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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.

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.

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. 

In healthcare, a diagnosis is reached after a thorough physical assessment and analysis of the patient's medicinal history, as well as the utilization of appropriate diagnostic tests and procedures. 1.7 million People worldwide lose their lives every year due to complications from chronic kidney disease (CKD). Despite the availability of other diagnostic approaches, this investigation relies on machine learning because of its superior accuracy. Patients with chronic kidney disease (CKD) who experience health complications like high blood pressure, anemia, mineral-bone disorder, poor nutrition, acid abnormalities, and neurological-complications may benefit from timely and exact recognition of the disease's levels so that they can begin treatment with the most effective medications as soon as possible. Several works have been investigated on the early recognition of CKD utilizing machine-learning (ML) strategies. The accuracy of stage anticipations was not their primary concern. Both binary and multiclass classification methods have been used for stage anticipation in this investigation. Random-Forest (RF), Support-Vector-Machine (SVM), and Decision-Tree (DT) are the prediction models employed. Feature-selection has been carried out through scrutiny of variation and recursive feature elimination utilizing cross-validation (CV). 10-flod CV was utilized to assess the models. Experiments showed that RF utilizing recursive feature removal with CV outperformed SVM and DT.

Cloud computing technology could bring about cost-effectiveness, scalability, usage easiness, and flexibility against environmental changes. Despite several advantages of this technology, the acceptance and movement to the cloud computing environment occurs slowly, particularly in several organizations in developing countries. Cloud computing allows an individual to share distributed sources and services. This study aims to identify the optimal security framework in cloud computing, focusing on the Infrastructure Communications Company as a case study. The method used in this study is descriptive (non-test) and the correlative research scheme is PLS (partial least squares). The participants of the current study were selected among the Tehran Communication Infrastructure Company employees. Based on the Cochran formula and the research population which was 600, 234 were selected using the random sampling method. To measure the security framework in cloud computing, the questionnaires related to Joils and Opria (2017), Tari (2014), Qio and Gayi (2017), and Sing et al. (2016) were used. Findings indicate that the impacts of technological and technical factors, experienced human resources, financial resource provision and secure infrastructures on information technology security were significant (0.01). Moreover, information technology management and supporting regulations on security risk assessment have significant effects. The assessment of security risk has a significant effect on information security. Additionally, information security management and supporting regulations have a significant effect on Goal setting (0.01). Goal setting has a significant effect on environmental and physical security. Based on the results, the evaluated model of the research could explain 0.53 of information security management, 0.50 of security evaluation, 0.36 of goal setting, 0.55 of information security, and 0.35 of environmental security.

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.

Purpose: The purpose of this research was to provide a model for dynamic knowledge management in Iranian government organizations.Method: This research is applied in terms of purpose, survey-exploratory in terms of approach, and qualitative in terms of type. The statistical population of this research was a group of experts, including university professors, and senior managers of the Zanjan Province Industry, Mining and Trade Organization, and based on theoretical sampling, 11 of them were selected as a statistical sample and were interviewed. The approach adopted in this research to analyze the interviews was theme analysis.Findings: The results of the research led to the presentation of a new model in the field of dynamic knowledge management in Iranian government organizations, including five main variables (including: promotional levers of dynamic knowledge management, intra-organizational factors of dynamic knowledge management, extra-organizational factors of dynamic knowledge management, executive levers of dynamic knowledge management, and expected consequences of dynamic knowledge management).Conclusion: The results of this research showed that if dynamic knowledge management is implemented well in Iran's government organizations, it can be expected that organizational productivity and agility and the satisfaction of stakeholders will improve.

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: The field of providing information and the method of publishing information has permanently been subject to modification and alteration, and as we know, with the introduction of computer technology in the field of librarianship and the change in the way of providing services, the imperative task of information dissemination has been reserved for librarians. The dissemination of information technology into the education system has led to the emergence of a new concept called e-learning. The task of libraries is to provide infrastructures for information retrieval through the production of integration, organization, and distribution of knowledge. The methods that libraries employ for e-learning include learning collections, tools, and facilities necessary for studying, improving the quality of reference services, and ensuring universal access to books. Therefore, this research aims to identify the factors influencing e-learning in information retrieval.Method: This current research is developmental was conducted using a qualitative approach and grounded theory. The population of the study consisted of 20 experts in the field of information technology in public libraries across the country, who were selected through purposive non-probability sampling. Data were collected through interviews and analyzed through three stages of open, axial, and selective coding, based on which the research model was designed.Findings: The findings showed that e-learning in information retrieval contains of six main dimensions, 45 sub-dimensions, and 85 concepts, which are presented in a paradigm model including causal factors (quality of e-learning website design, quality of education in e-learning environments, employees' enthusiasm for developing knowledge capabilities, employees' belief in continuous training), contextual factors (suitable technical equipment (hardware, software, and network), availability of necessary infrastructure, high accessibility, periodic purchase of required equipment, ease of learning and simplicity of teaching platforms (instructors)), interveners (competence of instructors in course delivery, course development based on indigenous data, organizational culture and atmosphere), central factors (strategies for enhancing the quality of e-learning in information retrieval, processes for improving the quality of e-learning in information retrieval, infrastructures for improving the quality of e-learning in information retrieval), strategic factors (existence of an appropriate incentive system for promoting knowledge sharing (systemic strategy), security of software used (educational approach), efficient support and feedback mechanisms (responsiveness strategy)), and consequences (consistency of goals and plans, adequate understanding of e-learning, formulation of standards, capability in information retrieval).Conclusion: Based on the dimensions, main factors, and sub-factors, the impacts of e-learning in information retrieval can be measured and managed in the studied community.

This research delves into the socio-economic aspects of online gambling in Iran, exploring the underlying cultural drivers that have contributed to its rapid growth in recent years. Online gambling's prevalence is intricately linked to cultural norms and values, both overt and covert, which have shaped its emergence in the country. Despite the religious, legal, and cultural taboos associated with gambling in Iran, this study investigates the cultural motifs that have challenged these obstacles, particularly among the youth. To unravel the psychological mechanisms at play among young online gamblers, this study adopts a qualitative approach, employing in-depth interviews with 17 male online gamblers aged between 20 and 40, alongside participatory observations. The data is analyzed thematically, with a focus on cultural motifs that reinforce mental accounting biases, drawing from the principles of behavioral economics. Notably, the central theme that emerges from this analysis is the "psychology of success", a worldview that influences the mindset and actions of individuals engaged in online gambling. The findings of this study reveal a significant thematic alignment between the teachings of the psychology of success and the cultural elements that bolster cognitive biases in the speech and conduct of online gamblers. The psychology of success, which emphasizes a sense of agency and empowerment, appears to drive cultural change and contributes to the widespread acceptance of online gambling despite its illegitimate status. Furthermore, the study highlights a connection between the prevalence of online gambling and the devaluation of the national currency.

Today, gamification is being used in various areas such as education, health, and business to enhance engagement and increase the system's efficiency. Despite significant scholarly interest, in many cases, undesirable results have been achieved using gamified solutions. This highlights the need for further research to explore these challenges through innovative methodologies and to devise new solutions. Addressing this gap, we conducted a systematic review of the literature on the emerging and growing subject of gamification using the PRISMA methodology and proposed a novel model for the strategic development of future gamification studies. The research led to the identification of 48 qualified empirical studies which have been analyzed to outline the existing views, gaps, and consequently the implications for future research. Through the analysis, we delineate the impact and effectiveness of gamification, highlighting its potential to transform user experience positively when implemented with strategic finesse. Consequently, we propose a novel model for the strategic development of future gamification studies, presenting it in three main dimensions: Contexts, Users, and Elements, and for each dimension, significant and less-paid topics are discussed. In addition, we represent six main suggestions for the design of the entire gamified system: Decision-Making Methods, Success Factors, Validation Methods, Dynamic Design Approach, Timeframe, and Modern Technology. Our proposed model not only facilitates a deeper understanding of gamified systems but also offers actionable insights and guidelines for both academics and practitioners. It is meticulously designed to assist researchers and practitioners in crafting more effective gamified systems that are customized to meet specific user needs and environmental contexts. By doing so, it aims to maximize the sustainable benefits of gamification, ensuring that these systems deliver significant and lasting impacts. This strategic approach integrates the latest advancements in technology and dynamic design principles, establishing a robust framework for the future of gamification research and application.

In today’s world, there is a notable focus on incorporating disabled people within the community and the workplace. Advancements in artificial intelligence (AI) have the potential to significantly impact empowering individuals with disabilities to enhance inclusivity and autonomy for this demographic in the era of Society 5.0. This paper aims to offer a bibliometric analysis of the increasing number of publications addressing the potential impact of AI on disabled individuals and their future employment. To conduct this analysis, Scopus served as the bibliographic source, using Disability, Employment, and Future Workforce as the search terms, yielding 203 publications on the subject of study from 1973 to 2024. The analysis was conducted using VOS viewer. The results indicate that as Society 5.0 evolves, advancements in AI have the potential to significantly empower individuals with disabilities, enhancing inclusivity and autonomy for this demographic.

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.

Nowadays, many companies cannot see the digital investment that plays a main role in the IR 4.0. Therefore, this study is investigating the study of investment as plays a critical role in an analytical activity to assess the benefits and costs of an investment and can be used as an investment justification. Traditional investment appraisal uses a financial approach where the benefits and costs are quantified in a certain amount of value for money and then compared in value. Moreover, this study is revealed the fruitful outcomes because revealed the investment valuation method with NPV (Net Present Value) and ROV (Real Option Valuation). ROV is an alternative to financial valuation. Seeding from the same philosophy as Financial Option, ROV has advantages in handling the flexibility, risk, and volatility that may occur from an investment. Thus, ROV is considered more able to appreciate an investment that has these characteristics. Investment appraisal with ROV is better able to appreciate investment than traditional financial methods, as shown by ROV's NPV results in the case of marketing with Loyalty points through email communication as a digital investment that are greater than ordinary NPV. This is because ROV can appreciate flexibility in investments that have choices of investment plans in the future

The object of the research is the economic dynamic of a depressed low-productive economy, as exemplified by the modern Ukrainian economy. With the purpose to analyze the main causes and consequences of such an economy, the characteristic tendencies of its functioning, activation of the processes of reformation and growth, there was developed the dynamic economic model with significant share of consumer import and export of raw materials, with the use of IT technology. The model also takes into account the socio-economic clustering of a society. It is formalized in the space of economic variables, which describes respectively the savings (liquid capital) of the main social groups involved in the economy, the prices of consumer products in the domestic and foreign markets, the price of exported raw materials for the exchange rate.The model is intended for qualitative analysis of the processes occurring in the economy described by it, and for conducting computational experiments on the basis of information technologies in simulation mode with its parameters, which allows to identify the most characteristic features of the object of the research. The results of experimental researches with the model allowed to establish the main periods of economic dynamics represented by the dynamic variables model, its specificity and social consequences for the society, which is characterized by a bimodal distribution of savings. There was investigation the dependence of the mode solution from it parameters which means in practice the dependence of economic dynamics from the change of individual conditions and factors of economic development.The obtained results are important for informational and analytical support of decision making processes in order to bring the being studied economy out of a low-productive state.