• Journal of Multimedia Information System
• /
• v.4 no.2
• /
• pp.73-78
• /
• 2017

The Future Video Coding (FVC) is a new state of the art video compression standard that is going to standardize, as the next generation of High Efficiency Video Coding (HEVC) standard. The FVC standard applies newly designed block structure, which is called quadtree plus binary tree (QTBT) to improve the coding efficiency. Also, intra and inter prediction parts were changed to improve the coding performance when comparing to the previous coding standard such as HEVC and H.264/AVC. Experimental results shows that we are able to achieve the average BD-rate reduction of 25.46%, 38.00% and 35.78% for Y, U and V, respectively. In terms of complexity, the FVC takes about 14 times longer than the consumed time of HEVC encoder.

• Journal of Environmental Impact Assessment
• /
• v.22 no.1
• /
• pp.109-116
• /
• 2013

By IPCC climate change scenario, the socioeconomic actions such as the land use change are closely associated with the climate change as an up zoning action of urban development to increase green gas emission to atmosphere. Prediction of the land use change with rational quality can provide better data for understanding of the climate change in future. This study aims to predict land use change of Cheongju in future and SLEUTH model is used to anticipate with the status quo condition, in which the pattern of land use change in future follows the chronical tendency of land use change during last 25 years. From 40 years prediction since 2000 year, the area urbanized compared with 2000 year increases up to 87.8% in 2040 year. The ratios of the area urbanized from agricultural area and natural area in 2040 are decreased to 53.1% and 15.3%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.4
• /
• pp.633-636
• /
• 2022

The reduction of energy consumption at the base station (BS) has become more important recently. In this paper, we consider the adaptive muting of the antennas based on the predicted future traffic load to reduce the energy consumption where the number of active antennas is adaptively adjusted according to the predicted future traffic load. Given that traffic load is sequential data, three different RNN structures, namely long-short term memory (LSTM), gated recurrent unit (GRU), and bidirectional LSTM (Bi-LSTM) are considered for the future traffic load prediction. Through the performance evaluation based on the actual traffic load collected from the Afghanistan telecom company, we confirm that the traffic load can be estimated accurately and the overall power consumption can also be reduced significantly using the antenna musing.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.135-135
• /
• 2021

In water resources management, rainfall prediction with high accuracy is still one of controversial issues particularly in countries facing heavy rainfall during wet seasons in the monsoon climate. The aim of this study is to develop an artificial neural network (ANN) for predicting future six months of rainfall data (from April to September 2020) from daily meteorological data (from 1971 to 2019) such as rainfall, temperature, wind speed, and humidity at Seoul, Korea. After normalizing these data, they were trained by using a multilayer perceptron (MLP) as a class of the feedforward ANN with 15,000 neurons. The results show that the proposed method can analyze the relation between meteorological datasets properly and predict rainfall data for future six months in 2020, with an overall accuracy over almost 70% and a root mean square error of 0.0098. This study demonstrates the possibility and potential of MLP's applications to predict future daily rainfall patterns, essential for managing flood risks and protecting water resources.

• Journal of Digital Convergence
• /
• v.18 no.2
• /
• pp.205-211
• /
• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Journal of Industrial Technology
• /
• v.18
• /
• pp.443-452
• /
• 1998

The future water quality of Youngwol Dam was predicted using FEMWASP. In the this study, point and non-point source in the basin was investigated in detail, and future pollutant loading was computed by various prediction technique. The water quality of 29 sites was analyzed over four seasons. FEMWASP was used to predict future water quality of Youngwol lake and downstream of proposed dam. Future water quality of Youngwol lake was predicted to configure eutrophication status, management criteria was suggested to minimize the pollution problems coming from future eutrophication. Discharge rate of dam was decided as 30CMS to conserve the water quality, and overall design of dam was changed.

• The Korean Journal of Applied Statistics
• /
• v.26 no.6
• /
• pp.1019-1032
• /
• 2013

The accurate prediction of future mortality is an important issue due to recent rapid increases in life expectancy. An accurate estimation and prediction of mortality is important to future welfare policies. The optimal selection of a mortality model is important to estimate and predict mortality; however, the period of time series data used is also an important issue. It is essential to understand that the time series data for mortality is short in Korea and the data before 1982 is incomplete. This paper divides the time series of Korean mortality into two sets to compare the parameter estimates of the LC model and LC model with a cohort effect by the period of data used. A modeling and prediction of the mortality index and cohort effect index as well as the evaluation of future life expectancy is conducted. Finally, some suggestions are proposed for the future prediction of mortality.

• Journal of the Korean Society of Safety
• /
• v.33 no.4
• /
• pp.98-104
• /
• 2018

Macroscopic accident analyses have been conducted to incorporate transportation safety into long-term transportation planning. In macro-level accident prediction model, exposure variable(e.g. a settled population) have been used as fundamental explanatory variable under the concept that each trip will be subjected to a probable risk of accident. However, a settled population may be embedded error by exclusion of active population concept. The objective of this research study is to develop macro-level accident prediction model using floating population variable(concept of including a settled population and active population) collected from mobile phone data. The concept of accident prediction models is introduced utilizing exposure variable as explanatory variable in a generalized linear regression with assumption of a negative binomial error structure. The goodness of fit of model using floating population variable is compared with that of the each models using population and the number of household variables. Also, log transformation models are additionally developed to improve the goodness of fit. The results show that the log transformation model using floating population variable is useful for capturing the relationships between accident and exposure variable and generally perform better than the models using other existing exposure variables. The developed model using floating population variable can be used to guide transportation safety policy decision makers to allocate resources more efficiently for the regions(or zones) with higher risk and improve urban transportation safety in transportation planning step.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.23 no.9
• /
• pp.587-594
• /
• 2011

This paper describes the investigation on current state of cold storage facilities, and analysis on the demand prediction in the near future. And based on the analysis results, we prospect the scale of cold storage facilities in the near future. The main analysis results are summarized by the followings ; The present circumstances of cold storage facility are determined by investigating actual loading capacity, average stock amounts, and return number of cold storage facility. From the results, the present situation for cold storage facility is about 3% over. It is found that the average stock amounts increase gradually, and accordingly that the demand of cold storage facility is predicted to be increased, resulting that the capacity of cold storage facilities in 2013 expects to reach up to 5,250,000 ton. It is considered that the results of demand prediction has significant implications on the management of cold storage facility in the near future.

• Journal of Industrial Technology
• /
• v.29 no.A
• /
• pp.27-36
• /
• 2009

Reliability plays a pivotal role in products safety and quality. DoD RIAC recently developed a new reliability prediction methodology, $217Plus^{TM}$, for electronic systems. It officially replaces the well-known MIL-HDBK-217 and is expected to be widely used. Although theoretic study about $217Plus^{TM}$ and its application towards field systems seem to be attractive, it is also desirable to understand the general background of its development. In this paper, we performed a historical review of the arenas related to reliability prediction. Due to the vast of materials, our scope was limited to the development of $217Plus^{TM}$. We first reviewed Rome Laboratory and RIAC. We then explained the development course of reliability methods, MIL-HDBK-217, PRISM, and 217-Plus. This review will form not only a good understanding of the methodology but a basis for future study. We conclude this study with provision of future research areas.