The Yeongweol Group is a Lower Paleozoic mixed carbonate-siliciclastic sequence in the Taebaeksan Basin of Korea, and consists of five lithologic formations: Sambangsan, Machari, Wagok, Mungok, and Yeongheung in ascending order. Sequence stratigraphic interpretation of the group indicates that initial flooding in the Yeongweol area of the Taebaeksan Basin resulted in basal siliciclastic-dominated sequences of the Sambangsan Formation during the Middle Cambrian. The accelerated sea-level rise in the late Middle to early Late Cambrian generated a mixed carbonate-siliciclastic slope or deep ramp sequence of shale, grainstone and breccia intercalations, representing the lower part of the Machari Formation. The continued rise of sea level in the Late Cambrian made substantial accommodation space and activated subtidal carbonate factory, forming carbonate-dominated subtidal platform sequence in the middle and upper parts of the Machari Formation. The overlying Wagok Formation might originally be a ramp carbonate sequence of subtidal ribbon carbonates and marls with conglomerates, deposited during the normal rise of relative sea level in the late Late Cambrian. The formation was affected by unstable dolomitization shortly after the deposition during the relative sea-level fall in the latest Cambrian or earliest Ordovician. Subsequently, it was extensively dolomitized under the deep burial diagenetic condition. During the Early Ordovician (Tremadocian), global transgression (viz. Sauk) was continued, and subtidal ramp deposition was sustained in the Yeongweol platform, forming the Mungok Formation. The formation is overlain by the peritidal carbonates of the Yeongheung Formation, and is stacked by cyclic sedimentation during the Early to Middle Ordovician (Arenigian to Caradocian). The lithologic change from subtidal ramp to peritidal facies is preserved at the uppermost part of the Mungok Formation. The transition between Sauk and Tippecanoe sequences is recognized within the middle part of the Yeongheung Formation as a minimum accommodation zone. The global eustatic fall in the earliest Middle Ordovician and the ensuing rise of relative sea level during the Darrwillian to Caradocian produced broadly-prograding peritidal carbonates of shallowing-upward cyclic successions within the Yeongheung Formation. The reconstructed relative sea-level curve of the Yeongweol platform is very similar to that of the Taebaek platform. This reveals that the Yeongweol platform experienced same tectonic movements with the Taebaek platform, and consequently that both platform sequences might be located in a body or somewhere separately in the margin of the North China platform. The significant differences in lithologic and stratigraphic successions imply that the Yeongweol platform was much far from the Taebaek platform and not associated with the Taebaek platform as a single depositional system. The Yeongweol platform was probably located in relatively open shallow marine environments, whereas the Taebaek platform was a part of the restricted embayments. During the late Paleozoic to early Mesozoic amalgamations of the Korean massifs, the Yeongweol platform was probably pushed against the Taebaek platform by the complex movement, forming fragmented platform sequences of the Taebaeksan Basin.
This study examines the change of female labor market structure during the last several decades, focusing the effects of demographic factors such as declining fertility and increasing educational attainment of women. Women of the recent cohort tend to postpone their first marriages, to attain higher levels of education, and to have smaller number of children than women of the old cohort. This demographic trend results in the change of the population compositions in a way that population subgroups with high labor force participation have been increased. In addition, women of each population subgroup supply their labor in the market with higher rate than their old cohort counterparts. The labor force participation rate of highly educated women, and of married women has been increased faster than that of women with low education and of unmarried women. Although childbirth is still one of the most critical barrier for the women's participation, more and more women with young children tend to work for pay than ever before. In spite of the demographic change which is supportive to the increasing labor force participation, the Korean labor market have lost its female participants for the last year of the economic restructuring, reflecting demand-side factors as well as demographic factors are essential to determine the labor force participation of women.
This paper deals with a strategic investment decision model for improving investment profit in shipping industry. Despite the quantitative expansion of Korean shipping business, many shipping firms have suffered financial difficulties due to financial and operating risks that result from the characteristics of capital-intensive business as well as of volatility of shipping markets. As a result, managers in charge of making an investment decision, particularly in tramper business sector, are required to take both financial and operating risk factors into consideration. Put it differently, managers are strongly recommended to avoid these risks by ship asset play; buy-low and sell-high, which results in considerable capital gain and cost reduction. In addition, managers in shipping industry are also recommended to consider the ship chartering investment alternative when the freight markets show extreme volatility as the case of 2008 triggered by sub-prime mortgage financial crisis in USA. For example, the BDI suffered plunging down from 1000 in 2008 to 100 in 2010. Consequently, the 4th largest shipping company in Korea, DAEHAN Shipping Co., has collapsed primarily due to excessive tonnage expansion during the peak time of bulk market. In sum, the strategic investment decision model, suggested in this paper, is designed to include such factors as capital gain by asset play, timely chartering for alternative shipping service, and optimization of operating profit by tonnage adjustment in accordance with change in the shipping markets concerned.
Journal of the Korean Institute of Intelligent Systems
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v.17
no.4
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pp.563-568
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2007
This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.
The World Health Organization (WHO) declared the third pandemic in history after the Hong Kong flu and swine flu. The outbreak of Corona 19 dramatically reduced exchanges between countries, while rapid contagion created a time gap in economic fluctuations by country. In January 2020, the trade dispute between the US and China entered into a consensus phase, but the economic decoupling phenomenon caused by Corona 19 made it difficult for China to balance trade with the US and made it difficult to comply with the terms of the trade dispute agreement between the US and China. President Trump attributed the responsibility for the spread of Corona 19 to China, and pointed out that the cause of the economic downturn was the infringement of Chinese trade secrets and illegal copies, and protectionism arose. As a result, China protested fiercely, and the conflict with the United States deepened. The US has declared trade sanctions on Huawei and SMIC, which are key companies in China's semiconductor industry, and is predicting the risk of a disconnection of the semiconductor value chain between the US and China. The separation of the value chain of the semiconductor industry has the potential to have a big impact on the semiconductor industry, a structure that is highly specialized and monopolized by certain countries and companies in the value chain. This paper aims to deal with the risk of disconnection in the semiconductor value chain between the US and China reignited by Corona 19, the impact and change of the global semiconductor industry value chain, and the response strategies of Korean semiconductor companies.
The capital structure of the shipping business, which is characterized by its capital intensity and extreme market volatility, is closely related to long-term stability. Research in this area has been conducted mostly in the form of deriving the determinants of capital structure from company-wise financial ratios. This research, on the other hand, has a different approach to the topic. It identifies the relationship between actual cash profit and loss and other variables - i.e. actual vessel prices, interest rates and leverage ratio - by employing historical simulation. The result demonstrates that the P anamax cash profit shows 0 (break-even point) when the debt weight reaches 64.38% (debt ratio 180.74%) and the Cape, 73.04% (debt ratio 270.92%). Additionally, the ships of different types show a divided pattern for the pre- and post-'Super Boom'. It indicates that the business area and the market cycle should be considered when a leverage strategy is established. This research benefits shipping companies set a rational leverage strategy as well as delivers a reasonable guideline to government authorities for the development of a sound policy on shipping finance.
Journal of the Korean Institute of Landscape Architecture
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v.51
no.2
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pp.42-53
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2023
This paper explores the recent development of environmental aesthetics and critically examines the main agendas, claims, issues, and implications of everyday aesthetics, which is emerging as an important branch of environmental aesthetics. Environmental aesthetics began in the context of cultural change and environmentalism in the 1960s and expanded in the second half of the 20th century with a solid theoretical foundation. At the beginning of the 21st century, it entered a process of diversification of objects and subjects. Having reached academic maturity, environmental aesthetics has expanded into theoretical territory considering the urban environment and the human environment, providing practical coordinates as a discourse for planning and designing urban environments and landscapes. The most notable achievement of environmental aesthetics since the mid-2000s is the establishment of 'everyday aesthetics'. Yuriko Saito, who is leading the research on everyday aesthetics, expanded the objects and scope of aesthetic theory to everyday objects, events, activities, and environments. She excavates the microscopic and sensory aspects of everyday life, which have been overlooked by conventional art-centered aesthetics, through the lens of aesthetics. She reinterprets various layers of phenomena in contemporary urban landscapes and analyzes how the 'power of the aesthetic' hidden in everyday life profoundly affects the quality of life and the state of the world. Saito examines the appreciation of the distinctive characteristics and ambiance inherent in everyday objects and environments and proposes a 'moral-aesthetic judgment' to alert citizens to the environmental, social, and political consequences of everyday aesthetic appreciation and response. This paper identifies the issues and implications of everyday aesthetics as first, the expansion of aesthetics and the ambiguous everyday, second, the moral-aesthetic judgment and the aesthetics of care, and third, urban regeneration landscapes and aesthetic literacy. In particular, the moral virtues of everyday aesthetics that Saito proposes, such as care, thoughtfulness, sensitivity, and respect, provide a critical reference for the practice of contemporary urban regeneration landscapes. The 'aesthetic literacy' is a key concept demonstrating why an environmental aesthetics perspective is necessary to interpret everyday urban environments and landscapes.
Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.
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