• Journal of Conservation Science
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• v.33 no.6
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• pp.399-416
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• 2017

The 'Wat Phou and Associated Ancient Settlements within the Champasak Cultural Landscape' of Laos was designated as a UNESCO World Cultural Heritage in 2001. The uppermost structure of the Sanctuary in Wat Phou has been destroyed and being variably damaged, maintenance is required through scientific and systematic diagnosis. The Sanctuary of Wat Phou was constructed mainly using sandstones and bricks. There are physical damages including fracture, break out, exfoliation and interval as well as biological damages by lichen, mosses and weeds. According to the ultrasonic velocity measurement and property evaluation of the sandstones of the Sanctuary in Wat Phou, weathering index of the eastern side sandstones is 0.10 to 0.74 (mean 0.36), showing MW grade. Southern and northern side sandstones have relatively higher properties with average weathering indices of 0.30 and 0.32. The results of slope analysis of the Sanctuary, indicated that the 4th spot in the southern side has the largest slope of $5^{\circ}W$, seemingly due to the unstable ground around the Sanctuary. Based on the relative level measurement and past drawings, the Sanctuary is verified to have been located on ground with a certain slope rather than flatland. The ground of the southern side is inclined $1.51^{\circ}$ more than that of the northern side, which will affect the structural stability of the temple. The interval width of the selected southern spot is the largest with an average width of 159.5 mm, and the largest width is 328.3 mm at the top, since the width increases above rather than below, seemingly due to the unequal subsidence of the ground. Constant maintenance for conservation is required for the structural stability of the Sanctuary in Wat Phou, which was partly collapsed and has also suffered physical damage.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.88-93
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• 2011

Purpose: As to analytical method of data, the AutoQUANT software in which it is used quantitative rating of the myocardial perfusion SPECT are reported that there is a difference. Therefore the measured value error of the mutual program is expected to be generated even if the quantitative analysis is made data of the same patient. The purpose of this study is to offer the comparative analysis of myocardial extract method in Quantitative Perfusion SPECT. Materials and methods: We analyzed the 51 patients who were examined by Tc-99m MIBI gated myocardial SPECT in nuclear medicine department of Pusan National University Hospital from June to December 2010(34 men, 17 women, mean age $66.5{\pm}9.9$). We acquired the extracted image in myocardial extract protocol. QPS program that uses the AutoQUANT software measured TID(Transient Ischemic Dilation), ESD(Extent of Stress Defect), SSS(Summed Stress Score). Then analyzed the results. Results: The correlation of appyling myocardial extract is TID(r=0.98), ESD(r=0.99), SSS(r=0.99). In the 95% confidence limit, there was no satistically significant difference(TID p=0.78, ESD p=0.31, SSS p=0.19). After blinding test with a physician for making a qualitative analysis, there was no difference. Conclusion: Quantitative indices in QPS program showed good correlation and the results showed no statistically signigicant difference. The variance between method was small. therefore, the functional parameters by each method can be used interchangeably. Also, we expect patient's satisfaction.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.191-204
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• 2010

Recently, the CO2 emission and energy consumption have become critical global issues to decide the future of nations. Especially, the spread of IT products and the increased use of internet and web applications result in the energy consumption and CO2 emission of IT industry though information technologies drive global economic growth. EU, the United States, Japan and other developed countries are using IT related environmental regulations such as WEEE(Waste Electrical and Electronic Equipment), RoHS(Restriction of the use of Certain Hazardous Substance), REACH(Registration, Evaluation, Authorization and Restriction of CHemicals) and EuP(Energy using Product), and have established systematic green business/IT strategies to enhance the competitiveness of IT industry. For example, the Japan government proposed the "Green IT initiative" for being compatible with economic growth and environmental protection. Not only energy saving technologies but energy saving systems have been developed for accomplishing sustainable development. Korea's CO2 emission and energy consumption continuously have grown at comparatively high rates. They are related to its industrial structure depending on high energy-consuming industries such as iron and steel Industry, automotive industry, shipbuilding industry, semiconductor industry, and so on. In particular, export proportion of IT manufacturing is quite high in Korea. For example, the global market share of the semiconductor such as DRAM was about 80% in 2008. Accordingly, Korea needs to establish a systematic strategy to respond to the global environmental regulations and to maintain competitiveness in the IT industry. However, green competitiveness of Korea ranked 11th among 15 major countries and R&D budget for green technology is not large enough to develop energy-saving technologies for infrastructure and value chain of low-carbon society though that grows at high rates. Moreover, there are no concrete action plans in Korea. This research aims to deduce the priorities of the Korean green business/IT strategies to use multi attribute weighted average method. We selected a panel of 19 experts who work at the green business related firms such as HP, IBM, Fujitsu and so on, and selected six assessment indices such as the urgency of the technology development, the technology gap between Korea and the developed countries, the effect of import substitution, the spillover effect of technology, the market growth, and the export potential of the package or stand-alone products by existing literature review. We submitted questionnaires at approximately weekly intervals to them for priorities of the green business/IT strategies. The strategies broadly classify as follows. The first strategy which consists of the green business/IT policy and standardization, process and performance management and IT industry and legislative alignment relates to government's role in the green economy. The second strategy relates to IT to support environment sustainability such as the travel and ways of working management, printer output and recycling, intelligent building, printer rationalization and collaboration and connectivity. The last strategy relates to green IT systems, services and usage such as the data center consolidation and energy management, hardware recycle decommission, server and storage virtualization, device power management, and service supplier management. All the questionnaires were assessed via a five-point Likert scale ranging from "very little" to "very large." Our findings show that the IT to support environment sustainability is prior to the other strategies. In detail, the green business /IT policy and standardization is the most important in the government's role. The strategies of intelligent building and the travel and ways of working management are prior to the others for supporting environment sustainability. Finally, the strategies for the data center consolidation and energy management and server and storage virtualization have the huge influence for green IT systems, services and usage This research results the following implications. The amount of energy consumption and CO2 emissions of IT equipment including electrical business equipment will need to be clearly indicated in order to manage the effect of green business/IT strategy. And it is necessary to develop tools that measure the performance of green business/IT by each step. Additionally, intelligent building could grow up in energy-saving, growth of low carbon and related industries together. It is necessary to expand the affect of virtualization though adjusting and controlling the relationship between the management teams.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.1-7
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• 2018

$^{68}Ga$ was eluted from a $^{68}Ge/^{68}Ga$ radionuclide generator. $^{68}Ga$ decays into $^{68}Zn$, with a half life=67.8min. The decay is 88.9 % by ${\beta}$+ and 11.1 % by EC. The main ${\beta}$+ decay (87.7 %) is to the ground level of $^{68}Zn$ and it is a pure positron emission branch. A small fraction decays ${\beta}$+ (1.2 %) into an excited level of $^{68}Zn$, which promptly decays into the ground level with a ${\gamma}$ (1.077 Mev). This can constitute prompt gamma contamination in the PET data, if the 1.077 Mev ${\gamma}$ has a scatter interaction in the patient, and generates a lower energy ${\gamma}$ in coincidence with the positron annihilation pair. The purpose of this study was to evaluate standardized uptake value(SUV) before and after applying prompt gamma rays correction on $^{68}Ga$-DOTATOC PET/CT image. Fifty patient underwent PET/CT 1 hour after injection of the $^{68}Ga$-DOTATOC. The SUVmax and SUVmean of lesions and normal tissues (Pituitary, Lung, Liver, Spleen, Kidney, Intestine) were evaluated before and after applying prompt gamma correction on $^{68}Ga$-DOTATOC PET/CT image. Additionally, the SUVmax of each lesions and SUVmean of the soft tissues were measured on images. and target to background ratios (TBR) were calculated as quantitative indices. Among 15 patients, 25 of lesions (Pancreas, Liver, Thoracic Spine, Brain) with increased uptake on $^{68}Ga$-DOTATOC PET/CT image. SUVmax and SUVmean were increased in lesion site and normal tissue after prompt gamma rays correction. TBR was $51.51{\pm}49.28$ and $55.50{\pm}53.12$ before and after prompt gamma rays correction, respectively. (p<0.0001)

• Investigative Magnetic Resonance Imaging
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• v.2 no.1
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• pp.14-30
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• 1998

Manganese is an essential element in the body. It is mainly deposited in the liver and to a lesser degree in the basal ganglia of the brain and eliminated through the bile duct. Rapid turnover of managanese in the body makes it difficult to evaluate the manganese exposure in workers, esecially in those with irregular or intermittent exposure, like welders. Therefore, conventional biomarkers, including blood and urine manganese can provide only a limited information about the long-tern or cumulative exposure to manganese. Introduction of magnetic resonance imaging (MRI) made a progress in the assessment of manganese exposure in the medical conditions related to manganese accumulation, e. g. hepatic failure and long-term total parenteral nutrition. Manganese shortens spin-lattice(T1) relaxation time on MRI due to its paramagnetic property, resulting in high signal intensity (HSI) on T1-weighted image(T1W1) of MRI. Manganese deposition in the brain, therefore, can be visualizedas an HSI in the globus pallidus, the substantia nigra, the putamen and the pituitary. clinical and epidemiologic studies regarding the MRI findings in the cases of occupational and non-occupational manganese exposure were reviewed. relationships between HSI on T1W1 of MRI and age, gender, occupational manganese exposure, and neurological dysfunction were analysed. Relationships betwen biological exposure indices and HSI on MRE werealso reviewed. Literatures were reviewed to establish the relationships between HSI, Manganese deposition in the brain, pathologic findings, and neurological dysfunction. HSI on T1W1 of MRI reflects regional manganese deposition in the brain. This relationship enables an estimation of regional manganese deposition in the brain by analysing MR signal intensity. Manganese deposition in the brain can induce a neuronal loss in the basal ganglia but functional abnormality is supposed to be related to the cumulative exposure of manganese in the brain, use of brain MRI for the assessment of exposure in a group of workers seems to be hardly rationalized, while ti can be a useful adjunct for the evaluation of manganese exposure int he cases with suspected manganese-related health problems.

• 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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.2
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• pp.81-89
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• 2023

Lime-treated fertilizer (LTF) is manufactured using the lime stabilization method with food waste. LTF is effective in neutralizing acidic soil, improving nutrient and organic matter content in soil, and increasing crop productivity. However, excessive use of LTF in agricultural land can have undesirable effects, such as reduced crop growth and nutrient accumulation in soil. This study was evaluated the effect of different application ratios of LTF on the crop yield index (%), nutrient (N, P₂O₅, K₂O) uptake index (%), and soil chemical properties. The following treatments were applied: untreated (UT), NPK (NPK), NPK+calcium hydroxide (CH), and NPK+1-, 2-, 4-, and 8-times of LTF (LTF1, 2, 4, and 8). The yield index for LTF1 was the highest among different LTF treatments. Moreover the yield index for spring and winter cabbage in LTF1 treatment was 10% and 21% higher, respectively, than that in NPK treatment. The yield and nutrient indices were decreased with the increase in LTF application ratio. The soil pH and EC tended to increase with the increase in LTF ratio, and were the highest at 8.2 and 2.1, respectively, after cultivation for LTF8 (P<0.05). With the increase in soil pH, the soil inorganic nitrogen (NH₄-N, NH₃-N) and available phosphate (Av. P₂O₅) levels were decreased (P<0.05). Our results suggest that LTF1 (643 kg 10a^-1) is an appropriate ratio for improving soil chemical properties and increasing crop yield.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.