• Journal of Korean Society of Forest Science
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• v.9 no.1
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• pp.1-44
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• 1969

The important results which have been obtained in the investigation can be recapitulated as follows. 1. As demostrated by the experimental results and analyses concerning their effects in the on-ground type mushroom house, the constructions in relation to the side wall and ceiling of the experimental houses showed a sufficient heat insulation on effect to protect insides of the houses from outside climatic conditions. 2. As the effect on the solar type experimental mushroom house which was constructed in a half basement has been shown by the experimental results and analyses, it has been proved to be effective for making use of solar heat. However there were found two problems to be improved for putting solar houses to practical use in the farm mushroom growing: (1) the construction of the roof and ceiling should be the same as for the on-ground type house, and (2) the solar heat generating system should be reconstructed properly. A trial solar heat generating system is shown in Fig. 40. 3. Among several ventilation systems which have been studied in the experiments, the underground earthen pipe and ceiling ventilation, and vertical side wall and ceiling ventilation systems have been proved to be most effective for natural ventilation. 4. The experimental results have shown that ventilation systems such as the vertical side wall and underground ventilation systems are suitable to put to practical use as natural ventilation systems for farm mushroom houses. These ventilation systems can remarkably improve the temperature of fresh air which is introduced into the house by heat transfers within the ventilation passages, so as to approach to the desired temperature of the house without any cooling or heating operation. For example, if it is assuming that x is the outside temperature and y is the amount of temperature adjustment made by the influence of the ventilation system, the relationships that exist between x and y can be expressed by the following regression lines. Underground iron pipe ventilation system ${\cdots}{\cdots}$ y=0.9x-12.8 Underground earthen pipe ventilation system ${\cdots}{\cdots}$y=0.96x-15.11 Vertical side wall ventilation system${\cdots}{\cdots}$ y=0.94x-17.57 5. The experimental results have shown that the relationships existing between the admitted and expelled air and the $Co_2$ concentration can be described with experimental regression lines or an exponent equation as follows: 1) If it is assumed that x is an air speed cm/sec. and y is an expelled air speed in cm/sec. in a natural ventilation system, since the y is a function of the x, the relationships that exist between x and y can be expressed by the regression lines shown below: 2) If it is assumed that x is an admitted volume of air in $m^3/hr$ and y is an expelled volume of air in $m^3/hr$ in a natural ventilation system, since the y is a function of the x, the relationships that exist between x and y can be expressed by the regression lines shown below. 3) If it is assumed that the expelled air speed in cm/sec and replacement air speed in cm/sec. at the bed surface in a natural ventilation system are shown as x and y, respectively, since the y is a function of the x, the relationships that exist between x and y can be expressed by the following regression line: G.E. (100%)- C.V. (50%) ventilation system${\cdots}$ y=0.54X+0.84 4) If it is assumed that the replacement air speed in cm/sec. at the bed surface is shown as x, and $CO_2$ concentration which is expressed by multiplying 1000 times the actual value of $CO_2$ % is shown as y, in a natural ventilation system, since the y is a function of the x the relationships that exist between x and y can be expressed by the following regression line: G.E. (100%)- C.V. (50%) ventilation system${\cdots}{\cdots}$ y=114.53-6.42x 5) If it is assumed that the expelled volume of air is shown as x and the $CO_2$ concentration which is expressed by multiplying 1000 times the actual of $CO_2$ % is shown as y in a natural ventilation system, since the y is a function of of the x, the relationships that exist between x and y can be expressed by the following exponent equation: G.E. (100%)-C.V. (50%) ventilation system${\cdots}{\cdots}$ $$y=127.18{\times}1.0093^{-X}$$ 6. The experimental results have shown that the ratios of the crass sectional area of the G.E. and C.V. vent to the total cubic capacity of the house, required for providing an adequate amount of air in a natural ventilation system, can be estimated as follows: G.E. (admitting vent of the underground ventilation)${\cdots}{\cdots}$ 0.30-0.5% (controllable) C.V. (expelling vent of the ceiling ventilation)${\cdots}{\cdots}$ 0.8-1.0% (controllable) 7. Among several heating devices which were studied in the experiments, the hot-water boilor which was modified to be fitted both as hot-water toiler and as a pressureless steam-water was found most suitable for farm mushroom growing.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.319-326
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• 2015

Recently in the fields o f stochastic optimal control ( SOC) and reinforcemnet l earning (RL), there have been a great deal of research efforts for the problem of finding data-based sub-optimal control policies. The conventional theory for finding optimal controllers via the value-function-based dynamic programming was established for solving the stochastic optimal control problems with solid theoretical background. However, they can be successfully applied only to extremely simple cases. Hence, the data-based modern approach, which tries to find sub-optimal solutions utilizing relevant data such as the state-transition and reward signals instead of rigorous mathematical analyses, is particularly attractive to practical applications. In this paper, we consider a couple of methods combining the modern SOC strategies and approximate inference together with machine-learning-based data treatment methods. Also, we apply the resultant methods to a variety of application domains including financial engineering, and observe their performance.

• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.159-174
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• 2013

This paper mainly deals with the appropriation of ship voyage allocation, using a heuristic regression model, in order to reduce total costs incurred in port, yard and at sea under the specific port condition. Because of different behavior of costs incurred in port, yard and at sea, an effort to minimize these costs by adjusting the number of voyages for three ship classes(50,000, 100,000, and 150,000-ton) should be made. For instance, if the port managers attempt to reduce the sea transport cost by increasing the annual allocated number of ship voyages classed 150,000-ton for economies of scale, they have no choice but to suffer a significant increase in queueing cost due to port congestion. To put it differently, there are trade-off relationships among the costs incurred in port, yard, and at sea. We utilized a computer simulation result to perform a couple of regression analyses in order to figure out the appropriate range of allocated number of voyages of each ship class using a heuristic approach. The detailed analytical results will be shown at the main paper. We also suggested a net present value(NPV) model to make a proper investment decision for an additional berth of 200,000-ton class that alleviates port congestion and reduces transport cost incurred both in port and at sea.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.1
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• pp.51-62
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• 2009

This study was carried out development a new composting system to lower copper and zinc concentration in plg sludge compost and conduct an inquiry into the possibility of crop cultivation. The concentrations of nitrogen, phosphorus and pH averaged 4.4%, 6.3% and 7.57, respectively, which were higher concentrations than in commercial organic fertilizers, and the concentrations of copper and zinc averaged 805 and 1,704 mg/kg, respectively, which were beyond the heavy metal concentration limit in byproduct compost. Hydrated citric acid I lowered the concentrations of copper and zinc by 58% and 97%, respectively and hydrated oxalic acid II lowered the concentrations of copper and zinc by 48% and 56%, respectively in pig sludge compost. Lower concentrations of copper and zinc in pig sludge resulted from the enhanced hydrated-citric acid concentration in organic acid solution mixed with distilled water. The concentrations of copper and zinc were 330, and 41 mg/kg in the pig sludge treated with 100% hydrated citric acid. Agitation composting system stabilized the compost earlier than the stationary composting system, in which the stabilization condition was confirmed by higher temperature by $4^{\circ}C$ at highest temperature and 7 days earlier cooling down after highest temperature. The levels of germination index (G.I) 80 were obtained 15 and 20 days after composting in agitation and stationary composting system, respectively. The concentrations of copper and zinc were 2.4 and 4.26 mg/kg respectively in soils amended with pig sludge compost after removing process of heavy metals by citric acid, but 8.0 and 22.37 mg/kg, respectively in soils amended with Pig Sludge. The concentrations of heavy metals was highest in com cultivated in soils amended with pig sludge. The copper and zinc concentrations In corn leaves were 75.2 and 50.56 mg/kg respectively, which were 4 and 2 fold higher than the com cultivated in soils amended with pig sludge compost after heavy metal removing process by hydrated citric acid.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2575-2583
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• 1998

The productionof the highly relible softwae systems and theirs performance evaluation hae become important interests in the software industry. The software evaluation has been mainly carried out in ternns of both reliability and performance of software system. Software reliability is the probability that no software error occurs for a fixed time interval during software testing phase. These theoretical software reliability models are sometimes unsuitable for the practical testing phase in which a software error at a certain testing stage occurs by causes of the imperfect debugging, abnornal software correction, and so on. Such a certatin software testing stage needs to be considered as an outlying stage. And we can assume that the software reliability does not improve by means of muisance factor in this outlying testing stage. In this paper, we discuss Bavesian software reliability growth modeling and estimation procedure in the presence of an imidentitied outlying software testing stage by the modification of Jehnski Moranda. Also we derive the Bayes estimaters of the software reliability panmeters by the assumption of prior information under the squared error los function. In addition, we evaluate the proposed software reliability growth model with an unidentified outlying stage in an exchangeable model according to the values of nuisance paramether using the accuracy, bias, trend, noise metries as the quantilative evaluation criteria through the compater simulation.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.