مطالب

The growing accessibility of web pages to internet users, coupled with the increasing reliance on search engines for daily tasks, underscores the rising importance of search engine optimization (SEO). This research aims to explore the impact of the web visibility index, a key SEO metric, and the utilization of SEO tools on the optimization of university websites. The novelty of this study lies in its examination of the specific influence of the web visibility index and other SEO metrics on university website optimization. Findings reveal significant enhancement in the web visibility index across most universities studied. A comparative analysis of the top 20 universities and their associated libraries sheds light on the factors contributing to increased web visibility. SEO tools and the SISTRIX Toolbox were employed for comparative purposes. Results indicate that the University of UOC boasts the highest web visibility index of 0.0276, while UNED, USE, and UV universities have a web visibility index of 0, indicating the lowest visibility.

Cloud computing has emerged as a pivotal technology for managing and processing data, with a primary objective to offer efficient resource access while minimizing expenses. The allocation of resources is a critical aspect that can significantly reduce costs. This process necessitates the continuous assessment of the current status of each resource to design algorithms that optimize allocation and enhance overall system performance. Numerous algorithms have been developed to address the challenge of resource allocation, yet many fail to satisfy requirements of time efficiency and load balancing in cloud computing environments. This paper introduces a novel approach that classifies tasks according to their resource demands, employs a modified particle swarm optimization (PSO) algorithm, and incorporates load balancing strategies. The proposed method initially clusters tasks based on their resource requirements, subsequently utilizes the PSO algorithm to determine the best task-to-resource assignments, and finally implements a load balancing algorithm to reduce costs through balanced load distribution. The validity of the proposed method is tested and simulated using the Cloudsim tool. The simulation results indicate that the proposed method achieves lower average response time, waiting times, and energy consumption than existing baseline methods.

Due to the popularity of mobile phones and the internet, as well as the development of electronic devices and various software, numerous benefits and facilities have emerged. However, misuse of these tools can lead to serious problems such as deliberate harm to others or cyber victimization. This study utilizes the Everyday Activities Theory and questionnaire techniques to analyze the risk factors and stimulating reasons for cyber victimization among citizens of Kashan City. According to the research findings, there is a significant relationship between independent variables such as online protection, online proximity to motivated offenders, risky offline activities, online attractive targets, deviant lifestyle, and the level of cyber victimization. Among these, the correlation between online proximity to motivated offenders and cyber victimization is greater than other independent variables (r=0.505, sig=0.000). Path analysis results also indicate that the linear combination of the independent variables present in the model can explain 37% of the variance in cyber victimization.

Evidence-based policymaking stands at the forefront of contemporary governance, where data and evidence have emerged as indispensable allies in shaping effective and informed decisions. This article embarks on a comprehensive exploration of the challenges and critical issues encountered when data assumes the role of evidence in policy formulation. The foundation of this investigation is rooted in the extensive body of literature on evidence-based policy-making. We delve into the scholarly discourse, tracing the evolution of policy formulation from relying on intuition to being guided by empirical insights. As we navigate through this intellectual landscape, the crucial role of data as a catalyst for this transformation becomes apparent. Delving deeper, we will explore the intricacies of data and the rise of big data. Once regarded as mere numbers, data now represents the currency of the information age. Its volume, velocity, and variety characterize it, making it a powerful tool for generating evidence and formulating policies. As we explore its features, we uncover the potential of data to unlock unprecedented insights and inform governance with empirical precision. To conduct a comprehensive examination of the difficulties encountered when utilizing data as evidence in policy-making, we employ a rigorous scoping review methodology. Through meticulous screening, we have identified and analyzed 36 exemplary articles that offer invaluable insights into the multifaceted landscape of data-driven governance. These articles provide a comprehensive overview of the challenges, which can be grouped into three distinct clusters: technical challenges arising from data complexities, legal and privacy dilemmas intertwined with governance, and the formidable issues faced by policymakers. Our discussion unravels the intricate web of challenges, ranging from data quality and integration to confidentiality, ethics, and governance issues. We delve into the intricacies of data access, the fight against bias, and the challenges posed by data volume and complexity. Simultaneously, we explore the complex legal landscape of data ownership, security, sharing, and compliance. The challenges policymakers face in fostering data-driven cultures, navigating resource constraints, and communicating data-driven insights are brought to the forefront. In conclusion, our exploration sheds light on the complex challenges and crucial issues that underlie the use of data as evidence in evidence-based policy-making. This research underscores the transformative power of data in governance and emphasizes the challenges and pressing issues associated with using data as evidence in policymaking.

The present study investigates Peer Review Ethics (PRE) in scientific journals in Iran, with a specific focus on compiling the PRE statement for the Journal of Information Processing and Management (JIPM). Moreover, qualitative analysis was conducted on the PRE statements of the journals published by the Ministry of Science, Research, and Technology (MSRT). The review process and documents of the JIPM were then analyzed. This evidence-based case study was conducted using a mixed-method approach, which included three research methods: researcher-based, data-based, and research-based. A focus group discussion (FGD) was also conducted to validate the research findings. The findings showed that PRE elements were classified such as "timeliness," "confidentiality," "bias," "conflict of interest," "research misconduct," "respectful and fair expressions," "constructive and objective feedback," and "accountability and responsibility." The analysis of ethical statements in MSRT journals found that only half of the journals published PRE statements. In addition, 102 instances of violations of PRE, accounting for 15% of each review, were identified in documents submitted for review in JIPM.