• Progress in Medical Physics
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• v.23 no.4
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• pp.317-325
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• 2012

The Varian PORTALVISION (Varian Medical Systems, US) shows significant overresponses as the off-center distance increases compared to the predicted dose. In order to correct the dose discrepancy, the off-axis correction is applied to VARIAN iX linear accelerators. The portal dose for $38{\times}28cm^2$ open field is acquired for 6 MV, 15 MV photon beams and also are predicted by PDIP algorithm under the same condition of the portal dose acquisition. The off-axis correction is applied by modifying the $40{\times}40cm^2$ diagonal beam profile data which is used for the beam profile calibration. The ratios between predicted dose and measured dose is modeled as a function of off-axis distance with the $4^{th}$ polynomial and is applied to the $40{\times}40cm^2$ diagonal beam profile data as the weight to correct measured dose by EPID detector. The discrepancy between measured dose and predicted dose is reduced from $4.17{\pm}2.76$ CU to $0.18{\pm}0.8$ CU for 6 MV photon beam and from $3.23{\pm}2.59$ CU to $0.04{\pm}0.85$ CU for 15 MV photon beam. The passing rate of gamma analysis for the pyramid fluence patten with the 4%, 4 mm criteria is improved from 98.7% to 99.1% for 6 MV photon beam, from 99.8% to 99.9% for 15 MV photon beam. IMRT QA is also performed for randomly selected Head and Neck and Prostate IMRT plans after applying the off-axis correction. The gamma passing rare is improved by 3% on average, for Head and Neck cases: $94.7{\pm}3.2%$ to $98.2{\pm}1.4%$, for Prostate cases: $95.5{\pm}2.6%$, $98.4{\pm}1.8%$. The gamma analysis criteria is 3%, 3 mm with 10% threshold. It is considered that the off-axis correction might be an effective and easily adaptable means for correcting the discrepancy between measured dose and predicted dose for IMRT QA using EPID in clinic.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.150-161
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• 2018

Recently, unmanned aircraft EM (electromagnetic) survey based on ICT (Information and Communication Technology) has been widely utilized because of the efficiency in regional survey. We performed the theoretical study on the unmanned airship EM system developed by KIGAM (Korea Institute of Geoscience and Mineral resources) as part of the practical application of unmanned aircraft EM survey. Since this system has different configurations of transmitting and receiving loops compared to the conventional aircraft EM systems, a new technique is required for the appropriate interpretation of measured responses. Therefore, we proposed a method to calculate the EM field for the arbitrary shaped transmitter and verified its validity through the comparison with analytic solution for circular loop. In addition, to simulate the magnetic responses by three-dimensionally (3D) distributed anomalies, we have adapted our algorithm to 3D frequency-domain EM modeling algorithm based on the edge-FEM (finite element method). Though the analysis on magnetic field responses from a subsurface anomaly, it was found that the response decreases as the depth of the anomaly increases or the flight altitude increases. Also, it was confirmed that the response became smaller as the resistivity of the anomaly increases. However, a nonlinear trend of the out-of-phase component is shown depending on the depth of the anomaly and the used frequency, that makes it difficult to apply simple analysis based on the mapping of the magnitude of the responses and can cause the non-uniqueness problem in calculating the apparent resistivity. Thus, it is a prerequisite to analyze the appropriate frequency band and flight altitude considering the purpose of the survey and the site conditions when conducting a survey using the unmanned aircraft EM system.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.34 no.2
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• pp.83-92
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• 2008

In this study, the antioxidative effects, inhibitory effects on tyrosinase and elastase and components of Fagopyrum esculetum extracts were investigated. Fagopyrum esculetum used for this study is hulls and dehulled seeds. The free radical(1,1-diphenyl-2-picrylhydrazyl radical, DPPH) scavenging activities($FSC_{50}$) and reactive oxygen species(ROS) scavenging activities($OSC_{50}$) of extract/fractions from Fagopyrum esculetum were measured. The aglycone($3.5{\pm}0.0{\mu}g/mL$) and ethyl acetate fractions($0.2{\pm}0.1{\mu}g/mL$) of hulls showed the most effective scavenging activities. The protective effects on the rose-bengal sensitized photohemolysis of human erythrocytes were investigated. The ethyl acetate fraction exhibited the most prominent cellular protective effect(${\tau}_{50},\;771.7{\pm}9.9 min$ at 10 ${\mu}g/mL$). The inhibitory effect of aglycone fraction of hull and dehulled seeds on tyrosinase were examined ($53.6{\pm}0.5{\mu}g/mL,\;35.6{\pm}0.4{\mu}g/mL$, respectively). And The inhibitory effect of aglycone fraction of hull and dehulled seeds on elastase were investigated($3.7{\pm}0.4{\mu}g/mL\;and\;6.0{\pm}0.7{\mu}g/mL$ respectively). But 50% ethanol extract rarely exhibited the inhibitory activity on tyrosinase and elastase. (+)-Catechin and (-)-epicatechin were contained in ethyl acetate fraction of dehulled seeds. And ethyl acetate fraction of hull contains flavonoids of hyperin, quercetin, rutin and so on. These results indicate that extract/fractions of Fagopyrum esculentum can function as antioxidants in biological systems, particularly skin exposed to UV radiation by scavenging $^1O_2$ and other ROS, and protect cellular membranes against ROS. Fagopyrum esculentum extract could be used as a new cosmeceutical for whitening and anti-wrinkle products.

• Journal of the Korean Geographical Society
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• v.28 no.2
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• pp.148-162
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• 1993

There is much speculation that modern capi-talist society is undergoing fundamental and qualitative chnge towards flexible specialization. The purpose of this study is to examine this hypothesis. This paper focusses on: the idea of flexible specialization; the significance of this transition; industrial district; and the implicati-ons of this new production system for Korean industrial space. Main arguments of this study are as follows: First, as all different groups of researchers apply the idea of flexible specialization according to their own specifications, the current debate on this topic is not much fruitful. Not surpri-singly, the concept of flexible specialization has overlapped with subocontracting. This intergration of subcontracting into flexible specialization systems, however, is inappropriate because the two concepts have different historical contexts. The other cause of this controversy is its inherent weekness, conceptual ambiguity. Thus, today's flexibility becomes tomorrow's rigidity. Secondly, transition towards flexible speciali-zation has only been partially achieved even in advanced capitalist countries. The application of dualistic explanatory framework, such as rigidity versus flexibiity, mass production versus small-lot multi-product production, and de-skilling versus re-skilling, has resulted in great exaggeration of the transformation, from Fordism to post-Fordism. There is no intermediary part between two places. Considering that the workers allocated to the Fordist mass production assembly line are not as large as one might imagine, the shift from mass to flexible production has only limited implications for the transformation of capitalist economy. Thirdly, 'industrial district' contorversy has contributed to highlighting the importance of small firms and areas as production space. The agglomeration of small firms in specific areas is common in Korea, but it is quite different from the industrial district based on flexible specialization. The Korean phenomenon stems from close interactions with its major parent firm rather than interactions between flexible, specialized, autonomous and technology-intensive smll firms. Most Korean subcontractors are still low-skilled, labour-intensive, and heavily dependent on their mojor parent firms. Thus, the assertion that the Seoul Metropolitan Area adopts flexible specialization has no base. Fourthly, the main concern of flexible speciali zation is small firms. However, the corporate organization that needs product diversification and technological specialization is oligopolistic large corporations typified by multinational corporations. It is because of this that most of these organizations are adoptiong Fordist mass production methods. The problem of product diversification will be resolved naturally if economic internationalization progresses further. What is more important for business success is the quality and price competitiveness of firms rather than product diversification. Lastly, in order to dispel further misunderst-anding on this issue, it is imparative that the conceptual ambiguity is resolved most urgently. This study recommends adoption of more speci-fied and direct terminology (such as, factory automation, computer design, out-sourcing, the exploitation of part-time labor, job redesign) rather than that of ideological ones (such as, Taylorism, Fordism, neo-Taylorism, neo-Fordism, post-fordism, flexible specialization, peripheral post-Fordism). As the debates on this topic just started, we still have long way to go until consensus is reached.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.1
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• pp.18-29
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• 2010

Offshore subsurface storage of $CO_2$ is regarded as one of the most promising options to response severe climate change. Marine geological storage of $CO_2$ is to capture $CO_2$ from major point sources, to transport to the storage sites and to store $CO_2$ into the offshore subsurface geological structure such as the depleted gas reservoir and deep sea saline aquifer. Since 2005, we have developed relevant technologies for marine geological storage of $CO_2$. Those technologies include possible storage site surveys and basic designs for $CO_2$ transport and storage processes. To design a reliable $CO_2$ marine geological storage system, we devised a hypothetical scenario and used a numerical simulation tool to study its detailed processes. The process of transport $CO_2$ from the onshore capture sites to the offshore storage sites can be simulated with a thermodynamic equation of state. Before going to main calculation of process design, we compared and analyzed the relevant equation of states. To evaluate the predictive accuracies of the examined equation of states, we compare the results of numerical calculations with experimental reference data. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the captured $CO_2$ mixture contains many impurities such as $N_2$, $O_2$, Ar, $H_{2}O$, $SO_{\chi}$, $H_{2}S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification and transport processes. This paper analyzes the major design parameters that are useful for constructing onshore and offshore $CO_2$ transport systems. On the basis of a parametric study of the hypothetical scenario, we suggest relevant variation ranges for the design parameters, particularly the flow rate, diameter, temperature, and pressure.

• Archives of design research
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• v.18 no.3 s.61
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• pp.5-14
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• 2005

In the past, consumers sought utilitarian and defensive consumption in an attempt to move to a balanced state. However, today's consumers go beyond this to consume more for hedonic and creative reasons if not for sheer pleasure. There is an obvious shift from the type of consumption that satisfies basic desires through the characteristics, convenience and quality of goods and services to an era of 'experiential consumption,' in which consumers pursue distinctive value systems and way of life along with a total 'experience' provided by such goods and services. Such a sign of the times has given birth to the experience design that aims at maximizing the strategic use of experiences in design. Research on this subject is gradually increasing. The research and application peformed even without the proper understanding about the concepts and purposes of experience design, however, is likely to deviate from the true nature in its process or method. Also, they are likely to cause rather than solve problems. Accordingly, this study examined the meaning of experience from a spatial aspect, focusing on areas that recognize the experience as economically valuable, making the most of it substantively. The main concept of experience practical used on-line is enhancement of the usability of a medium by reflecting the experience of users accustomed to both off-line and on-line environments and materializing the environment doser to and more familiar with the users, thus allowing them to comfortably use the medium. This is to allow the users to feel more comfortable. The experience practical used pertaining to off-line is a tool to fulfill the sensitivity of users, with efforts to create new, future-oriented consumer values. This, based on the understanding of consumer behavior, seeks to maximize the consumption experience of consumers by providing a combination of sensual and sensitive experiences as well as to enhance the existing experiences by permitting users to create new, extended experiences from the fixed characteristics of products. Furthermore, it aims to provide consumers with the hedonic experience of play through the joy, fun and uniqueness of alternate experiences.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.195-204
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• 2008

With the growth of airline management, as well as computer and IT security, the international trade in this modern society has been rapidly increasing, Along with the advancing, airplanes have become a universal means of communication. However, the complications associated with airplane safety have also been brought up as a result, the most concerning of which is terrorism. One of the main counterplans for preventing terrorism is Ground security activities the core of Ground security activities is absolute safety for passengers in both passenger terminal and freight terminal. Subastral security refers to physical protection, proximity control and 100% security search and freight guarding of the passengers' possessions, and the personnel's duties to perform such jobs are be! coming more crucial. On the other hand, Airport security check has bee n gradually developing since the 1960's, when hijacking began to take place. Although the airports have been providing more safe and comfortable services to their customers, terrorism is still happening today. When Ground security activities is minute, the users feel displeasure and discomfort, yet considering solely their convenience can brings problems in achieving safety. Since the 9.11 terror in 2001, the idea of improving and strengthening airport security was reinforced and a considerable amount of estate is being spent today for invention and application of new technology. Various nations, including the United States, have been improving their systems of security through public services; public police department is actively carrying out their duties in airports as well. In San Francisco International Airport, private police department is in charge of collection of data, national events, VIP protection, law enforcement, cooperation within facilities, daily-based patrol and traffic control. Under guidance and supervision of national organizations, such as TSA, general police department interprets X-Rays, operates metal detectors, checks passports or IDs and observes reactions to explosives. Under these circumstances, studies about advancement of cooperation and duties of general police department and private police department necessitated: especially about private police department and their training for searching equipments, decrease in number of turn over rate, invention of technology and prior settlement in estate for security. The privacy of the public, who make up the major population of airport passengers, must also be minimized. In the following research, the activities of police departments in San Francisco International Airport will be analyzed in order to understand recent actions of the United States on airport security.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.