• Title/Summary/Keyword: Forecasting Ability

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An Empirical Study for the Cognition of the Convergence Human Resource for the companies - focus on the Firms in Deajeon Region - (융합형 인재에 대한 기업의 인식 분석 연구 - 대전지역 기업을 중심으로 -)

  • Seo, Yong-Mo;Shim, Sang-Oh;Kim, Eung-Kyu;Choi, Jong-In
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.5
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    • pp.2045-2053
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    • 2012
  • The primary purpose of this paper is to identify the cognition of the convergence human resource for firms. For this purpose, Data have been collected from 110 firms in Daejeon city and studied the convergence human resource which recognized by firms on the company competitive power level. The results of this empirical studies are summarized as fellows. We classified in company competitive power as leading chaser, innovators and late chaser. In the talent, leading chasers demanded the total designer, problem solver and insighter, innovators demanded the total designer, problem solver and specialist, and late chasers demanded the traditional humanity. In technology management, all group think important fields. In the demanding forecasting for the market and technologies, leading chasers and innovators demanded the CEO, R&D researcher and a middle manager as the important position. For this education, they demanded the convergence ability of other technologies, the up-to-date abilities of product and technology and the understandings of market needs. In the convergence talent or leader, leader chaser and innovator demanded the specialist who attempted to combine others industries, who know well in technology and management, and the specialist who attempted to combine others technologies. But, late chaser demanded the specialist who attempted to combine others industries.

Analysis of Airborne LiDAR-Based Debris Flow Erosion and Deposit Model (항공LiDAR 자료를 이용한 토석류 침식 및 퇴적모델 분석)

  • Won, Sang Yeon;Kim, Gi Hong
    • Journal of Korean Society for Geospatial Information Science
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    • v.24 no.3
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    • pp.59-66
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    • 2016
  • The 2011 debris flow in Mt. Umyeonsan in Seoul, South Korea caused significant damages to the surrounding urban area, unlike other similar incidents reported to have occurred in the past in the country's mountainous regions. Accordingly, landslides and debris flows cause damage in various surroundings, regardless of mountainous area and urban area, at a great speed and with enormous impact. Hence, many researchers attempted to forecast the extent of impact of debris flows to help minimize the damage. The most fundamental part in forecasting the impact extent of debris flow is to understand the debris flow behavior and sedimentation mechanism in complex three-dimensional topography. To understand sedimentation mechanism, in particular, it is necessary to calculate the amount of energy and erosion according to debris flow behavior. The previously developed debris flow models, however, are limited in their ability to calculate the erosion amount of debris flow. This study calculated the extent of damage caused by a massive debris flow that occurred in 2011 in Seoul's urban area adjacent to Mt. Umyeonsan by using DEM, created from aerial photography and airborne LiDAR data, for both before and after the damage; and developed and compared a debris flow behavioral analysis model that can assess the amount of erosion based on energy theory. In addition, simulations using the existing debris flow model (RWM, Debris 2D) and a comprehensive comparison of debris flow-stricken areas were performed in the same study area.

Estimation Model for Freight of Container Ships using Deep Learning Method (딥러닝 기법을 활용한 컨테이너선 운임 예측 모델)

  • Kim, Donggyun;Choi, Jung-Suk
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.5
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    • pp.574-583
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    • 2021
  • Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

A Study on Evaluation System of Risk Assessment at Coastal Activity Areas (연안활동장소의 위험도 평가체계 수립 연구)

  • Park, Seon Jung;Park, Seol Hwa;Seo, Heui Jung;Park, Seung Min
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.33 no.6
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    • pp.226-237
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    • 2021
  • Coastal safety accidents are characterized by a high proportion of human negligence and repeated occurrences of accidents caused by the same factors. The Korea Coast Guard prepares and implements various countermeasures to prevent accidents at coastal safety accident sites. However, there is a shortage of safety facilities and safety management personnel according to the limited budget. In addition, the ability to be proactively and proactively respond is low due to the limitations of the coastal safety accident risk forecasting system, which relies on the meteorological warning of the Korea Meteorological Administration. In this study, as part of preparing the foundation for establishing a preemptive and active coastal safety management system that can manage accident-causing factors, predict and evaluate risk, and implement response and mitigation measures after an accident occurs before coastal safety accidents occur. The establishment of a risk assessment system was proposed. The main evaluation factors and indicators for risk assessment were established through the analysis of the status of coastal safety accidents. The risk assessment methodology was applied to 40 major hazardous areas designated and managed by the Korea Coast Guard.

China and global leadership (Китай и глобальное лидерство)

  • Mikheev, Vasily;Lukonin, Sergey;Ignatev, Sergei
    • Analyses & Alternatives
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    • v.1 no.2
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    • pp.31-43
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    • 2017
  • The article is devoted to the theoretical and practical analysis of Chinese global leadership. The concept of leadership is applied as a methodology, which involves identifying the main factors, such as strategic power, the attractiveness of political institutions, the ability to provide acceptable ideas and the presence of allies that contribute to a comprehensive analysis of the country's leadership potential. The authors also describe the relevance of Chinese global leadership and analyze its domestic, economic and international causes. Moreover, the ''Belt and Road'' initiative is defined as the main mechanism for providing the influence of China on the global level which is now being changed its quantitative component, namely the increasing attention to the security aspects of this initiative. In addition to that, it is important to note that China maintains its economic and political positions in Africa, Central Asia and South-East Asia. Africa has a special role in the Chinese ''Belt and Road'' initiative as a recipient of Chinese investments and a site for the deployment of China's naval facilities to protect the trade routes. On the regional level, China will strive to become a leader of the trade and economic processes in the Asia-Pacific region, the South China Sea and the North Korea nuclear program issues. The American factor in modern international relations, namely so-called "Trump factor", which means the U.S. withdrawal from the Trans-Pacific Partnership and the Paris Agreement, will cause demand for Chinese leadership in the Asia-Pacific region and in the world as well. However, in this case a number of questions arise: is China prepared for this? Is Beijing able to bear greater responsibility? Does China have the potential for this? The article concludes that China will not become global leaders in the next 20-30 years, because of internal (political reforms) and foreign policy reasons (doctrinal formulation of foreign policy initiatives, military-political and economic power, international posture and relations with other states). The authors believe that the implementation of Chinese leadership is possible not on the condition of confrontation between China and the United States, but on the establishing of constructive relations between these countries. The last meeting between Trump and Xi Jinping showed a trend for creating channels for dialogue between Beijing and Washington, which can become the basis for interaction. An important place in the work is given to the analysis of development and forecasting the evolution of Russian-Chinese and U.S.-China relations. As for Russia, Moscow should conduct a policy that will not allow it to become a ''junior partner'' of China.

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Estimation of Long-term Water Demand by Principal Component and Cluster Analysis and Practical Application (주성분분석과 군집분석을 이용한 장기 물수요예측과 활용)

  • Koo, Ja-Yong;Yu, Myung-Jin;Kim, Shin-Geol;Shim, Mi-Hee;Akira, Koizumi
    • Journal of Korean Society of Environmental Engineers
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    • v.27 no.8
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    • pp.870-876
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    • 2005
  • The multiple regression models which have two factors(population and commercial area) have been used to forecast the water demand in the future. But, the coefficient of population had a negative value because proper regional classification wasn't performed, and it is not reasonable because the population must be a positive factor. So, the regional classification was performed by principal component and cluster analysis to solve the problem. 6 regional characters were transformed into 4 principal components, and the areas were divided into two groups according to cluster analysis which had 4 principal components. The new regression models were made by each group, and the problem was solved. And, the future water demands were estimated by three scenarios(Active, moderate, and passive one). The increase of water demand ore $89.034\;m^3/day$ in active plat $49,077\;m^3/day$ in moderate plan, and $19,996\;m^3/day$ in passive plan. The water supply ability as scenarios is enough in water treatment plant, however, 2 reservoirs among 4 reservoirs don't have enough retention time in all scenarios.