• Journal of Navigation and Port Research
• /
• v.46 no.4
• /
• pp.385-391
• /
• 2022

In this study, a multivariate time series analysis was conducted to identify various variables that impact ocean freight rates in addition to supply and demand factors. First, we used the ClarkSea Index, Clarksons Average Bulker Earnings, and Clarksons Average Tanker Earnings provided by the Shipping Intelligence as substitute variables for the dependent variable, ocean freight. The following ndependent variables were selected: World Seaborne Trade, World Fleet, Brent Crude Oil Price, World GDP Growth Rate, Industrial Production (IP OECD) Growth Rate, Interest Rate (US$ LIBOR 6 Months), and Inflation (CP I OECD) through previous studies. The time series data comprise annual data (1992-2020), and a regression analysis was conducted. Results of the regression analysis show that the World Seaborne Trade and Brent Crude Oil P rice impacted the ClarkSea Index. Only the World Seaborne Dry Bulk Trade impacted the Clarksons Average Bulker Earnings, World Seaborne Oil Trade, Brent Crude Oil Price, IP, and CP I on the Clarksons Average Tanker Earnings.

• Journal of the Korea Safety Management & Science
• /
• v.24 no.3
• /
• pp.39-46
• /
• 2022

This study has found the socio-economic factors that affect occupational accidents and measured the influence quantitatively. We built the panel data of 4 countries (Japan, Germany, the U.S., and the U.K.) and the analysis model counted on the fixed effect model to reflect the countries' differences. The fatal occupational injury rates in the analyzed countries had a statistically significant relationship with the level of per capita GDP, the proportion of the construction industry, the rate of male workers, annual average working hours, the rate of workers in manufacturing and construction industries, etc. The annual average working hours have a positive correlation with the fatal occupational injury rate. To reduce occupational accidents effectively, we should be monitoring and researching various factors that can affect the occurrence of occupational accidents such as worker characteristics, changing industrial structure, and changes in working hours.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.3A
• /
• pp.163-171
• /
• 2012

The signal model and weighted-average based estimation techniques are proposed to estimate the angle-of-arrival (AOA) parameters of multiple clusters for a low data rate ultrawide band (LR-UWB) based wireless positioning system. It is observed that the weighted-average based AOA estimation technique gives an optimal AOA estimate under few clusters condition, and the average based AOA estimation technique gives a correct AOA estimate under many clusters condition through computer simulation. Also, we can observe that the variance estimation error decreases as SNR increases, and the proposed techniques are superior to the conventional technique from the viewpoint of performance.

• Journal of Computing Science and Engineering
• /
• v.5 no.4
• /
• pp.338-345
• /
• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

• Journal of the Korean Society of Safety
• /
• v.22 no.6
• /
• pp.46-54
• /
• 2007

The purpose of this study was to examines the burning rate of fire retardant treated wood in the cone heater with a one-dimensional integral model. The wood samples used in this study were four species. The species of woods are Redwood, White oak, Douglas fir and Maple. Each sample was nominally 50mm thick and 100mm square. Samples were exposed to a range of incident heat fluxes 10 to $35kW/m^2$ using the cone heater. A one-dimension integral model has been used to predict burning rate, heat of gasification, flame heat fluxes, charring rate and char depth of samples. As a result measurement of mass loss rate, softwoods(Redwood and Douglas fir) has relatively low value than those for hardwoods(White oak and Maple). Average charring rate of woods in case of fire retardant treatment showed reduction effect of 41.29%, 50.00%, 48.18% and 60.82% for Redwood, Douglas fir, White fir and Maple, respectively. Almost all the predictions from integral model showed faster charring than those measured. Average difference between predictions and experimental data was 16%, 9.5% and 11.8% for N, F1 and F2 respectively. Water-soluble fire retardant used in this study find out more effect in hardwood than softwood from the result of measurement of mass loss rate and average charring rate.

• Journal of Wetlands Research
• /
• v.25 no.2
• /
• pp.75-82
• /
• 2023

Data for measuring the flow rate of streams are used as important basic data for the development and maintenance of water resources, and many experts are conducting research to make more accurate measurements. Especially, in Korea, monsoon rains and heavy rains are concentrated in summer due to the nature of the climate, so floods occur frequently. Therefore, it is necessary to measure the flow rate most accurately during a flood to predict and prevent flooding. Thus, the U.S. Geological Survey (USGS) introduces 1, 2, 3 point method using a flow meter as one way to measure the average flow rate. However, it is difficult to calculate the average flow rate with the existing 1, 2, 3 point method alone.This paper proposes a new 1, 2, 3 point method formula, which is more accurate, utilizing one probabilistic entropy concept. This is considered to be a highly empirical study that can supplement the limitations of existing measurement methods. Data and Flume data were used in the number of holesman to demonstrate the utility of the proposed formula. As a result of the analysis, in the case of Flume Data, the existing USGS 1 point method compared to the measured value was 7.6% on average, 8.6% on the 2 point method, and 8.1% on the 3 point method. In the case of Coleman Data, the 1 point method showed an average error rate of 5%, the 2 point method 5.6% and the 3 point method 5.3%. On the other hand, the proposed formula using the concept of entropy reduced the error rate by about 60% compared to the existing method, with the Flume Data averaging 4.7% for the 1 point method, 5.7% for the 2 point method, and 5.2% for the 3 point method. In addition, Coleman Data showed an average error of 2.5% in the 1 point method, 3.1% in the 2 point method, and 2.8% in the 3 point method, reducing the error rate by about 50% compared to the existing method.This study can calculate the average flow rate more accurately than the existing 1, 2, 3 point method, which can be useful in many ways, including future river disaster management, design and administration.

• The Journal of Fisheries Business Administration
• /
• v.36 no.2 s.68
• /
• pp.97-120
• /
• 2005

This study focused on manufactures of meat and fish products among food manufactures, made a time series data for the period from 1983 to 2002, and applied the data to Hecksher-Ohlin model to analyze the elements of pattern of export in food processing industries of Korea. The results are as follows; First, the average annual growth rate of constant exports has increased for meat product and fish product industries in Korea. But, for fish product industries, it has decreased at large since the mid-1990s. Second, the average annual growth rate of physical capital index has increased for meat product and fish product industry, The rate has been more higher for fish product industry than for meat product industry. Third, the average annual growth rate of labor index has decreased for both meat and fish products industries. Fourth, physical capital index has had no significant impact on constant exports for meat product industry, while labor index has had a significant impact on it. Fifth, physical capital index has had a significant impact on constant exports for fish product industry, while labor index has had no significant impact on it.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.23 no.11
• /
• pp.1272-1279
• /
• 2012

In this paper, models for the average-year rain rate distribution and the correlation between the worst-month and the average-year rain rate distribution in domestic environment were proposed, using the rainfall measurement data with 1-minute integration time of Korea Meteorological Administration. Comparison of the proposed model with the existing ITU-R model showed that the average rain rate of the proposed model for the exceed time rate of 0.01 % is about 28 % higher than that of the ITU-R recommendation. In addition, the correlation model between the worst-month and the average-year rain rate distribution was quite different from the ITU-R model. It is recommended that the domestic rain rate distribution model should be used for calculation of the statistical characteristics of rain attenuation(exceeded-time-rate distribution of rain attenuation) which is essential for the design of wireless communication systems in domestic environment.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.773-782
• /
• 2004

In this paper, a random shock model for a system is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arriving according to another Poisson process of rate $\lambda$ repairs the system only if the state of the system is below a threshold $\alpha$. After assigning various costs to the system, we calculate the long-run average cost and show that there exist a unique value of arrival rate $\lambda$ and a unique value of threshold $\alpha$ which minimize the long-run average cost per unit time.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.11
• /
• pp.1407-1413
• /
• 2019

In this paper, we assume that another transmitter can transmit its data signal in the same frequency band in order to maximize the frequency efficiency of non-orthogonal multiple access(NOMA) systems. We also focus on the improvement in fairness performance of receiver's data rates, not the maximization of sum data rate for NOMA systems. Thus, in this paper, we propose a power allocation scheme to enhance the fairness performance of average data rates of receivers considering the NOMA systems in the presence of interference. Assuming Rayleigh fading channels, the average data rates of receivers are defined, and the power allocation coefficients to improve the data-rate fairness are derived by using high signal-to-noise power ratio approximation. In addition, through simulations, it is shown that the proposed power allocation scheme can improve the data-rate fairness in the NOMA system with interference.