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This work serves to propose a national electronic health system based on the Big Data approach. First of all, we assessed the practice of health information systems (HIS) in Morocco and their obstacles. We performed a survey that was founded on 24 questions to specify the necessary details on this topic. This study shows that there is a primary need for the establishment of an HIS that facilitates the control, analysis, and management of health data in Morocco. For this reason, we have proposed the implementation of the Moroccan Health Data Bank (MHDB). This system will be based on powerful big data technologies that save, manage, and process health data with greater efficiency. The information present in this proposed system can provide the necessary resources for several actors to exploit this wealth, which is embodied in this massive data. We have developed a general description of the MHDB, its components, its conceptual architecture, and an example of a use case.

Purpose: This research aimed to identify and evaluate the risks of content production in the governmental digital libraries of Tehran.Method: In terms of essence, this research is synthetic (library studies, qualitative and quantitative), and regarding purpose, it is an applied one.  In the first part, using the studies of the research literature, a set of indicators related to the risks of content production in the governmental libraries of Tehran was obtained. The second part of this research involved a fuzzy Delphi approach that was conducted at two stages among 20 experts. In this stage, a researcher-made questionnaire based on the indicators obtained from the first stage was used. The third part of the research was a survey-analysis conducted with a quantitative method using a questionnaire made out based on the results of qualitative stage with three criteria: the probability of occurrence, effect intensity, and the inability of organization to respond and was distributed among 100 managers and experts of governmental digital libraries in Tehran.Findings: In this research, the risks of content production were identified and fell into nine major categories (human force, environmental factors, infrastructure, protection and maintenance,  creators`  technical rights, integration, content evaluation of sources and authors and information security).Conclusion: The results of this evaluation show that digital libraries are not exactly at their best level when it comes to their responses to the risk of human resources, authors' rights, and integration risks.

Heart failure is a severe medical ailment that significantly impacts patients’ well-being and the healthcare system. For improved results, early detection and immediate treatment are essential. This work aims to develop and evaluate predictive models by applying sophisticated ensemble learning techniques. In order to forecast heart failure, we used a clinical dataset from Kaggle. We used the well-known ensemble techniques of bagging and random forest (RF) to create our models. With a predicted accuracy of 82.74%, the RF technique, renowned for its versatility and capacity to handle complex data linkages, fared well. The bagging technique, which employs several models and bootstrapped samples, also demonstrated a noteworthy accuracy of 83.98%. The proposed model achieved an accuracy of 90.54%. These results emphasize the value of group learning in predicting cardiac failure. The area under the ROC curve (AUC) was another metric to assess the model’s discriminative ability, and our model achieved 94% AUC. This study dramatically improves the prognostic modeling for heart failure. The findings have extensive implications for clinical practice and healthcare systems and offer a valuable tool for early detection and intervention in cases of heart failure.

Purpose: This study extends the current understanding of customer engagement by examining the impact of relationship bonding and relationship quality on customer engagement in value creation for online taxis.Method: A quantitative research design was used to validate the hypotheses proposed in this research. Customer engagement has become an important metric for measuring the quality of relationships between brands and their customers. Despite this, there has been limited research into how relationship bonds affect the effectiveness of building such a relationship in online taxi services. A survey was conducted using the convenience method among 600 users of online transportation services in the city of Urmia, Iran to test the theoretical model. Structural equation modelling in software Amos 23 were used in this study to test the research hypotheses. Findings: Findings showed that relationship bonding (financial, social, and structural) positively affects the quality of online relationships. Moreover, it was found that the quality of online relationships had a positive impact on all four aspects of customer engagement value (lifetime value, influence value, customer knowledge value, and customer referral value).Conclusion: In order to demonstrate the promotion of customer engagement through relationship bonds and online relationship quality, the study adds new data to the literature on online taxis services. Online taxi services are able to offer open innovation structures to help them   increase customer engagement, gather innovative ideas and integrate them into their operations. In this regard, in order to enrich ideas, customers who have successfully come up with new ideas should be rewarded.

Purpose: The purpose of this research was to provide a model for predicting time series of financial information based on the Lyapunov representation of information using chaos theory.Method: This research is applied in its purpose, which is conducted using a quantitative approach. The research ranks as descriptive-causal accounting research based on actual information in companies' financial statements. The research method is the "post-event" type and was carried out using chaos theory and Saida's method based on the Lyapunov view.Findings: The findings showed that during the ADF test, the null hypothesis was rejected at a level of less than 5% type 1 error and 95% confidence, and it shows that the data is not static. During the substitution analysis test and its significance level, the behavior of the time series of the main financial information is significantly different compared to their substitutes. The obtained value was calculated to describe the production process of all data sets for μ = 2, ApEnMax equal to 0.65 and rMax equal to 0.32, and for μ = 3, ApEnMax equal to 0.6 and rMax equal to 0.44. The value of the Lyapunov profile in stability at a certain point is less than zero and in the limited cycle of stability is equal to zero and in chaos, it is greater than zero and smaller than ∞, and in noise it is equal to ∞.Conclusion: The results show that higher returns, encourage investors to invest and increase the flow of capital. It is believed that companies' stock returns are a function of systematic risk, and systematic risk represents the changes in the return rate of a share compared to the changes in the return rate of the entire stock market.

Purpose: The purpose of this study was to prioritize the factors affecting consumer-buying behavior in online social media marketing.Method: The analysis and validation of indicators were conducted using the mixed method of structural equation modeling and partial least squares. Additionally, the IPMA matrix was utilized to determine the importance and type of performance of each factor. The research data were influenced by consumer information, predominantly consisting of women with a master's degree aged between 36 and 50 years. The study employed a non-probability sampling method common for online surveys, and 466 individuals were examined using Cohen's effect size formula.Findings: The research findings indicated that consumer engagement was the most important factor, and ease of use exhibited the highest level of performance in the overall social media model. Furthermore, consumer engagement was identified as the most important factor, while electronic word-of-mouth (EWOM) demonstrated the highest performance level on Instagram. Conversely, EWOM was deemed the most important factor, with consumer engagement displaying the highest performance level on Telegram. These results can be utilized by marketers to influence consumer purchasing behavior and craft online marketing strategies accordingly.Conclusion: Companies utilizing online social media platforms are advised to enhance consumer engagement and performance by implementing short-term techniques and effective strategies, such as incorporating online chat functionalities in the user environment. Instagram, being the most widely used social media platform and an online shopping hub for consumers, showcased acceptable performance in terms of consumer engagement. Hence, companies need to take measures to elevate performance levels to match their importance. In the case of Telegram, EWOM emerged as the most crucial factor among others, with a commendable performance rating. Businesses can bolster their Customer Relationship Management (CRM) units and enhance WOM initiatives to the fullest extent possible.

Purpose: The key to startup success is a brand-centric approach that combines brand leadership strategy with creative, targeted, and cost-effective business methods. In the brand-centered approach, all company processes revolve around the development of brand identity in continuous interaction with customers, to create long-term competitive advantages for the brand. The purpose of this research is to investigate the impact of entrepreneurship-based branding in cyberspace on the performance of startups.Method: The current research is of an applied type and with a mixed method and a sequential qualitative-quantitative approach, first qualitative and then quantitative data was collected and analyzed. Due to the small size of the population, sampling was not done and all 52 people were examined. Smart PLS software was used to analyze quantitative data and test research hypotheses and implement structural equation modeling. Confirmatory factor analysis was also used to test the significance of the relationships and the fit of the obtained measurement models. To analyze the data and test the research hypotheses, the structural equation modeling method was applied.Findings: Qualitative findings showed that the branding model based on entrepreneurship in cyberspace includes six main themes and 18 sub-themes. Causal factors include risk-taking categories, business situation analysis, and brand content capabilities; Background factors include the categories of brand organizational structure, market orientation, and brand orientation; intervening conditions include the categories of legal infrastructure, customer characteristics, and economic uncertainty; the central category includes the three categories of brand vision depiction, brand integrity and entrepreneurial capabilities; strategies including three categories of brand positioning, strategic planning for branding and value creation; And the consequences include three categories of competitive advantage, strategic brand development and brand identity development. Quantitative findings showed that the causal conditions of branding with a score of 26.719 has a positive and significant effect on entrepreneurial branding; Entrepreneurial branding with a score of 4.873 on value-based brand positioning; And value-based positioning with a score of 29.960 has a positive and significant effect on the performance of startups.Conclusion: The results indicate that the branding model based on entrepreneurship in cyberspace and its impact on the performance of startups includes six main themes and 18 sub-themes, and branding based on entrepreneurship in cyberspace has a positive and significant effect on the performance of startups.

Information technology (IT) governance has become a crucial area of study because of the growing corpus of research in the area. This study aims to conduct both a literature review and bibliometric analysis focusing on three specific research questions: (RQ1) examining the trends in publications and citations, (RQ2) recognizing the most impactful countries, journals, and authors, and (RQ3) investigating popular research areas and trending topics in IT governance. Data surrounding IT governance research were obtained through the Scopus database, with a total of 1,510 documents published from 1995 to February 2023. The extracted documents were analysed using Harzing’s Publish or Perish, VOSviewer, and Bibliometrics sub-tool Biblioshiny software. Publications have continued to rise since 2004 when the United States has had the greatest influence over IT governance publication and research collaboration, while Indonesia is the most prolific. Primary sources on IT governance research were taken from conference proceedings related to IT topics. As for authors, Pereira R from Portugal is at the top of the list while Van Grembergen W from Belgium is the most influential. This study is the first to identify and propose themes and current hotspots in IT governance research which serves as a guide for future researchers and professionals.

The present research examines the benefits of implementing knowledge management (KM) principles in the Jordanian banking sector to enhance performance. The study emphasizes the significance of Artificial Intelligence (AI) and how Jordanian banks utilize it to improve the quality of customer service they provide. This study targets managers at all levels and focuses on the Jordanian banking sector as its research environment. A questionnaire is created to gather information from a random sample to achieve the research's objectives. The study involves a sample of 250 managers. Additionally, the research adopts a descriptive methodology, and SPSS is used to analyze the data. The statistical findings provide robust evidence for the importance of performance expectations, social influence, and perceived risk in influencing consumer intentions. Marketers and decision-makers within the banking industry can leverage these insights to shape their long-term strategies for effectively utilizing and maximizing AI technology in the banking sector. Furthermore, by providing policymakers and practitioners of Jordanian commercial banks with insight into the variables influencing user satisfaction, the findings will help these complex institutions operate more effectively.

This study investigates the relationship between the user interface and problem-solving towards the continuous intention to use the services. New products or services will always face tough challenges for the customer, especially when the new procedures require them to learn and change some behaviors. Chatbots are also facing the same situation in Malaysia, where customers refuse to accept using chatbots to represent their physical presence. To understand customer behaviors, a quantitative survey was designed. Four hundred twenty-two data were collected from the online survey method. As per the results, the predictors of chatbot continuous intention are user interface and problem-solving. Apart from that, this study also measures the role of mediator, namely trust and customer satisfaction. This study contributes to unique academic and practical insights that can be used to explore the effectiveness of chatbots. The results revealed that both predictors were significant towards the continuous intentions. Besides, the role of the mediator was found to be significant and relevant in the relationship between trust and customer satisfaction and customer satisfaction and trust towards continuous attention.

In terms of storage and consumption, blockchain technology is poised to transform the way we manage healthcare data. The primary goal is to empower individuals to take charge of their health records, allowing them to become independent of the institutions or organizations they use. Elec-tronic Health Records (EHRs) can be tracked in a novel and unique way through blockchain tech-nology and smart contracts. This technology can give patients more control over their data. Health practitioners and institutions, such as hospitals, may be granted access to patient data controlled by other organizations. This research highlights how blockchain technology can be used to manage EHRs while improving operational efficiency through process simplification and transparency. Additionally, the study proposes an architecture for managing and sharing healthcare data across enterprises. The suggested approach could significantly reduce the time required to transfer patient data among various health organizations while lowering overall costs.

Purpose: The purpose of this research is to present and explain the establishment pattern of the fifth-generation university in Islamic Azad Universities. Future thinking and the university system's policy in higher education have become necessary with the effectiveness of virtual and electronic learning. Higher education based on digital developments has entered a new era where competition and quality are its main characteristics. One of the challenges facing universities in the new millennium is the concept of the fifth-generation universityMethod: This research was conducted using a qualitative-inductive approach and the Strauss-Corbin grounded theory method. The research tool (data collection) is a semi-structured interview. Using the grounded theory method, the data obtained from the interviews, conducted with 10 professors and managers of Islamic Azad University, were analyzed during three stages of open, central, and selective codingFindings: 20 general categories in the form of a paradigm model including factors including causal conditions ( knowledge development; new social needs; internal organizational factors; external organizational factors; mechanisms of first-generation universities, second-generation universities, third-generation universities, and fourth generation universities) central phenomenon (establishment of the fifth generation university), underlying conditions (creating social, cultural and political in the university; economic development of the university; organizational support platforms), intervening conditions (the existence of a dynamic environment and structure in the university) and strategies (changing the educational approach; environmental re-engineering; academic effectiveness; development architecture) and consequences (elite development; comprehensive effectiveness of the university; The emergence of the characteristics of the fifth generation university) is the result of this investigationConclusion: The establishment of a fifth-generation university in higher education can lead to the optimization of the resource allocation behavior of different stakeholders and prevent the waste of resources (financial resources, life or time of students, etc.), which leads to the overall effectiveness of the university; The establishment of the fifth generation university and the development of civilization. 

The term "clickbait" refers to content specifically designed to capture readers' attention, often through misleading headlines, leading to frustration among social media users. In this study, titled "Mushakkal," which translates to "variety" in Arabic, we utilized a Convolutional Neural Network (CNN)—a deep learning approach—to detect clickbait within an Arabic dataset. We compared three optimizers: RMSprop, Adam, and Adadelta, evaluating various parameter settings to determine the most effective combination for detecting clickbait in Arabic content. Our findings revealed that the CNN model performed best when both pre-processing and Word2Vec techniques were applied. The Adam optimizer outperformed the others, achieving a Macro-F1 score of 77%. The RMSprop optimizer closely followed, attaining a Macro-F1 score of 76%. In contrast, Adadelta proved to be the least effective for classifying Arabic text.

Getting highly accurate output in biomedical data processing concerning biomedical signals and images is impossible because biomedical data are generated from various electronic and electrical resources that can deliver the data with noise. Filtering is widely used for signal and image processing applications in medical, multimedia, communications, biomedical electronics, and computer vision. The biggest problem in biomedical signal and image processing is developing a perfect filter for the system. Digital filters are more advanced in precision and stability than analog filters. Digital filters are getting more attention due to the increasing advancements in digital technologies. Hence, most medical image and signal processing techniques use digital filters for preprocessing tasks. This paper briefly explains various filters used in medical image and signal processing. Matlab is a famous mathematical, analytical software with a platform and built-in tools to design filters and experiment with different inputs. Even though this paper implements filters like, Mean, Median, Weighted Average, Guassian, and Bilateral in Python to verify their performance, a suitable filter can be selected for biomedical applications by comparing their performance.

Purpose: The libraries of medical sciences universities have much more diverse goals and services than can be publically conceived, so providing services related to information resources is one of the most important challenges facing these organizations.Method: The present study is an applied research based on its purpose and descriptive-analytical as regards method. The study utilized the semi-structured interview method to obtain the factors affecting the provision of health information resources services. Sampling was conducted based on a purposeful method and experts’ viewpoints. The sampling was carried out the fuzzy Delphi technique which aimed to provide a solution for the issues. A researcher-made questionnaire was used to check the factors obtained from 62 central libraries of medical sciences.Findings: In general, six types of services were determined as health information resource services in specific central libraries, including tools for exploring the online book registration network, selection tools, interlibrary loan, free educational tools, additional book publishing tests, and content evaluation. Additionally, eight factors were identified, including providing services of specialized bibliographic review by librarians, consultation services to users, dissemination and provision of selective information services on Persian and Non-Persian sources, overcoming the weaknesses of librarians without library education, increasing the diversity of medical sciences library services, utilizing new technologies to compensate for deficiencies and lack of resources, improving the social function of the library as a social institution, and offering various electronic services such as databases and digital resources. These identified factors were found to influence the provision of health information resources.Conclusion: Various factors may affect the provision of health information resources services in universities of medical sciences, most importantly improvement of the social functions of libraries.

Purpose: In contemporary times, augmented reality is a cornerstone technology within the tourism sector. Nonetheless, the inclination towards embracing and utilizing augmented reality applications in tourism hinges upon multifaceted determinants, meriting examination through the integrated lens of technology acceptance and use theory. Concurrently, these determinants sway individuals' hedonistic motivations to engage with such apps. This juncture holds significance for managerial considerations, delineating pivotal factors influencing the adoption of this technology. Hence, this present inquiry explores the nexus between the technology acceptance and use theory and the hedonistic motivations for tourism augmented reality apps on mobile platforms within the Iranian context.Method: The current research's statistical population consists of users of tourism augmented reality apps. The sample size is 201 users. The data collection tool is a questionnaire. A structural equation test was used to analyze the data.Findings: The research findings indicate that four factors, namely performance expectancy, effort expectancy, social influence, and facilitating conditions, have a positive and significant impact on the hedonic motivation to use tourism augmented reality apps. Moreover, all four factors of the Unified Theory of Acceptance and Use of Technology (UTAUT) positively influenced the intention to use augmented reality applications on mobile phones. Additionally, hedonic motivation was shown to positively and significantly affect the intention to use tourism augmented reality apps on mobile phones. Notably, hedonic motivation is a crucial mediator between the Unified Theory of Acceptance and Use of Technology (UTAUT) dimensions and the intention to use augmented reality applications. However, the mediating role of hedonic motivation was not supported for performance expectancy and behavioral intention.Conclusion: This research investigates the factors influencing the motivation to use augmented reality (AR) apps in tourism. It finds that performance expectancy, effort expectancy, social influence, and facilitating conditions positively impact hedonic motivation for AR app usage. The study validates the Unified Theory of Acceptance and Use of Technology (UTAUT) for predicting AR app adoption. Notably, hedonic motivation mediates between UTAUT dimensions and intention to use AR technology, suggesting implications for enhancing AR app design in the tourism sector.