• International conference on construction engineering and project management
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• 2007.03a
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• pp.653-661
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• 2007

Overseas construction projects tend to be more complex than domestic projects, being exposed to more external risks, such as politics, economy, society, and culture, as well as more internal risks from the project itself. It is crucial to have an early understanding of the project condition, in order to be well prepared in various phases of the project. This study compares a structural equation model and multiple regression analysis, in their capacity to predict cost performance of international construction projects. The structural equation model shows a more accurate prediction of cost performance than does regression analysis, due to its intrinsic capability of considering various cost factors in a systematic way.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.171-175
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• 2017

The purpose of the farmstead-specific early warning service system for weather risk management is to develop custom-made risk management recommendations for individual farms threatened by climate change and its variability. This system quantifies weather conditions into a "weather risk index" that is customized to crop and its growth stage. When the risk reaches the stage where it can cause any damage to the crops, the system is activated and the corresponding warning messages are delivered to the farmer's mobile phone. The messages are sent with proper recommendations that farmers can utilize to protect their crops against potential damage. Currently, the technology necessary to make the warning system more practical has been developed, including technology for forecasting real-time weather conditions, scaling down of weather data to the individual farm level and risk assessments of specific crops. Furthermore, the scientific know-how has already been integrated into a web-based warning system (http://new.agmet.kr). The system is provided to volunteer farmers with direct, one-on-one weather data and disaster warnings along with relevant recommendations. In 2016, an operational system was established in a rural catchment ($1,500km^2$) in the Seomjin river basin.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.17-27
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• 2007

Since early 1990s, several developed countries have applied the Electronic Toll Collection System (ETCS) to toll roads in order to solve traffic congestion and delay problems at toll plazas. For the successful operation of the ETCS, it is important to correctly forecast the ETCS using rate. In this study, it was conceived to develop a sophisticated demand forecasting model of the ETCS for toll roads in Changwon City The Binary Logit and neural network models were tested for the model considering 11 explaining variables. The best results in prediction accuracy and goodness-of-fit were obtained on the neural network model. However, because of the difficulty in predicting the 11 variables and its fitness in wide range, the Binary Logit model which considers three policy variables only is recommended as the model to forecast the ETCS using rate.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.791-793
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• 2013

Colorectal cancer is one of the most common cancers. The aim of this study is determination its trends in Kerman province and individual cities separately until year 2016. This analytical and modeling study was based of cancer registry data of Kerman University of Medical Sciences, collected during 2001-2010. Among 20,351 cancer case, 792 were colorectal cancer cases in age group 18-93 years with a mean of 59.4 and standard deviation of 15.1. By applying time series and data trends, incidences were predicted until 2016 for the province and each city, with adjustment for population size. In colorectal cases, 413 (52%) were male, and 379 (48%) were female. The annual increasing rate in Kerman province overall was and can be expected to be 6%, and in the cities of the province Rafsanjan, Bardsir, Bam, Kerman, Baft, Sirjan, Jiroft, Kahnuj and Manujan had an increasing range from 5 to 14% by the year 2016. But in Ravar, Zarand and Shahrbabak reduction in rates of at least 2% could be predicted. The time series showed that the trend of colorectal cancer in female will increase 15% and in male 7% by year 2016. Given the trend of this cancer is increasing so that resources will be consumed in the treatment of the patients, efforts shoudlbe focused on prevention and early diagnosis of the disease. Screening could have an important role leading to improved survival.

• Journal of Preventive Medicine and Public Health
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• v.53 no.3
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• pp.158-163
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• 2020

Objectives: In the current early phase of the coronavirus disease 2019 (COVID-19) outbreak, Bali needs to prepare to face the escalation of cases, with a particular focus on the readiness of healthcare services. We simulated the future trajectory of the epidemic under current conditions, projected the impact of policy interventions, and analyzed the implications for healthcare capacity. Methods: Our study was based on the first month of publicly accessible data on new confirmed daily cases. A susceptible, exposed, infected, recovered (SEIR) model for COVID-19 was employed to compare the current dynamics of the disease with those predicted under various scenarios. Results: The fitted model for the cumulative number of confirmed cases in Bali indicated an effective reproduction number of 1.4. Interventions have decreased the possible maximum number of cases from 71 125 on day 86 to 22 340 on day 119, and have prolonged the doubling time from about 9 days to 21 days. This corresponds to an approximately 30% reduction in transmissions from cases of mild infections. There will be 2780 available hospital beds, and at the peak (on day 132), the number of severe cases is estimated to be roughly 6105. Of these cases, 1831 will need intensive care unit (ICU) beds, whereas the number of currently available ICU beds is roughly 446. Conclusions: The healthcare system in Bali is in danger of collapse; thus, serious efforts are needed to improve COVID-19 interventions and to prepare the healthcare system in Bali to the greatest extent possible.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.407-414
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• 2014

The Internet is a highly distributed and complex system consisting of billion devices and has become the field of various kinds of conflicts during the last two decades. As a matter of fact, various actors utilise the Internet for illicit purposes, such as for performing distributed denial of service attacks (DDoS) and for spreading various types of aggressive malware. Despite the fact that numerous services provide information regarding the threat level of the Internet, they are mostly based on information acquired by their sensors or on offline statistical sampling of various security applications (antivirus software, intrusion detection systems, etc.). This paper introduces proactive threat observatory system (PROTOS), an open-source early warning system that does not require a commercial license and is capable of estimating the threat level across the Internet. The proposed system utilises both a global and a local approach, and is thus able to determine whether a specific host is under an imminent threat, as well as to provide an estimation of the malicious activity across the Internet. Apart from these obvious advantages, PROTOS supports a large-scale installation and can be extended even further to improve the effectiveness by incorporating prediction and forecasting techniques.

• Korean journal of applied entomology
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• v.48 no.1
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• pp.59-65
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• 2009

This study was conducted to determine pheromone trap type and height in forecasting populations of R. clavatus in soybean fields using pheromone. The most effective pheromone trap type and height in forecasting populations of R. clavatus were fish trap and 60 cm above ground. Ratio of R. clavatus adults female and male in soybean field was 1.5 to 1 and Piezodorus hybneri was also attracted to the aggregation pheromone trap of R. clavatus. Attractiveness of two stink bug species caught on synthesis pheromone of R. clavatus was surveyed with imported production and synthesized production. Imported pheromone attracted only adult of R. clavatus, but synthesized pheromone attracted both adult of R. clavatus and P. hybneri. Change of population of R. clavatus was observed using pheromone trap and sweeping method in soybean field. Adults of R. clavatus occurred from early August and the population reached its peak in early September when pheromone trap was used. In case of sweeping method, its fluctuation pattern was similar to that of pheromone trap.

• Economic and Environmental Geology
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• v.42 no.2
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• pp.143-152
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• 2009

Recent raw material prices fluctuation has been unexpectedly high and that made Korean economic activities to be depressed. Because most raw material supply in Korea depends upon oversea imports, unexpected raw material price fluctuation affects Korean industrial economies through macroeconomic variables. So Korean government enforces some political measures such as demand management and the supply-security assurance as long-range policies, and reservation and general early warning system as short-range policies. In short-range policies, it is necessary to be expected short term fluctuation. Up to recently, there have been many researches and most of those researches use parametric methods or time series analyses. Because those methods and analyses often generate inadequate relations among variables, it is possible that some consistent variables are left out or the results are misunderstood. This study, therefore, is aim to mitigate those methodological problems and find the relatively appropriate model for economic explanation. So that, in this paper, by using non-parametric signal approach method mitigating some shortages of previous researches and forecasting properly short-range prices fluctuation of non-ferrous materials are presented empirically.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.385-391
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• 2000

Recently, neural network research for forecasting the consecutive controlling rules of the future is being progressed, using the series data which are different from the traditional statistical analysis methods. In this paper, we suggest the pruning algorithm for the fast and exact weather forecast that excludes the hidden layer of the early optional designed nenral network. There are perform the weather forecast experiments using the 22080 kinds of weather data gathered from 1987 to 1996 for proving the efficiency of this suggested algorithm. Through the experiments, the early optional composed $26{\times}50{\times}1$ nenral network became the most suitable $26{\times}2{\times}1$ structure through the pruning algorithm suggested, in the optimum neural network $26{\times}2{\times}1$, in the case of the error temperature ${\pm}0.5^{\circ}C$, the average was 33.55%, in the case of ${\pm}1^{\circ}C$, the average was 61.57%, they showed more superior than the average 29.31% and 54.47% of the optional designed structure, also. we can reduce the calculation frequency more than maximum 25 times as compared with the optional sturcture neural network in the calculation frequencies.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.31-39
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• 2014

It has been a long time since cars had become important means of transportation in human life. Since 1970s, cars have been increasing steadily because of rising individual income and changing lifestyle toward leisure and convenience. The number of cars is just 1.8 per thousand populations in 1970s, however, in 2012, it has increased to 291.15. Forecasting the demand for cars would be useful to plan, construction or management in the field of motor industry, road building and establishing facilities. Our study predicts the demand of cars through estimating the growth curve model. Especially, we include ageing variables to forecasting identifying the effect of ageing on the demand of cars. The main findings are as follows. In 2045, the number of cars is expected to reach 486.8 per thousand populations with passing a primary saturation point at early 2020s. Also, due to effect of ageing, the predicted demand of cars is about 10% lower than in case of which if ageing effect not exist.