Sentiment Analysis Technique for Textual Reviews Using Neutrosophic Set Theory in the Multi-Criteria Decision- Making System

Hilal Anwer Mustafa,Alzahrani Jaber S.,Alsolai Hadeel,Negm Noha,Nafie Faisal Mohammed,Motwakel Abdelwahed,Yaseen Ishfaq,Hamza Manar Ahmed 한국컴퓨터산업협회 2023 Human-centric Computing and Information Sciences Vol.13 No.-

In recent times, numerous decision-making procedures are not only based on the decision-making of choices, but also public perceptions of possible solutions. In a multi-criteria-based decision-making system, user preferences have been deeply considered. Sentiment analysis, on either side, is similar to natural language processing dedicated to the creation of methods capable of assessing evaluations and determining their intensity. The main aim of this research is to make efficient decisions using social media tweets. The proposed method uses the SentiRank method and neutrosophic set theory to make decisions and rank the reviews. Novel multi-criteria-based neutrosophic theory is used in this research for decision-making. An assembled neutral vocabulary, and the adapted VADER, are used to create Neutro-VADER, a novel version. Every evaluation of a product feature is given a positive, neutral, or negative scores of sentiment by the Neutro-VADER. A unique idea at this level is to use the positive, neutral, and negative scores on emotion to represent reality, uncertainty, and falsehood participation levels of a neutrosophic number. The testing findings support the value of sentiment data through reviews in the ranking procedure. The performance metrics used in the systems are precision, recall, and F1 measures and accuracy for evaluating the aspect detection module. The system performs better in food, service, and pricing categories, whereas the anecdotes group gives bad results. F1 and accuracy level shows better results in the proposed system by using SentiRank and the neutrosophic set theory method.

Presentation Attack Detection (PAD) for Iris Recognition System on Mobile Devices-A Survey

Motwakel, Abdelwahed,Hilal, Anwer Mustafa,Hamza, Manar Ahmed,Ghoneim, Hesham E. International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.spc12

The implementation of iris biometrics on smartphone devices has recently become an emerging research topic. As the use of iris biometrics on smartphone devices becomes more widely adopted, it is to be expected that there will be similar efforts in the research community to beat the biometric by exploring new spoofing methods and this will drive a corresponding requirement for new liveness detection methods. In this paper we addresses the problem of presentation attacks (Spoofing) against the Iris Recognition System on mobile devices and propose novel Presentation Attack Detection (PAD) method which suitable for mobile environment.

Presentation Attack Detection (PAD) for Iris Recognition System on Mobile Devices-A Survey

Motwakel, Abdelwahed,Hilal, Anwer Mustafa,Hamza, Manar Ahmed,Ghoneim, Hesham E. International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.12

The implementation of iris biometrics on smartphone devices has recently become an emerging research topic. As the use of iris biometrics on smartphone devices becomes more widely adopted, it is to be expected that there will be similar efforts in the research community to beat the biometric by exploring new spoofing methods and this will drive a corresponding requirement for new liveness detection methods. In this paper we addresses the problem of presentation attacks (Spoofing) against the Iris Recognition System on mobile devices and propose novel Presentation Attack Detection (PAD) method which suitable for mobile environment.

Image Analysis Fuzzy System

Abdelwahed Motwakel,Adnan Shaout,Anwer Mustafa Hilal,Manar Ahmed Hamza International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.1

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

Integrating ICT in the Sudanese Kindergartens by Means of Developing a Computerized Application for The Pre-School Education, In Order to Improve Cognitive Development:

MOHAMMED, AMGAD ATTA ABDELMAGEED,DRAR, SUHANDA SAFALDEEN MOHAMMED,HILAL, ANWER MUSTAFA,CHRISTENSEN, LARS RUNE International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.12

The current Sudanese preschool system depends on limited methods of education, children's education needs to be equipped to keep pace with technological development, also, the large gap that exists between the families and the Kindergartens, where many parents have no idea on how their child progresses in the KG context. The aim of this research is to integrate ICT in the preschool education to enhance and improve the preschool education, by building an Integrated Educational Application (Computerized Application for Preschool Education CAPE) which will help to improve the learning outcomes. The researchers used the Experimental Research Methodology, the characteristic of CAPE application is; suitable for children's age, the application style is more attractive to the children and contains a different way to help children get learning. Alawaeel and the Smart Child Kindergartens in Republic of Sudan were selected as a sample of the study, with sample size specifically, 50 children's. Also, the Central Bank of Sudan Kindergarten was selected as one of the institutional Kindergartens for easy communication with parents of children with a sample size 21 children. The study found that; using CAPE application in KG enables children to increase general learning effects and developing child's cognitive skills. Also, the children who were allowed to use CAPE by their parents are performed better in the overall evaluation of KG lessons. Also, using the CAPE in the Pre-School education helps the parents following their children's progress better and more reliable. The researcher recommends that to apply the computerized application and includes the second level. Also, converting the computerized program into an application to be used by children by their self, without the intervention of parents.

Integrating ICT in the Sudanese Kindergartens by Means of Developing a Computerized Application for The Pre-School Education, In Order to Improve Cognitive Development:

MOHAMMED, AMGAD ATTA ABDELMAGEED,DRAR, SUHANDA SAFALDEEN MOHAMMED,HILAL, ANWER MUSTAFA,CHRISTENSEN, LARS RUNE International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.spc12

The current Sudanese preschool system depends on limited methods of education, children's education needs to be equipped to keep pace with technological development, also, the large gap that exists between the families and the Kindergartens, where many parents have no idea on how their child progresses in the KG context. The aim of this research is to integrate ICT in the preschool education to enhance and improve the preschool education, by building an Integrated Educational Application (Computerized Application for Preschool Education CAPE) which will help to improve the learning outcomes. The researchers used the Experimental Research Methodology, the characteristic of CAPE application is; suitable for children's age, the application style is more attractive to the children and contains a different way to help children get learning. Alawaeel and the Smart Child Kindergartens in Republic of Sudan were selected as a sample of the study, with sample size specifically, 50 children's. Also, the Central Bank of Sudan Kindergarten was selected as one of the institutional Kindergartens for easy communication with parents of children with a sample size 21 children. The study found that; using CAPE application in KG enables children to increase general learning effects and developing child's cognitive skills. Also, the children who were allowed to use CAPE by their parents are performed better in the overall evaluation of KG lessons. Also, using the CAPE in the Pre-School education helps the parents following their children's progress better and more reliable. The researcher recommends that to apply the computerized application and includes the second level. Also, converting the computerized program into an application to be used by children by their self, without the intervention of parents.

Quantum-Enhanced Machine Learning Algorithms for Heart Disease Prediction

Alotaibi Saud S.,Mengash Hanan Abdullah,Dhahbi Sami,Alazwari Sana,Marzouk Radwa,Alkhonaini Mimouna Abdullah,Mohamed Abdullah,Hilal Anwer Mustafa 한국컴퓨터산업협회 2023 Human-centric Computing and Information Sciences Vol.13 No.-

Heart disease has grown more prominent among various age groups. Early prediction of heart failure and treating them with the most care can the human life. Today healthcare system depends on a computer-aided diagnosis system. Quantum improved machine learning approaches are a critical factor, play a significant role in healthcare systems due to their robust nature, and build novel medical traits, patient data, and management of patients’ record and chronic disease detection, etc. Traditional machine learning approaches effectively predict heart disease but still lack efficiency due to noise and appropriate feature size. This informs the researchers to use quantum improved ML that will provide the accurate prediction of chronic diseases in a granular way. Applying these merits of quantum computing, healthcare systems are implementing quantum-based machine learning (QML) approaches for predicting heart disease. This paper proposes a quantum ML with quantum particle swarm optimization (QPSO) to predict heart disease and compare it with the traditional ML approach called multilayer perceptron (MLP) using the evaluation metrics. It uses exploratory preprocessing to normalize the input heart disease data. The number of qubits is the number of features in the dataset. The efficiency of the quantum-ML approaches is evaluated using publicly available heart disease dataset. The proposed QML with QPSO secured an improved accuracy of 96.7%, a false detection rate of 0.09, and a computation time is 135ms. However, the comparison results prove that QML with QPSO confirmed satisfactory results in predicting heart disease with improved accuracy.