• Journal of Hydrogen and New Energy
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• v.33 no.1
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• pp.95-104
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• 2022

Micro hydropower is a readily available renewable energy source that can be harvested utilizing hydrokinetic turbines from shallow water canals, irrigation and industrial channel flows, and run-off river stream flows. These sources generally have low head (<1 m) and low velocity which makes it difficult to harvest energy using conventional turbines. A horizontal-axis screw turbine was designed and numerically tested to extract power from such low-head water sources. The 3-bladed screw-type turbine is placed horizontally perpendicular to the incoming flow, partially submerged in a narrow water channel at no-head condition. The turbine hydraulic performances were studied using Computational Fluid Dynamics models. Turbine design parameters such as the shroud diameter, the hub-to-shroud ratios, and the submerged depths were obtained through a steady-state parametric study. The resulting turbine configuration was then tested by solving the unsteady multiphase free-surface equations mimicking an actual open channel flow scenario. The turbine performance in the shallow channel were studied for various Tip Speed Ratios (TSR). The highest power coefficient was obtained at a TSR of 0.3. The turbine was then scaled-up to test its performance on a real site condition at a head of 0.3 m. The highest power coefficient obtained was 0.18. Several losses were observed in the 3-bladed turbine design and to minimize losses, the number of blades were increased to five. The power coefficient improved by 236% for a 5-bladed screw turbine. The fluid losses were minimized by increasing the blade surface area submerged in water. The turbine performance was increased by 74.4% after dipping the turbine to a bottom wall clearance of 30 cm from 60 cm. The final output of the novel horizontal-axis screw turbine showed a 2.83 kW power output at a power coefficient of 0.63. The turbine is expected to produce 18,744 kWh/year of electricity. The design feasibility test of the turbine showed promising results to harvest energy from small hydropower sources.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.499-508
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• 2022

A lot of research has been carried out on the Hangeul generation model using deep learning, and recently, research is being carried out how to minimize the number of characters input to generate one set of Hangul (Few-Shot Learning). In this paper, we propose a CKFont2 model using only 14 letters by analyzing and improving the CKFont (hereafter CKFont1) model using 28 letters. The CKFont2 model improves the performance of the CKFont1 model as a model that generates all Hangul using only 14 characters including 24 components (14 consonants and 10 vowels), where the CKFont1 model generates all Hangul by extracting 51 Hangul components from 28 characters. It uses the minimum number of characters for currently known models. From the basic consonants/vowels of Hangul, 27 components such as 5 double consonants, 11/11 compound consonants/vowels respectively are learned by deep learning and generated, and the generated 27 components are combined with 24 basic consonants/vowels. All Hangul characters are automatically generated from the combined 51 components. The superiority of the performance was verified by comparative analysis with results of the zi2zi, CKFont1, and MX-Font model. It is an efficient and effective model that has a simple structure and saves time and resources, and can be extended to Chinese, Thai, and Japanese.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.489-498
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• 2022

Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

• Korea Trade Review
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• v.41 no.4
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• pp.131-155
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• 2016

Recently, the global trade environment has been composed of transactions in trade through integration of the global supply chain network. As FTAs are being signed between countries, the country of origin (COO) system on products has become an important issue. Companies are procuring raw materials through global sourcing and supplying to the retail markets. This research deducted major factors regarding the verification and utilization of the COO system through research on domestic and international literatures, and verified the mediating effects on the verification and utilization elements of the country image and the brand image of COO on the performance of the COO system through empirical study. For the purpose of this research, we conducted a survey implementing the COO system and analyzed the 152 data collected. The results of this research is as follows: First, the external verification level of the COO system has an impact on the performance of the COO system, and a mediating effect on the country image and the brand image of the COO. Second, the management capability of the COO has an impact on the performance of the COO system, and a mediating effect on the brand image of the COO. A research comparing and analyzing the difference in establishment of the verification system of the COO depending on the size of a corporation is necessary.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.471-485
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• 2023

Recently, due to the nature of blockchain that guarantees users' anonymity, more and more cases are being exploited for crimes such as illegal transactions. However, cryptocurrency is protected in cryptocurrency wallets, making it difficult to recover criminal funds. Therefore, this study acquires artifacts from the data and memory area of a local PC based on user behavior from four browser extension wallets (Metamask, Binance, Phantom, and Kaikas) to track and retrieve cryptocurrencies used in crime, and analyzes how to use them from a digital forensics perspective. As a result of the analysis, the type of wallet and cryptocurrency used by the suspect was confirmed through the API name obtained from the browser's cache data, and the URL and wallet address used for the remittance transaction were obtained. We also identified Client IDs that could identify devices used in cookie data, and confirmed that mnemonic code could be obtained from memory. Additionally, we propose an algorithm to measure the persistence of obtainable mnemonic code and automate acquisition.

• The Korean Journal of Franchise Management
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• v.1 no.1
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• pp.19-42
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• 2010

Since circulation market whole surface opening, traditional market is real condition that is looked away more gradually to consumer as reasons of international retail firms and domestic enterprise firms to enter distribution industry, internet mail order rapid increase by information-oriented society, the pursuit of upgradation and normalization by elevation of income level and consumption pattern change that consideration convenience with young consumers as the central figure. Therefore, the purpose of this study is to analyze stagnation cause of traditional market and problem within a change of new distribution environment, and to develop new approaches for dealing with domestic traditional market relationship prompting competition through activation example analysis of foreign traditional market and domestic traditional market. The result of the study indicated that there are a lot of cases that are begun by a few's merchant with leadership that has been will which is strong in activation in beginning in market's occasion that succeed in activation. In particular, software side such as operational efficiency or marketing expertise strengthening of management is that effect is high relatively than hardware side market activation. Also essential to the settlement of credit transactions using credit cards is important for expanding the effort, for the expansion of credit card merchant credit card advantage and raise awareness among traders about the expected effects is needed. Though these study finding submits plan that create market ecosystem so that many consumers may become place that could visit naturally and create pleasure and convenience, and time, monetary, psychological value of shopping to traditional market, there is sense.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.1-23
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• 2011

The Freedom of Information System has been introduced into the society based on the Fair Trade Transactions Act, which was established by Fair Trade Commission (FTC) on May, 2002. However, the system itself has showed limitations in guaranteeing a reliability and transparency of the disclosure document. Thus, since February, 2008, FTC not only made franchisors to register disclosure documents but also adopted the Disclosure Document Registration System, which forced them to provide registered disclosure documents to franchise applicants and franchisee. Franchisors consider the newly adopted Disclosure Document Registration System a restrictive system. However, considering the recent trend of fast growing franchising industry and the importance of being competitive, franchisors need to utilize the disclosure documents to promote their business and to gain trusts from franchise applicants by providing truthful information. In that way, franchisors will be able to establish a foundation that franchising industry might be successful and reduce the agency fee by cutting out conflicts with franchisees. Thus, this study aims to study the ways of effective preparation of disclosure document and its utilization from a franchisor viewpoint.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.582-583
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.584-585
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.