• Title/Summary/Keyword: Saudi Arabia

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Testing Whether New Is Better Than Used of Specified Age Using Moments Inequalities

  • Ahmad, Ibrahim A.;Al-Wasel, Ibrahim A.
    • International Journal of Reliability and Applications
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    • v.3 no.1
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    • pp.17-23
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    • 2002
  • The class of “new better than used of a specified age” is a large and practical class of life distributions. Its properties, applicability, and testing was discussed by Hollander, Park and Proschan (1986). Their test, while remaining the yardstick for this class, suffers from weak efficiency and weak power, especially for specified ages below the average age. Thus, it is beneficial to have an alternative testing procedure that would work better for early ages and still work well for later ages. This is exactly the subject of the current note. The test developed here is also simpler than that of Hollander, et. al. (1986).

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Single Sensor Charging System with MPPT Capability for Standalone Streetlight Applications

  • Osman, Siti Rahimah;Rahim, Nasrudin Abd.;Selvaraj, Jeyraj;Al-Turki, Yusuf A.
    • Journal of Power Electronics
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    • v.15 no.4
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    • pp.929-938
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    • 2015
  • Maximum power point tracking (MPPT) and battery charging control are two important functions for a solar battery charger. The former improves utilization of the available solar energy, while the latter ensures a prolonged battery life. Nevertheless, complete implementation of both functions can be complex and costly, especially for low voltage application such as standalone street lamps. In this paper, the operation of a solar battery charger for standalone street light systems is investigated. Using only one voltage sensor, the solar charger is able to operate in both MPPT and constant voltage (CV) charging mode, hence providing high performance at a low cost. Using a lab prototype and a solar simulator, the operation of the charger system is demonstrated and its performance under varying irradiance is validated.

A Goodness of Fit Approach to Major Lifetesting Problems

  • Ahmad, Ibrahim A.;Alwasel, Ibrahim A.;Mugdadi, A.R.
    • International Journal of Reliability and Applications
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    • v.2 no.2
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    • pp.81-97
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    • 2001
  • Lifetesting problems have been the subject of investigations for over three decades. Most suggested approaches are markedly different from those used in the related but wider goodness of fit problems. In the current investigation, it is demonstrated that a goodness of fit approach is possible in many lifetesting problems and that It results in simpler procedures that are asymptotically equivalent or better than standard ones. They may also have superior finite sample behavior. Several perennial classes are addressed here. The class of increasing failure rate (IFR) and the class of new better than used (NBU) are addressed first. In addition, we provide testing for a newer and practical class of new better than used in convex ordering (NBUC) due to Cao and Wang (1991). Other classes can be developed similarly and this point is illustrated with the classes of new better than used in expectation (NBUE) and harmonic new better than used in expectation (HNBUE).

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COVID-19 Prediction model using Machine Learning

  • Jadi, Amr
    • International Journal of Computer Science & Network Security
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    • v.21 no.8
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    • pp.247-253
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    • 2021
  • The outbreak of the deadly virus COVID-19 is said to infect 17.3Cr people around the globe since 2019. This outbreak is continuously affecting a lot of new people till this day and, most of it is said to under control. However, vaccines introduced around the world can help mitigate the risk of the virus. Apart from medical professionals, prediction models are also said to combinedly help predict the risk of infection based on given datasets. This paper is based on publication of a machine learning approach using regression models to predict the output based on dataset which have indictors grouped based on active, tested, recovered and critical cases along with regions and cities covering most of it from Dubai. Hence, the active cases are tested based on the other indicators and other attributes. The coefficient of the determination (r2) is 0.96, which is considered promising. This model can be used as an frame work, among others, to predict the resources related to the dangerous outbreak.

Impact of Environmental Attitudes on the Judgment of Non-Professional Investors in Saudi Arabia

  • Abdullah, Pr.;Alutaibi, T.
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.93-102
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    • 2021
  • This paper aims to study the influence of environmental attitudes on the choice of non-professional investors. It highlights the role of environmental performance assurance on investment judgments. This choice is due to the motivation and importance that investors place on the disclosure of environmental information. The main purpose of the research is focused on the empirical approach justified by the use of a questionnaire addressed to 200 non-professional investors. The results show that attitudes towards the environment do not correlate with the importance that gives this category of investors to the environmental information.. Subsequently, the results prove that the disclosure of an environmental assurance report has a positive impact on investment judgments independently of their appreciation of the environmental information concerning that of financial order.

AraProdMatch: A Machine Learning Approach for Product Matching in E-Commerce

  • Alabdullatif, Aisha;Aloud, Monira
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.214-222
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    • 2021
  • Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

Distance Learning for Students with Intellectual Disability during the Emerging Coronavirus Pandemic: Opportunities and Challenges from Parents' Perspectives

  • Alnefaie, Adhwaa M.;Bagadood, Nizar H.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.85-92
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    • 2021
  • Distance learning for students with intellectual disabilities can prove beneficial, particularly if adjusted to their educational characteristics and needs. This study seeks to identify the views of parents living in Saudi Arabia, regarding the opportunities offered by distance learning for students with intellectual disabilities, alongside their challenges during the Covid-19 pandemic. The research employed qualitative methods using semi-structured interviews with six parents of students with intellectual disabilities. The results revealed a number of both opportunities and challenges, including issues related to the family, in addition, the data highlighted difficulties related to the educational process (i.e. a lack of variety of educational methods) and technical issues related to access to the Internet and the insufficient computer skills of both teachers and students. The findings have several important implications for future practice, including the need for training workshops for parents concerning the online platform, as well as further research to determine students' perspectives of their experiences with distance learning.

The Investigation of Employing Supervised Machine Learning Models to Predict Type 2 Diabetes Among Adults

  • Alhmiedat, Tareq;Alotaibi, Mohammed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.9
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    • pp.2904-2926
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    • 2022
  • Currently, diabetes is the most common chronic disease in the world, affecting 23.7% of the population in the Kingdom of Saudi Arabia. Diabetes may be the cause of lower-limb amputations, kidney failure and blindness among adults. Therefore, diagnosing the disease in its early stages is essential in order to save human lives. With the revolution in technology, Artificial Intelligence (AI) could play a central role in the early prediction of diabetes by employing Machine Learning (ML) technology. In this paper, we developed a diagnosis system using machine learning models for the detection of type 2 diabetes among adults, through the adoption of two different diabetes datasets: one for training and the other for the testing, to analyze and enhance the prediction accuracy. This work offers an enhanced classification accuracy as a result of employing several pre-processing methods before applying the ML models. According to the obtained results, the implemented Random Forest (RF) classifier offers the best classification accuracy with a classification score of 98.95%.

Differential Item Functioning (DIF) of the Arabic Version of the SONTUS

  • Alhaythami, Hassan M.
    • International Journal of Computer Science & Network Security
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    • v.22 no.5
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    • pp.49-54
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    • 2022
  • The objective of this study was to examine the function of the items on the Arabic version of the Social Networking Time Use Scale (SONTUS) using Differential Item Functioning (DIF) across groups of university students in SA (i.e., males and females at UQU). The findings of this study indicated that some of the items in the Arabic version of the SONTUS functioned differently across male and female students in SA. University faculty and administrators in Saudi Arabia as well as in the Arabic world can benefit from understanding students use of SNS.

Possibility of Inclusive Adaptation of The ABA Intervention at School

  • Saigh, Budor H.
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.83-88
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    • 2022
  • Applied Behaviour Analysis (ABA) is the applied science where strategies are derived from the principles of behaviour and are applied to improve meaningful social behaviours [3]. This study investigates the possible inclusive value of the use ABA in schools in Saudi Arabia. Interviews were conducted with two ABA therapists and a support teacher in order to address this possibility. From the research findings, it emerged how ABA is one of the cognitive-behavioural intervention models and therefore, can be generalised to other disorders or diagnoses and the applied behavioural analysis does have an inclusive value as it structures individualized activities for the increase of both personal and social skills and these activities allow the subject to work on his or her skills, which are, however, absolutely preparatory to the inclusion of the subject in the classroom context.