• Korean Journal of Soil Science and Fertilizer
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• v.5 no.2
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• pp.1-38
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• 1972

This study, designed to establish a classification system of paddy soils and suitability groups on productivity and management of paddy land based on soil characteristics, has been made for the paddy soils on the Gimje-Mangyeong plains. The morphological, physical and chemical properties of the 15 paddy soil series found on these plains are briefly as follows: Ten soil series (Baeggu, Bongnam, Buyong, Gimje, Gongdeog, Honam, Jeonbug, Jisan, Mangyeong and Suam) have a B horizon (cambic B), two soil series (Geugrag and Hwadong) have a Bt horizon (argillic B), and three soil series (Gwanghwal, Hwagye and Sindab) have no B or Bt horizons. Uniquely, both the Bongnam and Gongdeog series contain a muck layer in the lower part of subsoil. Four soil series (Baeggu, Gongdeog, Gwanghwal and Sindab) generally are bluish gray and dark gray, and eight soil series (Bongnam, Buyong, Gimje, Honam, Jeonbug, Jisan, Mangyeong and Suam) are either gray or grayish brown. Three soil series (Geugrag, Hwadong and Hwagye), however, are partially gleyed in the surface and subsurface, but have a yellowish brown to brown subsoil or substrata. Seven soil series (Bongnam, Buyong, Geugrag, Gimje, Gongdeog, Honam and Hwadong) are of fine clayey texture, three soil series (Baeggu, Jeonbug and Jisan) belong to fine loamy and fine silty, three soil series (Gwanghwal, Mangyeong and Suam) to coarse loamy and coarse silty, and two soil series (Hwagye and Sindab) to sandy and sandy skeletal texture classes. The carbon content of the surface soil ranges from 0.29 to 2.18 percent, mostly 1.0 to 2.0 percent. The total nitrogen content of the surface soil ranges from 0.03 to 0.25 percent, showing a tendency to decrease irregularly with depth. The C/N ratio in the surface soil ranges from 4.6 to 15.5, dominantly from 8 to 10. The C/N ratio in the subsoil and substrata, however, has a wide range from 3.0 to 20.25. The soil reaction ranges from 4.5 to 8.0. All soil series except the Gwanghwal and Mangyeong series belong to the acid reaction class. The cation exchange cpacity in the surface soil ranges from 5 to 13 milliequivalents per 100 grams of soil, and in all the subsoil and substrata except those of a sandy texture, from 10 to 20 milliequivalents per 100 grams of soil. The base saturation of the soil series except Baeggu and Gongdeog is more than 60 percent. The active iron content of the surface soil ranges from 0.45 to 1.81 ppm, easily-reduceable manganese from 15 to 148 ppm, and available silica from 36 to 366 ppm. The iron and manganese are generally accumulated in a similar position (10 to 70cm. depth), and silica occurs in the same horizon with that of iron and manganese, or in the deeper horizons in the soil profile. The properties of each soil series extending from the sea shore towards the continental plains change with distance and they are related with distance (x) as follows: y(surface soil, clay content) = $$-0.2491x^2+6.0388x-1.1251$$ y(subsoil or subsurface soil, clay content) = $$-0.31646x^2+7.84818x-2.50008$$ y(surface soil, organic carbon content) = $$-0.0089x^2+0.2192x+0.1366$$ y(subsoil or subsurface soil, pH) = $$-0.0178x^2-0.04534x+8.3531$$ Soil profile development, soil color, depositional and organic layers, soil texture and soil reaction etc. are thought to be the major items that should be considered in a paddy soil classification. It was found that most of the soils belonging to the moderately well, somewhat poorly and poorly drained fine and medium textured soils and moderately deep fine textured soils over coarse materials, produce higher paddy yields in excess of 3,750 kg/ha. and most of the soils belonging to the coarse textured soils, well drained fine textured soils, moderately deep medium textured soils over coarse materials and saline soils, produce yields less than 3,750kg/ha. Soil texture of the profile, available soil depth, salinity and gleying of the surface and subsurface soils etc. seem to be the major factors determining rice yields, and these factors are considered when establishing suitability groups for paddy land. The great group, group, subgroup, family and series are proposed for the classification categories of paddy soils. The soil series is the basic category of the classification. The argillic horizon (Bt horizon) and cambic horizon (B horizon) are proposed as two diagnostic horizons of great group level for the determination of the morphological properties of soils in the classification. The specific soil characteristics considered in the group and subgroup levels are soil color of the profile (bluish gray, gray or yellowish brown), salinity (salic), depositonal (fluvic) and muck layers (mucky), and gleying of surface and subsurface soils (gleyic). The family levels are classified on the basis of soil reaction, soil texture and gravel content of the profile. The definitions are given on each classification category, diagnostic horizons and specific soil characteristics respectively. The soils on these plains are classified in eight subgroups and examined under the existing classification system. Further, the suitability group, can be divided into two major categories, suitability class and subclass. The soils within a suitability class are similar in potential productivity and limitation on use and management. Class 1 through 4 are distinguished from each other by combination of soil characteristics. Subclasses are divided from classes that have the same kind of dominant limitations such as slope(e), wettness(w), sandy(s), gravels(g), salinity(t) and non-gleying of the surface and subsurface soils(n). The above suitability classes and subclasses are examined, and the definitions are given. Seven subclasses are found on these plains for paddy soils. The classification and suitability group of 15 paddy soil series on the Gimje-Mangyeong plains may now be tabulated as follows.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of architectural history
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• v.14 no.1 s.41
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• pp.89-105
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• 2005

The central aim of this thesis is to see if the structure of Palsangjeon(捌相殿) in Pubjoo Temple(法住寺), a five sto wooden pagoda in Chosen(朝鮮) Dynasty, was handed down from the ancient and middle ages. This study was performed through an analysis of Gilt-Bronze Pagoda built in Koryo(高麗) period. In other words, it is aimed at analyzing which lineage the structure of Palsangjeonbelongs to as a wooden pagoda. In analyzing the structure of Palsangjeon, I attempted to find out its source from the remains of Koryo period prior to the Chosen Dynasty. Examples are the Gilt-Bronze Pagoda, built during the Koryo period. I have also examined its relationship with other existing wooden pagodas and remains. The analysis of Palsangjeon, a five story wooden pagoda in Chosen Dynasty, focuses on the following: First, I explored the possibilities of whether the structure of Palsangjeon was newly invented in Chosen Dynasty, or if it had been derived from the wooden pagodas in the Koryo period. Secondly, I tried to find out if the stable vertical planes, with a great successive diminution ratio, were derived from the middle age, i.e. Koryo period. The results of the study of Palsangjeon through Gilt-Bronze Pagoda analysis are as follows: 1. The structure of Gilt-Bronze Pagoda, a wooden pagoda from the Koryo period, is roughly classified into the accumulation type, using pipe pillars, and the one story type using whole pillars. In the accumulation type, stories are connected in either a flat format or an intervening format. The Gilt-Bronze Pagoda is mainly composed of pipe pillars, with some whole pillars. However, the central pillar was omitted in the building structure. Generally, the upper and lower stories are connected by pipe pillars in a crutch format. All the pillars, whether they are pipe pillars or whole pillars, used Naiten(內轉) technology. The Eave supporter has the Haang type(下昻) and the Muhaang type(無下昻). In most cases, high balustrades are furnished, but few tables of high balustrades have been found. The slanting roof formats have been handed down from Paekche(百濟), Silla(新羅), or Koryo(高麗). However, the structure of the octagon is assumed to be derived from Koguryo(高句麗). The structure of the Gilt-Bronze Pagoda from the Koryo period is mainly composed of accumulated flat squares, with some spire types. intervening format, the structure of Palsangjeon used whole pillars in a half story format in which upper level side pillars are installed on the lower level tie beam. From the Bronze Pagoda from the Koryo period, we can assume that the half story format of wooden pagodas that has stable vertical planes with a great successive diminution ratio was created during the mid-Koryo period at the latest and had been idly developed by the time of the Chosen Dynasty. 3. The whole pillars in Palsangjeon are also found in Gilt-Bronze Pagodas from the Koryo period. Hence, all of the pillars in Palsangjeon seem to have been handed down from the ancient construction technology. They were also used in the construction of wooden pagodas from the Koryo period. Therefore, it is assumed that Palsangjeon was constructed using the construction technology of the Chosen Dynasty that had been developed from the wooden pagoda construction technology of the Koryo period. The stable vertical planes with a great successive diminution ratio in Palsangjeon are derived from ancient Korean wooden pagodas, which have developed into indigenous Korean wooden pagodas with fairly stable vertical planes and a great design, in the half story format of Koryo and Chosen Dynasty. Therefore, it is assumed that the structure of Palsangjeon has a systematic relationship with traditional Korean wooden pagodas and is one of the indigenous Korean wooden pagoda structures. 4. In China, the intervening format has been mainly used between stories in multi-story architecture since the ancient days. At the same time, the flat format as also used in ancient and middle ages. However, the flat format was replaced by whole pillars during the Ming(明) and Manchu(淸) Dynasties, in favor of simple and compact construction. The half-story format, in which upper level side pillars are installed on tie beams, has been found in some cases, but it doesn't seem to have been the primary construction technology. Few traces of the half-story format have been found in multi-story architecture in Japan, and it has not been used as a general construction format. By contrast, the half-story format, which seems to have been derived from the Koryo period, was used as a general construction format in multi-story architecture of the Chosen Dynasty. The construction technology of multi-story architecture is related to that of multi-story wooden pagodas, but they have different production technologies. It seems that the structure of Palsangjeon did not just adopt the construction technology of multi-story architecture in the Chosen Dynasty, but it was developed from wooden pagodas in the Koryo period, including the Gilt-Bronze Pagoda. 5. Since the ancient days, most Chinese and Japanese wooden pagodas have adopted an accumulation type of structure using pipe pillars, with accumulated pointed towers. On the other hand, though most Korean wooden pagodas have also adopted an accumulation type of structure from the ancientdays, one story type using whole pillars was created in the Koryo and Chosen Dynasties. The wooden pagoda structure of Palsangjeon, with stable vertical planes in a half story format, is a unique Korean construction technology, different from the construction technologies of Chinese and Japanese wooden pagodas. This thesis clearly determined the structural characteristics of Palsangjeon. However, various remains have yet to be analyzed in depth, to establish an accurate construction technology system. In the beginning of this thesis, I had difficulty in precisely interpreting the internal structure of the Gilt-Bronze Pagoda from its appearance. However, in the process of study, the more serious problem was that there are few remains or ruins of multi-story architecture in ancient and the middle ages of Korea. Therefore, it is urgent to discover various remains in the future. This thesis succeeded in determining the structural characteristics of Palsangjeon. However, it fell short of clarifying the structural lineage of the stable vertical planes, although they show indigenous Korean architectural taste, representing the unique national emotion, and the construction format of multi-story wooden pagodas in Korea. I hope this is clarified in the future research.

• Journal of Korean Society of Archives and Records Management
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• v.1 no.1
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• pp.201-230
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• 2001

Conserving the recored cultural inheritance is actually the duty of all of us. Above all, the management and conservation of archives and documents is up to archivists who have technical knowledge about archival science. Archivists have to not only conserve archives and documents but also carry out classifying and appraising them in order to define them as current historic ones. The fundamental education about archival science is made up of history and law. Because Archive is the organisation which manage archives and documents produced by legal and administrative actions. Although there are still arguments about technical knowledge and degree archivists have to acquire, most of them prefer the studies related with history and emphasize legal studies to be the general boundary of archivits' ideology and trust. The training course about conservation of archives is conducted in about 9 National Archives of Torino, Milano, Venezia, Genova, Bologna, Parma, Roma, Napoli, Palermo. The training course in 19th was mostly based on the lectures of Phaleography, Diplomatics. There were not the education about archival science yet. Toward the end of 19th and 20th, people stressed the most basic subject in the training course of National Archive was not Phaleography and Diplomatics but archival science. The goal of archival science is to study the institution and organisation transferring archives and documents to Archive. And also it help archivists not wander about with ignorance of organisational and original procedures and divisions but know exactly theirs works. Like this, the studies on institution and organisation have got in the saddle as a branch of archival science since a few ten years. While archival science didn't evoke sympathy among people and experienced the tedious and difficult path in italy and other countries, Archive was managed by experts of other branches. As a result, there were a lot of faults in Archival Science. Specializing training course for Italian archivists came into being under the backdrop of Social Science Institute of Roma National University in 1925. The archival course of universities accomplished by the studies of history, law and economy. And such as Eugenio Casanova and Giorgio Cencetti were devoted archival science was abled to settle down in national archive. The training course for experts of 'archival science, 'Phaleography and Diplomatics' in National Archive of Bologna(Archivio di Stato di Bologna) is one of courses conducted in 17 National Archives in italy. This course is gratuitous and made up of 8 subjects(Archivistica, Paleografia, Diplomatica, Storia dell' Archivio, Notariato e documenti privati, istituzione medievale, istituzione moderna, istituzione contemporanea) students have to complete for two years. Students can receive the degree through passing twice written exam and once oral test. After department of Culture and education finally puts the marks of students, the chief Nationa Archive of Bologna confer the degree of 'archival science Phaleography and Diplomatics' on students passing the exams. This degree authenticates trainees' qualification which enables him to work at the archive in province, district and administrative capital city and archive of comunity and so on. Italian training course naturally leads archivists to keep in contact with valuable cultural inheritance through training in Archive. And it shows the intention to strengthen the affinity with each documents in the spot of archival management before training archivists. Also this is appraised as one of positive policies to conserve the local cultual inheritante in connection with the original qualitity of national archive with testify the history of each region. Traning course for archivist in Italy shows us the way how we have to prepare and proceed it. First, from producing documents to conserving than forever there has introduced 'original order that is to say a general rule to respect the first order given at the time producing documents'. Management of administrative documents is related consistently with one of historical documents. Second, the traning course for archivist is managing around 17 national archives. because italian national archive lay stress not or rducation of theory bus on train for archivest working in the first time of archival science. Third, diplomatics and phaleography for studies about historical document support archives. Forth, the studies on history id proceeding by cooperation between archivist and historian around archive. How our duties is non continuinf disputer who has to conserve and manage document and archives, but traing experts who having ability, vision and flexible thought, responsibility about archivals.

• Korean journal of applied entomology
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• v.16 no.3 s.32
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• pp.171-179
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• 1977

Since the outbreak of the brown planthopper (Nilaparvata lugens) in 1915 caused tremendous losses in rice production, one of the more effective method of prevention of such a disaster could be the establishment of longterm forecasting system, In 1916 the author indicated there was a correlation between sunspot activities and brown planthopper and the white back planthopper outbreaks. However, the examples seem to be too small size to state a definite correlation. The purpose of the present study IS to revi~w the history of the brown planthopper outbreaks, and to establish a more effective forcasting system. The present forcasting methods are based on light trap catches of adults which already migrate into this country from mainland China. The regular cycle of 11.2 years of sunspot activity began in 1710, and was continued to present. To gather more records of brown planthopper, the author checked 'Joseon Wangjo Silrok' and analized the so-called 'Hwang' 'Hwang-chung' and 'Chung' which have multiple meanings, together with 'Samguk Sagi' 'Goryo Sa' and 'Munheon Bigo.' The results obtained by the about from review of these old literature citations revealed that ten species of insect and unknown species were involved: i. e., pine moth (Dendrolimus spectabilis), army worm (Mythimna separata), brown planthopper (Nilarvata lugens), white-back planthopper (Sogatella furcifera), migratory locust (Locutsa migratoria), rice stem borer (Chilo suppressalis,), mole cricket (Gryllotalpa africana), rice-plant weevil (Echinocnemus squameus), cut worm (Euxoa segetum), and mulberry pyralid Margaronia pyloalis) The suspected incidence of planthopper in old records expressed by 'Hwang' or 'Chung' revealed a total or 25 out of 37 in 'Samguk sagi,' 21 out of 49 in 'Goryo sa,' 9 of 73 in 'Wanjo-silrog,' and none of 8 in 'Munheon bigo' were planthoppers. Therefore, a total of 36 out of 167 records of insect incidence in the old literature can be possibly attributed to planthoppers. The brown planthopper and white-back planthopper migrate together to Korea every year from mainland China, However, the number of each species are differ by year. In 1975 outbreak the brown planthopper was dominant; and the white-back planthopper prevailed in 1946 and 1977 outbreaks, During the course of this study, the author was able to add a new record of outbreak of planthop per. In 1916 the white-back planthopper outbreak caused serious losses in Chungcheong-namdo and Jeonla-namdo, with losses estimated as high as 160 and 190 thousand seok (23.2 and 27.5 thousand M/T), in Naju and Secheon county, respectively. Since 1912, major outbreaks of brown planthopper or white-back planthopper have been recored 5 times. These occurrences coincide and well matched the period of minimum number of sunspots, With these authenticated records of planthoppers, the author believes there is a close correlation between brown planthopper and white-back planthopper outbreaks in Korea and sunspot activities. Therefore, in years of low number of sunspots, we should watch for and expect outbreaks of these. insects. At this time, it will be necessary to provide all possible prevention measures.

• Journal of Animal Science and Technology
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• v.49 no.4
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• pp.459-470
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• 2007

Domestically, finishing pigs are marketed at 110 kg on an average. However, it is thought to be feasible to increase the market weight to 120kg or greater without decreasing the carcass quality, because most domestic pigs for pork production have descended from lean-type lineages. The present study was undertaken to investigate the growth efficiency and profitability of ‘high’-market wt pigs and the physicochemical characteristics and consumers' acceptability of the high-wt carcass. A total of 96 (Yorkshire × Landrace) × Duroc-crossbred gilts and barrows were fed a finisher diet ad laibtum in 16 pens beginning from 90-kg BW, after which the animals were slaughtered at 110kg (control) or ‘high’ market wt (135 and 125kg in gilts & barrows, respectively) and their carcasses were analyzed. Average daily gain and gain:feed did not differ between the two sex or market wt groups, whereas average daily feed intake was greater in the barrow and high market wt groups than in the gilt and 110-kg market wt groups, respectively(P<0.01). Backfat thickness of the high-market wt gilts and barrows corrected for 135 and 125-kg live wt, which were 23.7 and 22.5 mm, respectively, were greater (P<0.01) than their corresponding 110-kg counterparts(19.7 & 21.1 mm). Percentages of the trimmed primal cuts per total trimmed lean (w/w), except for that of loin, differed statistically (P<0.05) between two sex or market wt groups, but their numerical differences were rather small. Crude protein content of the loin was greater in the high vs. 110-kg market group (P<0.01), but crude fat and moisture contents and other physicochemical characteristics including the color of this primal cut were not different between the two sexes or market weights. Aroma, marbling and overall acceptability scores were greater in the high vs. 110-kg market wt group in sensory evaluation for fresh loin (P<0.01); however, overall acceptabilities for cooked loin, belly and ham were not different between the two market wt groups. Marginal profits of the 135- and 125-kg high-market wt gilt and barrow relative to their corresponding 110-kg ones were approximately -35,000 and 3,500 wons per head under the current carcass grading standard and price. However, if it had not been for the upper wt limits for the A- and B-grade carcasses, marginal profits of the high market wt gilt and barrow would have amounted to 22,000 and 11,000 wons per head, respectively. In summary, 120～125-kg market pigs are likely to meet the consumers' preference better than the 110-kg ones and also bring a profit equal to or slightly greater than that of the latter even under the current carcass grading standard. Moreover, if only the upper wt limits of the A- & B-grade carcasses were removed or increased to accommodate the high-wt carcass, the optimum market weights for the gilt and barrow would fall upon their target weights of the present study, i.e. 135 and 125 kg, respectively.

• 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.