Evaluation of the Usefulness of MapPHAN for the Verification of Volumetric Modulated Arc Therapy Planning (용적세기조절회전치료 치료계획 확인에 사용되는 MapPHAN의 유용성 평가)
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- The Journal of Korean Society for Radiation Therapy
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- v.25 no.2
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- pp.115-121
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- 2013
Purpose: Latest linear accelerator and the introduction of new measurement equipment to the agency that the introduction of this equipment in the future, by analyzing the process of confirming the usefulness of the preparation process for applying it in the clinical causes some problems, should be helpful. Materials and Methods: All measurements TrueBEAM STX (Varian, USA) was used, and a file specific to each energy, irradiation conditions, the dose distribution was calculated using a computerized treatment planning equipment (Eclipse ver 10.0.39, Varian, USA). Measuring performance and cause errors in MapCHECK 2 were analyzed and measured against. In order to verify the performance of the MapCHECK 2, 6X, 6X-FFF, 10X, 10X-FFF, 15X field size
The total forest land area in Korea accounts for some 67 percent of the nation's land total. Its productivity, however, is very low. Consequently, forest production accounts for only about 2 percent of the gross national product and a minor proportion of no more than about 5 percent versus primary industry. In this case, however, only the direct income from forestry is taken into account, making no reference to the forestry output induced by other industrial sectors. The value added Or the induced forestry output in manufacturing the primary wood products into higher quality products, makes a larger contribution to the economy than direct contribution. So, this author has tried to analyze the structure of forestry and compute the repercussion effect and the induced output of primary forest products when utilized by other industries for their raw materials, Hsing the input-output table and attached tables for 1963 and 1966 issued by the Bank of Korea. 1. Analysis of forestry structure A. Changes in total output Durng the nine-year period, 1961-1969, the real gross national product in Korea increased 2.1 times, while that of primary industries went up about 1. 4 times. Forestry which was valued at 9,380 million won in 1961, was picked up about 2. 1 times to 20, 120 million won in 1969. The rate of the forestry income in the GNP, accordingly, was no more than 1.5 percent both in 1961 and 1962, whereas its rate in primary industries increased 3.5 to 5.4 percent. Such increase in forestry income is attributable to increased forest production and rise in timber prices. The rate of forestry income, nonetheless, was on the decrease on a gradual basis. B. Changes in input coefficient The input coefficient which indicates the inputs of the forest products into other sectors were up in general in 1966 over 1963. It is noted that the input coefficient indicating the amount of forest products supplied to such industries closely related with forestry as lumber and plywood, and wood products and furniture, showed a downward trend for the period 1963-1966. On the other hand, the forest input into other sectors was generally on the increase. Meanwhile, the input coefficient representing the yolume of the forest products supplied to the forestry sector itself showed an upward tendency, which meant more and more decrease in input from other sectors. Generally speaking, in direct proportion to the higher input coefficient in any industrial sector, the reinput coefficient which denotes the use of its products by the same sector becomes higher and higher. C. Changes in ratio of intermediate input The intermediate input ratio showing the dependency on raw materials went up to 15.43 percent m 1966 from 11. 37 percent in 1963. The dependency of forestry on raw materials was no more than 15.43 percent, accounting for a high 83.57 percent of value added. If the intermediate input ratio increases in any given sector, the input coefficient which represents the fe-use of its products by the same sector becomes large. D. Changes in the ratio of intermediate demand The ratio of the intermediate demand represents the characteristics of the intermediary production in each industry, the intermediate demand ratio in forestry which accunted for 69.7 percent in 1963 went up to 75.2 percent in 1966. In other words, forestry is a remarkable industry in that there is characteristics of the intermediary production. E. Changes in import coefficient The import coefficient which denotes the relation between the production activities and imports, recorded at 4.4 percent in 1963, decreased to 2.4 percent in 1966. The ratio of import to total output is not so high. F. Changes in market composition of imported goods One of the major imported goods in the forestry sector is lumber. The import value increased by 60 percent to 667 million won in 1966 from 407 million won in 1963. The sales of imported forest products to two major outlets-lumber and plywood, and wood products and furniture-increased to 343 million won and 31 million won in 1966 from 240million won and 30 million won in 1963 respectively. On the other hand, imported goods valued at 66 million won were sold to the paper products sector in 1963; however, no supply to this sector was recorded in 1963. Besides these major markets, primary industries such as the fishery, coal and agriculture sectors purchase materials from forestry. 2. Analysis of repercussion effect on production The repercussion effect of final demand in any given sector upon the expansion of the production of other sectors was analyzed, using the inverse matrix coefficient tables attached to the the I.O. Table. A. Changes in intra-sector transaction value of inverse matrix coefficient. The intra-sector transaction value of an inverse matrix coefficient represents the extent of an induced increase in the production of self-support products of the same sector, when it is generated directly and indirectly by one unit of final demand in any given sector. The intra-sector transaction value of the forestry sector rose from 1.04 in 1963 to 1, 11 in 1966. It may well be said, therefore, that forestry induces much more self-supporting products in the production of one unit of final demand for forest products. B. Changes in column total of inverse matrix coefficient It should be noted that the column total indicates the degree of effect of the output of the corresponding and related sectors generated by one unit of final demand in each sector. No changes in the column total of the forestry sector were recorded between the 1963 and 1966 figures, both being the same 1. 19. C. Changes in difference between column total and intra-sector transaction amount. The difference between the column total and intra-sector transaction amount by sector reveals the extent of effect of output of related industrial sector induced indirectly by one unit of final demand in corresponding sector. This change in forestry dropped remarkable to 0.08 in 1966 from 0.15 in 1963. Accordingly, the effect of inducement of indirect output of other forestry-related sectors has decreased; this is a really natural phenomenon, as compared with an increasing input coefficient generated by the re-use of forest products by the forestry sector. 3. Induced output of forestry A. Forest products, wood in particular, are supplied to other industries as their raw materials, increasng their value added. In this connection the primary dependency rate on forestry for 1963 and 1966 was compared, i. e., an increase or decrease in each sector, from 7.71 percent in 1963 to 11.91 percent in 1966 in agriculture, 10.32 to 6.11 in fishery, 16.24 to 19.90 in mining, 0.76 to 0.70 in the manufacturing sector and 2.79 to 4.77 percent in the construction sector. Generally speaking, on the average the dependency on forestry during the period 1963-1966 increased from 5.92 percent to 8.03 percent. Accordingly, it may easily be known that the primary forestry output induced by primary and secondary industries increased from 16, 109 million won in 1963 to 48, 842 million won in 1966. B. The forest products are supplied to other industries as their raw materials. The products are processed further into higher quality products. thus indirectly increasing the value of the forest products. The ratio of the increased value added or the secondary dependency on forestry for 1963 and 1966 showed an increase or decrease, from 5.98 percent to 7.87 percent in agriculture, 9.06 to 5.74 in fishery, 13.56 to 15.81 in mining, 0.68 to 0.61 in the manufacturing sector and 2.71 to 4.54 in the construction sector. The average ratio in this connection increased from 4.69 percent to 5.60 percent. In the meantime, the secondary forestry output induced by primary and secondary industries rose from 12,779 million Wall in 1963 to 34,084 million won in 1966. C. The dependency of tertiary industries on forestry showed very minor ratios of 0.46 percent and 0.04 percent in 1963 and 1966 respectively. The forestry output induced by tertiary industry also decreased from 685 million won to 123 million won during the same period. D. Generally speaking, the ratio of dependency on forestry increased from 17.68 percent in 1963 to 24.28 percent in 1966 in primary industries, from 4.69 percent to 5.70 percent in secondary industries, while, as mentioned above, the ratio in the case of tertiary industry decreased from 0.46 to 0.04 percent during the period 1963-66. The mining industry reveals the heaviest rate of dependency on forestry with 29.80 percent in 1963 and 35.71 percent in 1966. As it result, the direct forestry income, valued at 8,172 million won in 1963, shot up to 22,724 million won in 1966. Its composition ratio lo the national income rose from 1.9 percent in 1963 to 2.3 per cent in 1966. If the induced outcome is taken into account, the total forestry production which was estimated at 37,744 million won in 1963 picked up to 105,773 million won in 1966, about 4.5 times its direct income. It is further noted that the ratio of the gross forestry product to the gross national product. rose significantly from 8.8 percent in 1963 to 10.7 percent in 1966. E. In computing the above mentioned ratio not taken into consideration were such intangible, indirect effects as the drought and flood prevention, check of soil run-off, watershed and land conservation, improvement of the people's recreational and emotional living, and maintenance and increase in the national health and sanitation. F. In conclusion, I would like to emphasize that the forestry sector exercices an important effect upon the national economy and that the effect of induced forestry output is greater than its direct income.
Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.
The flow theory becomes one of the most important frameworks in the internet research arena. Hoffman and Novak proposed a hierarchical flow model showing the antecedents and outcomes of flow and the relationship among these variables in the hyper-media computer circumstances (Hoffman and Novak 1996). This model was further tested after their initial research (Novak, Hoffman, and Yung 2000). At their paper, Hoffman and Novak explained that the balance of challenge and skill leads to flow which means the positive optimal state of mind (Hoffman and Novak 1996). An imbalance between challenge and skill, leads to negative states of mind like anxiety, boredom, apathy (Csikszentmihalyi and Csikszentmihalyi 1988). Almost all research on the flow 4-channel model have been focusingon flow, the positive state of mind (Ellis, Voelkl, and Morris 1994 Mathwick and Rigdon 2004). However, it also needs to examine the formation of the negative states of minds and their outcomes. Flow researchers explain play or playfulness as antecedents or the early state of flow. However, play has been regarded as a distinct concept from flow in the flow literatures (Hoffman and Novak 1996; Novak, Hoffman, and Yung 2000). Mathwick and Rigdon discovered the influences of challenge and skill on play; they also observed the influence of play on web-loyalty and brand loyalty (Mathwick and Rigdon 2004). Unfortunately, they did not go so far as to test the influences of play on state of mind. This study focuses on the relationships between state of mind in the flow 4-channel model and play. Early research has attempted to hypothetically explain state of mind in flow theory, but has not been tested except flow until now. Also the importance of play has been emphasized in the flow theory, but has not been tested in the flow 4-channel model context. This researcher attempts to analyze the relationships among state of mind, skill of play, challenge, state of mind and web loyalty. For this objective, I developed a measure for state of mind and defined the concept of play as a trait. Then, the influences of challenge and skill on the state of mind and play under on-line shopping conditions were tested. Also the influences of play on state of mind were tested and those of flow and play on web loyalty were highlighted. 294 undergraduate students participated in this research survey. They were asked to respond about their perceptions of challenge, skill, state of mind, play, and web-loyalty to on-line shopping mall. Respondents were restricted to students who bought products on-line in a month. In case of buying products at two or more on-line shopping malls, they asked to respond about the shopping mall where they bought the most important one. Construct validity, discriminant validity, and convergent validity were used to check the measurement validations. Also, Cronbach's alpha was used to check scale reliability. A series of exploratory factor analyses was conducted. This researcher conducted confirmatory factor analyses to assess the validity of measurements. All items loaded significantly on their respective constructs. Also, all reliabilities were greater than.70. Chi-square difference tests and goodness of fit tests supported discriminant and convergent validity. The results of clustering and ANOVA showed that high challenge and high skill leaded to flow, low challenge and high skill leaded to boredom, and low challenge and low skill leaded to apathy. But, it was different from my expectation that high challenge and low skill didnot lead to anxiety but leaded to apathy. The results also showed that high challenge and high skill, and high challenge and low skill leaded to the highest play. Low challenge leaded to low play. 4 Structural Equation Models were built by flow, anxiety, boredom, apathy for analyzing not only the impact of play on state of mind and web-loyalty, but also that of state of mind on web-loyalty. According the analyses results of these models, play impacted flow and web-loyalty positively, but impacted anxiety, boredom, and apathy negatively. Results also showed that flow impacted web-loyalty positively, but anxiety, boredom, and apathy impacted web-loyalty negatively. The interpretations and implications of the test results of the hypotheses are as follows. First, respondents belonging to different clusters based on challenge and skill level experienced different states of mind such as flow, anxiety, boredom, apathy. The low challenge and low skill group felt the highest anxiety and apathy. It could be interpreted that this group feeling high anxiety or fear, then avoided attempts to shop on-line. Second, it was found that higher challenge leads to higher levels of play. Test results show that the play level of the high challenge and low skill group (anxiety group) was higher than that of the high challenge and high skill group (flow group). However, this was not significant. Third, play positively impacted flow and negatively impacted boredom. The negative impacts on anxiety and apathy were not significant. This means that the combination of challenge and skill creates different results. Forth, play and flow positively impacted web-loyalty, but anxiety, boredom, apathy had negative impacts. The effect of play on web-loyalty was stronger in case of anxiety, boredom, apathy group than fl ow group. These results show that challenge and skill influences state of mind and play. Results also demonstrate how play and flow influence web-loyalty. It implies that state of mind and play should be the core marketing variables in internet marketing. The flow theory has been focusing on flow and on the positive outcomes of flow experiences. But, this research shows that lots of consumers experience the negative state of mind rather than flow state in the internet shopping circumstance. Results show that the negative state of mind leads to low or negative web-loyalty. Play can have an important role with the web-loyalty when consumers have the negative state of mind. Results of structural equation model analyses show that play influences web-loyalty positively, even though consumers may be in the negative state of mind. This research found the impacts of challenge and skill on state of mind in the flow 4-channel model, not only flow but also anxiety, boredom, apathy. Also, it highlighted the role of play in the flow 4-channel model context and impacts on web-loyalty. However, tests show a few different results from hypothetical expectations such as the highest anxiety level of apathy group and insignificant impacts of play on anxiety and apathy. Further research needs to replicate this research and/or to compare 3-channel model with 4-channel model.
Drilling position is one of the most important factors affecting on the blasting effects. There has been many reports on several blasting factors of burn-cut by Messrs. Brown and Cook, but in this study the author tried to compare drilling positions of burn-cut to pyramid-cut, and also to correlate burn-cut effects of drilling patterns, not being dealt by Prof. Ito in his theory, which emphasized on dynamical stress analysis between explosion and free face. According to former theories, there break out additional tensile stress reflected at the free face supplemented to primary compressive stress on the blasting with one-free-face. But with these experimented new drilling patterns of burn-cut, more free faces and nearer distance of each drilling holes make blasting effects greater than any other methods. To promote the above explosive effect rationary, it has to be considered two important categories under-mentioned. First, unloaded hole in the key holes should be drilled in wider diameter possibly so that it breaks out greater stress relief. Second, key holes possibly should have closer distances each other to result clean blasting. These two important factors derived from experiments with, theories of that the larger the dia of the unloaded hole, it can be allowed wider secondary free faces and closes distances of each holes make more developed stress relief, between loaded and unloaded holes. It was suggested that most ideal distance between holes is about 4 clearance in U. S. A., but the author, according to the experiments, it results that the less distance allow, the more effective blasting with increased broken rock volume and longer drifted length can be accomplished. Developed large hole burn-cut method aimed to increase drifting length technically under the above considerations, and progressive success resulted to achieve maximum 7 blasting cycles per day with 3.1m drifting length per cycle. This achievement originated high-speed-drifting works, and it was also proven that application of Metallic AN-FO on large hole burn-cut method overcomes resistance of one-free-face. AN-FO which was favored with low price and safety handling is the mixture of the fertilizer or industrial Ammonium-Nitrate and fuel oil, and it is also experienced that it shows insensible property before the initiation, but once it is initiated by the booster, it has equal explosive power of Ammonium Nitrate Explosives (ANE). There was many reports about AN-FO. On AN-FO mixing ratio, according to these experiments, prowdered AN-FO, 93.5 : 6.5 and prilled AN-FO 94 : 6, are the best ratios. Detonation, shock, and friction sensities are all more insensitive than any other explosives. Residual gas is not toxic, too. On initation and propagation of the detonation test, prilled AN-FO is more effective than powered AN-FO. AN-FO has the best explosion power at 7 days elapsed after it has mixed. While AN-FO was used at open pit in past years prior to other conditions, the author developed new improved explosives, Metallic AN-FO and Underwater explosive, based on the experiments of these fundmental characteristics by study on its usage utilizing AN-FO. Metallic AN-FO is the mixture of AN-FO and Al, Fe-Si powder, and Underwater explosive is made from usual explosive and AN-FO. The explanations about them are described in the other paper. In this study, it is confirmed that the blasting effects of utilizing AN-FO explosives are very good.
Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.
Myogilsang on Diamond Mountain, signed and dated (2000) by Seon-u Yeong (1946-2009), is the first work by a North Korean artist to enter the collection of the National Museum of Korea (fig. 1a). The donor acquired the painting directly from the artist in Pyeongyang in 2006. In consequence, there are no issues with the painting's authenticity.This painting is the largest among all existing Korean paintings, whether contemporary or from the Joseon Dynasty, to depict this iconography (see chart 1. A Chronological List of Korean Myogilsang Paintings.) It is ink and color on paper, measures 130.2 × 56.2 centimeters, and is in a hanging scroll format. Since this essay is intended as a brief introduction of the painting and not in-depth research into it, I will simply examine the following four areas: 1. Seon-u Yeong's background; 2. The location and the traditional appellation of the rock-cut image known as Myogilsang; 3. The iconography of the image; and 4) A comparative analysis of Seon-u Yeong's painting in light of other paintings on the same theme. Finally, I will present two more of his works to broaden the understanding of Seon-u Yeong as a painter. 1. Seon-u Yeong: According to the donor, who met Seon-u at his workshop in the Cheollima Jejakso (Flying Horse Workshop) three years before the artist's death, he was an individual of few words but displayed a firm commitment to art. His preference for subjects such as Korean landscapes rather than motifs of socialist realism such as revolutionary leaders is demonstrated by the fact that, relative to his North Korean contemporaries, he seems to have produced more paintings of the former. In recent years, Seon-u Yeong has been well publicized in Korea through three special exhibitions (2012 through 2019). He graduated from Pyeongyang College of Fine Arts in 1969 and joined the Central Fine Arts Production Workshop focusing on oil painting. In 1973 he entered the Joseon Painting Production Workshop and began creating traditional Korean paintings in ink and color. His paintings are characterized by intense colors and fine details. The fact that his mother was an accomplished embroidery specialist may have influenced on Seon-u's choice to use intense colors in his paintings. By 1992, he had become a painter representing the Democratic People's Republic of Korea with several titles such as Artist of Merit, People's Artist, and more. About 60 of his paintings have been designated as National Treasures of the DPRK. 2. The Myogilsang rock-cut image is located in the Manpok-dong Valley in the inner Geumgangsan Mountain area. It is a high-relief image about 15 meters tall cut into a niche under 40 meters of a rock cliff. It is the largest of all the rock-cut images of the Goryeo period. This image is often known as "Mahayeon Myogilsang," Mahayeon (Mahayana) being the name of a small temple deep in the Manpokdong Valley (See fig. 3a & 3b). On the right side of the image, there is an intaglio inscription of three Chinese characters by the famous scholar-official and calligrapher Yun Sa-guk (1728-1709) reading "妙吉祥"myogilsang (fig. 4a, 4b). 3. The iconography: "Myogilsang" is another name for the Bhodhisattva Mañjuśrī. The Chinese pronunciation of Myogilsang is "miaojixiang," which is similar in pronunciation to Mañjuśrī. Therefore, we can suggest a 妙吉祥 ↔ Mañjuśrī formula for the translation and transliteration of the term. Even though the image was given a traditional name, the mudra presented by the two hands in the image calls for a closer examination. They show the making of a circle by joining the thumb with the ring finger (fig. 6). If the left land pointed downward, this mudra would conventionally be considered "lower class: lower life," one of the nine mudras of the Amitabha. However, in this image the left hand is placed across its abdomen at an almost 90-degree angle to the right hand (fig. 6). This can be interpreted as a combination of the "fear not" and the "preaching" mudras (see note 10, D. Saunders). I was also advised by the noted Buddhist art specialist Professor Kim Jeong-heui (of Won'gwang University) to presume that this is the "preaching" mudra. Therefore, I have tentatively concluded that this Myogilsang is an image of the Shakyamuni offering the preaching mudra. There is no such combination of hand gestures in any other Goryeo-period images. The closest I could identify is the Beopjusa Rock-cut Buddha (fig. 7) from around the same time. 4. Comparative analysis: As seen in
With the advent of knowledge-based society, the revitalization of technological innovation type SMEs, termed "inno-biz" hereafter, has been globally recognized as a government policymakers' primary concern in strengthening national competitiveness, and much effort is being put into establishing polices of boosting the start-ups and innovation capability of SMEs. Especially, in that the inno-biz enables national economy to get vitalized by widening world markets with its superior technology, and thus, taking the initiative of extremely competitive world markets, its growth and development has greater significance. In the case of Korea, the government has been maintaining the policies since the late 1990s of stimulating the growth of SMEs as well as building various infrastructures to foster the start-ups of the SMEs such as venture businesses with high technology. In addition, since the enactment of "Innovation Promotion Law for SMEs" in 2001, the government has been accelerating the policies of prioritizing the growth and development of inno-biz. So, for the sound growth and development of Korean inno-biz, this paper intends to offer effective management strategies for SMEs and suggest proper policies for the government, by researching into the effect of technological innovation capability and technology commercialization capability as the primary business resources on business performance in Korean SMEs in the light of market information orientation. The research is carried out on Korean companies characterized as inno-biz. On the basis of OSLO manual and prior studies, the research categorizes their status. R&D capability, technology accumulation capability and technological innovation system are categorized into technological innovation capability; product development capability, manufacturing capability and marketing capability into technology commercialization capability; and increase in product competitiveness and merits for new technology and/or product development into business performance. Then the effect of each component on business performance is substantially analyzed. In addition, the mediation effect of technological innovation and technology commercialization capability on business performance is observed by the use of the market information orientation as a parameter. The following hypotheses are proposed. H1 : Technology innovation capability will positively influence business performance. H1-1 : R&D capability will positively influence product competitiveness. H1-2 : R&D capability will positively influence merits for new technology and/or product development into business performance. H1-3 : Technology accumulation capability will positively influence product competitiveness. H1-4 : Technology accumulation capability will positively influence merits for new technology and/or product development into business performance. H1-5 : Technological innovation system will positively influence product competitiveness. H1-6 : Technological innovation system will positively influence merits for new technology and/or product development into business performance. H2 : Technology commercializing capability will positively influence business performance. H2-1 : Product development capability will positively influence product competitiveness. H2-2 : Product development capability will positively influence merits for new technology and/or product development into business performance. H2-3 : Manufacturing capability will positively influence product competitiveness. H2-4 : Manufacturing capability will positively influence merits for new technology and/or product development into business performance. H2-5 : Marketing capability will positively influence product competitiveness. H2-6 : Marketing capability will positively influence merits for new technology and/or product development into business performance. H3 : Technology innovation capability will positively influence market information orientation. H3-1 : R&D capability will positively influence information generation. H3-2 : R&D capability will positively influence information diffusion. H3-3 : R&D capability will positively influence information response. H3-4 : Technology accumulation capability will positively influence information generation. H3-5 : Technology accumulation capability will positively influence information diffusion. H3-6 : Technology accumulation capability will positively influence information response. H3-7 : Technological innovation system will positively influence information generation. H3-8 : Technological innovation system will positively influence information diffusion. H3-9 : Technological innovation system will positively influence information response. H4 : Technology commercialization capability will positively influence market information orientation. H4-1 : Product development capability will positively influence information generation. H4-2 : Product development capability will positively influence information diffusion. H4-3 : Product development capability will positively influence information response. H4-4 : Manufacturing capability will positively influence information generation. H4-5 : Manufacturing capability will positively influence information diffusion. H4-6 : Manufacturing capability will positively influence information response. H4-7 : Marketing capability will positively influence information generation. H4-8 : Marketing capability will positively influence information diffusion. H4-9 : Marketing capability will positively influence information response. H5 : Market information orientation will positively influence business performance. H5-1 : Information generation will positively influence product competitiveness. H5-2 : Information generation will positively influence merits for new technology and/or product development into business performance. H5-3 : Information diffusion will positively influence product competitiveness. H5-4 : Information diffusion will positively influence merits for new technology and/or product development into business performance. H5-5 : Information response will positively influence product competitiveness. H5-6 : Information response will positively influence merits for new technology and/or product development into business performance. H6 : Market information orientation will mediate the relationship between technology innovation capability and business performance. H7 : Market information orientation will mediate the relationship between technology commercializing capability and business performance. The followings are the research results : First, as for the effect of technological innovation on business performance, the technology accumulation capability and technological innovating system have a positive effect on increase in product competitiveness and merits for new technology and/or product development, while R&D capability has little effect on business performance. Second, as for the effect of technology commercialization capability on business performance, the effect of manufacturing capability is relatively greater than that of merits for new technology and/or product development. Third, the mediation effect of market information orientation is identified to exist partially in information generation, information diffusion and information response. Judging from these results, the following analysis can be made : On Increase in product competitiveness, directly related to successful technology commercialization of technology, management capability including technological innovation system, manufacturing capability and marketing capability has a relatively strong effect. On merits for new technology and/or product development, on the other hand, capability in technological aspect including R&D capability, technology accumulation capability and product development capability has relatively strong effect. Besides, in the cast of market information orientation, the level of information diffusion within an organization plays and important role in new technology and/or product development. Also, for commercial success like increase in product competitiveness, the level of information response is primarily required. Accordingly, the following policies are suggested : First, as the effect of technological innovation capability and technology commercialization capability on business performance differs among SMEs; in order for SMEs to secure competitiveness, the government has to establish microscopic policies for SMEs which meet their needs and characteristics. Especially, the SMEs lacking in capital and labor are required to map out management strategies of focusing their resources primarily on their strengths. And the government needs to set up policies for SMEs, not from its macro-scaled standpoint, but from the selective and concentrative one that meets the needs and characteristics of respective SMEs. Second, systematic infrastructures are urgently required which lead technological success to commercial success. Namely, as technological merits at respective SME levels do not always guarantee commercial success, the government should make and effort to build systematic infrastructures including encouragement of M&A or technology trade, systematic support for protecting intellectual property, furtherance of business incubating and industrial clusters for strengthening academic-industrial network, and revitalization of technology financing, in order to make successful commercialization from technological success. Finally, the effort to innovate technology, R&D, for example, is essential to future national competitiveness, but its result is often prolonged. So the government needs continuous concern and funding for basic science, in order to maximize technological innovation capability. Indeed the government needs to examine continuously whether technological innovation capability or technological success leads satisfactorily to commercial success in market economic system. It is because, when the transition fails, it should be left to the government.
The purpose of this paper was to schedule optimum cutting strategy which could maximize the total yield under certain restrictions on periodic timber removals and harvest areas from an industrial forest, based on a linear programming technique. Sensitivity of the regulation model to variations in restrictions has also been analyzed to get information on the changes of total yield in the planning period. The regulation procedure has been made on the experimental forest of the Agricultural College of Seoul National University. The forest is composed of 219 cutting units, and characterized by younger age group which is very common in Korea. The planning period is devided into 10 cutting periods of five years each, and cutting is permissible only on the stands of age groups 5-9. It is also assumed in the study that the subsequent forests are established immediately after cutting existing forests, non-stocked forest lands are planted in first cutting period, and established forests are fully stocked until next harvest. All feasible cutting regimes have been defined to each unit depending on their age groups. Total yield (Vi, k) of each regime expected in the planning period has been projected using stand yield tables and forest inventory data, and the regime which gives highest Vi, k has been selected as a optimum cutting regime. After calculating periodic yields and cutting areas, and total yield from the optimum regimes selected without any restrictions, the upper and lower limits of periodic yields(Vj-max, Vj-min) and those of periodic cutting areas (Aj-max, Aj-min) have been decided. The optimum regimes under such restrictions have been selected by linear programming. The results of the study may be summarized as follows:- 1. The fluctuations of periodic harvest yields and areas under cutting regimes selected without restrictions were very great, because of irregular composition of age classes and growing stocks of existing stands. About 68.8 percent of total yield is expected in period 10, while none of yield in periods 6 and 7. 2. After inspection of the above solution, restricted optimum cutting regimes were obtained under the restrictions of Amin=150 ha, Amax=400ha,