• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.377-396
• /
• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.9
• /
• pp.419-430
• /
• 2023

Currently, NFTs have no dominant application except for the proof of ownership for digital content, and it also have small liquidity problem, which makes their price difficult to predict. Real estate usually has very high barriers to investment due to its high pricing. Real estate can be converted into NFTs and also divided into small value fungible tokens (FTs), and it can increase the the volume of the investor community due to more liquidity and better accessibility. In this document, we implement and design a system that allows ordinary users can invest on high priced real estate utilizing Black Litterman (BL) model-based Portfolio investment interface. To this end, we target a set of real estates pegged as collateral and issue NFT for the collateral using blockchain. We use oracle to get the current real estate information and to monitor varying real estate prices. After tokenizing real estate into NFTs, we divide the NFTs into easily accessible price FTs, thereby, we can lower prices and provide large liquidity with price volatility limited. In addition, we also implemented BL based asset portfolio interface for effective portfolio composition for investing in multiple of real estates with small investments. Using BL model, investors can fix the asset portfolio. We implemented the whole system using Solidity smart contracts on Flask web framework with public data portals as oracle interfaces.

• Journal of Food Hygiene and Safety
• /
• v.35 no.3
• /
• pp.271-278
• /
• 2020

Enterotoxigenic Escherichia coli is one of the major causative infectious agents of diarrhea in newborn and post-weaning pigs and leads to a large economic loss worldwide. However, there is limited information on the distribution and characterization of virulence genes in E. coli isolated from diarrheic piglets, which also applies to the current status of pig farms in Korea. To investigate the prevalence and characterization of virulence genes in E. coli related to diarrhea in piglets, the rectal swab samples of diarrheic piglets (aged 2 d to 6 w) were collected from 163 farms between 2013 and 2016. Five to 10 individual swab samples from the same farm were pooled and cultured on MacConkey agar plates, and E. coli were identified using the API 32E system. Three sets of multiplex PCRs were used to detect 13 E. coli virulence genes. As a result, a total of 172 E. coli isolates encoding one or more of the virulence genes were identified. Among them, the prevalence of individual virulence gene was as follows, (1) fimbrial adhesins (43.0%): F4 (16.9%), F5 (4.1%), F6 (1.7%), F18 (21.5%), and F41 (3.5%); (2) toxins (90.1%): LT (19.2%), STa (20.9%), STb (25.6%), Stx2e (15.1%), EAST1 (48.3%); and (3) non-fimbrial adhesin (19.6%): EAE (14.0%), AIDA-1 (11.6%) and PAA (8.7%), respectively. Taken together, various pathotypes and virotypes of E. coli were identified in diarrheic piglets. These results suggest a broad array of virulence genes is associated with coliform diarrhea in piglets in Korea.

• Journal of KIISE:Computing Practices and Letters
• /
• v.12 no.3
• /
• pp.192-207
• /
• 2006

Today, the SSL protocol has been used as core part in various computing environments or security systems. But, the SSL protocol has several problems, because of the rigidity on operating. First, SSL protocol brings considerable burden to the CPU utilization so that performance of the security service in encryption transaction is lowered because it encrypts all data which is transferred between a server and a client. Second, SSL protocol can be vulnerable for cryptanalysis due to the key in fixed algorithm being used. Third, it is difficult to add and use another new cryptography algorithms. Finally. it is difficult for developers to learn use cryptography API(Application Program Interface) for the SSL protocol. Hence, we need to cover these problems, and, at the same time, we need the secure and comfortable method to operate the SSL protocol and to handle the efficient data. In this paper, we propose the SSL component which is designed and implemented using CBD(Component Based Development) concept to satisfy these requirements. The SSL component provides not only data encryption services like the SSL protocol but also convenient APIs for the developer unfamiliar with security. Further, the SSL component can improve the productivity and give reduce development cost. Because the SSL component can be reused. Also, in case of that new algorithms are added or algorithms are changed, it Is compatible and easy to interlock. SSL Component works the SSL protocol service in application layer. First of all, we take out the requirements, and then, we design and implement the SSL Component, confidentiality and integrity component, which support the SSL component, dependently. These all mentioned components are implemented by EJB, it can provide the efficient data handling when data is encrypted/decrypted by choosing the data. Also, it improves the usability by choosing data and mechanism as user intend. In conclusion, as we test and evaluate these component, SSL component is more usable and efficient than existing SSL protocol, because the increase rate of processing time for SSL component is lower that SSL protocol's.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.32 no.3
• /
• pp.154-167
• /
• 2014

The results of this study conducted to identify the substance, regional characteristics or landscaping of Namwon Yonghogugok, which is the only valley of Jiri Mountain, based on Kim Samun's 'Yonghokugok-Gyeongseungannae(龍湖九曲景勝案內)', 'Yongseongji(龍城誌)' and position, meaning of letters carved and projection technique by ArcGIS10.0 on the rocks are as below. The feature landscapes of the canyon of Yonghogugok, which is an incised meander and one of the Eight beautiful scenery of Namwon, ponds, cliffs and rocks generated with metamorphic rocks and granites weathered by rapids torrents. As a result of measuring the GPS coordinates of the letters carved on the rocks, excluding the 3 Gok Hakseoam and the distances based on the origin and destination of the letters carved on the rocks using the API(Application Programming Interface) function of Daum map, the total distance of Yonghogugok was 3.5km and the average distance between the each Gok was 436.5m. It is assumed that Yonghogugok was designated by Sarim(士林) of the Kiho School(畿湖學派) related to Wondong Hyangyak(元洞鄕約) which is the main agent of Yonghojeongsa(龍湖精舍), the forerunner of Yonghoseowon(龍湖書院), between the late Joseon Dynasty and the early Japanese colonial era, in 1927. Its grounds are the existence of Yonghoyeongdang mentioned on 'Yonghojeongsilgi'(龍湖亭實記), records of 'Haeunyugo(荷隱遺稿)', 'Yonghopumje(龍湖品題)' of Bulshindang(佛神堂), 'Yonghojeongsadonggu Gapjachun(龍湖精舍洞口 甲子春)' letters carved on the rocks and 'Yonghogugok-Shipyeong(龍湖九曲十詠)' posted on Mokgandang of Yonghoseowon. Comprehensively considering the numerous poetry society lists carved on the stone wall of Punghodae(風乎臺), the Sixth Gok Yuseondae, its stone mortar, 'Bangjangjeildongcheon(方丈第一洞天)' of Bulshindang and Gyoryongdam(交龍潭), the Yonghoseokmun(龍湖石門) letters carved on the rocks, Yeogungseok adjacent to the First Gok and Fengshui facilities, centered on Yonghoseowon and Yonghojeong, Yonghogugok can be understood as a unique valley culture formed with the thoughts of Confucianism, Buddhism, Taoism and Fengshui. 'Yonghogugok-Gyeongseungannae' provides very useful information to understand the place name, called by locals and landscaping aspects of Yonghogugok in the late Joseon Dynasty. In addition, the meaning of "Nine dragons" and even though 12 chu(湫: pond) of Yonghogugok Yongchudong including Bulyeongchu, Guryongchu, Isuchu, Goieumchu and Daeyachu are mentioned on Yongseongji, a part of them cannot be confirmed now. Various place names and facilities relevant to Guryong adjacent to Yonghogugok are the core of the place identity. In addition, the accurate location identification and the delivery of the landscaping significance of the 12 ponds is expected to provide landscaping attractiveness of Yonghogugok and become very useful contents for landscaping storytelling and a keyword of storyboard.

• Journal of Animal Science and Technology
• /
• v.53 no.1
• /
• pp.29-34
• /
• 2011

Using the materials collected from nine farms in a three-way cross system to produce commercial pigs produced from F1 sows (Landrace $\times$ Large White) $\times$ Duroc, the power of individual discrimination and parentage of the 13 microsatellite (MS) marker set that has been suggested for individual/brand identification (traceability) was empirically tested. Initially, genotypes of the parental population ($F_1$ sows and Duroc), and commercial pigs were determined and the genotype frequency and polymorphic index were estimated using the Cervus 2.0 program. The probability of identity among genotypes of random individuals, that random half sibs and that of full sib individuals, based on the genotypes from 91 $F_1$ sows and Duroc were expected to be $4.94{\times}10^{-34}$, $8.16{\times}10^{-23}$ and $2.01{\times}10^{-08}$, respectively, using the API-CALC version 1.0 program. When commercial pigs were included, the estimates increased to $3.74{\times}10^{-35}$, $5.48{\times}10^{-25}$ and $2.96{\times}10^{-11}$, respectively. For the empirical verification of the estimated powers of individual discrimination and parentage, the parentage test was performed for 452 commercial pigs using PAPA version 2.0, and individuals with the same genotype were investigated using the Cervus version 2.0 program. Parents for all commercial pigs were successfully estimated and no identical individual was identified in the pedigree. Although the individual discriminating power was not fully verified because of the lack of individuals corresponding with the theoretical power, the 100% efficiency of parentage test was clearly confirmed. Therefore, we believe that the 13 MS marker set in conjunction with management record/information for the pig production kept in a farm/brand should be useful in the pork traceability in a brand unit.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.4
• /
• pp.199-209
• /
• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.65-82
• /
• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Animal Science and Technology
• /
• v.48 no.1
• /
• pp.77-90
• /
• 2006

The purpose of this study was to isolate cellulolytic and hemicellulolytic anaerobic bacteria inhabiting from gut of ruminants and investigate their hydrolytic enzyme activities. Extracellular CMCase activities of H-strains isolated from the rumen of a Holstein dairy cow were higher than those of D- and DC- strains from the rumen and large intestine of Korean spotted deer. Most isolated bacteria utilized more efficiently Dehority's artificial medium containing starch, glucose and cellobiose (DAS) than those in Dehority's artificial medium containing cellulose only (DAC). The results of biochemical reactions and sugar fermentation indicated that the isolated bacteria belong to one of bacterial strains of Peptostreptococcus spp., Bifidobacterium spp., Prevotela ruminicola/buccae, Clostridium beijer/butyricum and Streptococcus intermedis which are not highly cellulolytic. Activities of Avicelase, xylanase, β-D-glucosidase, α-L-arabinofuranosidase and β-xylosidase of the isolated anaerobic bacteria in DAS were higher than those in DAC. In conclusion, the results indicated the higher enzyme activities of the isolated strains cultured in DAS medium were mainly caused by their specific carbohydrate utilization for enzyme production and growth rate. The highly cellulolytic bacteria were not isolated in the present experiment. Thus further research is required to investigate characteristics of gut bacteria from Korean spotted deer.

• Journal of KIISE:Software and Applications
• /
• v.37 no.4
• /
• pp.323-339
• /
• 2010

The complexity of embedded systems and the effort to develop them has been rising in proportion with their importance. Also, the heterogeneity of the hardware and software parts in embedded systems makes it more challenging to develop. Errors caused by hardware/software interfaces, especially, account for up to 13 percent of failures with an increasing trend. Therefore, verifying the interface between hardware and software in embedded system is one of the most important research areas. However, current approaches such as co-simulation method and model checking have explicit limitations. In this paper, we propose the synthesizable interface co-verification framework for hardware/software co-design. Firstly, we introduce the separate interface specifications for the heterogeneous components to describe hardware design and software design. Our specifications are expressive enough to describe both. We also provide the transformation rules from the software specification to the hardware specification so that the whole system can be described from the software view. Secondly, we address the solution of verifying the interface of the software and hardware design by adopting and extending existing verification-techniques and extending them. In hardware interface verification, we exploit the model checking technique and provide more efficient verification by closing the hardware design from the assumption of the software behavior which is ensured by software verification step. Lastly, we generate the interface codes such as device APIs, device driver, and device controller from the specification so that verified hardware and software codes can be synthesized without extra efforts.