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This paper contributes to the issue of eGovernment implementation in Saudi Arabia by discussing the current situation of ministry websites. It evaluates the rate of web development progress of vital government websites in Saudi Arabia using the eGovernment stage model. In 2010, Saudi Arabia ranked 58th in the world and 4th in the Gulf region in eGovernment readiness according to United Nations reports. In particular, Saudi Arabia has ranked 75th worldwide for its online service index and its components compared to the neighbouring Gulf country of Bahrain, which was ranked 8th for the same index. While this is still modest in relation to the Saudi government expectation concerning its vision for eGovernment implementation for 2010, and the results achieved by the neighbouring Gulf countries such as Bahrain and the United Arab Emirates on the eGovernment index, the Saudi government has endeavoured to meet the public needs concerning eGovernment and carry out the implementation of eGovernment properly. Governments may heed the importance of actively launching official government websites as the main portals for delivering their online services to all the different categories of eGover
This paper presents the preliminary findings of a study researching the diffusion and the adoption of online retailing in Saudi Arabia. It reports new research that identifies and explores the key issues that positively and negatively influence the decision of Saudi customers to buy from online retailers in Saudi Arabia. Although Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. While the overall research project involves exploratory research using mixed methods, the focus of this paper is on a quantitative analysis of responses obtained from a survey of Saudi customers, with the design of the questionnaire instrument being based on the findings of a qualitative analysis reported in a previous paper. The main findings of the current analysis include a list of key factors that affect Saudi customers' purchase from Saudi online retailers, and quantitative indications of the relative strengths of the various relationships.
There are significant differences in innovation performance between countries. Additionally, the pharmaceutical sector is stronger in some countries than in others. This suggests that the development of the pharmaceutical industry can influence a country's innovation performance. Using the Global Innovation Index and selected performance measures of the pharmaceutical sector, this study examines how the pharmaceutical sector influences the innovation performance of countries from the European context. The dataset of 27 European countries was analysed using simple, and multiple linear regressions and Pearson correlation. Our findings show that only three indicators of the pharmaceutical industry, more precisely pharmaceutical Research and Development, pharmaceutical exports, and pharmaceutical employment explain the innovation performance of a country largely. Pharmaceutical Research and Development and exports have a significant positive impact on a country's innovation performance, whereas employment in the pharmaceutical industry has a slightly negative impact. Additionally, global innovation performance has been found to positively influence life expectancy. We further outline t
With the loosening of the male guardianship system (Wilaya) in the Kingdom of Saudi Arabia (KSA), this study examines the contribution of m-government to the empowerment of Saudi women. We employ the key concepts of Sen's Capability Approach (CA) to understand how m-government services in the KSA have provided opportunities for women to become empowered. The findings of the study indicate that m-government contributes towards women's empowerment by providing opportunities to participate in social and economic activities. However, there are also key social and cultural factors that impede the use of m-government services for empowerment, and we found these to include religious beliefs, Saudi traditions and customs, and husbands' jealousy. The study makes some important contributions to theory and practice by being the first study to focus on the use that Saudi women make of the opportunities now available to them to access government services through m-government applications and to address the cultural barriers which may function to prevent their access.
COVID-19 was announced by the World Health Organisation (WHO) as a global pandemic. The severity of the disease spread is determined by various factors such as the countries' health care capacity and the enforced lockdown. However, it is not clear if a country's climate acts as a contributing factor towards the number of infected cases. This paper aims to examine the relationship between COVID-19 and the weather of 89 cities in Saudi Arabia using machine learning techniques. We compiled and preprocessed data using the official daily report of the Ministry of Health of Saudi Arabia for COVID-19 cases and obtained historical weather data aligned with the reported case daily reports. We preprocessed and prepared the data to be used in models' training and evaluation. Our results show that temperature and wind have the strongest association with the spread of the pandemic. Our main contribution is data collection, preprocessing, and prediction of daily cases. For all tested models, we used cross-validation of K-fold of K=5. Our best model is the random forest that has a Mean Square Error(MSE), Root Mean Square (RMSE), Mean Absolute Error (MAE), and R{2} of 97.30, 9.86, 1.85, and 82.3\%
DevOps has gained high importance in the global software industry due to the ease of software development, testing and deployment it provides. However, the Saudi software industry has not been able to adopt DevOps at a great pace due to various factors. This study, thus, aimed to examine different factors that hindered the adoption of DevOps in the Saudi software industry. Also, recommendations are provided at the end for Saudi Arabia to enhance the adoption of DevOps in its software industry. To accomplish the aims, this study used a literature review and interviews to gather data and examine it to produce the findings. The findings of the study highlight lack of support from organizational management and lack of laws as the major factors for the adoption of DevOps in the Saudi software industry.
The digital transformation of pharmaceutical industry is a challenging task due to the high complexity of involved elements and the strict regulatory compliance. Maintenance activities in the pharmaceutical industry play an essential role in ensuring product quality and integral functioning of equipment and premises. This paper first identifies the key challenges of digitalization in pharmaceutical industry and creates the corresponding problem space for key involved elements. A literature review is conducted to investigate the mainstream maintenance strategies, digitalization models, tools and official guidance from authorities in pharmaceutical industry. Based on the review result, a semantic-driven digitalization framework is proposed aiming to improve the digital continuity and cohesion of digital resources and technologies for maintenance activities in the pharmaceutical industry. A case study is conducted to verify the feasibility of the proposed framework based on the water sampling activities in Merck Serono facility in Switzerland. A tool-chain is presented to enable the functional modules of the framework. Some of the key functional modules within the framework are implem
This article uses the hierarchical linear modelling (HLM) technique to explain causally the Mathematics Performance achievement of students in Saudi Arabia. Particularly, the HLM technique was applied to the TIMSS 2011 data set where five variables (Home educational resources (BSBGHER), Like learning mathematics (BSBGSLM), Self-confidence in mathematics (BSBGSCM), Engaged in mathematics learning (BSBGEML), Value learning math (BSBGSVM)) at the student level and three variables (Emphasis on academic success (BCBGEAS), School discipline and safety (BCBGDAS), and Instruction affected by mathematics resources shortages (BCBGMRS) at the school level, were used to build the hierarchical linear model so as to predict the status of mathematically 8th grader. The final model suggested that all the student level factors are found to be significant but their impact on achievement do not vary significantly across the population of schools, i.e. BSBGHER, BSBGSLM, BSBGSCM, BSBGEML, and BSBGSVM significantly predicted the status of Mathematics Performance achievement of students in Saudi Arabia. At the school level, it is found that BCBGDAS and BCBGMRS have a significant impact on performance. Ho
The small and medium-sized enterprise (SME) sector represents one of the fundamental pillars in the trade field. It contributes significantly to raising the economies of countries by providing significant numbers of job opportunities, which are beneficial to directly supporting national economies. One of the most important obstacles facing this sector in the information technology era is the lack of online trading channels with consumers, which require more financial support than the their capabilities. Therefore, e-Malls might be one of the best low-cost solutions to overcome this obstacle. Also, they provide electronic platforms that include most SME requirements for sales via electronic channels as well as offer essential technical support. According to a report published in 2013 by the Saudi Arabian Monetary Agency (SAMA), the percentage of SMEs is equivalent to 90% of the total number of companies in Saudi Arabia, which is numbered at 848,500. The e-Mall is a modern idea in Saudi Arabia that requires the use of the Disunion Of Innovation (DOI) approach to diffuse e-Malls through determining companies requirements and difficulties. Therefore, this paper focuses on the factors t
Many drugs have been withdrawn from the market worldwide, at a cost of billions of dollars, because of patient fatalities due to them unexpectedly disturbing heart rhythm. Even drugs for ailments as mild as hay fever have been withdrawn due to an unacceptable increase in risk of these heart rhythm disturbances. Consequently, the whole pharmaceutical industry expends a huge effort in checking all new drugs for any unwanted side effects on the heart. The predominant root cause has been identified as drug molecules blocking ionic current flows in the heart. Block of individual types of ionic currents can now be measured experimentally at an early stage of drug development, and this is the standard screening approach for a number of ion currents in many large pharmaceutical companies. However, clinical risk is a complex function of the degree of block of many different types of cardiac ion currents, and this is difficult to understand by looking at results of these screens independently. By using ordinary differential equation models for the electrical activity of heart cells (electrophysiology models) we can integrate information from different types of currents, to predict the effect
When effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, home quarantine and far-reaching shutdown of public life are the only available strategies to prevent the spread of epidemics. Based on an extended SEIR (susceptible-exposed-infectious-recovered) model and continuous-time optimal control theory, we compute the optimal non-pharmaceutical intervention strategy for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible. In this case, the optimal control must meet competing requirements: First, the minimization of disease-related deaths, and, second, the establishment of a sufficient degree of natural immunity at the end of the measures, in order to exclude a second wave. Moreover, the socio-economic costs of the intervention shall be kept at a minimum. The numerically computed optimal control strategy is a single-intervention scenario that goes beyond heuristically motivated interventions and simple "flattening of the curve." Careful analysis of the computed control strategy reveals, however, that the obtained solution is in fact a tightrope walk close to t
In this paper, we introduce SaudiBERT, a monodialect Arabic language model pretrained exclusively on Saudi dialectal text. To demonstrate the model's effectiveness, we compared SaudiBERT with six different multidialect Arabic language models across 11 evaluation datasets, which are divided into two groups: sentiment analysis and text classification. SaudiBERT achieved average F1-scores of 86.15\% and 87.86\% in these groups respectively, significantly outperforming all other comparative models. Additionally, we present two novel Saudi dialectal corpora: the Saudi Tweets Mega Corpus (STMC), which contains over 141 million tweets in Saudi dialect, and the Saudi Forums Corpus (SFC), which includes 15.2 GB of text collected from five Saudi online forums. Both corpora are used in pretraining the proposed model, and they are the largest Saudi dialectal corpora ever reported in the literature. The results confirm the effectiveness of SaudiBERT in understanding and analyzing Arabic text expressed in Saudi dialect, achieving state-of-the-art results in most tasks and surpassing other language models included in the study. SaudiBERT model is publicly available on \url{https://huggingface.co/
Publication patterns of 79 forest scientists awarded major international forestry prizes during 1990-2010 were compared with the journal classification and ranking promoted as part of the 'Excellence in Research for Australia' (ERA) by the Australian Research Council. The data revealed that these scientists exhibited an elite publication performance during the decade before and two decades following their first major award. An analysis of their 1703 articles in 431 journals revealed substantial differences between the journal choices of these elite scientists and the ERA classification and ranking of journals. Implications from these findings are that additional cross-classifications should be added for many journals, and there should be an adjustment to the ranking of several journals relevant to the ERA Field of Research classified as 0705 Forestry Sciences.
While cyber security has become a prominent concept of emerging information governance, the Kingdom of Saudi Arabia has been dealing with severe threats to individual and organizational IT systems for a long time. These risks have recently permeated into educational institutions, thereby undermining the confidentiality of information as well as the delivery of education. Recent research has identified various causes and possible solutions to the problem. However, most scholars have considered a reductionist approach, in which the ability of computer configurations to prevent unwanted intrusions is evaluated by breaking them down to their constituent parts. This method is inadequate at studying complex adaptive systems. Therefore, the proposed project is designed to utilize a holistic stance to assess the cybersecurity management and policies in Saudi Arabian universities. Qualitative research, entailing a thorough critical review of ten public universities, will be utilized to investigate the subject matter. The subsequent recommendations can be adopted to enhance the security of IT systems, not only in institutional settings but also in any other environment in which such structur
The informatization practice of countries all over the world has shown that the level of a government's informatization is one main factor that can affect its international competitive power. At present, e-government construction is regarded as one of the most important tasks for the national economy and society upliftment and informatization in Saudi Arabia. Unlike the traditional governments, an e-government takes on a new look with its framework and operation mode more suitable for the contemporary era. In fact, it is a basic national strategy to promote Saudi Arabia's informatization by means of e-government construction. This talk firstly introduces the basic concepts and relevant viewpoints of egovernment, then reviews the development process of e-government in Saudi Arabia, and describes the current states, development strategies of e-government in Saudi Arabia. And also review e-government maturity models and synthesize them e-government maturity models are investigated, in which the authors have proposed the Delloite's six-stage model, Layne and Lee four-stage model and Accenture five-stage model. So, the main e-government maturity stages are: online presence, interaction,
The integration of Internet of Things (IoT) technologies in agriculture holds promise for transforming farming practices, particularly in the Kingdom of Saudi Arabia (KSA). This study explores the adoption of smart farming practices among KSA farmers. Due to the geographical location and nature of KSA, it faces significant challenges in agriculture. The objective of this research is to discuss how IoT will enhance agriculture in KSA and identify its current usage by conducting a study on Saudi farmers with varying ages, regions, and years of experience. The results indicate that 90% of the farmers encounter challenges in farming, and all of them express interest in adopting smart farming to address these issues. While 60% of farmers are currently utilizing IoT technologies, they encounter challenges in implementing smart farming practices. Thus, smart farming presents solutions to prevalent challenges including adverse weather, water scarcity, and labor shortages, though barriers include cost and educational challenges.
Data science has become increasingly essential for the production of official statistics, as it enables the automated collection, processing, and analysis of large amounts of data. With such data science practices in place, it enables more timely, more insightful and more flexible reporting. However, the quality and integrity of data-science-driven statistics rely on the accuracy and reliability of the data sources and the machine learning techniques that support them. In particular, changes in data sources are inevitable to occur and pose significant risks that are crucial to address in the context of machine learning for official statistics. This paper gives an overview of the main risks, liabilities, and uncertainties associated with changing data sources in the context of machine learning for official statistics. We provide a checklist of the most prevalent origins and causes of changing data sources; not only on a technical level but also regarding ownership, ethics, regulation, and public perception. Next, we highlight the repercussions of changing data sources on statistical reporting. These include technical effects such as concept drift, bias, availability, validity, accur
We report on the gamma-ray activity of the blazar Mrk 501 during the first 480 days of Fermi operation. We find that the average LAT gamma-ray spectrum of Mrk 501 can be well described by a single power-law function with a photon index of 1.78 +/- 0.03. While we observe relatively mild flux variations with the Fermi-LAT (within less than a factor of 2), we detect remarkable spectral variability where the hardest observed spectral index within the LAT energy range is 1.52 +/- 0.14, and the softest one is 2.51 +/- 0.20. These unexpected spectral changes do not correlate with the measured flux variations above 0.3GeV. In this paper, we also present the first results from the 4.5-month-long multifrequency campaign (2009 March 15 - August 1) on Mrk 501, which included the VLBA, Swift, RXTE, MAGIC and VERITAS, the F-GAMMA, GASP-WEBT, and other collaborations and instruments which provided excellent temporal and energy coverage of the source throughout the entire campaign. The average spectral energy distribution of Mrk 501 is well described by the standard one-zone synchrotron self-Compton model. In the framework of this model, we find that the dominant emission region is characterized b
This paper introduces the Saudi Privacy Policy Dataset, a diverse compilation of Arabic privacy policies from various sectors in Saudi Arabia, annotated according to the 10 principles of the Personal Data Protection Law (PDPL); the PDPL was established to be compatible with General Data Protection Regulation (GDPR); one of the most comprehensive data regulations worldwide. Data were collected from multiple sources, including the Saudi Central Bank, the Saudi Arabia National United Platform, the Council of Health Insurance, and general websites using Google and Wikipedia. The final dataset includes 1,000 websites belonging to 7 sectors, 4,638 lines of text, 775,370 tokens, and a corpus size of 8,353 KB. The annotated dataset offers significant reuse potential for assessing privacy policy compliance, benchmarking privacy practices across industries, and developing automated tools for monitoring adherence to data protection regulations. By providing a comprehensive and annotated dataset of privacy policies, this paper aims to facilitate further research and development in the areas of privacy policy analysis, natural language processing, and machine learning applications related to pr
Generally, open innovation is a lucrative research topic within industries relying on innovation, such as the pharmaceutical industry, which are also known as knowledge-intensive industries. However, the dynamics of drug pipelines within a small-medium enterprise level in the global economy remains concerning. To reveal the actual situation of pharmaceutical innovation, we investigate the feature of knowledge flows between the licensor and licensee in the drug pipeline based on a multilayer network constructed with the drug pipeline, global supply chain, and ownership data. Thus, our results demonstrate proven similarities between the knowledge flows in the drug pipeline among the supply chains, which generally agrees with the situation of pharmaceutical innovation collaborated with other industries, such as the artificial intelligence industry.