• Journal of Navigation and Port Research
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• v.41 no.4
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• pp.243-250
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• 2017

Seaports are not longer considered to be single entities for which the main activity is to load and discharge cargo, but rather as fundamental hubs within a complex supply chain serving global production networks. From a public perspective, they hold a key role in terms of their economic impact at the local, regional and national level by generating value added activity and employment. This issue is becoming increasingly pivotal for ports and their stakeholders. The objective of the study is to estimate a regression model of the value added activity and employment figures of 17 Italian ports for which there are no publications available. Concerning port system reform in Italy, the research intends to provide policy makers with a tool to measure the effects produced by ports and their importance to local communities and regions. The paper finds that in all Italian ports, the direct effects are larger than the indirect effects, and the bigger socio-economic effects are found in the biggest ports.

• Journal of the Korean GEO-environmental Society
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• v.12 no.10
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• pp.63-72
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• 2011

The high capacity bi-directional pile load test is an optimum pile load test method for high-rised buildings. Especially, a high pressure and double-acting bi-directional pile load testing, a special type of the high capacity bi-directional pile load test, is the most practical way to overcome limitations of loading capacities and constraints of field conditions, which was judged to be a very useful test method for requiring high loading capacities. Total of 2 high capacity bi-directional pile load tests(P-1 and P-2) were conducted in high-rised building sites in Korea. Based on the field load test results, the sufficiency ratio of loading capacities to design loads for P-1 and P-2 were 3.3 and 2.1, respectively. For P-2, the load test could not verify the design load if 1-directional loads applied slightly smaller than the actual applied load. Also, high capacity bi-directional pile load tests were difficult to determine an ultimate state of ground or piles, although the loads were applied until their maximum loads. Hence, finite element analyses were conducted to determine their ultimate states by calibrating and extrapolate with test results.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1918-1923
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• 2009

결정질 암반에서 지하수의 수리적 특성을 파악하기 위해 수행되고 있는 수리시험 방법은 정률법, 정압법, 순간주입(회복)법 등 세 가지로 구분할 수 있다. 본 연구에서 다루는 정압주입시험 (Constant Head Injection Test, CHIT)은 위의 정압법의 한 종류로 토목공학, 지질공학 분야에서 대상 구간의 투수계수 추정을 위해 널리 쓰이는 수리 시험이며, 이는 단일 패커나 이중패커를 이용하여 시험 구간을 격리하고, 격리된 구간에 일정한 압력으로 물을 주입하여 주입되는 물의 양을 파악함으로써, 시험 구간의 수리전도도(Hydraulic conductivity)를 산출하는 전통적인 수리시험이다. 본 연구에서는 수치실험을 통해 시험 구간 및 주입 압력의 크기 등 인위적인 요인에 의해 도출되는 투수계수가 어떻게 달라지는지에 대해 평가해 보았다. 일반적으로 단열 암반에서 수행한 정압주입시험의 해석에 있어 매질을 균질, 등방성 다공질이라는 가정으로 구간별 투수량계수를 산출하기 때문에, 다공성 매질의 지하수 유동을 모사하는 MODFLOW를 수치모사 코드로서 이용하였다. 시험구간의 크기 및 주입압력에 대한 민감도 분석 결과, 시험구간의 크기에 상관없이 수치모의에서 입력한 수리전도도 값에 비해 낮은 수리전도도 값이 산출되었으며, 주입 압력이 클수록 산출되는 수리전도도 값이 매질의 수리전도도 값과 차이가 났다. 민감도 분석 결과 현장수리시험에서 정압 주입시험에 의한 구간별 수리전도도 산출함에 있어 시험구간의 크기와 주입 압력 값에 대하여 고려해야 한다고 판단된다.

• Journal of Labour Economics
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• v.30 no.1
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• pp.31-53
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• 2007

This paper, using the sample of male workers in manufacturing industry from the HCCP (Human Capital Corporate Panel) data, analyzes the effects of trade union on the level and dispersion of wages. One of the advantages of the HCCP data is that it enables a researcher to control the effect of individual firm's 'ability to pay' on wage. All relevant variables controlled, the union effect is estimated to be 5-8%. Yet this figure seriously underestimates the wage advantage enjoyed by union workers, because union sets the "price" for experience low and the price for tenure high and at the same time extends tenure of workers by adopting strong employment protection policy. The paper also analyzes the effects of union on the wage inequality. The results are mixed: overall wage inequality is smaller in union sector while standard deviation is larger when all the personal characteristics are controlled.

• Tuberculosis and Respiratory Diseases
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• v.59 no.3
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• pp.279-285
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• 2005

Background : Ambient particles during Asian dust events are usually less than $10{\mu}m$ in size, and known to be associated with the adverse effects on the general population. There is little evidence linking Asian dust to adverse effects on the airways. In 2002, the authors found that particulate matter during Asian dust events had an effect on the symptoms and pulmonary function of patients with bronchial asthma. An aggravating factor might be that of a viral infection, but this remains unclear. Conversely, it has been speculated that African dust may carry the virus responsible for foot and mouth disease. Asian dust events are also likely to be responsible for transporting viruses, some of which are pathogenic, and common in many environments. Therefore, in this study, air samples were screened for the presence of viruses. Methods : Air samples were collected 20 times each during Asian dust events and under non-dust conditions, for at least 6 hours per sample, using a high volume air sampler (Sibata Model HV500F), with an airflow rate of 500L/min, between April and August 2003, and between April and August 2004. The samples were then screened for the presence of targeted viruses (Influenza A, B, Hog cholera virus, and Aphthovirus) using a polymerase chain reaction method. Results : One Asian dust event occurred between April and August 2003, and 3 between April and August 2004, with a 24 hour average PM10 level of $148.0{\mu}g/m^3$. The 24 hour average PM10 level was $57{\mu}g/m^3$. There was a significant difference in the PM10 concentration between dusty and clear days. No viruses (Influenza virus, Aphthovirus, and Hog cholera virus) were identified in the air samples obtained during the dusty days. Conclusions : Although no virus was detected in this study, further studies will be needed to identify suspected viruses carried during Asian dust events, employing more appropriate virus detection conditions.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.