Israa Kamal - Academia.edu (original) (raw)
Papers by Israa Kamal
International Journal of Advanced Computer Science and Applications, 2016
University web portals are considered one of the main access gateways for universities. Typically... more University web portals are considered one of the main access gateways for universities. Typically, they have a large candidate audience among the current students, employees, and faculty members aside from previous and future students, employees, and faculty members. Web accessibility is the concept of providing web content universal access to different machines and people with different ages, skills, education levels, and abilities. Several web accessibility metrics have been proposed in previous years to measure web accessibility. We integrated and extracted common web accessibility metrics from the different accessibility tools used in this study. This study evaluates web accessibility metrics for 36 Jordanian universities and educational institute websites. We analyze the level of web accessibility using a number of available evaluation tools against the standard guidelines for web accessibility. Receiver operating characteristic quality measurements is used to evaluate the effectiveness of the integrated accessibility metrics.
A new binary (bit-level) lossless image compression method based on a well-known error correcting... more A new binary (bit-level) lossless image compression method based on a well-known error correcting BCH codes has been introduced in this paper. The BCH encoder converts the message of k bits to a codeword of length n by adding 3 parity bits. In contrast the decoder eliminates these parity bits after verifying the received message; therefore, the proposed method utilizes this idea by dividing the image into blocks of size 7 bits. These blocks entered to the BCH decoder who eliminates the parity bits. This reduces the block size to 4 bits. The output will be in two folds first the compressed image file and the second a file contains the keys. Each block is tested to find if it is a valid block or not (valid / non-valid codeword). In order to distinguish between them during the decompression process, the proposed method adds 1 for the valid codeword and 0 for the invalid codeword and saved in another file to be the key that used in the decoding stage. We then implement the Huffman codes...
IJCSNS, 2011
Moodle is introduced as an e-learn system in many courses at the Information Technology faculty i... more Moodle is introduced as an e-learn system in many courses at the Information Technology faculty in Isra University. Prior to using Moodle at the university, there had been many obstacles relating to course management such as the finding an appropriate time that suits all students to carry out tests and quizzes; marking and providing feedback to the students within a short period of time; registration for tutorial sessions; and providing lecture materials and general faculty announcements. In this research, 20% of computer skills students were surveyed to shed some light on their perceptions of using Moodle as an e-learning system in Isra University. The evaluation results of using Moodle platform shows promising opportunities to support and improve upon this platform in Isra University classes. This study helps to introduce the e-learning system to all Isra University students and to support the understanding of the overall learning process, learning motivation, legitimatize application of knowledge, and a challenge for improving the teaching behaviors.
sersc.org
... 5 No. 3, July, 2011 15 A New Lossless Image Compression Technique Based on Bose, Chandhuri an... more ... 5 No. 3, July, 2011 15 A New Lossless Image Compression Technique Based on Bose, Chandhuri and Hocquengham (BCH) Codes Rafeeq Al-Hashemi, Israa Wahbi Kamal ... The technique is applicable in this medical application domain [12]. Muthaiah et al. ...
The aim of this paper is to develop effective machine learning and deep learning models using gen... more The aim of this paper is to develop effective machine learning and deep learning models using genetic algorithms that can accurately classify hate speech sentiments and contribute to mitigating the negative impact of hate speech online. The research explores different techniques for data preprocessing, feature selection, and model training, including genetic support vector machines (SVM), genetic naive Bayes algorithm, and genetic convolutional neural networks (CNN). Performance evaluation is performed using metrics such as precision, recall, F1 score, and accuracy. When comparing the previous classifiers, it was observed that the SVM algorithm was superior with an accuracy of 0.93 and an F1 score of 0.96, followed by the deep learning genetic networks with an accuracy of 0.91 and an F1 score of 0.92, and finally the naive genetic Bayes algorithm with an accuracy of 0.87 and an F1 score of 0.92. The paper presented a comparison between its results and the results of previous studies conducted on the same dataset, and it was observed that the SVM algorithm was superior with an accuracy of 0.93 over the study that used AraBERT, which gave an accuracy of 0.80, and over the study that used SVM, which gave an accuracy of 0.87.
The detection of exoplanets is essential for advancing our knowledge of planetary systems beyond ... more The detection of exoplanets is essential for advancing our knowledge of planetary systems beyond our solar system. The performance of several machine learning models to detect exoplanet candidates in the Cumulative Kepler Objects of Interest (KOI) is evaluated in this study. We applied ensemble learning techniques, including Random Forest, Gradient Boosting, Voting Classifier, Stacking Classifier and feature selection approaches, ANOVA F test, Mutual Information Gain, Recursive Feature Elimination (RFE). The best performance among the models was obtained by Gradient Boosting with a mean accuracy of 99.80%, and a mean F1 score of 99.81%, which surpassed the other classifiers. Gradient Boosting was not only the most accurate classifier, but it also achieved the highest F1 score, just a little low behind the Stacking and Voting Classifiers. This result shows the effectiveness of Gradient Boosting for exoplanet detection and demonstrates the merit of combining ensemble learning with high dimensional feature selection techniques to improve classification accuracy.
International Journal of Advanced Computer Science and Applications, 2016
University web portals are considered one of the main access gateways for universities. Typically... more University web portals are considered one of the main access gateways for universities. Typically, they have a large candidate audience among the current students, employees, and faculty members aside from previous and future students, employees, and faculty members. Web accessibility is the concept of providing web content universal access to different machines and people with different ages, skills, education levels, and abilities. Several web accessibility metrics have been proposed in previous years to measure web accessibility. We integrated and extracted common web accessibility metrics from the different accessibility tools used in this study. This study evaluates web accessibility metrics for 36 Jordanian universities and educational institute websites. We analyze the level of web accessibility using a number of available evaluation tools against the standard guidelines for web accessibility. Receiver operating characteristic quality measurements is used to evaluate the effectiveness of the integrated accessibility metrics.
A new binary (bit-level) lossless image compression method based on a well-known error correcting... more A new binary (bit-level) lossless image compression method based on a well-known error correcting BCH codes has been introduced in this paper. The BCH encoder converts the message of k bits to a codeword of length n by adding 3 parity bits. In contrast the decoder eliminates these parity bits after verifying the received message; therefore, the proposed method utilizes this idea by dividing the image into blocks of size 7 bits. These blocks entered to the BCH decoder who eliminates the parity bits. This reduces the block size to 4 bits. The output will be in two folds first the compressed image file and the second a file contains the keys. Each block is tested to find if it is a valid block or not (valid / non-valid codeword). In order to distinguish between them during the decompression process, the proposed method adds 1 for the valid codeword and 0 for the invalid codeword and saved in another file to be the key that used in the decoding stage. We then implement the Huffman codes...
IJCSNS, 2011
Moodle is introduced as an e-learn system in many courses at the Information Technology faculty i... more Moodle is introduced as an e-learn system in many courses at the Information Technology faculty in Isra University. Prior to using Moodle at the university, there had been many obstacles relating to course management such as the finding an appropriate time that suits all students to carry out tests and quizzes; marking and providing feedback to the students within a short period of time; registration for tutorial sessions; and providing lecture materials and general faculty announcements. In this research, 20% of computer skills students were surveyed to shed some light on their perceptions of using Moodle as an e-learning system in Isra University. The evaluation results of using Moodle platform shows promising opportunities to support and improve upon this platform in Isra University classes. This study helps to introduce the e-learning system to all Isra University students and to support the understanding of the overall learning process, learning motivation, legitimatize application of knowledge, and a challenge for improving the teaching behaviors.
sersc.org
... 5 No. 3, July, 2011 15 A New Lossless Image Compression Technique Based on Bose, Chandhuri an... more ... 5 No. 3, July, 2011 15 A New Lossless Image Compression Technique Based on Bose, Chandhuri and Hocquengham (BCH) Codes Rafeeq Al-Hashemi, Israa Wahbi Kamal ... The technique is applicable in this medical application domain [12]. Muthaiah et al. ...
The aim of this paper is to develop effective machine learning and deep learning models using gen... more The aim of this paper is to develop effective machine learning and deep learning models using genetic algorithms that can accurately classify hate speech sentiments and contribute to mitigating the negative impact of hate speech online. The research explores different techniques for data preprocessing, feature selection, and model training, including genetic support vector machines (SVM), genetic naive Bayes algorithm, and genetic convolutional neural networks (CNN). Performance evaluation is performed using metrics such as precision, recall, F1 score, and accuracy. When comparing the previous classifiers, it was observed that the SVM algorithm was superior with an accuracy of 0.93 and an F1 score of 0.96, followed by the deep learning genetic networks with an accuracy of 0.91 and an F1 score of 0.92, and finally the naive genetic Bayes algorithm with an accuracy of 0.87 and an F1 score of 0.92. The paper presented a comparison between its results and the results of previous studies conducted on the same dataset, and it was observed that the SVM algorithm was superior with an accuracy of 0.93 over the study that used AraBERT, which gave an accuracy of 0.80, and over the study that used SVM, which gave an accuracy of 0.87.
The detection of exoplanets is essential for advancing our knowledge of planetary systems beyond ... more The detection of exoplanets is essential for advancing our knowledge of planetary systems beyond our solar system. The performance of several machine learning models to detect exoplanet candidates in the Cumulative Kepler Objects of Interest (KOI) is evaluated in this study. We applied ensemble learning techniques, including Random Forest, Gradient Boosting, Voting Classifier, Stacking Classifier and feature selection approaches, ANOVA F test, Mutual Information Gain, Recursive Feature Elimination (RFE). The best performance among the models was obtained by Gradient Boosting with a mean accuracy of 99.80%, and a mean F1 score of 99.81%, which surpassed the other classifiers. Gradient Boosting was not only the most accurate classifier, but it also achieved the highest F1 score, just a little low behind the Stacking and Voting Classifiers. This result shows the effectiveness of Gradient Boosting for exoplanet detection and demonstrates the merit of combining ensemble learning with high dimensional feature selection techniques to improve classification accuracy.