• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.1-10
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• 2014

The characteristics of internet traffic was dramatically changed recently. Especially, the ratio of video traffic in internet network is highly increased. Because the video traffic changes the traditional interactive traffic transport into one way contents delivery, internet network pricing structure is not efficient to reflect this changes. The fundamental reason for these is the discontinuity between the cost and revenue of the internet traffic. Although the internet traffic is forecasted to grow highly, the revenue of network provider is not expected to increase as such. The present paper investigates various alternatives to improve the present business model and to accommodate traffic growth. Then, the desirable options is proposed to invoke the innovation and to reflect the price signal according to some criteria.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.617-620
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• 2017

The periodic monitoring of crop conditions and timely estimation of crop yield are of great importance for supporting agricultural decision-makings, as well as for effectively coping with food security issues. Remote sensing has been regarded as one of effective tools for crop condition monitoring and crop type classification. Since 2010, RDA (Rural Development Administration) has been developing technology for monitoring on crop condition using remote sensing and model. These special papers address recent state-of-the-art of remote sensing and geospatial technologies for providing operational agricultural information, such as, crop yield estimation methods using remote sensing data and process-oriented model, crop classification algorithm, monitoring and prediction of weather and climate based on remote sensing data,system design and architecture of crop monitoring system, history on rice yield forecasting method.

• Journal of Korean Society of Forest Science
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• v.50 no.1
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• pp.29-35
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• 1980

The purpose of this study is to analyze and to forecast the long-term domestic demand and export demand for timber in Korea by regression models with time series data during 1962~1978. The method applied in this study was econometric analysis using Time Series Processor. The most important explanatory variables of timber demand were found to be the production activities of wood products industries to the prices of substitute goods. On the basis of the long-term forecast made according to the guidelines of the Fifth Five-Year Plan. According to the projection, domestic timber demand is projected at 8 million cubic meters in 1987 and 10.6 million cubic meters in 1991. On the other hand, the total demand (domestic demand plus export demand) for timber is projected 21.4 million cubic meters in 1987 and 27.2 million cubic meters in 1991.

• Journal of the Korea Concrete Institute
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• v.20 no.5
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• pp.627-634
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• 2008

This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.213-218
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• 2017

High-voltage power systems operate in order to generate and transmit electric power at power stations. Compared to low-power systems, high-power systems are complex in structure, large-scale, and expensive. When high-power cable accidents occur, most facilities are incapacitated-including low-power systems-causing huge economic losses. Great care must therefore be taken in designing, installing and managing power systems. Although dependent on installation circumstances and usage conditions, in some cases the cross-sectional areas of cables fall short of the critical area due to the expansion of and improper design and installation of power facilities. In this situation, the exceeded ampacity (allowable current) above the critical value caused by the operating current initiates the deterioration processes of power cables. In order to systematically monitor power cables operating at power stations, we have developed the first device of its kind in Korea. In this paper, we present the analyzed characteristics of expected temperatures of cables based on the load current of high-voltage cables operating at Korean Western Power Co. Ltd. We can predict the lifetime of cables by analyzing the temperature obtained from our device.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.167-177
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• 2019

The enhancement of national competitiveness in future society is the discovery and training of excellent SW convergence gifted. In order to cultivate these SW convergence gifted, reinforcing competence of teachers in charge should be made first. Therefore, in this paper, artificial intelligence education contents, one of the core technologies of the 4th Industrial Revolution era, were developed to reinforcing competence of SW convergence gifted teachers. After setting the direction of artificial intelligence education content, we constructed educational content suitable for secondary SW convergence gifted education, and designed and developed it in detail. The composition of artificial intelligence education content consists of machine learning and tensor flow understanding, linear regression machine learning implementation for numerical prediction, and multiple linear regression-based price prediction machine learning implementations. The developed educational contents were verified by experts with qualitative aspects. In the future, we expect that the educational content of artificial intelligence proposed in this paper will be useful for strengthening the ability of SW convergence gifted teachers.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.5
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• pp.281-293
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• 2021

Oil and steel prices, which are major pricescosts in the shipbuilding industry, were predicted. Firstly, the error of the moving average line (N=3-5) was examined, and in all three error analyses, the moving average line (N=3) was small. Secondly, in the linear prediction of data through existing theory, oil prices rise slightly, and steel prices rise sharply, but in reality, linear prediction using existing data was not satisfactory. Thirdly, we identified the limitations of linear prediction methods and confirmed that oil and steel price prediction was somewhat similar to actual moving average line prediction methods. Due to the high volatility of major price flows, large errors were inevitable in the forecast section. Through the time series analysis method at the end of this paper, we were able to achieve not bad results in all analysis items relative to artificial intelligence (Prophet). Predictive data through predictive analysis using eight predictive models are expected to serve as a good research foundation for developing unique tools or establishing evaluation systems in the future. This study compares the basic settings of artificial intelligence programs with the results of core price prediction in the shipbuilding industry through time series prediction theory, and further studies the various hyper-parameters and event effects of Prophet in the future, leaving room for improvement of predictability.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.161-166
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• 2021

The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.577-582
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• 2024

In 2007, the first domestic pet insurance policies were introduced, and by 2023, numerous insurance products had been developed. The pet insurance market has been expanding steadily. However, as of 2022, only 0.8% of all pet owners have subscribed to pet insurance. Pet owners hesitate to enroll in pet insurance due to expensive premiums, unclear coverage details, and strict enrollment criteria. This paper proposes a model capable of detecting pet eye diseases and predicting their health age. Initially, EfficientNet is employed to identify the pet's eye disease, while OpenCV is utilized to locate and measure the size of the disease, enabling the calculation of the pet's healthy age. By leveraging the calculated health age, the aim is to aid insurance companies in determining pet insurance premiums. This model can facilitate the calculation of reasonable pet insurance rates based on the pet's eye condition and health age. Ultimately, the objective is to implement a system capable of detecting pet eye conditions and predicting their health age.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.51-58
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• 2024

This paper examines the differences between the Korean and American stock markets using the Kospi and S&P 500 indices and discusses policy implications through them. To this end, in addition to the existing time series analysis method, a deep learning method was used to compare markets, and the comparison was made in terms of stock price forecasting ability and data generation ability. In monthly data, the difference between time series was not large, and in daily data, the difference in terms of stability was weak, and there was no significant difference in predictive power or simulation data generation. As shown in the results of this study, if there is not much difference in market price movement patterns between Korea and the United States, tax benefits for long-term stocks investment will be effective against the side effects of short selling.