• Food Science of Animal Resources
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• v.30 no.6
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• pp.975-988
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• 2010

Two experiments were conducted to determine whether water extracts from Artemisia capillaries (A. capillaries) and Camellia sinensis (C. sinensis) could be used as alternatives to antibiotic growth promoters in broiler feed. The experiment 1 was verified their chemical composition, extracts yields, total phenolic compounds concentration, antioxidant activity, antimicrobial activity, and chicken splenocytes proliferation through in vitro test. The extract yields of A. capillaries and C. sinensis were 26.5 and 16.8%, respectively. Total phenolic compounds concentrations of them expressed as gallic acid equivalent were 15.28 and 26.74 mg/mL, respectively. Electron donating abilities of them expressed as $SC_{50}$ showing 50% DPPH radical scavenging were 0.30 and 0.06 mg, respectively. Bacterial inhibitory rates of them against Escherichia coli, Staphylococcus aureus, and Salmonella Typhimurium were ranged from 42.1 to 52.3% and from 21.6 to 33.7%, respectively. And, these extracts increased proliferation of chicken splenocytes. Especially, A. capillaris was more excellent than Echinacea and Concanavalin A known as T-cell stimulator. The experiment 2 was investigated their effects on growth performance, relative organ weight, cecal microflora, blood biochemical parameters, and splenic cytokines mRNA expression in broiler chicks. Four hundred eighty 1-day-old male broiler chicks (Ross 308) were divided in to 4 treatment groups with 4 replicates of 30 birds in each group: NC (control, no antibiotics), PC (avilamycin, 10 ppm; salinomycin, 60 ppm), AC (A. capillaries, 100 ppm), and CS (C. sinensis, 100 ppm); treatments were administered through water supplementation. Final body weight was significantly higher in all treated groups than in NC (p<0.05). Cecal Salmonella numbers were significantly or somewhat decreased in all treated groups than in NC (p<0.05). The relative weights and lengths of the small intestine were more significantly decreased in the PC and AC groups than in the other groups. Cecal Salmonella numbers were significantly or somewhat decreased in all treated groups than in the NC group (p<0.05). The contents of total cholesterol, aspatate aminotransferase, and alanine aminotransferase in blood serum were more significantly decreased in all treated groups than in NC (p<0.05). In conclusion, these results suggested the possibility that these extracts could serve as alternatives for antibiotic growth promoters.

• Journal of the Korean earth science society
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• v.21 no.4
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• pp.437-448
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• 2000

The Middle Carboniferous Gabsan Formation is distributed in the Cheongrim area of southern Yeongwol and the Mt. Gachang area of Chungbuk Province. This study was carried out to investigate the lithological characters and geochemical composition of the limestones and to find out controlling structures of the limestones of the formation. The limestones of the Gabsan Formation are characterized by the light gray to light brown in color and fine and dense textures. The limestone grains are composed of crinoid fragments, small foraminfers, fusulinids, gastropods, ostracods, etc. Due to the recrystallization, some limestones consist of fine crystalline calcites. The chemical analysis of limestones of the formation was conducted to find out the contents of CaO, MgO, Al$_2$O$_3$, Fe$_2$O$_3$ and SiO$_2$. The content of CaO ranges from 49.78-60.63% and the content of MgO ranges from 0.74 to 4.63% The contents of Al$_2$O$_3$ and Fe$_2$O$_3$ are 0.02-0.55% and 0.02${\sim}$0.84% , respectively. The content of SiO$_2$ varies from 1.55 to 4.80%, but some samples contain more than 6.0%. The limestones of the formation can be grouped into two according to the CaO content: One is a group of which CaO content ranges from 49.78 to 56.26% and the other is a group of which CaO content varies from 59.36 to 60.38%. In the first group, the contents of Al$_2$O$_3$, Fe$_2$O$_3$ and SiO$_2$ range very irregularly according to the CaO content. In the second group, the values of MgO, Al$_2$O$_3$, Fe$_2$O$_3$ and SiO$_2$ are nearly same. Detailed structural analysis of mesoscopic structures and microstructures indicates the five phase of deformation in the study area. The first phase of deformation(D$_1$) is characterized by regional scale isoclinal folds, and bedding parallel S$_1$ axial plane foliation which is locally developed in the mudstone and sandstone. Based on the observations of microstructures, S$_1$ foliations appear to be developed by grain preferred orientation accompanying pressure-solution. During second phase of deformation, outcrop scale E-W trending folds with associated foliations and lineations are developed. Microstructural observations indicate that crenulation foliations were formed by pressure-solution, grain boundary sliding and grain rotation. NNW and SSE trending outcrop scale folds, axial plane foliations, crenulation foliations, crenulation lineations, intersection lineations are developed during the third phase of deformation. On the microscale F$_3$ fold, axial plane foliations which are formed by pressure solution are well developed. Fourth phase of deformation is characterized by map scale NNW trending folds. The pre-existing planar and linear structures are reoriented by F$_4$ folds. Fifth phase of deformation developed joints and faults. The distribution pattern of the limestones is mostly controlled by F$_1$ and F$_4$ folds.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.35-52
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• 2019

As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.

• Korean Journal of Heritage: History & Science
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• v.52 no.2
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• pp.142-171
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• 2019

The dragon is an imaginary animal that appears in the legends and myths of the Orient and the West. While dragons have mostly been portrayed as aggressive and as bad omens in the West, in the Orient, as they symbolize the emperor or have an auspicious meaning, dragons signify a positive meaning. In addition, as the dragon symbolizes the emperor and its type has been diversified considering it as a divine object that controls water, people have tried to express it as a figure. The records related to dragons in the Goryeo dynasty appeared with diverse topics in 'History of Goryeo' and are generally contents related to founding myths, rituals for rain, and Shinii (神異), etc. The founding myth emphasizes the legality of the Goryeo dynasty through the dragon, and this influenced the formation of the dragon's descendants. In addition, the ability to control water, which is a characteristic of the dragon, was symbolized as an earth dragon related to the rainmaking ritual, i.e., wishing for rain during times of drought. Since the dragon was the symbol of the royal family, the use of the dragon by common people was strictly restricted. Furthermore, the association of a bronze dragon mirror with the royal family is hard to be excluded. The type and quantity of bronze double dragon mirrors discovered to have existed during the Goryeo dynasty is great, and the production and the distribution of bronze mirrors with double dragons seem to have been more active compared to other bronze mirrors, as bronze mirrors with double dragons produced during Goryeo and bronze mirrors originating in China were mixed. Therefore, in this article, the characteristics of diverse bronze mirrors from the 10th century to the 14th century in China were examined. It seems that the master craftsmen who produced bronze mirrors with double dragons during the Goryeo dynasty were influenced by Chinese composition patterns when making the mirrors. Because there were many cases where a bronze mirror's country of origin could not easily be determined, in order to identify the differences between bronze double dragon mirrors produced during the Goryeo dynasty and bronze mirrors produced in China, meticulous analysis was required. Thus, to ascertain that Goryeo mirrors were not imitations of bronze mirrors with double dragons originating in China but produced independently, the mirrors were examined using the bronze double dragon mirror type classification system existing in our country. Bronze mirrors with double dragons are classified into three types: Type I, which has the style of the Yao dynasty, includes the greatest proportion; however, despite there being only a small quantity for comparison, Types II and III were selected for the analysis of the bronze mirrors with double dragons made in Goryeo because they have unique composition patterns. As mentioned above, distinguishing bronze mirrors made during Goryeo from bronze mirrors made in China is challenging because Goryeo bronze mirrors were made under the influence of China. Among them, since the manufacturing place of the bronze mirrors with double dragons found at the nine-story stone pagoda in Woljeongsa Temple in Pyeongchang is questionable and the composition pattern of the bronze mirror is hard to find on bronze mirrors with double dragons made in China, the manufacturing place of those bronze mirrors were examined. These bronze mirrors with double dragons were considered as bronze mirrors with double dragons made during the Goryeo dynasty adopting the Yao dynasty style composition pattern as aspects of the composition pattern belonged to Type I, and the detailed combination of patterns is hard to find in mirrors produced in China.

• Korean Journal of Heritage: History & Science
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• v.38
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• pp.5-42
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• 2005

Based on a field investigation of intangible cultural asset # 2, author Sir Shin Seok-bong of Daejeon Metropolitan Cityinvestigated the music of Antaek-gut, which is the base and core of Anjoon-gut, and found the following musical features: A Jang-gu(drum) and Kkoaengkwari(gong) were used to recitethe Sutra(kyungmoon) of Anjoon-gut. The Jang-gu, located on the right side, played an accompaniment role with regular beats when the Sutra was recited. The Kkoaengkwari, located on the left side, played the role of covering the caesura of the Sutra passages, so it is played with various rhythmic variations in accordance with Kojang(鼓杖). This is one way of playing Korean national classical music that has temporary caesuras, depending on the rector's bre! ath or the contents of a Sutra during the Sutra chanting, with the Jang-gu covering the pause with its variation. In other words, when being played in concert, the instruments that play the main melody are at rest while another instrument takes its turn to play the main melody as a form of prolonged sound. The rhythmic cycles of the sutras of Antaek-gut recited with this instrumental accompaniment consist of five types; a) Woemarch-jangdan (a single beat) of 4 meter by 3 bit, b) Dumarch-jangdan (two beats) of 8 meter by 3 bit, c) Saemarch-jangdan (three beats) of 4 meter by 3 bit with a fast tempo, d) Mak-gojang, uniform beats with a standardized rhythm, and e) incomplete beats deviated from the regular beats. Sir Shin Seok-bong chanted Chang (唱), a traditional native song which he called 'Cheong (淸)' with a cycle of 'Dumarch-jangdan' throughout the places of Antaek-gut. Only 'Toesonggyung' a chant for the gate that was the last location of the Antaek, was chanted with a cycle of 'Woemarch-jan! gdan'. In addition, 'Saemarch-jangdan' and 'Mak-gojang' that had comparatively faster tempos than the former two jangdans, were played without a chant when a female shaman was dancing and catching her spirit-invoking wand. The 'Saemarch-jangdan', particularly, was played while dancing began at a relatively slow tempo, then proceeded at a violent tempo and then back again to the slow tempo. This shows one of the representative tempos of our music with a slow-fast-slow tempo. The organizational tones were 'mi-la-do'-re'', and its key tones of 'mi-la-do'' were performed with perfect fourth and minor third, which was the same as those of Menari-tori. However, it did not show a typical Sigimse, an ornamental tone, of Menari-tory, whose first tone, 'mi', is vibrated and its Sigimse is gliding down from the tone 're' to 'do'. That is because the regional tone-tori of Chungcheong-do have a relatively weaker musical expression than that of Gyeongsang-do. In addition, the rhythmic types in accordance with the words of a song for the Antaek-gut music had a comparatively faster tempo than the other sutras. Also, it was only with 'Toesonggyeong' that the tone 'la' continuously appeared throughout the melody and showed 'a syllabic rhythm', while other places consisted of either a 'syncopation' or 'melismatic' rhythm. Finally, according to a brief investigation of the tone organization in accordance with each sutra, the tone 'la' was given more weight. The tone procedure showed a mainly ascending 'la-do'' and the descending 'la-mi' with minor third and perfect fourth. Also, the overall tempo proceeded with M.M.♩.=116-184, while the tempo for the Gut proceeded with M.M.♩.=120-140, which was suitable for reciting a Sutra.

• Journal of Applied Biological Chemistry
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• v.57 no.3
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• pp.267-277
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• 2014

Objective of this paper is to assess the available data on the pesticide uses and regulations in the golf courses, and provide the nationwide systematic management options. Numbers of golf courses in Korea are rapidly increasing from 2000s and reached at 421 sites by the end of 2011. Accordingly pesticide usage has been increased with years in direct proportion to the increasing number of golf courses. Amounts of pesticide applied in 2011 were 118,669 kg as of an active ingredient and were in the orders of fungicides (54.9%) > insecticides (24.4%) > herbicides (13.3%) > growth regulators (0.1%). Average pesticide usages in 2011 were 280.9 kg per golf course and $5.4kg\;ha^{-1}$. Frequencies of the residual pesticide detections in green and turf were higher than those in fairway and soil, respectively. Residue of highly toxic pesticides was not detected in golf courses. Ministry of Environment in 2010 has developed the 'golf course pesticide monitoring and management system' which is the advanced online registry for kind and amount of pesticides applied in each golf course. This system is intended for monitoring of the pesticide uses and residual levels and protecting the environmental pollution from pesticides in the golf course. In 2009, management of pesticides in the golf courses became the task of Ministry of Environment, being merged from many federal agency and ministries. The protocol for the site-specific best management practices, on which to base results from the risk assessment, should be set for pesticides in the golf to minimize the environmental impacts.

• Korean Journal of Soil Science and Fertilizer
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• v.12 no.4
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• pp.169-178
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• 1980

Ammonium nitrate explosion technique was applied to seek a convenient method for the establishment of orchard on the undulating to rolling land or hill side of Pogog clay loam soil (Fine Aquic Fragiudalfs : Planosols) having high bulk density and low permeability. Explosions were made by three ammonium nitrate explosives placed in the bottom of 90cm deep auger hole with every 2m interval (Explosion I) and 4m interval (Explosion II) respectively. The effect of the explosion on physical properties of the soil was investigated and compared with the effect induced by manual digging, excavation of $1m{\times}1m$ in diameter and depth (Manual digging I) and trenching of $1m{\times}1m{\times}25m$ in width, depth, and length (Manual digging II) respectively. The results investigated after 7 months from the treatments are summarized as follows : 1. The explosion or manual digging reduced bulk density and hardness, whereas the treatments increased porosity, hydraulic conductivity, and available moisture-holding capacity of the soil. 2. The explosion of 4 m interval improved physical properties of the soil to optimum level up to 70cm of the distance from the explosion core in the range of depth 0-60cm, while in the case of depth from 60 to 100cm the optimum level was achieved only within 50cm radius. 3. When exploded in 2 m interval, the effect in the 0-60cm depth was overlapped between two explosion cores. The effect in the depth between 60 and 100cm, however, was found to be independent of the explosion intervals. 4. The manual digging was only costly and laborious but effective only within the work-up zone. 5. For the soils having bulk density higher than $1.4g/cm^3$ after the treatments, the field capacity determined 72 hours after a heavy rain was lower than the laboratory estimate at the suction of 1/3 atm. 6. The top growth of apple tree for the first year revealed that the explosion seemed better treatment than the manual digging, even though the difference was insignificant.