• Clinics in Shoulder and Elbow
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• v.1 no.2
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• pp.266-277
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• 1998

Forty-nine partial thickness rotator cuff tears underwent arthroscopic debridement or repair, and were followed up for a minimum of two years. Follow-up evaluations of the results were completed using a detailed functional questionnaire which was comprised of a rating of the UCLA shoulder scale and return to the previous sports activity and job. The average age of the 49 study patients was 46.5 years(range, 14 to 67 years). The patients were divided into four groups on the basis of the onset of the patient's symptoms. Thirty-five patients(72%) had partial tearing only on the articular surface, six(12%) on the bursal surface, and eight(16%) on both surfaces. Group I consisted of 21 patients with an average age of 56.7. Partial tearing in group I was attributed to the impingement syndrome. In group II, partial tearing of the rotator cuff was related to the anterior instability of the shoulder. This group included 9 patients with an average age of 27.9. In group III, all of the 8 patients were overhead athletes with an average age of 21.8. In this group, no isolated instances of significant trauma were related to the development of the shoulder pain. In group IV, 11 patients noted that a significant traumatic event preceded the onset of their pain. The average age of the patients was 34.9. Overall, 82% of the patients demonstrated satisfactory results and 18% revealed unsatisfactory results. The worst UCLA score and rate of return to the prior activity was noted in group III. In conclusion, partial thickness rotator cuff tear can be caused by subacromial impingement, instability, repetitive microtrauma, and macrotrauma. Arthroscopic debridement of partial tear of the rotator cuff provides a favorable outcome except in overhead athletes.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.321-331
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• 2022

In this study, we tried to present a method for calculating the amount of regression using a watershed modeling method that can simulate the hydrological mechanism of water balance analysis and agricultural water based on watershed unit. Using the soil water assessment tool (SWAT), a watershed water balance analysis was conducted considering the simulation of paddy fields for the Manbongcheon Standard Basin (97.34 km²), which is a representative agricultural area of the Yeongsan river basin. Before evaluating return flow, the SWAT was calibrated and validated using the daily streamflow observation data at Naju streamflow gauge station (NJ). The coefficient of determination (R²), Nash-Sutcliffe Efficiency (NSE), Root-Mean-Square Error (RMSE) of NJ were 0.73, 0.70, 0.64 mm/day. Based on the calibration results for three years (2015-2017), the quick return flow and the return rate compared to the water supply amount for the irrigation period (April 1 to September 30) were calculated, and the average return flow rate was 53.4%. The proposed method of this study may be used as foundation data to optimal agricultural water supply plan for rational watershed management.

• Journal of Construction Engineering and Project Management
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• v.1 no.3
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• pp.28-37
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• 2011

Domestic construction companies are suffering from financing difficulties in the wake of the economic slump in Korea and abroad. During this economic slump, real estate investment trusts (REITs), facilitators for improving financing and stimulating construction businesses, have increasingly expanded since their introduction in 2001. However, in terms of growth speed and marketing size, Korean REITs are falling behind those of other nations. The purpose of this study is to suggest a method for composing a portfolio using the Markowitz portfolio selection model to stimulate REITs. The main contents are as follows. First, a comparative analysis was conducted of increased REIT profit with the application of the Markowitz model and the average REIT profit rate from July 3, 2007, to July 21, 2008, during the investment analysis periods. The results showed that the total profit rate from the Markowitz model was about 10% higher than the average REIT profit rate. Second, the sensitivity was analyzed according to the portfolio's data-gathering and replacement cycle to measure the optimum cycle and yield. The six-mouth profit data collection period showed about 16% higher profits with the Markowitz model than with the REITs. The two-week portfolio change period resulted in about 11% higher profits with the Markowitz model than with the REITs.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of Industrial Convergence
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• v.19 no.5
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• pp.21-34
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• 2021

The purpose of this study is to find out what the investment efficiency of BW is from an investor's point of view and to suggest an efficient investment plan to investors. The research method is to investigate the coupon interest rate, maturity interest rate, issuance date, right exercise start and end date, maturity date, exercise price, etc. for BW issued from 2014 to July 2021. By connecting them, it was attempted to quantitatively understand the efficiency of investment in BW and the effect of new stock acquisitions. As a result of the study, the ratio of the number of days in excess of the exercise price was 41.3% of the available days for new stocks, so it was analyzed that the investment efficiency of bonds with warrants was not high. The return on the exercise start date was 24.8% on average and the return on the end date was 52.6% on average, showing a positive return on average, so it was derived in line with investor expectations. The number of stocks with negative returns on the exercise start date was 1.47 times higher than the number of stocks with positive returns, and the number of stocks with negative returns on the end date was 1.16 times higher than the number of positive stocks.

• The Journal of Fisheries Business Administration
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• v.25 no.2
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• pp.115-145
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• 1994

The objetives of this study are to find the economic feasibility of the polyculture and to give the economic information of the polyculture for aquaculture fishermen. The polyculture is defined as the rearing of several species together to make more efficient use of the growing space and the total ground environment. The economic feasibility analysis in the polyculture involves the profitability, the productivity, and the risk reduction effect. The results of the economic feasibility analysis in the polyculture are as follows; First, in the profitability analysis, the solid utilization of ground in the polyculture is more profitable than the monoculture. The profitability owing to the plane utilization of the ground in the polyculture is positioned between those of the monoculture of each speices. Second, in the productivity analysis, oyster and sea squirt are diminishing returns to scale. Third, the variation on the average rate of return in the polyculture products is smaller than that of the monoculture. Finally, the result of comparison between the polyculture and the monoculture shows that the polyculture in coastal area is more profitable and more efficient than the monoculture. Most of cultivating species are selective in their diet Thus, stocking different kinds of cultivating species will efficiently utilize space and food It seems that polyculture is more appropriate for those species that live in different ecological niches. We think that the production per unit of ground can be increased, and the fixed cost per unit of output be reduced, so the polyculture is more profitable than the monoculture. Based on the above results, we concludes that the polyculture is economically feasible when profitability and productivity are increased and simultaneously the variation of average rate of return in the polyculture is smaller than that of the monoculture.

• Journal of Aquaculture
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• v.20 no.3
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• pp.194-198
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• 2007

Reproductive traits of Palaemon gravieri such as embryo size, number of embryo (fecundity), incubation period, larval development mode, larval development period, larval survival and larval growth were described and compared to analyze the correlation among those traits. Embryo volume is a primary factor determining other ensuing reproductive features. Egg volume was $0.042mm^3$ in the first developmental stage. Embryo volume in P. gravieri was comparatively small which is indicative of great number of embryo (y = 3.0161x + 0.0185 $R^2$ = 0.74 positive isometric relationship) and relatively long incubation period. Larvae survived from zoea 1 to post-larvae and it took 45 days at $22^{\circ}C$. Survival rate of the larvae was rather great in the early stage and thereafter steadily decreased. Daily growth rate of larvae in P. gravieri at $22^{\circ}C$ was 0.0195 mm on average. They grew steadily as time went by. Incubation period was between 10-14 days at $22^{\circ}C$. Larval development mode was almost complete planktotrophic. PNR (point of no return) appeared to be the third day on average. Survival rate of larvae without feeding declined rapidly between 3 and 4 days. Larval development period and stage frequency were 23-30 days and 11 stages which imply prolonged larval period and high mortality. The pattern of brood production followed fast successive parturial pattern. Most ovigerous female had mature ovary when they performed parturial molt soon after hatching (larval release).

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.346-356
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• 2000

This paper aims to analyse the relationship between R＆D investment and economic growth in Korea. The analysis result shows 38 percent of average economic growth rate(7.1%) of Korea between 1976 and 1998 was achieved by the growth of Total Factor Productivity (TFP), and the R&D investment during the period contributed in achieving the economic growth rate by as much as 9.86 percent. In the process of the estimate, the rate of return of the R&D investment from both government and private was calculated as 47 percent. The relationship between private R&D investment, government R&D investment and the GDP was also investigated, and it was estimated that the private sector invested 2.0 percent of the GDP in R&D during the period, and was found that 1 won of government R&D investment induced 0.202 won of private sector's R&D investment. However, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed in a mathematical form, because of the lack of the data to establish this relationship. However, this paper believe that the time-lag effect in this relationship was included implicitly by using the data of 23 years.

• Journal of Biosystems Engineering
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• v.16 no.2
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• pp.124-132
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• 1991

This study was carried out to obtain the information needed in the development of forward speed control system and the improvement of combine performance. The effects of variety, grain moisture content and forward speed on the combine load characteristics were investigated through experiments. The results of this study are summarized as follows. 1. A data acquisition system was developed to measure the engine speed and the torques and speeds of the threshing cylinder, dean-grain auger and tailings-return auger. The system consisted of transducers, signal conditioner, interface board and microcomputer. The system accuracy is better than ${\pm}2.3%$ full scale. 2. Linear regression equations were obtained for the torque, speed and power requirement of threshing cylinder for different paddy varieties, grain moisture contents and feed rates. 3. The maximum value of relative frequency for threshing cylinder torque decreased as the increase in feed rate and moisture content. The range of torque fluctuation was 1.2~3.7 and 1.2~1.9 times the average and maximum torque, respectively. The maximum value of power spectrum density (PSD) appeared to be about 11 Hz regardless of paddy variety, grain moisture content and feed rate. 4. The speed of tailings return thrower decreased rapidly at below 900rpm, and it fell to near zero about 3 seconds after that time. When the travelling of combine harvester was stopped immediately after sensing the overload, it took about 7 seconds for a full recovery of the no-load speed of tailings return thrower.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.