• Journal of the Korea Institute of Building Construction
• /
• v.24 no.2
• /
• pp.273-284
• /
• 2024

This study investigates the impact of international oil price fluctuations on overseas construction orders secured by domestic and foreign companies. The analysis employs statistical data spanning the past 20 years, encompassing international oil prices, overseas construction orders from domestic firms, and new overseas construction orders from the top 250 global construction companies. The correlation between these variables is assessed using correlation coefficients(R), determination coefficients(R²), and p-values. The results indicate a strong positive correlation between international oil prices and overseas construction orders. The correlation coefficient between domestic overseas construction orders and oil prices is found to be 0.8 or higher, signifying a significant influence. Similarly, a high correlation coefficient of 0.76 is observed between oil prices and new orders from leading global construction companies. Further analysis reveals a particularly strong correlation between oil prices and overseas construction orders in Asia and the Middle East, potentially due to the prevalence of oil-related projects in these regions. Additionally, a high correlation is observed between oil prices and orders for industrial facilities compared to architectural projects. This suggests an increase in plant construction volumes driven by fluctuations in oil prices. Based on these findings, the study proposes an entry strategy for navigating oil price volatility and maintaining competitiveness in the overseas construction market. Key recommendations include diversifying project locations and supplier bases; utilizing hedging techniques for exchange rate risk management, adapting to local infrastructure and market conditions, establishing local partnerships and securing skilled local labor, implementing technological innovations and digitization at construction sites to enhance productivity and cost reduction The insights gained from this study, coupled with the proposed overseas expansion strategies, offer valuable guidance for mitigating risks in the global construction market and fostering resilience in response to international oil price fluctuations. This approach is expected to strengthen the competitiveness of domestic and foreign construction firms seeking success in the international arena.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.12 no.3
• /
• pp.170-177
• /
• 2007

In this study, the long-term predictability of El Nino and La Nina events of Pusan National University Coupled General Circulation Model(PNU/CME CGCM) developed from a Research and Development Grant funded by Korea Meteorology Administration(KMA) was examined in terms of the correlation coefficients of the sea surface temperature between the model and observation and skill scores at the tropical Pacific. For the purpose, long-term global climate was hindcasted using PNU/CME CGCM for 12 months starting from April, July, October and January(APR RUN, JUL RUN, OCT RUN and JAN RUN, respectively) of each and every years between 1979 and 2004. Each 12-month hindcast consisted of 5 ensemble members. Relatively high correlation was maintained throughout the 12-month lead hindcasts at the equatorial Pacific for the four RUNs starting at different months. It is found that the predictability of our CGCM in forecasting equatorial SST anomalies is more pronounced within 6-month of lead time, in particular. For the assessment of model capability in predicting El Nino and La Nina, various skill scores such as Hit rates and False Alarm rate are calculated. According to the results, PNU/CME CGCM has a good predictability in forecasting warm and cold events, in spite of relatively poor capability in predicting normal state of equatorial Pacific. The predictability of our CGCM was also compared with those of other CGCMs participating DEMETER project. The comparative analysis also illustrated that our CGCM has reasonable long-term predictability comparable to the DEMETER participating CGCMs. As a conclusion, PNU/CME CGCM can predict El Nino and La Nina events at least 12 months ahead in terms of NIino 3.4 SST anomaly, showing much better predictability within 6-month of leading time.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.26 no.2
• /
• pp.399-415
• /
• 1999

From bacteria to mammalian cells, one of the most important mediators of intracellular signal transduction mechanisms which regulate a variety of intracellular processes is free calcium. In salivary acinar cells, elevation of intracellular calcium concentration ($[Ca^{2+}]_i$) is essential for the salivary secretion induced by parasympathetic stimulation. However, in addition to $[Ca^{2+}]_i$, gap junctions which couple individual cells electrically and chemically have also been reported to regulate enzyme secretion in pancreatic acinar cells. Since the plasma membrane of salivary acinar cells has a high density of gap junctions, and these cells are electrically and chemically coupled with each other, gap junctions may modulate the secretory function of salivary glands. In this respect, I planned to investigate the role of gap junctions in the modulation of salivary secretion and $[Ca^{2+}]_i$, using mandibular salivary glands of rats. In order to measure the salivary flow rate, fluid was collected from the cannulated duct of the isolated perfused rat mandibular glands at 2 min intervals. $[Ca^{2+}]_i$, was measured from the cells loaded with fura-2 by spectrofluorometry. The results obtained were as follows: 1. CCh-induced salivary secretion was reversibly inhibited by 1 mM octanol, a gap junction blocker. 2. CCh-induced increase in $[Ca^{2+}]_i$, was also reversed by the application of 1 mM octanol. 3. Octanol did not block the initial increase in $[Ca^{2+}]_i$ caused by CCh, which suggested that the reduction of $[Ca^{2+}]_i$, caused by gap junction blockade was not resulted from the inhibition of $Ca^{2+}$ release from intracellular $Ca^{2+}$ stores. 4. Addition of octanol during stimulation with $1{\mu}M$ thapsigargin, a potent microsomal ATPase inhibitor, reduced $[Ca^{2+}]_i$, to the basal level. This suggested that inhibition of gap junction permeability closed plasma membrane $Ca^{2+}$ channels. 5. 2,5-di-tert-butyl-1,4-benzohydroquinone (TBQ) generated $[Ca^{2+}]_i$ oscillations resulting from periodic influx of $Ca^{2+}$ via plasma membrane. The TBQ-induced $[Ca^{2+}]_i$ oscillations were stopped by the application of 1mM octanol which implicated that gap junctions modulate the permeability of plasma membrane $Ca^{2+}$ channels. 6. Glycyrrhetinic acid, another well known gap junction blocker, also inhibited CCh-induced salivary secretion from rat mandibular glands. These results suggested that gap junctions play an important role in the modulation of fluid secretion from the rat mandibular glands and this was probably due to the inhibition of $Ca^{2+}$ influx through the plasma membrane $Ca^{2+}$ channels.

• Economic and Environmental Geology
• /
• v.45 no.6
• /
• pp.643-659
• /
• 2012

The Chungju Fe-REE deposit is located in the Kyemyeongsan Formation of the Ogcheon Group. The Kyemyeongsan Formation includes meta-volcanic rocks and pegmatite hosted REE deposit which show different kind of REE-containing minerals. The meta-volcanic rocks hosted REE deposits' main REE minerals are allanite, zircon, apatite, and sphene, whereas the pegmatite hosted REE deposits is mainly composed of fergusonite, and karnasurtite, zircon, thorite. The meta-volcanic rock hosted major REE mineral is allanite as the form of aggregation and contains 23.89-29.19 wt% TREO (Total Rare Earth Oxide), 4.71-9.92 wt% $La_2O_3$, 11.30-14.33 wt% $Ce_2O_3$, 0.11-0.29 wt% $Y_2O_3$, 0.15-0.94 wt% $ThO_2$, as a formula of (Ca, Y, REE, Th)$_{2.095}$(Mg, Al, Ti, Mn, $Fe^{3+})_{2.770}(SiO_4)_{2.975}(OH)$. Accompanying REE in a coupled substitution for $Ca^{2+}$ (M1 site) and $Al^{3+}-Fe^{2+}$ (M2 site) leads to a large chemical variety. Due to the allanite's high contents of Fe, it belongs to Ferrialanite. The pegmatite hosted deposit's domi-nant REE mineral is fergusonite as prismatic or subhedral grains associated with zircon, fluorite and karnasurtite. Geochemical composition of the fergusonite($YNbO_4$) suggests substitution of Y-REE and Y-Th in A-site, and Nb-Ta-Ti in B-site, furthermore the proportion of $Y_2O_3$ and $Nb_2O_5$ is oddly 1:1.5 comparing to the ideal ratio 1:1 and Nb is higher than Y, also A-site Y actively substitutes with REE. Karnasurtite in pegmatite variously ranges 9.16-22.88 wt% $Ce_2O_3$, 2.15-9.16 wt% and $La_2O_3$, 0.44-10.8 wt% $ThO_2$, as a calculated formula (Y, REE, Th, K, Na, Ca)$_{1.478}(Ti, Nb)_{1.304}$(Mg, Al, Mn, $Fe^{3+})_{0.988}$(Si, P)$_{1.431}O_7(OH)_4{\cdot}3H_2O$. Firstly the 870-860 Ma is the initial age of the supercontinent Rhodinia dispersal and subsequent A-1 type volcanism, which contains Fe, REE, and HFS(High Field Strength elements; Nb, Zr, Y etc.) elements in Fe-rich meta-volcanic rocks dominant Kyemyeongsan Formation, might mineralized allanite. Another synthesis is that regional metamorphism at late Paleozoic 300-280 Ma(Cho et al., 2002) might cause allanite mineralization. Also pegmatite REE mineralization highly related to the granite intrusion over the Chungju area in Jurassic(190 Ma; Koh et al., 2012). Otherwise above all, A-1 type volcanism at the same time of the Kyemyeongsan Formation development, regional metamorphism and pegmatite, might have caused REE mineralization. Although REE ore bodies display a close spatial association, each ore bodies display temporal distinction, different mineral assemblage and environment of ore formation.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.171-193
• /
• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.

• Journal of Food Hygiene and Safety
• /
• v.26 no.4
• /
• pp.322-329
• /
• 2011

This study was done to analyze the contents of minerals and vitamins to compare the measured values of minerals, vitamins with labeled values of them in food labeling and to investigate the ratio of measured values to labeled values in 437 specimen with minerals and vitamins - fortified commercial beverages and liquid teas. Content of calcium and sodium in samples after microwave digestion was analyzed with an ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometer) and vitamins were determined using by HPLC (High Performance Liquid Chromatography). The measured values of calcium were ranged 80.3~142.6% of the labeled values in 21 samples composed calcium - fortified commercial beverages and liquid teas. In case of sodium, measured values were investigated 33.9~48.5% of the labeled values in 21 sports beverages. The measured values of vitamin C, vitamin $B_2$ and niacin were ranged 99.7~2003.6, 81.1~336.7, 90.7~393.2% of the labeled values in vitamins - fortified commercial beverages and liquid teas, 57, 12, 11 samples. To support achievement of the accurate nutrition label, there must be program and initiatives for better understanding and guidances on food labelling and nutrition for food manufacture.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.51-69
• /
• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.35-48
• /
• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Food Hygiene and Safety
• /
• v.27 no.4
• /
• pp.375-387
• /
• 2012

The objective of this study is investigation of contamination levels and assessment of health risk effects of heavy metals in herbal pills. 31 Items and 93 samples were obtained for this investigation from major herbal medicine producing areas, herbal markets and on-line supermarkets from Jan to Jun in 2010. Inductively coupled plasma mass spectrometer method was conducted for the quantitative analysis of Pb, Cd and As. In addition, the mercury analyzer system was conducted for that of Hg without sample digestion. The average contents of heavy metals in samples were as follows : 0.87 mg/kg for Pb, 0.08 mg/kg for Cd, 2.87 mg/kg for As and 0.16 mg/kg for Hg, respectively. In addition, the average contents of heavy metals in different parts of plants, including cortex, fructus, herba, radix, seed, algae and others were 0.63 mg/kg, 3.94 mg/kg, 1.42 mg/kg, 1.05 mg/kg, 0.16 mg/kg, 22.31 mg/kg and 10.17 mg/kg, respectively. After the estimations of dietary exposure, the acceptable daily intake (ADI), the average daily dose (ADD), the provisional tolerable weekly intake (PTWI) and the relative hazard of heavy metals were evaluated. As the results, the relative hazards compared to PTWI in samples were below the recommended standard of JECFA as Pb 3.1%, Cd 0.9%, Hg 0.5%. Cancer risks through slope factor (SF) by Ministry of Environment Republic Korea and Environmental Protection Agency was $4.24{\times}10^{-7}$ for Pb and $3.38{\times}10^{-4}$ for As (assuming that the total arsenic content was equal to the inorganic arsenic). Based on our results, possible Pb-induced cancer risks in herbal pills according to parts used including cortex, fructus, herba, radix, seed, algae and others were $1.95{\times}10^{-7}$, $1.45{\times}10^{-6}$, $2.14{\times}10^{-7}$, $6.27{\times}10^{-7}$, $1.99{\times}10^{-8}$, $3.61{\times}10^{-7}$ and $9.64{\times}10^{-8}$, respectively. Possible As-induced cancer risks in herbal pills by parts used including cortex, fructus, herba, radix, seed, algae and others were $1.54{\times}10^{-5}$, $7.24{\times}10^{-5}$, $1.23{\times}10^{-4}$, $2.02{\times}10^{-5}$, $3.25{\times}10^{-6}$, $2.18{\times}10^{-3}$ and $5.67{\times}10^{-6}$ respectively. Taken together, these results indicate that the majority of samples except for some samples with relative high contents of heavy metals were safe.

• Korean Journal of Environmental Agriculture
• /
• v.37 no.4
• /
• pp.291-301
• /
• 2018

BACKGROUND: Rice is one of the main sources for inorganic arsenic among the consumed crops in the world population's diet. Arsenic is classified into Group 1 as it is carcinogenic for humans, according to the IARC. This study was carried out to assess dietary exposure risk of inorganic arsenic in husked rice and polished rice to the Korean population health. METHODS AND RESULTS: Total arsenic was determined using microwave device and ICP-MS. Inorganic arsenic was determined by ICP-MS coupled with HPLC system. The HPLC-ICP-MS analysis was optimized based on the limit of detection, limit of quantitation, and recovery ratio to be $0.73-1.24{\mu}g/kg$, $2.41-4.09{\mu}g/kg$, and 96.5-98.9%, respectively. The inorganic arsenic concentrations of daily exposure (included in body weight) were $4.97{\times}10^{-3}$ (${\geq}20$ years old) $-1.36{\times}10^{-2}$ (${\leq}2$ years old) ${\mu}g/kg\;b.w./day$ (PTWI 0.23-0.63%) by the husked rice, and $1.39{\times}10^{-1}$ (${\geq}20$ years old) $-3.21{\times}10^{-1}$ (${\leq}2$ years old) ${\mu}g/kg\;b.w./day$ (PTWI 6.47-15.00%) by the polished rice. CONCLUSION: The levels of overall exposure to total and inorganic arsenic by the husked and polished rice were far lower than the recommended levels of The Joint FAO/WHO Expert Committee on Food Additives (JECFA), indicating of little possibility of risk.