• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.457-461
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• 2007

In many applications, received signal strength indicator is used for location tracking and sensor nodes localization. For location finding, the distances between sensor nodes can be estimated by converting received signal's power into distance using path loss prediction model. Many researches have done the analysis of power-distance relationship for radio channel characterization. In indoor environment, the general conclusion is the non-linear variation of RSSI values as distance varied linearly. This has been one of the difficulties for indoor localization. This paper presents works on indoor RSSI characterization based on statistical methods to find the overall trend of RSSI variation at different places and times within the same room From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. This two factors are directly indicated by the two main parameters of path loss prediction model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.127-135
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• 2009

It is necessary to forecast the amount of the maximum electricity demand for stabilizing the flow of electricity. The time series data was collected from the Korea Energy Research between January 2000 and December 2006. The data showed that they had a strong linear trend and seasonal change. Winters seasonal model, ARMA model were used to examine it. Root mean squared prediction error and mean absolute percentage prediction error were a criteria to select the best model. In addition, a nonstationary generalized extreme value distribution with explanatory variables was fitted to forecast the maximum electricity.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.481-481
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• 2000

We investigated the structure-activity relationships on use of multi-layer neural networks. The relationships are techniques required in developments of medicines. Since many kinds of observations might be adopted on the techniques, we discussed some points between the observations and the properties of multi-layer neural networks. In the structure-activity relationships, an important property is not that standard deviations are nearly equal to zero for observed physiological activity, but prediction ability for unknown medicines. Since we adopted non-linear approximation, the function to represent the activity can be defined by observations; therefore, we believe that the standard deviations have not significance. The function was examined by "leave-one-out" method, which was originally introduced for the multi-regression analysis. In the linear approximation, the examination is significance, however, we believe that the method is inappropriate in case of nonlinear fitting as neural networks; therefore, we derived a new index fer the relationships from the differential of information propagation in the neural network. By using the index, we discussed physiological activity of an anti-cancer medicine, Mitomycine derivatives. The neuro-computing suggests that there is no direction to extend the anti-cancer activity of Mitomycine, which is close to the trend of anticancer developing.

• Journal of the Korea Institute of Building Construction
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• v.14 no.6
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• pp.631-637
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• 2014

Recently, following the application of modular housing techniques to not only residential sector, but also to business sector, the scope of modular housing market b expanding. In the case of other developed countries, such markets are entering into the maturity stage, though the market in Korea is not fully formed yet. Thus, it is difficult to check its trend to estimated mid- to long-term prospects of the market. In this context, the study predicted demand of the modular housing market by using a non-linear prediction model based on time series analysis. To get the prospects for the modular housing market, the quantity of housing supply was estimated based on the estimated quantity of newly built housings, and assumed that a portion of the supplied quantity would be the demand for modular housings. Based on the assumption of demand for modular housings, several scenarios were analyzed and the prospects of the modular housing market was obtained by utilizing the non-linear prediction model.

• Journal of the military operations research society of Korea
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• v.34 no.2
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• pp.79-101
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• 2008

This study is for improvement of repair part demand forecasting method of Republic of Korea Air Force aircraft. Recently, demand prediction methods are Weighted moving average, Linear moving average, Trend analysis, Simple exponential smoothing, Linear exponential smoothing. But these use fixed weight and moving average range. Also, NORS(Not Operationally Ready upply) is increasing. Recommended method of Box-Jenkins' ARIMA can solve problems of these method and improve estimate accuracy. To compare recent prediction method and ARIMA that use mean squared error(MSE) is reacted sensitively in change of error. ARIMA has high accuracy than existing forecasting method. If apply this method of study in other several Items, can prove demand forecast Capability.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1994.03a
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• pp.118-128
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• 1994

The planar anisotropic FEM analysis for predicting the earing profiles and draw-in amounts in the deep-drawing processes is introduced. An implicit, incremental, updated Lagrangian formulation with a rigid-viscoplastic constitutive equation is employed. Contact and friction are considered through the mesh-based unit vectors and the normal contact pressure. the consistent full set of governing relations, comprising equilibrium and geometric constraint equations, is appropriately linearized. Barlat's strain-rate potential is employed, whose in-plane anisotropic properties are taken into account with anisotropic coefficients and potential parameter. The linear triangular membrane elements are used for depicting the formed sheet. with the numerical simulations of deep drawing processes of flat-top cylindrical cup for the 2090-T3 aluminum effects on the earing behavior are examined. Earing predictions made for the 2090-T3 aluminum alloy sheet show good agreement with experiments, although some discrepancies were observed in the directional trend of cup height and thickness strains.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1997.10a
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• pp.135-138
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• 1997

The interaction of oblique monochromatic incident waves with a horizontal flexible membrane is investigated in the context of two-dimensional linear hydro-elastic theory. First, analytic diffraction and radiation solutions for a submerged impermeable horizontal membrane are obtained. Second, the theoretical prediction was compared with a series of experiments conducted in a two-dimensional wave tank at Texas A&M University. The measured reflection and transmission coefficients reasonably follow the trend of predicted values. Using the developed computer program, the performance of surface-mounted or submerged horizontal membrane wave barriers is tested with various system parameters and wave characteristics. It is found that the properly designed horizontal flexible membrane can be an effective wave barrier and its efficiency can be further improved using a porous material.

• The Journal of Engineering Geology
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• v.24 no.4
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• pp.643-648
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• 2014

Understanding of fracture networks and rock mass properties during tunnel construction is extremely important for the prediction of dangers during excavation, and for deciding on appropriate excavation techniques and support. However, rapid construction process do not allow sufficient time for surveys and interpretations for spatial distributions of fractures and rock mass properties. This study introduces a new statistical approach for predicting joint distributions at foreside of current excavation face during the excavation process. The proposed methodology is based on a cumulative space diagram for joint sets. The diagram displays the cumulative spacing between adjacent joints on the vertical axis and the sequential position of each joint plotted at equally spaced intervals on the horizontal axis. According to the diagram, the degree of linearity of points representing the regularity of joint spacing; a linear trend of the points indicates that the joints are evenly spaced, with the slope of the line being directly related to the spacing. The linear points which are stepped indicates that the fracture set show clustered distribution. A clustered pattern within the linear group of points indicates a clustered joint distribution. Fractures surveyed from an excavated space can be plotted on this diagram, and the diagram can then be extended further according to the plotted diagram pattern. The extension of the diagram allows predictions about joint spacing in areas that have not yet been excavated. To test the model, we collected and analyzed data during excavation of a 10-m-long tunnel. Fractures in a 3-m zone behind the excavation face were predicted during the excavation, and the predictions were compared with observations. The methodology yielded reasonably good predictions of joint locations.

• Microbiology and Biotechnology Letters
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• v.27 no.1
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• pp.54-61
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• 1999

Measurement of inhibition of bioluminescence in Photobacterium phosphoreum has been porposed as a sensitive and rapid procedure to monitor toxic substances. However, at first, $EC_{50}$ which shows degree of toxicity to each toxic substances must be calculated. QSAR (Quantitative Structure Activity Relationship) model can be used to estimate $EC_{50}$ to save time and endeavor. Moderately high correlation coefficients ($r^2{\geq}$ 0.97) were calculated from the linear correlation between $EC_{50}$ and molecular connectivity indices of CAHs (chlorinated aliphatic hydrocarbons)such as $^0X$, $^0X^V$, $^1X$, $^2X$ and $^3X^v_c$ and quadratic correlation between $EC_{50}$ and $^0X$, $^0X^V$, $^2X^V$, $^3X_c$, $^3X^V_c$ and P. It shows that the molecular connection indices in carbon structure is contributed to biological characters with linear relation and that in the other one with quadratic relation. The $EC_{50}$ of chlorophenol derivatives had quadratic relation with the value of octanol/water prtition coefficients ($r^2$=0.99) and linear and quadratic relation with the number of chlorine compound (($r^2{\geq}$0.94). This confirms the already known trend of increasing toxicity with increasing ability of a compound to diffuse through cell membrane and number of chlorine substitution.

• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.255-268
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• 2006

Recent 22-year (1981-2002) meteorological data of 58 Korea Meteorological Adminstration (KMA) station were analyzed to investigate spatial and temporal variation of surface air temperature (SAT) and ground surface temperature (GST) in Korea. Based on the KMA data, multiple linear regression (MLR) models, having two regression variables of latitude and altitude, were presented to predict mean surface air temperature (MSAT) and mean ground surface temperature (MGST). Both models showed a high accuracy of prediction with $R^2$ values of 0.92 and 0.94, respectively. The prediction of MGST is particularly important in the areas of geothermal energy utilization, since it is a critical parameter of input for designing the ground source heat pump system. Thus, due to a good performance of the MGST regression model, it is expected that the model can be a useful tool for preliminary evaluation of MGST in the area of interest with no reliable data. By a simple linear regression, temporal variation of SAT was analyzed to examine long-term increase of SAT due to the global warming and the urbanization effect. All of the KMA stations except one showed an increasing trend of SAT with a range between 0.005 and $0.088^{\circ}C/yr$ and a mean of $0.043^{\circ}C/yr$. In terms of meteorological factors controlling variation of GST, the effects of solar radiation, terrestrial radiation, precipitation, and snow cover were also discussed based on quantitative and qualitative analysis of the meteorological data.