• Land and Housing Review
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• v.15 no.1
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• pp.99-115
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• 2024

This study aims to investigate Marseille's Euromméditerranée project and provide policy implications for revitalizing domestic urban regeneration projects. First, we identify Euroméditerranée as a pivotal urban regeneration effort, executed by EPAEM-an organization fostering governance-driven project advancement through collaboration and investment from both central and local governments. This endeavor has significantly contributed to revitalizing Marseille, enriching the quality of life for its residents. Second, this urban regeneration project has the following notable features: consolidated approach with combination of full redevelopment and rehabilitation, integrated regeneration covering hardware-like physical regeneration and software-like economic, cultural, and environmental regeneration; government-type urban regeneration project structure. Finally, we suggest that policymakers should consider the economic scale in urban regeneration projects, national-level government organizations, and efficient public-private partnerships.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.209-223
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• 2024

Purpose - This article analyzes the impact of macroeconomic variables of the United States, China, and Korea on KOSPI and VKOSPI, in that United States and China have a great influence on Korea, having an export-driven economy. Design/methodology/approach - The influence of US, China, and Korea interest rates, industrial production index, consumer price index, US employment index, Chinese real estate index, and Korea's foreign exchange reserves on KOSPI and VKOSPI is analyzed on monthly basis from Jan 2012 to Aug 2023, using multifactor model. Findings - The KOSPI showed a positive relationship with the U.S. industrial production index and Korea's foreign exchange reserves, and a negative relationship with the U.S. employment index and Chinese real estate index. The VKOSPI showed a positive relationship with the Chinese consumer price index, and a negative relationship with the U.S. interest rates, and Korean foreign exchange reserves. Next, dividing the analysis into two periods with the Covid crisis and the analysis by country, the impact of US macroeconomic variables on KOSPI was greater than Chinese ones and the impact of Chinese macroeconomic variables on VKOSPI was greater than US ones. The result of the forward predictive failure test confirmed that it was appropriate to divide the period into two periods with economic event, the Covid Crisis. After the Covid crisis, the impact of macroeconomic variables on KOSPI and VKOSPI increased. This reflects the financial market co-movements due to governments' policy coordination and central bank liquidity supply to overcome the crisis in the pandemic situation. Research implications or Originality - This study is meaningful in that it analyzed the effects of macroeconomic variables on KOSPI and VKOSPI simultaneously. In addition, the leverage effect can also be confirmed through the relationship between macroeconomic variables and KOSPI and VKOSPI. This article examined the fundamental changes in the Korean and global financial markets following the shock of Corona by applying this research model before and after Covid crisis.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.7-21
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• 2024

There are various machine learning techniques such as Reinforcement Learning, Deep Learning, Neural Network Learning, and so on. In recent, Large Language Models (LLMs) are popularly used for Generative AI based on Reinforcement Learning. It makes decisions with the most optimal rewards through the fine tuning process in a particular situation. Unfortunately, LLMs can not provide any explanation for how they reach the goal because the training is based on learning of black-box AI. Reinforcement Learning as black-box AI is based on graph-evolving structure for deriving enhanced solution through adjustment by human feedback or reinforced data. In this research, for mutually exclusive decision-making, Mutually Exclusive Learning (MEL) is proposed to provide explanations of the chosen goals that are achieved by a decision on both ends with specified conditions. In MEL, decision-making process is based on the tree-based structure that can provide processes of pruning branches that are used as explanations of how to achieve the goals. The goal can be reached by trade-off among mutually exclusive alternatives according to the specific contextual conditions. Therefore, the tree-based structure is adopted to provide feasible solutions with the explanations based on the pruning branches. The sequence of pruning processes can be used to provide the explanations of the inferences and ways to reach the goals, as Explainable AI (XAI). The learning process is based on the pruning branches according to the multi-dimensional contextual conditions. To deep-dive the search, they are composed of time window to determine the temporal perspective, depth of phases for lookahead and decision criteria to prune branches. The goal depends on the policy of the pruning branches, which can be dynamically changed by configured situation with the specific multi-dimensional contextual conditions at a particular moment. The explanation is represented by the chosen episode among the decision alternatives according to configured situations. In this research, MEL adopts the tree-based learning model to provide explanation for the goal derived with specific conditions. Therefore, as an example of mutually exclusive problems, employment process is proposed to demonstrate the decision-making process of how to reach the goal and explanation by the pruning branches. Finally, further study is discussed to verify the effectiveness of MEL with experiments.

• Journal of Information Science Theory and Practice
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• v.12 no.3
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• pp.14-35
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• 2024

This qualitative study explores cyberbullying among college students through Habermas's Theory of Communicative Action to examine the dissonance between online interactions and principles of rational discourse. Cyberbullying is a pervasive issue in digital communication that undermines logical, evidence-based conversation, fostering environments where misinformation, manipulation, and harm thrive. By analyzing case studies from three universities, the research identifies the characteristics, dynamics, and emotional impacts of cyberbullying on victims, highlighting the role of social media platforms in facilitating these negative interactions. The findings reveal significant challenges to authentic and equal online conversations, driven by power imbalances and a lack of genuine communication, leading to psychological distress, erosion of self-esteem, and changes in behavior among victims. The study underscores the potential of social media design and policy interventions to mitigate cyberbullying, emphasizing the need for educational programs, technological solutions, and community support to promote a safer, more respectful digital environment. Key themes include the dynamics of cyberbullying, the suppression of rational discourse, the psychological and emotional consequences of inauthentic communication, and strategies for resilience and recovery. The research contributes to understanding cyberbullying's complexities and suggests a multifaceted approach to addressing it, aligning with Habermas's ideal of communicative rationality to foster healthier online communities. Future research should further explore the intersection of technology design, user behavior, and regulatory policies to combat cyberbullying effectively.

• Knowledge Management Research
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• v.25 no.3
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• pp.173-200
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• 2024

This study investigates the dynamics of the digital divide and social inclusion in a society increasingly influenced by artificial intelligence (AI) by 2035. Using a 2×2 matrix scenario analysis, the research explores future scenarios based on two axes: the level of AI technological advancement and societal response. The scenarios range from an "Inclusive AI Society," characterized by advanced AI technology and comprehensive societal measures, to an "AI Polarized Society," marked by rapid AI advancement but fragmented social responses, exacerbating inequalities. The study emphasizes the critical role of both technological and social strategies in addressing the challenges of AI-driven societies. It provides policy recommendations to mitigate potential disparities, highlighting the need for inclusive education, equitable access to AI benefits, and adaptive governance frameworks. The findings aim to inform policymakers and stakeholders about the impacts of AI on social inclusion and the digital divide, proposing strategies for fostering a balanced and equitable AI future.

• Wind and Structures
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• v.39 no.4
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• pp.271-285
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• 2024

The multiple-fan wind tunnel is an important facility for reproducing target wind field. Existing control methods for the multiple-fan wind tunnel can generate wind speeds that satisfy the target statistical characteristics of a wind field (e.g., power spectrum). However, the frequency-domain features cannot well represent the nonstationary winds of extreme storms (e.g., downburst). Therefore, this study proposes a multiple-fan wind tunnel control scheme based on Deep Reinforcement Learning (DRL), which will completely transform into a data-driven closed-loop control problem, to reproduce the target wind field in the time domain. Specifically, the control scheme adopts the Deep Deterministic Policy Gradient (DDPG) paradigm in which the strong fitting ability of Deep Neural Networks (DNN) is utilized. It can establish the complex relationship between the target wind speed time series and the current control strategy in the DRL-agent. To address the fluid memory effect of the wind field, this study innovatively designs the system state and control reward to improve the reproduction performance based on historical data. To validate the performance of the model, we established a simplified flow field based on Navier Stokes equations to simulate a two-dimensional numerical multiple-fan wind tunnel environment. Using the strategy of DRL decision maker, we generated a wind speed time series with minor error from the target under low Reynolds number conditions. This is the first time that the AI methods have been used to generate target wind speed time series in a multiple-fan wind tunnel environment. The hyperparameters in the DDPG paradigm are analyzed to identify a set of optimal parameters. With these efforts, the trained DRL-agent can simultaneously reproduce the wind speed time series in multiple positions.

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.122-139
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• 2015

Though the digital transition of terrestrial TV has been completed, the transmission system for terrestrial radio has not been determined and terrestrial radio still keeps its analog transmission. This study, under coorientation model, aims to explore the cognitive difference in recognizing important factors to be considered in deciding the digital radio transmission system between the employees of terrestrial broadcasters and then crucial issues related to the factors are driven. It has been found that the most big cognitive difference among the employees of three major terrestrial broadcasters lies in selecting frequency band for digital radio transmission. But there was little difference of opinion on simultaneous production-transmission, efficiency of frequency usage, broadcast quality and standards of service. The most disputable point in transition to digital radio broadcasting is selecting the frequency band for digital radio between the frequency bands used for FM radio broadcast (88-108MHz), terrestrial DMB (VHF Ch7~13) and FM radio adjacent broadcast band (76~88MHz: VHF Ch5~6). So, the question concludes into the selection issue between DAB+, HD-Radio, and DRM+. To improve the quality of radio broadcasting service and enhance the satisfaction of listeners, it is desirable to allow to operate both production system and transmission station, to enhance high transmission efficiency with minimum transmission facility, and to permit new entrance of broadcasters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1329-1338
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• 2015

This article aims to develop model for the right policy Tools available from the cause analysis regarding the regional differences of subway modal split in Seoul metropolitan area. This allows two major factors of the most influential subway modal split to be proved and Portfolio Analysis is conducted. The results are as follows. Firstly, the two primary factors affecting subway modal split were shown as subway adjacent area and local line bus. It signifies that expansion of subway adjacent area, establishing the number of the subway stations and increase of local line bus are required in order to improve a diminishing subway modal split. Following that, pattern of the improvement to strengthen better subway connections are classified according to the two areas which are Concentration Area of Improvement in Subway Station Area (CAISSA) and Concentration Area of Improvement in Local Bus (CAILB). Our study revealed that Ganbukgu, Seodaemungu, Geumcheongu, and Gwanakgu were selected as the area of CAILB and Songpagu, and Junggu were selected as the area of CAISSA. As all things are considered, transportation policy makers should be taken into account in the two main factors driven by our study according to types in order to enhance the future subway share proportion.

• KDI Journal of Economic Policy
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• v.14 no.3
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• pp.97-124
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• 1992

The recent sharp increase in wages has driven many Korean manufacturing firms to move into technology-intensive fields. The task of industrial restructuring is, however, rather difficult for small and medium-sized enterprises (hereafter, "SMEs") which suffer from limited R&D resources. If the R&D activities of SMEs are left unattended, industrial restructuring process may be retarded. Hence, the government-sponsored programs can be justified when used to promote the technological level of SMEs. Because of the limited internal R&D resources of SMEs, in particular human resources, the government-sponsored programs that depend on financial subsidies to stimulate the R&D activities of SMEs may not be recommended. Rather, a more desirable policy is programs to subsidize outside sourcing of SMEs. Basic principles of the program are; (i) that the government should establish R&D laboratories which are specialized in joint researches with SMEs in each industry; (ii) research projects of the laboratories should be funded by SMEs; the government's support covers only fixed costs such as construction costs in order to avoid moral hazard problem. (iii) technology adviser programs sponsored by the government should be improved; geographical distribution is to be expanded and the activities are to be monitored by local governments. Also foreign networks need be strengthened.

• Korean Journal of Construction Engineering and Management
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• v.6 no.3 s.25
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• pp.144-155
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• 2005

Since 1950s, the Korean housing market has continually experienced the chronicle lack of housing stock because of lower housing investment in comparison with a population explosion, prompt urbanization and rapid restructuring of family. The Korean housing market have thus been driven not by the pricing model by housing demand-supply chain but by the Korean housing policies focusing on the increase of housing supply and the living stability of the middle or low-income bracket. After all, repetitive economic vicious circle of housing price and the increase of unsold apartments aggravated the malfunction of the Korean housing market. Meanwhile, the Korean construction firms have exacerbated their profitability. Such terrible situations are mainly triggered by the Korean construction firms that weighed on the short-term profits and quick response of the government policy alterations rather than the prospect of housing market Therefore, this research focusing on the dynamics of housing market identified and classified the demand and supply elements that consist not only of housing system structures but also of the environmental elements that affect the structures. Based on the system thinking and traditional theory of consumer's choice, the interactions of these elements were constructed as a causal loop diagram that explains the mutual influences among housing subsystems with feedback loops. This paper describes and discusses about the causes of the dynamic changes in the Korean housing market. This study would help housing suppliers, including housing developers, construction firms, etc., to form a more comprehensive understanding on the fundamental issues that constitute the Korean housing market and thereby increasing their long term as well as minimizing the risk involved in the housing supply businesses.