• Fourth Industrial Review
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• v.4 no.1
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• pp.1-9
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• 2024

Purpose: Education is the part of a fundamental human right across the world. In recent years, the trend of virtual education has increased tremendously. The paper aims to find the impact of adoption, accessibility, interactions, knowledge, and satisfaction on the success of transformation towards virtual education. Research design, data and methodology: Primary data has been gathered through the use of responses from students taking admission in virtual higher education to standardized questionnaires. Of the 250, only 122 were considered complete and have been used in further studies. Convinced random sampling method has been used. The results were evaluated using the Likert Five-Point Scale. For applying these statistical tools software SmartPLS and SPSS 19 have been used. The fitness of the model has been re-checked through an Artificial Neural Network (ANN). Result: Results derived that adoption, accessibility, and interactions have a significant impact on knowledge, knowledge influences satisfaction level and satisfaction have a meaningful impact on the success of transformation towards virtual education. Conclusion: It can be concluded that virtual education has the potential to change the future of the education system and its potential in India. The highest importance is due to satisfaction (100%), adoption (98.7%), knowledge (91.4%), accessibility (62%), and interaction (29.2%).

• Journal of Wind Energy
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• v.14 no.4
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• pp.57-67
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• 2023

This study aimed to investigate differences in turbulence intensity and turbine loads among onshore wind farms located in various types of terrain. To achieve this, simulations were conducted for two onshore wind farms with identical wind turbines and capacity but situated on complex and flat terrains. The simulations used meteorological data gathered over a 10-year period from automatic weather stations nearest to the wind farms. WindSim and WindPRO software tools were employed for wind field and load analysis, respectively. The simulation results revealed that wind farm A, situated on complex terrain, exhibited significantly higher effective turbulence intensity than wind farm B on flat terrain, as expected. Consequently, the load indices of several wind turbines exceeded 100 % in wind farm A, indicating that the turbines could not reach their design lifespan. From the simulation study, aimed at reducing both the effective turbulence intensity and turbine loads, it became evident that while increasing turbine spacing could decrease effective turbulence intensity to some extent, it couldn't completely resolve the issue due to the inherently high ambient turbulence intensity on complex terrain. The problem with wind turbine loads could only be completely resolved by using wind turbines with a turbine class of A+, corresponding to a reference turbulence intensity of 0.18.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.37-48
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• 2023

Purpose - This study aims to explore the influence of emotional discrepancies among investors on the cryptocurrency market. It focuses on how varying emotions affect market dynamics such as volatility and trading volume in the context of Bitcoin trading. Design/methodology/approach - This study involves analyzing data from Bitcointalk.org, consisting of 57,963 posts and 2,215,776 responses from November 22, 2009, to December 31, 2022. Tools used include the Linguistic Inquiry and Word Count (LIWC) software for classifying emotional content and the Python Pattern library for sentiment analysis. Findings - The results show that heterogeneous emotional feedback, whether positive or negative, significantly influences Bitcoin's intraday volatility, skewness, and trading volume. These findings are more pronounced when the underlying emotion in the feedback is amplified. Research implications or Originality - This study underscores the significance of emotional factors in financial decision-making, especially within the realm of social media. It suggests that investors and market strategists should consider the emotional landscape of online forums when making investment choices or formulating market strategies. The research also paves the way for future studies regarding the behavioral impact of emotions on the cryptocurrency market.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.177-185
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• 2024

Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.259-266
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• 2024

One of the most time consuming issues in a city development is the identification of suitable areas for urban infrastructures and proper land uses. Suitability analysis is the process and procedures to find the best available land in given area -that is, the ability of a system to select the needs of users in land use. This paper studied the usage of Geographic Information System technique and methods for the selection of the most appropriate sites for public park in the city of Gwangju. GIS was used as a standard technique to find the best available sites for development in urban areas. For this cause, digital elevation model and spatial data were used to produce different thematic layers by using software Idrisi. Criteria for finding the suitable site for park development were decided to evaluate the land and the followings 4 criteria were selected: on land with less than 3 degrees in slope, outside a 200m buffer around lakes, on land currently designated as forests, and 20ha or greater in size. To meet and measure each criterion, distance and context operators were applied to reclassify the importance of certain weight and Boolean images were generated to meet the criteria. These weights and maps has been combined using ArcGIS tools and the final map was prepared showing the most suitable sites. We may assist city planners and government officials in future development of public facilities including parks and related land use plans at urban level and act as to ensure proper land use planning and management of the urban areas.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.105-110
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• 2024

Artificial intelligence is being used in various fields, and the coding paradigm is also changing. Although the development of various coding-enabled AIs such as ChatGPT and GitHub's Copilot is accelerating, these coding tools remain challenged with accuracy, security, licensing, and code quality. Therefore, in order to solve this problem, AI-generated code can be compiled in real-time to receive immediate feedback to increase development productivity and improve code quality. This study aims to test the combination of ChatGPT and Roslyn and apply it to real games to verify the practical feasibility of the technology.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.183-188
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• 2024

Recently, CCTV cameras have been installed not only in crowded streets but also in less frequently traveled alleyways. This is because CCTV increases the arrest rate. The arrest rate directly affects the crime rate, as potential criminals tend to avoid areas with high arrest rates. Therefore, this paper collects public data on CCTV installation locations, arrest rates, and crime rates in various regions, stores the collected data using the Hadoop big data system, and refines and processes the data using appropriate tools. Subsequently, R programming is employed to analyze and visualize the relationship between the number of CCTV installations and crime rates. By leveraging big data correlation analysis techniques, this study evaluates the effectiveness of CCTV installations.

• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.161-171
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• 2014

The Computer Education in Korea since 2000 mainly were 'how to use computer tools', Computer education from 2005 to emphasize problem-solving and programming, but did not perform well, and In 2010 it was not compulsory computer training. Thus, our country have training elementary and middle school students for computer education without creating a curriculum content of computer. U.S. and UK educate students computer training to foster future generations the essential core competencies to be recognized as a new educational curriculum. In this study, the basic course in computer studies of Korean is proposed as Information Science. Information science subject from middle school to first grade curriculum is consistently able to study was composed. The subarea of information science curriculum computer systems, software production, the fusion activity. The computer system is composed of 18 subdivisions, software production is composed of 11 subdivisions, and fusion activity was composed of 15 subdivisions. The results of the students' school life and social life in the future core competencies necessary to be available to train.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.785-802
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• 2017

As cyber threats using malicious code continue to increase, many security and vaccine companies are putting a lot of effort into analysis and detection of malicious codes. However, obfuscation techniques that make software analysis more difficult are applied to malicious codes, making it difficult to respond quickly to malicious codes. In particular, commercial obfuscation tools can quickly and easily generate new variants of malicious codes so that malicious code analysts can not respond to them. In order for analysts to quickly analyze the actual malicious behavior of the new variants, reverse obfuscation(=de-obfuscation) is needed to disable obfuscation. In this paper, general analysis methodology is proposed to de-obfuscate the software used by a commercial obfuscation tool, Themida. First, We describe operation principle of Themida by analyzing obfuscated executable file using Themida. Next, We extract original code and data information of executable from obfuscated executable using Pintool, DBI(Dynamic Binary Instrumentation) framework, and explain the implementation results of automated analysis tool which can deobfuscate to original executable using the extracted original code and data information. Finally, We evaluate the performance of our automated analysis tool by comparing the original executable with the de-obfuscated executable.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.859-872
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• 2003

Class hierarchies often constitute the backbone of object-oriented software. Their quality is therefore quite crucial. Building class hierarchies with good qualify is a very important and common tasks on the object oriented software development, but such hierarchies are not so easy to build. Moreover, the class hierarchy structure under construction is frequently restructured and refined until it becomes suitable for the requirement on the iterative and incremental development lifecycle. Therefore, there has been renewal of interest in all methodologies and tools to assist the object oriented developers in this task. In this paper, we define a set of quantitative metrics which provide a wav of capturing features of a rough estimation of complexity of class hierarchy structure. In addition to, we suggest a set of algorithms that transform a original class hierarchy structure into reorganized one based on the proposed metrics for class hierarchy structure. Furthermore, we also prove that each algorithm is "object-preserving". That is, we prove that the set of objects are never changed before and after applying the algorithm on a class hierarchy. The technique presented in this paper can be used as a guidelines of the construction, restructuring and refinement of class hierarchies. Moreover, the proposed set of algorithms based on metrics can be helpful for developers as an useful instrument for the object-oriented software development.velopment.