• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.79-84
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• 2022

The main purpose of the study is to identify the key aspects of legislative support standards in the countries of the European Union in the field of building a system of local self-government. The European Union during the history of its existence has developed a set of standards on which the systems of local self-government of the European Union member states and applicants for this status are built. The complexity and at the same time the importance of legislative regulation of the functioning of this system is evidenced by the fact that the legislation and principles of international law used by the European Union in the field of local self-government are among the "youngest". This is due to the role played by local self-government in the development of a democratic political system, as well as the search for an optimal balance between centralization and decentralization. Thus, the main task of the study is to analyze the legislative support standards in the countries of the European Union in the field of building a system of local self-government. As a result of the study, current trends and prerequisites for the legislative support standards in the countries of the European Union in the field of building a system of local self-government were investigated.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• Analyses & Alternatives
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• v.7 no.1
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• pp.171-200
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• 2023

This research aims to analyze the external activities of local governments in South Korea from the perspective of the developing trends in city diplomacy, contrary to the conventional and narrow concept regarding local government's international exchange and cooperation as a public diplomacy. In detail, this research intends to illustrate the following: first, to differentiate South Korean local governments' growing commitment to international affairs from public diplomacy; second, to highlight the integration of public diplomacy with other forms of diplomacy within the framework of city diplomacy. This research argues that city diplomacy in South Korea has gradually shown the following three trends and characteristics. First, South Korean local governments have recognized the importance of participating in multilateral diplomacy via city networks to find compelling solutions to non-traditional and transnational security threats. They perceive this external activity as an opportunity for policy sharing and problem-solving with foreign partners. Second, local governments in South Korea have been fostering various ways to institutionalize their involvement in foreign affairs and organizations, such as amendments to related laws and the launching of task forces, to pursue so-called sustainable and systematic international exchange and cooperation. Lastly, South Korean local governments have constructed multiple channels and multilevel governance in the form of public-private partnerships to enhance policy expertise and cope with diverse agendas.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.10-16
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• 2023

The ever-increasing amount of data generated by various industries and systems has led to the development of data mining techniques as a means to extract valuable insights and knowledge from such data. The electrical energy industry is no exception, with the large amounts of data generated by SCADA systems. This study focuses on the analysis of historical data recorded in the SCADA database of the Libyan Electricity Company. The database, spanned from January 1st, 2013, to December 31st, 2022, contains records of daily date and hour, energy production, temperature, humidity, wind speed, and energy consumption levels. The data was pre-processed and analyzed using the WEKA tool and the Apriori algorithm, a supervised machine learning technique. The aim of the study was to extract association rules that would assist decision-makers in making informed decisions with greater efficiency and reduced costs. The results obtained from the study were evaluated in terms of accuracy and production time, and the conclusion of the study shows that the results are promising and encouraging for future use in the Libyan Electricity Company. The study highlights the importance of data mining and the benefits of utilizing machine learning technology in decision-making processes.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.49-58
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• 2023

Renewable energy is not a new terminology. One of the fastest growing renewable energies is solar energy. The implementation of solar energy provides several advantages including the reduction of some of the environmental risks of fossil fuel consumption. This research elaborated the importance of the adaption of solar energy by developing a spatial decision support system (SDSS), while the Residential Solar Energy Adoption (RSEA) is an instantiation artifact in the form of an SDSS. As a GIS web-based application, RSEA allows stakeholders (e.g., utility companies, policymakers, service providers homeowners, and researchers) to navigate through locations on a map interactively. The maps highlight locations with high and low solar energy adoption potential that enables decision-makers (e.g., policymakers, solar firms, utility companies, and nonprofit organizations) to make decisions. A combined qualitative and quantitative methodological approach was used to evaluate the application's usability and user experience, and results affirmed the ability of the factors of utility, usefulness, and a positive user experience of the residential solar energy adoption of spatial decision support system (RSEA-SDSS). RSEA-SDSS in improving the decision-making process for potential various stakeholders, in utility, solar installations, policy making, and non-profit renewable energy domains.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.775-785
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• 2023

As processor technology advances, it has accelerated ISA extensions and increased the complexity of micro-architectures, leading to a continued rise in the importance of processor validation techniques. Recently, various fuzzing techniques have been introduced to discover undocumented instructions, and this study highlights the shortcomings of existing undocumented instruction fuzzing techniques and presents our observation on error cases in the latest processors from Intel and AMD. In particular, we analyzes the causes of false positives resulting from the fuzzer incorrectly judging CPU instruction length and proposes the length determination technique based on instruction execution information to improve accuracy.

• The Journal of Information Systems
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• v.32 no.3
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• pp.85-116
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• 2023

Purpose The importance of data as a key resource of the intelligence revolution is being highlighted, among all those phenomena MyData is attracting attention as a key concept by organizations and individuals that eventually leads the data economy. In this regard, this study was started to contribute to the successful settlement and continuous growth of the domestic MyData industry, which has just entered the system. Design/methodology/approach To develop and test all proposed casual relationships within the research model, we used the Value-Attitude-Behavior(VAB) model as a basic framework. A total of 385 copies were used for the final analysis, and for SPSS 25.0, MS-Excel 2016, and AMOS 24.0 to summarize respondent demographic characteristics, measurement model, and structural model. Findings Findings show that all proposed hypotheses were supported with the exception of the moderating effect of organizational information transparency between data controllability and perceived value, and between data controllability and attitude toward MyData service.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.49-56
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• 2023

Computer architecture serves as a link between application requirements and underlying technology capabilities such as technical, mathematical, medical, and business applications' computational and storage demands are constantly increasing. Machine learning these days grown and used in many fields and it performed better than traditional computing in applications that need to be implemented by using mathematical algorithms. A mathematical algorithm requires more extensive and quicker calculations, higher computer architecture specification, and takes longer execution time. Therefore, there is a need to improve the use of computer hardware such as CPU, memory, etc. optimization has a main role to reduce the execution time and improve the utilization of computer recourses. And for the importance of execution time in implementing machine learning supervised module linear regression, in this paper we focus on optimizing machine learning algorithms, for this purpose we write a (Diabetes prediction program) and applying on it a Practical Swarm Optimization (PSO) to reduce the execution time and improve the utilization of computer resources. Finally, a massive improvement in execution time were observed.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.21-29
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• 2023

Recently there has been an increase in interest and competition in sharing economy platforms. The success stories of many companies have spread in this field, such as Uber, but on the other hand, there are many other companies that have failed. We studied and analyzed the factors that affect the user's participation in the sharing economy platforms as an essential part of this system, and how to maintain the consumer's intention of use without compromising consumer satisfaction, as it has become an issue of great importance on the path to the success of the sharing platforms. Relying on the expanded valence framework and expectation confirmation theory as a basis, we constructed hypotheses that influence intention to participate in participatory platforms. Results show that system quality, trust, perceived benefits, and satisfaction are important factors that positively influence intention to continue to participate. This research is expected to help researchers move forward with research related to the future and help business managers understand user insights and integrate them with their business model to help the success, development and expansion of their business in the Kingdom of Saudi Arabia.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.505-513
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• 2024

This study investigates how consumers perceive the collection of behavioral information through 'cookies' on OTT platforms and the impact it has on personalized services. Through SPSS analysis on 120 consumers, which was conducted to examine four hypotheses, correlations were found between awareness of OTT companies' behavioral information collection and online tracking recognition, awareness and willingness to provide cookies, and the extent of confirming behavioral information collection terms during registration and online tracking recognition. The study concludes that consumer knowledge about behavioral information significantly influences the importance and intention to use personalized services, highlighting the need for regulatory measures by both companies and government entities.