۱.
Although there are several development processes for creating entertainment games, serious games, and gamified solutions, there is a need for a new consolidated process capable of developing different types of computer games and digital gamified solutions. This study covers the topic of computer games and gamified solutions design and development processes. First, processes of computer entertainment game production are introduced and investigated. Second, the paper describes gamification and serious game development processes. Finally, this study presents a new process called (DG)2DP to develop entertainment and serious computer games as well as digital gamified solutions. Two methods have been employed to evaluate the proposed game development method. First, the proposed process is assessed by 42 game development practitioners through an 8-factors questionnaire. Second, 16 experts that have applied the process are requested to rate the extent to which they would recommend the (DG)2DP to other game developers. The evaluation results show a 28.39% higher score for (DG)²DP than other processes. Furthermore, in comparison with other development processes, 81.25% of respondents agreed and strongly agreed to recommend the (DG)2DP to other game developers.
۲.
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.
۳.
Recently, many investors have become interested in investing in cryptocurrency market. Investing in an asset carries a lot of risk and may bankrupt the investor. The main way to control this risk is portfolio diversification. In this paper, we will investigate the effect of portfolio diversification by adding cryptocurrencies to the portfolio. We evaluate the performance of seven risk-based portfolio optimization strategies. these strategies are the minimum variance, inverse volatility, L2-norm constrained minimum variance, L2-norm constrained maximum decorrelation, risk parity portfolio and maximum diversification. Our portfolios consist of three markets stocks including, Tehran Stock Exchange, Commodities and Cryptocurrencies. Also, due to the fact that the cryptocurrency market has gained a significant attraction among investors, we will examine the positive and negative effects of adding the five selected currencies, simultaneously and separately to the base portfolio, which is Tehran Stock Exchange-Commodities portfolio. We investigate that whether adding cryptocurrencies to a stock portfolio can be considered as a tool to improve a risk-based portfolio. After analyzing portfolios, the best portfolio in each strategy and the best strategy in each portfolio are introduced from the aspects of risk, return and Sharpe ratio, and finally we have concluded that entering the cryptocurrency market in most of the strategies lead to an overall increase in the return, while the approach is to minimize the risk of the portfolio. So, it can be concluded that if the main goal is to build a more diversified portfolio, better outcome can be obtained for the investor considering the return gained.
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Harassment-based crimes targeting the spiritual integrity of victims are among the most numerous and varied offenses in cyberspace, ,which can be categorized under the general title of harassment in cyberspace. According to the unique properties and meta-variables of information and communication technology, the rate of harassment crime in cyberspace is more than that of real space. This study, a descriptive-analytical meta-analysis, aims to critically examine personality-based crimes and harassment in cyberspace. It seeks to identify the types of crimes, the characteristics of the victims, and the criminal profiles of the offenders. Findings reveal that these crimes are predominantly perpetrated by young men with diverse motivations, particularly of a sexual nature, targeting teenage girls. Based on these findings, it is recommended that legislators adopt a differential and aggravated approach to criminalize harassment against women and children. Additionally, addressing the role and needs of victims in crime responses is crucial. Furthermore, identifying and criminalizing emerging personality-based behaviors, balancing crime platform filtering, adopting participatory criminal policies involving non-governmental organizations, empowering users with preventive oversight and technical measures, and enhancing media literacy and cultural norm-setting are essential strategies for combating personality-based crimes.
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One of the most difficult problems in web research is security. Cryptography is the fundamental technique utilized in secure communication. One key element of cryptography is Public-Key Cryptography (PKC). In many PKCs, the Modular Exponentiation (ME) with large modulus is a crucial process. Efficient architecture design and hardware implementation of large integer Modular Exponentiation (ME) plays a vital role in computer science such as public key cryptography. Therefore, many researchers have devoted special interest to provide efficient architecture design and hardware implementation of large integer ME. This study presents and evaluates a novel architecture for the hardware implementation of ME. To achieve the maximum architectural and timing improvements, the critical path of the Left-to-Right (LtR) and Right-to-Left (RtL) ME architectures is reorganized and reordered using a modified modular multiplication. The implementation results on a Xilinx Virtex 5 FPGA demonstrate that the developed ME architectures have a better performance in comparison with other well-known ME architectures so far in the literatures.
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Corner detection, crucial for many computer vision tasks due to corner's distinct structural properties, often relies on traditional intensity-based detectors developed before 2000. This paper introduces a novel intensity-based corner detector that surpasses existing methods by solely analyzing pixel intensity within a 3×3 neighborhood. Our approach leverages a unique corner response function derived from intensity sorting and difference calculations. We conduct a comprehensive evaluation comparing our detector to seven established algorithms using five benchmark images with ground truth corner locations. The evaluation encompasses detection accuracy, localization error under varying noise levels, and repeatability under transformations and degradations. This assessment utilizes 28 diverse images without ground truth data. Experimental results demonstrate the proposed detector's superior overall performance by 3%. It achieves better accuracy in corner localization and reduces both missed detections and false positives. Furthermore, requiring only one parameter for adjustment, it offers computational efficiency and real-time processing potential. Additionally, the generated corner response map holds promise for integration with deep learning architectures, opening possibilities for further exploration.
