• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.266-272
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• 2022

Private specialized institutions differ from public ones in that they mostly act independently. This paper reports a study designed to assess the provision of specialized institutions for children with intellectual disabilities in Saudi Arabia. The approach taken in this study was qualitative, involving a case study strategy that enabled the researcher to gain rich and in-depth information based on the shared experiences of participants comprising institution leaders, educators and families from two specific specialized settings, one public and one private. The study aimed to examine the existing disparities in service delivery so as to develop a clear picture of the service quality provided by public specialized institutions for children with intellectual disabilities in Saudi Arabia. The results suggest that the weak relationship with inpatient and specialized institutions is a consequence of the parents' poor responsiveness, which may result in these institutes developing a negative impression of the parents. Conversely, the lack of active initiative on the part of the public specialized institutions led to a negative parental attitude towards these institutions. A sensible approach to resolving this problem might be to recognize that these institutions have a significant responsibility to encourage parents of children with intellectual disabilities to become involved in their children's learning, to promote positive attitudes.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.254-260
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• 2022

The purpose of this study was to identify the obstacles facing gifted students with learning disabilities (GSLDs) from the point of view of their teachers in the Makkah region and to find suggested solutions to overcome these obstacles. The study covered Makkah, Jeddah and Taif and used semi-structured interviews which included open-ended questions. The study findings indicated that there were several educational obstacles including the absence of adapted courses or specialized teachers for GSLDs category and the insufficient time for the students to express their talents. According to the findings, there were also societal obstacles including the society's failure to expect the presence of talents along with disabilities, or its denial or rejection of their talents in addition to ridiculing them. The findings also confirmed the existence of administrative obstacles including the lack of community partnership. There were also family obstacles such as the family's lack of encouragement for the students, and ignorance of the nature of GSLDs. The study came up with a number of solutions and proposals related to awareness, educational institutions, education and competitions for talented people with learning disabilities.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.288-294
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• 2022

This study aims to assess the knowledge of teachers working with students with autism spectrum disorder (ASD) regarding applied behaviour analysis (ABA). The study was concerned with teachers' knowledge of ABA, its application in the classroom, barriers to its use and desired training opportunities and/or resources to enhance teacher application of ABA strategies in the classroom. Data were collected via an online survey completed by 190 teachers with students diagnosed with ASD in British schools. The results revealed overall knowledge of ABA strategies for classrooms, with only some teachers uninformed about the broad use and some key elements, and general familiarity with skills crucial for applying ABA. Actual knowledge of ABA was found to be high. In terms of application of ABA, the majority of the teachers employed a wide range of known strategies. A number of barrier to the application of ABA were noted including a lack of knowledge and training, a lack of administrative support and a lack of time and physical resources. Theoretical knowledge is crucial for practical applications; however, practical training was found to be important to ensure intervention efficacy.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.212-222
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• 2022

There has been a rapid increase in the use of cloud email services. As a result, email encryption has become more commonplace as concerns about cloud privacy and security grow. Nevertheless, this increase in usage is creating the challenge of how to effectively be searching and filtering the encrypted emails. They are popular technologies of solving the issue of the encrypted emails searching through searchable public key encryption. However, the problem of encrypted email filtering remains to be solved. As a new approach to finding and filtering encrypted emails in the cloud, we propose a ciphertext-based encrypted policy attribute-based encryption scheme and keyword search procedure based on hidden policy ciphertext. This feature allows the user of searching using some encrypted emails keywords in the cloud as well as allowing the emails filter-based server toward filter the content of the encrypted emails, similar to the traditional email keyword filtering service. By utilizing composite order bilinear groups, a hidden policy system has been successfully demonstrated to be secure by our dual system encryption process. Proposed system can be used with other scenarios such as searching and filtering files as an applicable method.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.194-202
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• 2022

The use of public Wi-Fi has increased in recent years with many people like to spend their time outside in malls or café shops which provide public Wi-Fi for their customers. However, since the public Wi-Fi can be accessed from any device the security of public Wi-Fi plays a big role to prevent the stealing of information by an attacker with methods and techniques such as WPA, WPA2 and WPA3. However, it is well known to the attackers that these methods are not difficult to get hacked by the attacker device to take the client precious information. Some researches were done in increasing the security of public Wi-Fi each with their own different technique or algorithm to provide more secure connection to the public Wi-Fi and prevent any unauthorized user to connect to avoid stealing the data of another legal user. Theses research paper are evaluated to learn which method excel in protecting the public Wi-Fi security by giving an analysis to the methods provided by the research paper with comparing the pros and cons of each algorithm. Moreover, the research displays that there are methods to actually provide security to the public Wi-Fi with each being very different in implementation.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.201-212
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• 2022

Prior to the emergence of Covid-19, Saudi Arabia (SA) had never faced the challenge of dealing with a global pandemic. Significantly, the current crisis has impacted all industries and sectors in the country, including the healthcare system, and has led to an emphasis on human life being more precious and valuable than economic profit. This study focuses on the impact of Covid-19 on the health of nurses, including their quality of life, during 2020. Understanding the position of the nursing profession during the pandemic, including the most effective methods of preventing work-related stress is important. Information was acquired through an online survey method (i.e. self-completion), known as the Expanded Nursing Stress Scale (ENSS), which was distributed to nurses in all regions of SA. It was found that the main aspects impacting nurses' work-related stress include gender, employment type, training, and dealing with infected patients. In addition, they highlight that such stress plays a substantial role in patient safety and nurses' satisfaction at work, as well as the future survival of organizations. The emergence of Covid-19 as a novel infectious disease has increased nurses' uncertainty and work-related stress. The results of this research will provide insights into the views of both nurses and their managers, in order to identify the main indicators of stress.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.352-358
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• 2022

In this paper, we study the relationship between infection rates of covid 19 and the precautionary measures and strict protocols taken by Saudi Arabia to combat the spread of the coronavirus disease and minimize the number of infected people. Based on the infection rates and the timetable of precautionary measures, the best framework of precautionary measures was identified by applying the traveling salesman problem (TSP) that relies on ant colony optimization (ACO) algorithms. The proposed algorithm was applied to daily infected cases data in Saudi Arabia during three periods of precautionary measures: partial curfew, whole curfew, and gatherings penalties. The results showed the partial curfew and the whole curfew for some cities have the minimum total cases over other precautionary measures. The gatherings penalties had no real effect in reducing infected cases as the other two precautionary measures. Therefore, in future similar circumstances, we recommend first applying the partial curfew and the whole curfew for some cities, and not considering the gatherings penalties as an effective precautionary measure. We also recommend re-study the application of the grouping penalty, to identify the reasons behind the lack of its effectiveness in reducing the number of infected cases.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.149-156
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• 2022

The study aimed to identify the effectiveness of the training program based on the social story strategy for developing self-determination skills among students with autism spectrum disorder. The population of the study consisted of all students with autism spectrum disorder in the Desired Hope Association for People with Disabilities in Makkah Al-Mukarramah and the sample of the study consisted of (6) students. The study used the quasi-experimental approach with one group. To achieve the objectives of the study, the ARCS scale for self-determination skills was used, Hassan Al-Masry (2018). The results of the study revealed, through comparing the students' performances in their pre and post-tests regarding to the ARKS scale and through their answers on the scale, the effectiveness of the training program based on the social story for developing the skills of self-determination among students with autism spectrum disorder. The results also showed that there were statistically significant differences after applying the program when significance level was (0.001). The result came in favor of the post-test.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.182-192
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• 2022

All the aspects of human life have been affected by the novel coronavirus (Covid-19). It has rapidly spread in most countries including the Kingdom of Saudi Arabia. As a result, early precautionary actions aiming to minimise the virus effect are taken by the Saudi government. One of these actions is the sudden shift to online classes and suspending the attendees to all educational institutes. Such immediate change can have a significant effect on the educational process, especially for students. One can argue that students' information-seeking behaviour within the current situation can affect their learning quality and outcomes. Therefore, this paper examines the Saudi students' information-seeking behaviour by taking a sample of students from Umm Al-Qura University. A descriptive analysis is conducted with 193 students and two approaches are used to collect data, questionnaire and semi-structured interview. The results showed that the majority of students face difficulties when searching and retrieving e-resources from the university library website. The problems range from mainly poor User Experience (UX), network connection, multiple errors and lack of subscription with academic publishers.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.9-16
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• 2023

Speech can actively elicit feelings and attitudes by using words. It is important for researchers to identify the emotional content contained in speech signals as well as the sort of emotion that resulted from the speech that was made. In this study, we studied the emotion recognition system using a database in Arabic, especially in the Saudi dialect, the database is from a YouTube channel called Telfaz11, The four emotions that were examined were anger, happiness, sadness, and neutral. In our experiments, we extracted features from audio signals, such as Mel Frequency Cepstral Coefficient (MFCC) and Zero-Crossing Rate (ZCR), then we classified emotions using many classification algorithms such as machine learning algorithms (Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)) and deep learning algorithms such as (Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM)). Our Experiments showed that the MFCC feature extraction method and CNN model obtained the best accuracy result with 95%, proving the effectiveness of this classification system in recognizing Arabic spoken emotions.