• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.63-67
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• 2024

Recently, artificial intelligence (AI) workloads encompassing various industries such as smart logistics, FinTech, and entertainment are being executed on the cloud. In this paper, we address the scheduling issues of various AI workloads on a multi-tenant cloud system composed of heterogeneous GPU clusters. Traditional scheduling decreases GPU utilization in such environments, degrading system performance significantly. To resolve these issues, we present a new scheduling approach utilizing genetic algorithm-based optimization techniques, implemented within a process-based event simulation framework. Trace driven simulations with diverse AI workload traces collected from Alibaba's MLaaS cluster demonstrate that the proposed scheduling improves GPU utilization compared to conventional scheduling significantly.

• Korean Journal of Ecology and Environment
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• v.53 no.3
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• pp.275-285
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• 2020

Two specimens presumed to be hybrids of Rhodeus pseudosericeus and R. notatus were collected from the Sangcheon Stream of the Han River, Korea. The body color of natural hybrid individuals was yellowish brown, showing the intermediate characteristics of R. pseudosericeus and R. notatus, but overall, the characteristics of R. notatus were similar. Meristic and morphometric characters, the number of dorsal fin rays, anal fin rays and longitudinal row scales showed a hybrid index (HI) of 0, indicating the characters of R. notatus. The hybrid index of predorsal length (HI=74.6), preanal length (HI=75.3), and preventral length (HI=77.6) were similar to the characters of the R. pseudosericeus. Also four characters were appeared to have intermediate characters between R. pseudosericeus and R. notatus; number of gill rakers (HI=55.3), body depth (HI=67.9), snout length (HI=43.4), and inter orbital width (HI=44.8). The rest of 14 characters deviated between 0 and 100, showing unique characteristics of hybrid individuals. Recombination activating gene 1 (RAG1) analysis, hybrids were identified as natural hybrids due to the overlapping peaks of their parent species. Also, as a result of analysis using the cytochrome b gene (COB), one individual was derived from R. pseudosericeus, while the other was derived from R. notatus.

• Journal of Distribution Science
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• v.16 no.12
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• pp.47-56
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• 2018

Purpose - The potential use of cryptocurrencies in a retail environment proposes a rapid shift from the traditional financial system. Nakamoto(2008) defines Bitcoin as an open source alt-coin based on the blockchain technology. Luther(2016) insists that the new technology will be widely adopted for the digital payment processes. However, the use of Bitcoin is in the real world is still sparse. Despite the growing attention and purported benefits, it is doubtful whether the Bitcoin will be eagerly accepted by ordinary consumers in the mainstream market. To answer this question, this paper develops a causal model that has a dual path to explain the motivation to adopt Bitcoin. According to Glaser, Zimmermann, Haferkorn, Weber, and Siering(2014), Bitcoin is both an asset and a currency at the same time. In summary, the attitude towards Bitcoin may vary depending on whether the fin-tech product is viewed as an asset or as a currency. Based on the arguments, we propose that asset attitude and currency attitude will give influence to consumers' intention to adopt Bitcoin. Research design, data, and methodology - Quantitative data collection is conducted from a Bitcoin SIG(special interest group) working in an internet community. As a result, 192 respondents who know Bitcoin completed the survey. To analyze the causal relations in the research model, PLS-SEM(partial least squares structural equation modeling) method is used. Also, reliability and validity of measures are tested by performing Cronbach's alpha test, Fornell-Larcker test and confirmatory factor test. Results - Our test results show that every hypothesis is supported except the influence of perceived ease of use. In addition, we find that the relationships between constructs are different between the high innovative group and low innovative group. Conclusions - We provide evidence that asset attitude and currency attitude are key antecedents of Bitcoin adoption.

• Knowledge Management Research
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• v.21 no.1
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• pp.61-78
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• 2020

Recently, in the global financial transaction field, global transactions using computer systems and server hubs between foreign exchanges beyond the one-dimensional offline transactions and two-dimensional online transactions have been actively conducted. In the previous research by Lee Hyung-wook and Lee Min-jae (2018), as the globalization has accelerated following the development of digital technology and the expansion of ubiquitous communication network, the role of companies, the attribute of economic value creation and economic structure are being reorganized. It is said that O2O (Online to Offline) transactions are increasing due to the development. As a result, a new financial transaction paradigm is emerging that solves the inconveniences of existing financial services and enhances speed and convenience. Considering the global network trend and the rapidly developing and evolving digital bank environment, the necessity of utilizing the business platform model is emerging. However, despite this necessity, there are very limited cases in which such an attempt has been applied in practice. Accordingly, this study seeks to explore the business platform of the new financial transaction system. Specifically, the case study systematically examines the actual implementation of a unique network connection model with Koscom's global investment bank, which is currently in charge of the domestic financial transaction system, and improves ICT innovation performance and process through this. I would like to suggest a solution. In particular, this study analyzed a variety of business model construction and use cases by pursuing a platform connection with digital banks, which has recently been increasingly in demand. Therefore, this study intends to pursue the original and long-term profitability of the company by utilizing ICT innovation and platform business model, and also analyzes the convenience and excellence of trading for institutional and individual investors using the platform of digital bank. The implications of this study are significant in that it explores and explores the actual cases of ICT innovation and additional digital bank platform-connected business models based on this, and suggests a unique and preemptive business strategy of the company in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.177-185
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• 2016

As the fintech industry is growing at an incredible rate, mobile phones are positioned as the most important tool for financial transaction. However, with a rising number of malware applications, the types of attack and illegal access to mobile device are becoming more diverse and sophisticated. This paper studies the potential keylogger attack by exploiting the Accessibility Service in Android framework. This type of attack allows the malicious individual to use keylogger on the victim's Android mobile phone to steal passwords during mobile financial transaction regardless of security keypad setting. Lastly the paper proposes solutions to counter these types of attack by verifying the accessibility usage and amending the application guideline for accessibility.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.1
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• pp.170-183
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• 2017

The rapid growth of digital consumption has significantly changed the shopping behavior of consumers. The consumption paradigm is changing; subsequently, an omni-channel has been introduced that empowers consumers to interact with firms through a myriad of touch points in multiple channels. This study is to understand the perceptions and behavioral characteristics of consumers in the purchase process (e.g., information search and purchase phase). A qualitative method was adopted for this study and data were collected through semi-structured in-depth interviews with 15 omni-channel consumers. The results of this study were as follows. At the information search stage, consistency was the most important consideration for consumers who also wanted to retain channel-specific benefits. Consumers also searched for differentiated information among distribution channels. At the purchase stage, participants choose a shopping channel according to shopping values. They utilized newly introduced services (e.g., "online purchase, offline pick-up", FinTech) that combine retail channels. Our findings provide significance in managing omni-channel services. First, it is recommended that fashion retailers provide seamlessly integrated experience to consumer and adopt a consumer-centered channel choice strategy. Second, fashion retailers must maintain a constant attitude toward shopping experience to fashion, such as shopping enjoyment and exclusiveness.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.1-13
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• 2017

In this paper, a research model was designed to investigate the factors influencing the intention to use of mobile easy payment services in China. Our research model includes the service factors(instant connectivity, economic and security), social factors(subjective norms and image), the user's individual factors(self-efficacy personal innovativeness and suitability), perceived ease of use, perceived usefulness and intention to use. A survey was conducted to collect the data with users who have had the actual using experience about mobile easy payment services. In this research, the data were collected by online survey, and in final analysis, 439 users' questionnaires were used. The empirical paper proves research hypothesis by using SPSS 22.0 and AMOS 23.0. The results of the study are as follows: the mobile easy payment service factors, social factors and the user's individual factors partially give positive effects to perceived ease of use and perceived usefulness; perceived ease of use gives positive effects to perceived usefulness. In addition, perceived ease of use and perceived usefulness have positive effects to on intention to use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.41-48
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• 2017

Recently, there has been a lot of ongoing research regarding financial transactions and payments due to the emergence of financial technology (FinTech). Payments have been processed through cash and credit cards, and payment methods have been simplified and are more convenient, with mobile payment via mobile cards and mobile phones. This study offers a new mobile payment method by using a mobile phone instead of a card reader or terminal. For payments, authentication is processed with the user's biometrics and a built-in fingerprint scanner, and the payment is processed after receiving an authentication code issued by the authorizing institution to confirm the user's identity. User biometrics and payment information is secured from any kind of malicious hacker by saving it in a Fast Identity Online (FIDO) Trusted Execution Environment (TEE) section in a smartphone. Regarding key security, every key is securely created in the FIDO TEE section, providing secure mobile payment by neutralizing various malicious attacks, including sniffing and the man-in-the middle attack.

• The Journal of Information Systems
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• v.28 no.4
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• pp.333-358
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• 2019

Purpose The study aims to develop a data-based decision model for private bankers when recommending hedge funds to their customers in financial institutions. Design/methodology/approach The independent variables are set in two groups. The independent variables of the first group are aggressive investors, active investors, and risk-neutral type investors. In the second group, variables considered by private bankers include customer propensity to invest, reliability, product subscription experience, professionalism, intimacy, and product understanding. A decision-making variable for a private banker is in recommending a first-rate general private fund composed of foreign and domestic FinTech products. These contain dependent variables that include target return rate(%), fund period (months), safeguard existence, underlying asset, and hedge fund name. Findings Based on the research results, there is a 94.4% accuracy in decision-making when the independent variables (customer rating, reliability, intimacy, product subscription experience, professionalism and product understanding) are used according to the following order of relevant dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on fund period, and step 4 on hedge fund name. Next, a 93.7% accuracy is expected when decision-making uses the following order of dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on underlying asset, and step 4 on fund period. In conclusion, a private banker conducts a decision making stage when recommending hedge funds to their customers. When examining a private banker's recommendations of hedge funds to a customer, independent variables influencing dependent variables are intimacy, product comprehension, and product subscription experience according to a categorical regression model and artificial neural network analysis model.