• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.11
• /
• pp.2017-2022
• /
• 2007

In a memory, most power is dissipated in line of high capacitance such as decoder lines, word lines, and bit * lines. The decoder size as well as the parastic capacitances of the bit-line are going to reduce, if ROM core size reduces. This paper proposes to reduce a mathod of power dissipation for reducing ROM core size. Design result of ROM used in FFT[2], proposed method lead to up to 40.6%, 42.12%, 37.82% reduction in area, power consumption and number of Tr. respectively compared with previous method.

• New & Renewable Energy
• /
• v.19 no.3
• /
• pp.1-12
• /
• 2023

This study aims to evaluate the optimal size of the hydrogen facility to be installed in a zero-energy district in terms of load matching and facility efficiency. A mismatch between energy generation and consumption is a common occurrence in zero-energy districts. This mismatch adversely effects the energy grid. However, using an energy carrier such as hydrogen can solve this problem. To determine the optimal size of hydrogen fuel cells to be used on-site, simulation of hydrogen installation is required at both district-and building- levels. Each case had four operating schedules. Therefore, we evaluated eight scenarios in terms of load matching, heat loss, and facility operational efficiency. The results indicate that district-level installation of hydrogen facilities enables more efficient energy use. Additionally, based on the proposed model, we can calculate the optimal size of the hydrogen facility.

• International journal of advanced smart convergence
• /
• v.4 no.1
• /
• pp.45-53
• /
• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.

• Journal of KIISE:Computing Practices and Letters
• /
• v.9 no.4
• /
• pp.410-419
• /
• 2003

The buffer cache of general operating systems such as Linux manages file data by using global block replacement policy and read ahead. As a result, multimedia data with a low locality of reference and various consumption rate have low cache hit ratio and consume additional buffers because of read ahead. In this paper we have designed and implemented a new buffer allocation algorithm for multimedia data on Linux. Our approach keeps one read-ahead cache per every opened multimedia file and dynamically changes the read-ahead group size based on the buffer consumption rate of the file. This distributes resources fairly and optimizes the buffer consumption. This paper compares the system performance with that of Linux 2.4.17 in terms of buffer consumption and buffer hit ratio.

• KIEAE Journal
• /
• v.14 no.5
• /
• pp.59-65
• /
• 2014

Nowadays, reduction of energy use in buildings is a big issue, especially in public buildings like schools. The building structure is very simple in that, the room size, schedule and user number is similar across different schools. There are many policies which are suitable for this kind of buildings. Investigation of energy consumption pattern in primary school, middle school and high school in different cities of Korea has been done in this paper using statistical data from national organization and the data from IBM and Gyeonggi Provincial Office of Education, aimed at providing the basic data for the development of energy efficiency improvement policies of educational facilities. The study was divided according to climate, energy source type and public or private school, as different cities have different climates and accordingly different amount of energy sources are used. It was observed that, the average energy consumption in primary school is $36.9kWh/m^2$, in middle school is $20.5kWh/m^2$ and in high school $27.4kWh/m^2$. As further analysis, monthly energy consumption pattern has been analyzed for one city.

• Preventive Nutrition and Food Science
• /
• v.3 no.1
• /
• pp.77-84
• /
• 1998

To evaluate food consumption patterns of first generation Korean-American in Hawaii, questionnaires were developed using sociodemographic questions and food frequency questionnaire, which included 139 food items most often consumed among Korean foods and American foods. The questionnaires surveyed 157 first generation Korean-Americans in Hawaii. Mean daily servings for the first generation Korean-Americans were calculated for 139 food items combined into 41 food groups based on similarity in nutrient composition and serving size. The food groups which were consumed in amounts over one serving per day for all subjects were rice, Kimchi , non-citrus fruit , vegetables, organge/green vegetables. oil. margarine and coffee/tea. All subjects consumed less than one serving of hotdogs, hamburgers, pizza and pancakes per week(0.14 serving per day). The most notable characteristic of food consumption for first generation Korean-Americans was that they consumed more Korean food such as rice, Kimchi, soybean paste(Deenjang), soybean curd and seaweed than American foods. Compared with other groups based on age and gender, younger men showed significantly(p<0.05) more frequent consumption of beef/pork, sausages /hams /bacons and hambergers. Older men were significantly(p<0.05) more likely to consume Doenjang and less likely to consume pizza and hamburgers. Daily servings were below the recommended level for thegrains /bread/cereals group and fats/oils/sweets group for all subjects . Fruits/vegetables group servings exceeded the recommeded 5 daily servings for younger men. In correlations of daily servings of selected foods among Korean foods and American food with sociodemographic characteristics, this study showed that the older the subjects and the shorter the stay in Hawaii, subjects were more likely to consume Kroean foods.

• Asia-Pacific Journal of Business
• /
• v.11 no.3
• /
• pp.199-215
• /
• 2020

Purpose - This article tries to test if the conditional consumption capital asset pricing model (CCAPM) with bank credit for household as a conditional variable can explain the cross-sectional variation of stock returns in Korea. The performance of conditional CCAPM is compared to that of multifactor asset pricing models based on Arbitrage Pricing Theory. Design/methodology/approach - This paper extends the simple CCAPM to the conditional version of CCAPM by using bank credit for household as conditioning information. By employing KOSPI and KOSDAQ stocks as test assets from the second quarter of 2003 to the first quarter of 2018, this paper estimates risk premiums of conditional CCAPM and a variety of multifactor linear models such as Fama-French three and five-factor models. The significance of risk factors and the adjusted coefficient of determination are the basis for the comparison in models' performances. Findings - First, the paper finds that conditional CCAPM with bank credit performs as well as the multifactor linear models from Arbitrage Pricing theory on 25 test assets sorted by size and book-to-market. When using long-term consumption growth, the conditional CCAPM explains the cross-sectional variation of stock returns far better than multifactor models. Not only that, although the performances of multifactor models decrease on 75 test assets, conditional CCAPM's performance is well maintained. Research implications or Originality - This paper proposes bank credit for household as a conditional variable for CCAPM. This enables CCAPM, one of the most famous economic asset pricing models, to conform with the empirical data. In light of this, we can now explain the cross-sectional variation of stock returns from an economic perspective: Asset's riskiness is determined by its correlation with consumption growth conditional on bank credit for household.

• Journal of Convergence for Information Technology
• /
• v.9 no.1
• /
• pp.19-27
• /
• 2019

In recent years, with the advancement of IT technology, we expect data size of the world to increase 10 times in 2025. The rapid development of this Internet technology leads to the downsizing of the server system of the data center which manages and operates the data, the capacity of the storage medium, and the power consumption of the data center. In this paper, we propose an energy conservation policy and analyze it in real time by analyzing the power consumption pattern of the server system of the data center. The proposed system can monitor and analyze the power consumption pattern of the individual server system in the data center, and it can be expected that about 10% of the total power consumption of the data center will be saved by efficiently managing the actual operation time of the server system.

• International Journal of High-Rise Buildings
• /
• v.8 no.2
• /
• pp.101-106
• /
• 2019

Assessing the energy performance of supertall buildings often does not consider variations in energy consumption due to the change of environmental conditions such as temperature, pressure, and wind speed associated with differing elevations. Some modelers account for these changing conditions by using a conventional temperature lapse rate, but not many studies confirm to the appropriateness of applying it to tall buildings. This paper presents and discusses simulated annual energy consumption results from a 600 m tall skyscraper floor plate located in Dubai, UAE, assessed using ground level weather data, a conventional temperature lapse rate of $6.5^{\circ}C/km$, and more accurate simulated 600 m weather data. A typical office floorplate, with ASHRAE 90.1-2010 standards and systems applied, was evaluated using the EnergyPlus engine through the OpenStudio graphical user interface. The results presented in this paper indicate that by using ground level weather data, energy consumption at the top of the building can be overestimated by upwards of 4%. Furthermore, by only using a lapse rate, heating energy is overestimated by up to 96% due to local weather phenomenon such as temperature inversion, which can only be conveyed using simulated weather data. In addition, sizing and energy consumption of fans, which are dependent both on wind and atmospheric pressure, are not accurately captured using a temperature lapse rate. These results show that that it is important, with the ever increasing construction of supertall buildings, to be able to account for variations in climatic conditions along the height of the building. Adequately modeling these conditions using simulated weather data will help designers and engineers correctly size mechanical systems, potentially decreasing overall building energy consumption, and ensuring that these systems are able to provide the necessary indoor conditions to maintain occupant comfort levels.

• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.489-504
• /
• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.