• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.2
• /
• pp.85-95
• /
• 2019

The internal environment in pig house is closely related to the animal productivity. In addition, it is important to consider a working environment inside the pig house due to high gas and dust concentrations. The poor working environment inside the pig house can cause health problems including respiratory diseases. To analyze the working environment, it is important to evaluate the ventilation efficiency to effectively remove harmful gases and dust. The purpose of this study is to develop a 3D CFD model to analyze the working environment in the pig house. CFD model was validated by comparing air temperature distributions between CFD computed and field measured data. The average air flow rate at the pig height was 40.1 % lower than the working height when incoming air was concentrated on upper layer by the installed ventilation system on the experimental pig house. Using the validated CFD model, the regional ventilation efficiency was computed by the TGD(tracer gas decay) method at the pig and working heights. There was a difference of ventilation efficiency on 14 % between the air stagnated section and the rest sections. Stagnated gas concentration can be effected by animal and human health.

• The Journal of Industrial Distribution & Business
• /
• v.11 no.8
• /
• pp.31-38
• /
• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Soft Computing and Machine Intelligence
• /
• v.1 no.1
• /
• pp.11-23
• /
• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.6
• /
• pp.1046-1052
• /
• 2010

In residential house, photovoltaic (PV) system among various alternatives in renewable energy system is the most efficient and feasible solution for reducing energy consumption and electricity cost. However, relatively high initial cost make people reluctant to install PV system in their houses. Therefore, in the initial state for PV system installation in the house, it is very important to decide proper capacity of the PV system considering the expected energy usage and solar energy supplying condition with the house. This paper proposes a novel optimization model for deciding appropriate capacity of the PV system for residential house. The objective function of the model is to minimize the annual cost including electricity bill, operation and maintenance cost, and annual fixed cost calculated from the initial installation cost based on capital recovery factor (CRF). The model also shows the optimal inclining angle of PV panels of the system. In this paper, we estimate the PV output using PVWATTS (PV simulator of Office of Energy Efficiency and Renewable Energy) and find optimal solutions by Sequential Quadratic Programming (SQP) method using MATLAB software. The proposed approach is finally applied to a residential model house in Gangneung, Gangwon-Do and verified its feasibility for adopting to PV system design for residential houses.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.51 no.3
• /
• pp.71-78
• /
• 2009

Pipe section of bending part at the arch type pipe-house showed an ellipse with oblateness of 0.076 on the average. Flexural rigidity of bending part decreased by average 6.3% than that of an original round shape section. The deflection of arch type pipe-house measured by model experiments showed much bigger than the result of structural analysis. In case of arch type pipe-house, we supposed that the decrease of flexural rigidity for the bending part of pipes had an effect on deflection of roof under the working load. This effect should be considered in the structural analysis. Bending resistance of gable type pipe-house used a prefabricated connector which developed in this study showed about $1.5{\sim}1.8$ times stronger than that of the existing arch type or gable type processed bending. Therefore, we supposed that the gable-roofed prefabricated pipe-house is safer than arch type or bent gable type in case of heavy snowfall. According to house scales and section properties of steel pipe in use, safe snow depths and rafter intervals were presented for design of gable-roofed prefabricated pipe-house. Their standards were established in the range of the durable models recommended by RDA, and the comparative examinations were conducted by means of structural analysis. It was evaluated that the developed greenhouse model had a high applicability in the field.

• Journal of Environmental Science International
• /
• v.12 no.6
• /
• pp.583-591
• /
• 2003

The research on potential energy was conducted to conserve the high-exergy energy like primary energy and utilize waste heat from sewage. From the Point of view in using the waste heat, the energy Potential of waste water from the model house was simulated. From the results, when the heated water was supplied to the model house side in order to put unused energy to Practice use, heated water had higher energy Potential than unheated water, which was due to the discharge of most of unused energy. The possessing heat capacity of sewage from heated water was increased to 40-70 percents in comparison with that from the unheated water. Therefore, it can be used as energy source for improving coefficient of performance of heat pumps. By adopting the multiple heat pump into a model house, It showed that the possessing heat capacity of sewage was reduced. It was also found that the heat was recovered as energy source fur multiple heat pump in a model house.

• Proceeding of Spring/Autumn Annual Conference of KHA
• /
• 2008.11a
• /
• pp.167-172
• /
• 2008

The ultimate objective of this research is to develop the technologies for the construction of 100-year housing as the first task for improving housing environments. The technological development of 100-year housing makes it possible to advance construction technologies and part development, to develop long-life housing with durability and Flexibility responding to customers' needs for future living space. At first, for this purpose, the applications according to the types of the Standard Model of Long-life Housing are proposed to respond to the life-cycle of near-future demographic and social structure, and the construction of the Mock-up House execute based on the location selected during the 2nd year and the basic plan. Then the Standard Model of Long-life Housing are advanced and proposed through evaluating the field applicability of the Mock-Up House.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.41 no.4
• /
• pp.66-76
• /
• 1999

In this study , the optimum structural components for the rural house design using the light gauge cold-formed steel frame is proposed. The proposed components were optimzed by the developed model composed with the analysis model and LGC database. The analysis model adapts FEA(finite element analysis). LGC database and calculation of element force adapt the design criteria of KISC. The structure of house is divided into header, bearing wall and foof truss. The variable of the each structure of house are defined component which designed by the case of load, aize and space. The designed weight were used for optimization procedure of the divided components.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.7
• /
• pp.1128-1134
• /
• 2016

Demand response provides customer load reductions based on high market prices or system reliability conditions. One type of demand response, price-based program, induces customers to respond to changes in product rates. However, there are large-scale general and industrial customers that have difficulty changing their energy consumption patterns, even with rate changes, due to their electricity demands being commercial and industrial. This study proposes an in-house pricing model for large-scale general and industrial customers, particularly those with multiple business facilities, for self-regulating demand-side management and cost reduction. The in-house pricing model charges higher rates to customers with lower load factors by employing peak to off-peak ratios in order to reduce maximum demand at each facility. The proposed scheme has been applied to real world and its benefits are demonstrated through an example.

• Journal of Cadastre & Land InformatiX
• /
• v.48 no.2
• /
• pp.65-77
• /
• 2018

It is very important to understand the factors affecting the occurrence of vacant houses in research on them. The purpose of this study is to analyze the factors affecting the rural vacancy occurrence. This study set 121 research areas and selected eight independent variables (Aged house rate, housing transaction rate, house diffusion ratio, local extinction index, net migration rate, regional aging index, the ratio of the number of employees to population and financial independence rate) and one dependent variable (vacant house rate). As a result of the study, first, both Model 1 for the entire general agricultural fishing village area and Model 2 for the county (gun) area were statistically significant, there was no problem with the independence of residual. Second, local extinction index and aged house rate had a statistically significant positive (+) relationship in both Model 1 and Model 2. Third, diffusion ratio of house had a statistically significant positive (+) relationship only in Model 1, and housing transactions rate had a statistically significant negative (-) relationship in Model 2. The implications of the study were drawn as follows: First, the increase in the house diffusion ratio without growth in households and population suggests the increase of the probability of the vacancy occurrence in the area, and the higher the aged house rate, the higher the probability of the vacancy occurrence. Second, for the revitalization of housing transactions, it is necessary to have an investment inflow in the area for mid- to long-term development. Third, local extinction index has a significant relationship with vacant house rate, it is necessary to introduce a local revitalization policy from a long-term perspective for the permanence of the area.