam, Kakon Paul Avi, Ajmayeen Adil, Dipannyta Nandi","doi":"10.5815/ijitcs.2023.04.03","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.04.03","url":null,"abstract":"Predicting crop yields is one of the more difficult tasks in the agriculture sector. A fascinating area of research to estimate agricultural productivity has emerged from recent advancements in information technology for agriculture. Crop yield prediction is a technique for estimating crop production based on a variety of factors, including weather conditions and parameters such as temperature, rainfall, fertilizer, and pesticide use. In the world of agriculture, Data mining techniques are extremely popular. In order to predict the crop production for the following year, data mining techniques are employed and evaluated in the agricultural sector. In this paper, we carried out the comparison between Naive Bayes, K-nearest neighbor, Decision Tree, Random Forest, and K-Means clustering algorithms to predict crop yield in order to determine which method is most effective at doing so. The results show which algorithm is better suitable for this particular purpose by comparing these data mining algorithms for agricultural crop production and determining which algorithm is more successful for this outcome.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117152119","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 : 2023-08-08DOI: 10.5815/ijitcs.2023.04.04
Yashi Agarwal, P. Vamsi, Siddhanth Jain, Jayant Goel
The majority of collaborative learning and knowledge sharing (CLKS) platforms are built with numerous communication mediums, team and task management in mind. However, with the CLKS, the Question-Answering (QAs), User profile evaluation based on the quality of answers provided, and feeding of subject or project relevant data are all available. QAs are required for online or offline cooperation between team members or users. To that purpose, this paper presents a web application called CodeUP with features like QA system, Question similarity testing, and user profile rating for boosting communication and cooperation efficiency in CLKS for academic groups and small development teams. CodeUP is intended to be quickly established and step for academic or development groups to collaborate. As the CodeUP application supports the CLKS, it is also an ideal tool for academia and development teams to perform computer supported QA system and knowledge sharing in the sphere of work or study.
{"title":"CodeUP: A Web Application for Collaborative Question-answering System","authors":"Yashi Agarwal, P. Vamsi, Siddhanth Jain, Jayant Goel","doi":"10.5815/ijitcs.2023.04.04","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.04.04","url":null,"abstract":"The majority of collaborative learning and knowledge sharing (CLKS) platforms are built with numerous communication mediums, team and task management in mind. However, with the CLKS, the Question-Answering (QAs), User profile evaluation based on the quality of answers provided, and feeding of subject or project relevant data are all available. QAs are required for online or offline cooperation between team members or users. To that purpose, this paper presents a web application called CodeUP with features like QA system, Question similarity testing, and user profile rating for boosting communication and cooperation efficiency in CLKS for academic groups and small development teams. CodeUP is intended to be quickly established and step for academic or development groups to collaborate. As the CodeUP application supports the CLKS, it is also an ideal tool for academia and development teams to perform computer supported QA system and knowledge sharing in the sphere of work or study.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122211328","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 : 2023-08-08DOI: 10.5815/ijitcs.2023.04.02
Tahani M. Allam
Many studying systems of gene function work depend on the DNA motif. DNA motifs finding generate a lot of trails which make it complex. Regulation of gene expression is identified according to Transcription Factor Binding Sites (TFBSs). There are different algorithms explained, over the past decades, to get an accurate motif tool. The major problems for these algorithms are on the execution time and the memory size which depend on the probabilistic approaches. Our previous algorithm, called EIMF, is recently proposed to overcome these problems by rearranging data. Because cloud computing involves many resources, the challenge of mapping jobs to infinite computing resources is an NP-hard optimization problem. In this paper, we proposed an Impala framework for solving a motif finding algorithms in single and multi-user based on cloud computing. Also, the comparison between Cloud motif and previous EIMF algorithms is performed in three different motif group. The results obtained the Cloudera motif was a considerable finding algorithms in the experimental group that decreased the execution time and the Memory size, when compared with the previous EIMF algorithms. The proposed MOTIFSM algorithm based on the cloud computing decrease the execution time by 70% approximately in MOTIFSM than EIMF framework. Memory size also is decreased in MOTIFSM about 75% than EIMF.
{"title":"MOTIFSM: Cloudera Motif DNA Finding Algorithm","authors":"Tahani M. Allam","doi":"10.5815/ijitcs.2023.04.02","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.04.02","url":null,"abstract":"Many studying systems of gene function work depend on the DNA motif. DNA motifs finding generate a lot of trails which make it complex. Regulation of gene expression is identified according to Transcription Factor Binding Sites (TFBSs). There are different algorithms explained, over the past decades, to get an accurate motif tool. The major problems for these algorithms are on the execution time and the memory size which depend on the probabilistic approaches. Our previous algorithm, called EIMF, is recently proposed to overcome these problems by rearranging data. Because cloud computing involves many resources, the challenge of mapping jobs to infinite computing resources is an NP-hard optimization problem. In this paper, we proposed an Impala framework for solving a motif finding algorithms in single and multi-user based on cloud computing. Also, the comparison between Cloud motif and previous EIMF algorithms is performed in three different motif group. The results obtained the Cloudera motif was a considerable finding algorithms in the experimental group that decreased the execution time and the Memory size, when compared with the previous EIMF algorithms. The proposed MOTIFSM algorithm based on the cloud computing decrease the execution time by 70% approximately in MOTIFSM than EIMF framework. Memory size also is decreased in MOTIFSM about 75% than EIMF.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122237245","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 : 2023-08-08DOI: 10.5815/ijitcs.2023.04.01
M. Kovtun, V. Kovtun, Oleksandr Stokipnyi, Andrew Okhrimenko
Modern cryptosystems allow the use of operation in prime fields with special kind of modules that can speed up the prime field operation: multiplication, squaring, exponentiation. The authors took into account in the optimizations: the CPU architecture and the multiplicity of the degree of the modulus in relation to the machine word width. As example, shown adopted module reduction algorithms hard-coded for modern CPU in special form of pseudo-Mersenne prime used in MAC algorithm Poly1305, - in electronic signature algorithm EdDSA and - in short message encryption algorithm DSTU 9041. These algorithms have been software implemented on both 32-bit and 64-bit platforms and compared with Barrett modular reduction algorithm for different pseudo-Mersenne and generalized-Mersenne modules. Timings for proposed and Barrett algorithms for different modules are presented and discussed.
{"title":"Software Implementation of Modular Reduction by Pseudo-mersenne Primes","authors":"M. Kovtun, V. Kovtun, Oleksandr Stokipnyi, Andrew Okhrimenko","doi":"10.5815/ijitcs.2023.04.01","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.04.01","url":null,"abstract":"Modern cryptosystems allow the use of operation in prime fields with special kind of modules that can speed up the prime field operation: multiplication, squaring, exponentiation. The authors took into account in the optimizations: the CPU architecture and the multiplicity of the degree of the modulus in relation to the machine word width. As example, shown adopted module reduction algorithms hard-coded for modern CPU in special form of pseudo-Mersenne prime used in MAC algorithm Poly1305, - in electronic signature algorithm EdDSA and - in short message encryption algorithm DSTU 9041. These algorithms have been software implemented on both 32-bit and 64-bit platforms and compared with Barrett modular reduction algorithm for different pseudo-Mersenne and generalized-Mersenne modules. Timings for proposed and Barrett algorithms for different modules are presented and discussed.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115017430","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 : 2023-06-08DOI: 10.5815/ijitcs.2023.03.02
P. G., S. N
In recent days, the smart city project has been emerging concept all over the world. In this process, the proper communication between the sensors and the smart devices, and identification of optimal path between sensors and mutation sensors in large geographical area is very difficult. The main objective has been considered to overcome the drawbacks as mentioned above. The proposed algorithm is efficient to provide integrated communication of IoT-based ubiquitous networking (UBN) devices to improve in large geographically distributed area. The data storage capacity and accuracy of sensors and smart devices are enhanced using the proposed algorithm. The communication latency and data pre-processing of IoT-based UBN nodes deployed in smart cities are reduced. The proposed algorithm also analyses the performance of IoT-based UBN nodes by considering geographical testbeds that represent a smart city scenario. The analysis and comparison are carried out by considering the heuristic parameters. The proposed algorithm will also optimize the communication latency and data pre-processing time by analyzing various sensitivity levels by considering the heuristic parameters in different probability of nodes in smart cities. The proposed IoT-based UBN computing devices improve the objective function due to proper integrated communication between the sensors using a machine learning based regression algorithm. The proposed algorithm also identifies the probability sensitivity of optimal path between smart devices in a smart city thereby enhancing the connectivity of mutated sensor nodes. The proposed algorithm also enhances the probability of smart device connectivity to improve the accuracy, flexibility and large geographical coverage using machine learning based regression algorithm.
{"title":"An Efficient IoT-based Ubiquitous Networking Service for Smart Cities Using Machine Learning Based Regression Algorithm","authors":"P. G., S. N","doi":"10.5815/ijitcs.2023.03.02","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.03.02","url":null,"abstract":"In recent days, the smart city project has been emerging concept all over the world. In this process, the proper communication between the sensors and the smart devices, and identification of optimal path between sensors and mutation sensors in large geographical area is very difficult. The main objective has been considered to overcome the drawbacks as mentioned above. The proposed algorithm is efficient to provide integrated communication of IoT-based ubiquitous networking (UBN) devices to improve in large geographically distributed area. The data storage capacity and accuracy of sensors and smart devices are enhanced using the proposed algorithm. The communication latency and data pre-processing of IoT-based UBN nodes deployed in smart cities are reduced. The proposed algorithm also analyses the performance of IoT-based UBN nodes by considering geographical testbeds that represent a smart city scenario. The analysis and comparison are carried out by considering the heuristic parameters. The proposed algorithm will also optimize the communication latency and data pre-processing time by analyzing various sensitivity levels by considering the heuristic parameters in different probability of nodes in smart cities. The proposed IoT-based UBN computing devices improve the objective function due to proper integrated communication between the sensors using a machine learning based regression algorithm. The proposed algorithm also identifies the probability sensitivity of optimal path between smart devices in a smart city thereby enhancing the connectivity of mutated sensor nodes. The proposed algorithm also enhances the probability of smart device connectivity to improve the accuracy, flexibility and large geographical coverage using machine learning based regression algorithm.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124615194","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 : 2023-06-08DOI: 10.5815/ijitcs.2023.03.04
Carol W. Kimani, J. Obuhuma, Emily Roche
Universities across the globe have increasingly adopted Enterprise Resource Planning (ERP) systems, a software that provides integrated management of processes and transactions in real-time. These systems contain lots of information hence require secure authentication. Authentication in this case refers to the process of verifying an entity’s or device’s identity, to allow them access to specific resources upon request. However, there have been security and privacy concerns around ERP systems, where only the traditional authentication method of a username and password is commonly used. A password-based authentication approach has weaknesses that can be easily compromised. Cyber-attacks to access these ERP systems have become common to institutions of higher learning and cannot be underestimated as they evolve with emerging technologies. Some universities worldwide have been victims of cyber-attacks which targeted authentication vulnerabilities resulting in damages to the institutions reputations and credibilities. Thus, this research aimed at establishing authentication methods used for ERPs in Kenyan universities, their vulnerabilities, and proposing a solution to improve on ERP system authentication. The study aimed at developing and validating a multi-factor authentication prototype to improve ERP systems security. Multi-factor authentication which combines several authentication factors such as: something the user has, knows, or is, is a new state-of-the-art technology that is being adopted to strengthen systems’ authentication security. This research used an exploratory sequential design that involved a survey of chartered Kenyan Universities, where questionnaires were used to collect data that was later analyzed using descriptive and inferential statistics. Stratified, random and purposive sampling techniques were used to establish the sample size and the target group. The dependent variable for the study was limited to security rating with respect to realization of confidentiality, integrity, availability, and usability while the independent variables were limited to adequacy of security, authentication mechanisms, infrastructure, information security policies, vulnerabilities, and user training. Correlation and regression analysis established vulnerabilities, information security policies, and user training to be having a higher impact on system security. The three variables hence acted as the basis for the proposed multi-factor authentication framework for improve ERP systems security.
{"title":"Multi-Factor Authentication for Improved Enterprise Resource Planning Systems Security","authors":"Carol W. Kimani, J. Obuhuma, Emily Roche","doi":"10.5815/ijitcs.2023.03.04","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.03.04","url":null,"abstract":"Universities across the globe have increasingly adopted Enterprise Resource Planning (ERP) systems, a software that provides integrated management of processes and transactions in real-time. These systems contain lots of information hence require secure authentication. Authentication in this case refers to the process of verifying an entity’s or device’s identity, to allow them access to specific resources upon request. However, there have been security and privacy concerns around ERP systems, where only the traditional authentication method of a username and password is commonly used. A password-based authentication approach has weaknesses that can be easily compromised. Cyber-attacks to access these ERP systems have become common to institutions of higher learning and cannot be underestimated as they evolve with emerging technologies. Some universities worldwide have been victims of cyber-attacks which targeted authentication vulnerabilities resulting in damages to the institutions reputations and credibilities. Thus, this research aimed at establishing authentication methods used for ERPs in Kenyan universities, their vulnerabilities, and proposing a solution to improve on ERP system authentication. The study aimed at developing and validating a multi-factor authentication prototype to improve ERP systems security. Multi-factor authentication which combines several authentication factors such as: something the user has, knows, or is, is a new state-of-the-art technology that is being adopted to strengthen systems’ authentication security. This research used an exploratory sequential design that involved a survey of chartered Kenyan Universities, where questionnaires were used to collect data that was later analyzed using descriptive and inferential statistics. Stratified, random and purposive sampling techniques were used to establish the sample size and the target group. The dependent variable for the study was limited to security rating with respect to realization of confidentiality, integrity, availability, and usability while the independent variables were limited to adequacy of security, authentication mechanisms, infrastructure, information security policies, vulnerabilities, and user training. Correlation and regression analysis established vulnerabilities, information security policies, and user training to be having a higher impact on system security. The three variables hence acted as the basis for the proposed multi-factor authentication framework for improve ERP systems security.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"78 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129713252","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 : 2023-06-08DOI: 10.5815/ijitcs.2023.03.05
A. Huseynova, O. Mazanova
The article describes the application of the Smart City concept and the economic opportunities it creates, infrastructure and services, and opportunities to improve governance. The main features of the Smart City concept, development directions and evolution, standards and solutions, and factors and obstacles to its implementation have been analyzed by the author. The experience of different countries in the application of digital technologies is discussed. The article provides the scope and structure of the "smart" market, application stages, and scenarios The international experience in this direction was widely analyzed and examples were shown. The article talks about smart cities, the construction of which has already begun in Azerbaijan. The application of the smart city concept in Azerbaijan has been studied. It is stressed that the spread of digital technologies for the construction of a smart city in Azerbaijan is a prerequisite. The Network Readiness Index (NRI) identifies the indicators that are holding back Azerbaijan in the ranking for 2021.
{"title":"The Leading Role of Digital Technologies in the Development of the Smart City Concept in Azerbaijan","authors":"A. Huseynova, O. Mazanova","doi":"10.5815/ijitcs.2023.03.05","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.03.05","url":null,"abstract":"The article describes the application of the Smart City concept and the economic opportunities it creates, infrastructure and services, and opportunities to improve governance. The main features of the Smart City concept, development directions and evolution, standards and solutions, and factors and obstacles to its implementation have been analyzed by the author. The experience of different countries in the application of digital technologies is discussed. The article provides the scope and structure of the \"smart\" market, application stages, and scenarios The international experience in this direction was widely analyzed and examples were shown. The article talks about smart cities, the construction of which has already begun in Azerbaijan. The application of the smart city concept in Azerbaijan has been studied. It is stressed that the spread of digital technologies for the construction of a smart city in Azerbaijan is a prerequisite. The Network Readiness Index (NRI) identifies the indicators that are holding back Azerbaijan in the ranking for 2021.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124248903","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 : 2023-06-08DOI: 10.5815/ijitcs.2023.03.01
Edith Edimo Joseph, J. Isabona, Sunday Dare, Odaro Osayande, Okiemute Roberts Omasheye
The negative impact of out-of-school students' problems at the basic and high-school levels is always very weighty on the affected individuals, parents, and society at large. Owing to the weighty negative consequences, policymakers, different government agencies, educators and researchers have long been looking for how to effectively study and forecast the trends as a means of offering a concrete solution to the problem. This paper develops a better hybrid machine learning method, which combines the least square and support vector machine (LS-SVM) model for robust prediction improvement of out-of-school children trend patterns. Particularly, while other previous works only engaged some regional and few samples of out-of-school datasets, this paper focused on long-ranged global out-of-school datasets, collated by UNESCO between 1975- 2020. The proposed hybrid method exhibits the optimal precision accuracies with the LS-SVM model in comparison with ones made using the ordinary SVM model. The precision performance of both LS-SVM and SVM was quantified and a lower NRMSE value is preferred. From the results, the LS-SVM attained lower error values of 0.0164, 0.0221, 0.0268, 0.0209, 0.0158, 0.0201, 0.0147 and 0.0095 0.0188, compared to the SVM model that attained higher NRMSE values of 0.041, ,0.0628, 0.0381, 0.0490, 0.0501, 0.0493, 0.0514, 0.0617 and 0.0646, respectively. By engaging the MAPE indicator, which expresses the mean disconnection between the sourced and predicted values of the out-of-school data. By means of the MAPE, LS-SVM attained lower error values of 0.51, 1.88, 0.82, 2.38, 0.62, 2.55, 0.60, 0.60, 1.63 while SVM attained 1.83, 7.39, 1.79 7.01, 2.43, 8.79, 2.58, 4.13, 6.18. This implies that the LS-SVM model has better precision performance than the SVM model. The results attained in this work can serve as an excellent guide on how to explore hybrid machine-learning techniques to effectively study and predict out-of-school students among researchers and educators.
{"title":"Statistical and Machine Learning Approach for Robust Assessment Modelling of Out-of-School Children Rate: Global Perspective","authors":"Edith Edimo Joseph, J. Isabona, Sunday Dare, Odaro Osayande, Okiemute Roberts Omasheye","doi":"10.5815/ijitcs.2023.03.01","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.03.01","url":null,"abstract":"The negative impact of out-of-school students' problems at the basic and high-school levels is always very weighty on the affected individuals, parents, and society at large. Owing to the weighty negative consequences, policymakers, different government agencies, educators and researchers have long been looking for how to effectively study and forecast the trends as a means of offering a concrete solution to the problem. This paper develops a better hybrid machine learning method, which combines the least square and support vector machine (LS-SVM) model for robust prediction improvement of out-of-school children trend patterns. Particularly, while other previous works only engaged some regional and few samples of out-of-school datasets, this paper focused on long-ranged global out-of-school datasets, collated by UNESCO between 1975- 2020. The proposed hybrid method exhibits the optimal precision accuracies with the LS-SVM model in comparison with ones made using the ordinary SVM model. The precision performance of both LS-SVM and SVM was quantified and a lower NRMSE value is preferred. From the results, the LS-SVM attained lower error values of 0.0164, 0.0221, 0.0268, 0.0209, 0.0158, 0.0201, 0.0147 and 0.0095 0.0188, compared to the SVM model that attained higher NRMSE values of 0.041, ,0.0628, 0.0381, 0.0490, 0.0501, 0.0493, 0.0514, 0.0617 and 0.0646, respectively. By engaging the MAPE indicator, which expresses the mean disconnection between the sourced and predicted values of the out-of-school data. By means of the MAPE, LS-SVM attained lower error values of 0.51, 1.88, 0.82, 2.38, 0.62, 2.55, 0.60, 0.60, 1.63 while SVM attained 1.83, 7.39, 1.79 7.01, 2.43, 8.79, 2.58, 4.13, 6.18. This implies that the LS-SVM model has better precision performance than the SVM model. The results attained in this work can serve as an excellent guide on how to explore hybrid machine-learning techniques to effectively study and predict out-of-school students among researchers and educators.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"549 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131435892","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 : 2023-06-08DOI: 10.5815/ijitcs.2023.03.03
Najla Odeh, Sherin Hijazi
Web applications are becoming very important in our lives as many sensitive processes depend on them. Therefore, it is critical for safety and invulnerability against malicious attacks. Most studies focus on ways to detect these attacks individually. In this study, we develop a new vulnerability system to detect and prevent vulnerabilities in web applications. It has multiple functions to deal with some recurring vulnerabilities. The proposed system provided the detection and prevention of four types of vulnerabilities, including SQL injection, cross-site scripting attacks, remote code execution, and fingerprinting of backend technologies. We investigated the way worked for every type of vulnerability; then the process of detecting each type of vulnerability; finally, we provided prevention for each type of vulnerability. Which achieved three goals: reduce testing costs, increase efficiency, and safety. The proposed system has been validated through a practical application on a website, and experimental results demonstrate its effectiveness in detecting and preventing security threats. Our study contributes to the field of security by presenting an innovative approach to addressing security concerns, and our results highlight the importance of implementing advanced detection and prevention methods to protect against potential cyberattacks. The significance and research value of this survey lies in its potential to enhance the security of online systems and reduce the risk of data breaches.
{"title":"Detecting and Preventing Common Web Application Vulnerabilities: A Comprehensive Approach","authors":"Najla Odeh, Sherin Hijazi","doi":"10.5815/ijitcs.2023.03.03","DOIUrl":"https://doi.org/10.5815/ijitcs.2023.03.03","url":null,"abstract":"Web applications are becoming very important in our lives as many sensitive processes depend on them. Therefore, it is critical for safety and invulnerability against malicious attacks. Most studies focus on ways to detect these attacks individually. In this study, we develop a new vulnerability system to detect and prevent vulnerabilities in web applications. It has multiple functions to deal with some recurring vulnerabilities. The proposed system provided the detection and prevention of four types of vulnerabilities, including SQL injection, cross-site scripting attacks, remote code execution, and fingerprinting of backend technologies. We investigated the way worked for every type of vulnerability; then the process of detecting each type of vulnerability; finally, we provided prevention for each type of vulnerability. Which achieved three goals: reduce testing costs, increase efficiency, and safety. The proposed system has been validated through a practical application on a website, and experimental results demonstrate its effectiveness in detecting and preventing security threats. Our study contributes to the field of security by presenting an innovative approach to addressing security concerns, and our results highlight the importance of implementing advanced detection and prevention methods to protect against potential cyberattacks. The significance and research value of this survey lies in its potential to enhance the security of online systems and reduce the risk of data breaches.","PeriodicalId":130361,"journal":{"name":"International Journal of Information Technology and Computer Science","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126736125","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：