Pub Date : 2019-12-01DOI: 10.1109/ACIT47987.2019.8990995
A. Abdelnabi
This study proposes an analytical hierarchy process (AHP) model to select the best programming language to be Learned by novice programmers for Data Analytics Applications. as this will positively reduce the time and efforts of novice programmers. Furthermore, this will give him good and robust choice. The proposed model uses eight criteria, including: Popularity, data analytics support, volume of data can handle, speed of compiling, expressiveness, dreadfulness, programmers’ recommendations and average reasonable financial cost. Python, R, Java, SQL, Scala and C programming languages are used as alternatives. The results of this model show that python language is the best programming language for data analytics applications among the tested alternatives. Both inconsistency and sensitivity analysis are done and show that the model is robust.
{"title":"An Analytical Hierarchical Process Model to Select Programming Language for Novice Programmers for Data Analytics Applications","authors":"A. Abdelnabi","doi":"10.1109/ACIT47987.2019.8990995","DOIUrl":"https://doi.org/10.1109/ACIT47987.2019.8990995","url":null,"abstract":"This study proposes an analytical hierarchy process (AHP) model to select the best programming language to be Learned by novice programmers for Data Analytics Applications. as this will positively reduce the time and efforts of novice programmers. Furthermore, this will give him good and robust choice. The proposed model uses eight criteria, including: Popularity, data analytics support, volume of data can handle, speed of compiling, expressiveness, dreadfulness, programmers’ recommendations and average reasonable financial cost. Python, R, Java, SQL, Scala and C programming languages are used as alternatives. The results of this model show that python language is the best programming language for data analytics applications among the tested alternatives. Both inconsistency and sensitivity analysis are done and show that the model is robust.","PeriodicalId":138075,"journal":{"name":"Automation, Control, and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122666744","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 : 2018-11-01DOI: 10.1109/ACIT.2018.8672584
K. Maabreh
Database performance is a primary branch of information technology which deals with the proper management of the database. The primary goal of the data management is to provide the organizations daily routines with powerful applications that have to be run efficiently. Performance optimization has a critical role in improving the database usage. In particular, managing the massive amount of data generated daily by various users. The main target of this research is to evaluate the data partitioning technique in enhancing the performance of quires submitted to large databases. The encouraging results show that data partitioning could improve the performance of DBMS which manages massive databases. The experiments reveal that data partitioning has a remarkable impact on the query execution time in big databases, which exceeds 35% compared to small database size or not partitioned database.
{"title":"Optimizing Database Query Performance Using Table Partitioning Techniques","authors":"K. Maabreh","doi":"10.1109/ACIT.2018.8672584","DOIUrl":"https://doi.org/10.1109/ACIT.2018.8672584","url":null,"abstract":"Database performance is a primary branch of information technology which deals with the proper management of the database. The primary goal of the data management is to provide the organizations daily routines with powerful applications that have to be run efficiently. Performance optimization has a critical role in improving the database usage. In particular, managing the massive amount of data generated daily by various users. The main target of this research is to evaluate the data partitioning technique in enhancing the performance of quires submitted to large databases. The encouraging results show that data partitioning could improve the performance of DBMS which manages massive databases. The experiments reveal that data partitioning has a remarkable impact on the query execution time in big databases, which exceeds 35% compared to small database size or not partitioned database.","PeriodicalId":138075,"journal":{"name":"Automation, Control, and Information Technology","volume":"9 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120998398","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 : 2018-11-01DOI: 10.1109/ACIT.2018.8672722
Jafar Abo Nada, Mohammad Rasmi Al-Mosa
{"title":"A Proposed Wireless Intrusion Detection Prevention and Attack System","authors":"Jafar Abo Nada, Mohammad Rasmi Al-Mosa","doi":"10.1109/ACIT.2018.8672722","DOIUrl":"https://doi.org/10.1109/ACIT.2018.8672722","url":null,"abstract":"","PeriodicalId":138075,"journal":{"name":"Automation, Control, and Information Technology","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122037860","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 : 1900-01-01DOI: 10.1109/ACIT53391.2021.9677227
A. A. Shabibi, Tharaya Al Shabibi
{"title":"Teachers' Training Needs for Digital Competences","authors":"A. A. Shabibi, Tharaya Al Shabibi","doi":"10.1109/ACIT53391.2021.9677227","DOIUrl":"https://doi.org/10.1109/ACIT53391.2021.9677227","url":null,"abstract":"","PeriodicalId":138075,"journal":{"name":"Automation, Control, and Information Technology","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125389986","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 : 1900-01-01DOI: 10.1109/ACIT57182.2022.9994217
Maarouf Korichi, Aicha Korichi, M. Kherallah
Hand Dorsal identification is a type of biometric technology that has emerged in the past two decades. Because of its safety, accuracy, and efficacy, more and more researchers are participating in the study. In this short paper, A biometric based Hand dorsal identification system is proposed. However, due its potential capability to extract and differentiate between the system user, a CNN based deep learning approach named ALEXNET along with the tied rank normalization is used to extract the discriminant hand dorsal features. In order to perform the classification task, the Support Vector Machine is implemented. Our work is applied to a database known in this field and has produced a very promising result when using the Hong Kong Polytechnique hand dorsal database.
{"title":"An Effective Personal Identification System Using Hand Dorsal Modality and Deep Learning Approach","authors":"Maarouf Korichi, Aicha Korichi, M. Kherallah","doi":"10.1109/ACIT57182.2022.9994217","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994217","url":null,"abstract":"Hand Dorsal identification is a type of biometric technology that has emerged in the past two decades. Because of its safety, accuracy, and efficacy, more and more researchers are participating in the study. In this short paper, A biometric based Hand dorsal identification system is proposed. However, due its potential capability to extract and differentiate between the system user, a CNN based deep learning approach named ALEXNET along with the tied rank normalization is used to extract the discriminant hand dorsal features. In order to perform the classification task, the Support Vector Machine is implemented. Our work is applied to a database known in this field and has produced a very promising result when using the Hong Kong Polytechnique hand dorsal database.","PeriodicalId":138075,"journal":{"name":"Automation, Control, and Information Technology","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121998724","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 : 1900-01-01DOI: 10.1109/ACIT50332.2020.9300088
N. E. Elshaiekh, Khalfan Zahran Al Hiji
Due to the lack of knowledge, some people in the rural area in Oman often overlooking some diseases because of the long distance they need to go for seeing a Specialist or physician. Therefore, the proposed mobile knowledge based system will be designed based on data has been collected from related peoples to design a e-diagnosis system that could help in identifying some diseases such as dermatology disease with little effort for the people in the rural area of Oman. and thus, constructing a website e-diagnoses knowledge based to be used in evaluation of the disease's and taking different kind of decisions regarding to the diseases expect to provide required very accurate statistics figures regarding to these diseases. The research will use qualitative data collection method by collecting data from specialist's interviews, and thematic data analysis will be used. The expected system will allow the specialists to keep seeing their patients without leaving their clinics and will helps the rural peoples in Oman to see their specialist without leaving their village's. Therefore, the e-diagnosis knowledge based will be created to help the decision makers with deferent kind of statistical reports.
{"title":"The Role of E-diagnosis Knowledge Based System on Omani Society: Skin Disease as Case","authors":"N. E. Elshaiekh, Khalfan Zahran Al Hiji","doi":"10.1109/ACIT50332.2020.9300088","DOIUrl":"https://doi.org/10.1109/ACIT50332.2020.9300088","url":null,"abstract":"Due to the lack of knowledge, some people in the rural area in Oman often overlooking some diseases because of the long distance they need to go for seeing a Specialist or physician. Therefore, the proposed mobile knowledge based system will be designed based on data has been collected from related peoples to design a e-diagnosis system that could help in identifying some diseases such as dermatology disease with little effort for the people in the rural area of Oman. and thus, constructing a website e-diagnoses knowledge based to be used in evaluation of the disease's and taking different kind of decisions regarding to the diseases expect to provide required very accurate statistics figures regarding to these diseases. The research will use qualitative data collection method by collecting data from specialist's interviews, and thematic data analysis will be used. The expected system will allow the specialists to keep seeing their patients without leaving their clinics and will helps the rural peoples in Oman to see their specialist without leaving their village's. Therefore, the e-diagnosis knowledge based will be created to help the decision makers with deferent kind of statistical reports.","PeriodicalId":138075,"journal":{"name":"Automation, Control, and Information Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115409304","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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