Pub Date : 2019-01-01DOI: 10.5455/JJCIT.71-1541688581
Yousef E. M. Hamouda
{"title":"MODIFIED RANDOM BIT CLIMBING ( and #955; -MRBC) FOR TASK MAPPING AND SCHEDULING IN WIRELESS SENSOR NETWORKS","authors":"Yousef E. M. Hamouda","doi":"10.5455/JJCIT.71-1541688581","DOIUrl":"https://doi.org/10.5455/JJCIT.71-1541688581","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819430","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 : 2019-01-01DOI: 10.5455/jjcit.71-1557923217
Yanal S. Faouri, Hanin Sharif, L. Smadi, Hani Jamleh
{"title":"LOW PASS AND QUAD BAND PASS TUNABLE FILTER BASED ON STUB RESONATORS TECHNIQUE","authors":"Yanal S. Faouri, Hanin Sharif, L. Smadi, Hani Jamleh","doi":"10.5455/jjcit.71-1557923217","DOIUrl":"https://doi.org/10.5455/jjcit.71-1557923217","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819642","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 : 2019-01-01DOI: 10.5455/jjcit.71-1562700251
I. Alagha, Osama Dahrooj
{"title":"MULTI-LEVEL ANALYSIS OF POLITICAL SENTIMENTS USING TWITTER DATA: A CASE STUDY OF THE PALESTINIAN-ISRAELI CONFLICT","authors":"I. Alagha, Osama Dahrooj","doi":"10.5455/jjcit.71-1562700251","DOIUrl":"https://doi.org/10.5455/jjcit.71-1562700251","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819770","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 : 2019-01-01DOI: 10.5455/jjcit.71-1564729835
V. Kolisetty, D. Rajput
{"title":"A Review on the Significance of Machine Learning for Data Analysis in Big Data","authors":"V. Kolisetty, D. Rajput","doi":"10.5455/jjcit.71-1564729835","DOIUrl":"https://doi.org/10.5455/jjcit.71-1564729835","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"14 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820119","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 : 2019-01-01DOI: 10.5455/jjcit.71-1546551963
Sinam I. Idriss, A. Lawan
C4.5 is one of the most popular algorithms for rule base classification. Many empirical features in the algorithm exist, such as continuous number categorization, missing value handling and over-fitting. However, despite its promising advantage over the Iterative Dichotomiser 3 (ID3), C4.5 has the major setback of presenting the equivalent result as the ID3, especially when the same number of attributes is used. This paper proposes a technique that will handle the setback reported in C4.5. The performance of the proposed technique is measured based on better accuracy. The Entropy of Information Theory is measured to identify the central attribute for the dataset. The researchers apply exponential splitting information (EC4.5) in utilizing the central attribute of the same dataset. The result obtained on introducing Taylor series suggested a far better result than when the C4.5 (gain ratio) was introduced.
{"title":"An Improved C4.5 Model Classification Algorithm Based on Taylor's Series","authors":"Sinam I. Idriss, A. Lawan","doi":"10.5455/jjcit.71-1546551963","DOIUrl":"https://doi.org/10.5455/jjcit.71-1546551963","url":null,"abstract":"C4.5 is one of the most popular algorithms for rule base classification. Many empirical features in the algorithm exist, such as continuous number categorization, missing value handling and over-fitting. However, despite its promising advantage over the Iterative Dichotomiser 3 (ID3), C4.5 has the major setback of presenting the equivalent result as the ID3, especially when the same number of attributes is used. This paper proposes a technique that will handle the setback reported in C4.5. The performance of the proposed technique is measured based on better accuracy. The Entropy of Information Theory is measured to identify the central attribute for the dataset. The researchers apply exponential splitting information (EC4.5) in utilizing the central attribute of the same dataset. The result obtained on introducing Taylor series suggested a far better result than when the C4.5 (gain ratio) was introduced.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819467","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 : 2019-01-01DOI: 10.5455/jjcit.71-1556703387
Siaw-Hong Liew, Y. Choo, Y. Low
The electroencephalogram (EEG) signal is used as biometric modality, because it is proven to be unique, universal and collectable. This work aims to assess the performance of fuzzy-based techniques for brainprint authentication modelling. We benchmark the performance of Fuzzy-Rough Nearest Neighbour (FRNN) technique to the Discernibility Nearest Neighbour (D-kNN) and the Fuzzy Lattice Reasoning (FLR) techniques using the selected samples of brainwaves’ data from the original UCI EEG dataset. All the three classifiers are available in the fuzzy-rough version of WEKA implementation tool. Selected 9 EEG channels located at the midline and lateral regions were used in the experimentation. The coherence, mean of amplitudes and cross-correlation feature extraction methods were used to extract the EEG signals. The area under ROC curve (AUC) measurement of FRNN was promising against the D-kNN and FLR techniques. The FRNN model has achieved the best performance of AUC measure at 0.904 in opposition to the D-kNN and FLR models, where both recorded 0.770 and 0.563, respectively. However, the classification accuracy shows significantly no difference among the three classifiers. The results confirmed that the classification accuracy of D-kNN and FLR techniques is not reliable, because they are highly contributed by the true negative cases. Hence, we conclude that the FRNN model is less biased to imbalance data problem as compared to the D-kNN and FLR models. Future work of this research should focus on optimizing the EEG channel and feature selection in order to obtain a better data representation of biometric brainprint for more efficient authentication in imbalance data problem.
{"title":"Fuzzy-Rough Classification for Brainprint Authentication","authors":"Siaw-Hong Liew, Y. Choo, Y. Low","doi":"10.5455/jjcit.71-1556703387","DOIUrl":"https://doi.org/10.5455/jjcit.71-1556703387","url":null,"abstract":"The electroencephalogram (EEG) signal is used as biometric modality, because it is proven to be unique, universal and collectable. This work aims to assess the performance of fuzzy-based techniques for brainprint authentication modelling. We benchmark the performance of Fuzzy-Rough Nearest Neighbour (FRNN) technique to the Discernibility Nearest Neighbour (D-kNN) and the Fuzzy Lattice Reasoning (FLR) techniques using the selected samples of brainwaves’ data from the original UCI EEG dataset. All the three classifiers are available in the fuzzy-rough version of WEKA implementation tool. Selected 9 EEG channels located at the midline and lateral regions were used in the experimentation. The coherence, mean of amplitudes and cross-correlation feature extraction methods were used to extract the EEG signals. The area under ROC curve (AUC) measurement of FRNN was promising against the D-kNN and FLR techniques. The FRNN model has achieved the best performance of AUC measure at 0.904 in opposition to the D-kNN and FLR models, where both recorded 0.770 and 0.563, respectively. However, the classification accuracy shows significantly no difference among the three classifiers. The results confirmed that the classification accuracy of D-kNN and FLR techniques is not reliable, because they are highly contributed by the true negative cases. Hence, we conclude that the FRNN model is less biased to imbalance data problem as compared to the D-kNN and FLR models. Future work of this research should focus on optimizing the EEG channel and feature selection in order to obtain a better data representation of biometric brainprint for more efficient authentication in imbalance data problem.","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819629","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 : 2019-01-01DOI: 10.5455/jjcit.71-1559909066
Saeda awaida, Bassam Shargabi, Thamer Rousan
{"title":"Automated Arabic Essays Grading System based on F-Score and Arabic WordNet","authors":"Saeda awaida, Bassam Shargabi, Thamer Rousan","doi":"10.5455/jjcit.71-1559909066","DOIUrl":"https://doi.org/10.5455/jjcit.71-1559909066","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819702","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 : 2019-01-01DOI: 10.5455/jjcit.71-1562930035
K. K. Gola, Bhumika Gupta
{"title":"AN ENERGY EFFICIENT QUALITY OF SERVICE (QoS) PARAMETERS BASED VOID AVOIDANCE ROUTING TECHNIQUE FOR UNDERWATER SENSOR NETWORKS","authors":"K. K. Gola, Bhumika Gupta","doi":"10.5455/jjcit.71-1562930035","DOIUrl":"https://doi.org/10.5455/jjcit.71-1562930035","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70819980","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 : 2019-01-01DOI: 10.5455/jjcit.71-1564222281
Q. Qananwah, Hussein A. Alzoubi, Ruba Banimfarij, A. Dagamseh, Oliver Hayden
{"title":"The Utilization of EEG Signal in Video Compression","authors":"Q. Qananwah, Hussein A. Alzoubi, Ruba Banimfarij, A. Dagamseh, Oliver Hayden","doi":"10.5455/jjcit.71-1564222281","DOIUrl":"https://doi.org/10.5455/jjcit.71-1564222281","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820112","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: 10.5455/jjcit.71-1564059469
Ahmed Hassanein, M. Nour
{"title":"A PROPOSED MODEL OF SELECTING FEATURES FOR CLASSIFYING ARABIC TEXT","authors":"Ahmed Hassanein, M. Nour","doi":"10.5455/jjcit.71-1564059469","DOIUrl":"https://doi.org/10.5455/jjcit.71-1564059469","url":null,"abstract":"","PeriodicalId":36757,"journal":{"name":"Jordanian Journal of Computers and Information Technology","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70820104","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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