• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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• pp.609-615
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• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.17-25
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• 2009

This paper presents a methodology for a fall detection using the feature extraction method based on the neural network with weighted fuzzy membership functions (NEWFM). The distributed non-overlap area measurement method selects the minimized number of input features by removing the worst input features one by one. Nineteen number of wavelet transformed coefficients captured by a triaxial accelerometer are selected as minimized features using the non-overlap area distribution measurement method. The proposed methodology shows that sensitivity, specificity, and accuracy are 95%, 97.25%, and 96.125%, respectively.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.129-135
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• 2008

This paper presents a methodology to forecast KOSPI index by extracting fuzzy rules based on the neural network with weighted fuzzy membership functions (NEWFM) and the minimized number of input features using the distributed non-overlap area measurement method. NEWFM classifies upward and downward cases of KOSPI using the recent 32 days of CPPn,m (Current Price Position of day n for n-1 to n-m days) of KOSPI. The five most important input features among CPPn,m and 38 wavelet transformed coefficients produced by the recent 32 days of CPPn,m are selected by the non-overlap area distribution measurement method. For the data sets, from 1991 to 1998, the proposed method shows that the average of forecast rate is 67.62%.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.89-95
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• 2002

Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.399-410
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• 2008

This paper suggests a new retrieval method using weighted vector sum to resolve a problem of traditional location-based retrieval method, nearest neighbor (NN) query, and NN query using direction. The proposed method filters out data with the radius, and then the remained retrieval area is filtered by a direction information compounded of a user's moving direction, a pre-fixed interesting direction, and a pre-fixed retrieval angle. The moving direction is computed from a vector or a weighted vector sum of several vectors using a weight to adopt several cases. The retrieval angle can be set from traditional $360^{\circ}$ to any degree you want. The retrieval data for this method can be a still and moving image recorded shooting location, and also several type of media like text, web, picture offering to customer with location of company or resort. The suggested method guarantees more accurate retrieval than traditional location-based retrieval methods because that the method selects data within the radius and then removes data of useless areas like passed areas or an area of different direction. Moreover, this method is more flexible and includes the direction based NN.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.125-132
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• 2007

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM), NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The eight most important coefficients of d3 and d4 are selected by the non-overlap area distribution measurement method. The selected 8 coefficients are used for 3 data sets showing reliable accuracy rates 99,80%, 99,21%, and 98.78%, respectively, which means the selected input features are less dependent to the data sets. The ECG signal segments and fuzzy membership functions of the 8 coefficients enable input features to interpret explicitly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.23-27
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• 1997

This paper introduces the structural design optimization of a high speed machining center using multi-step optimization combined with G.A.(Genetic Algorithm) and Weighted Method. In this case, the design problem is to find out the best design variables which minimize the static compliance, the dynamic compliance, and the weight of the machine structure simultaneously. Dimensional thicknesses of the thirteen structural members of the machine structure are adopted as design variables. The first step is the cross-section configuration optimization, in which the area moment of inertia of the cross-section for each structural member is maximized while its area is kept constant The second step is a static design optimization, In which the static compliance and the weight of the machine structure are minimized under some dimensional and safety constraints. The third step IS a dynamic design optimization, where the dynamic compliance and the structure weight are minimized under the same constraints. After optunization, static and dynamic compliances were reduced to 62.3% and 95.7% Eorn the initial design, while the weight of the moving bodies are also in the feaslble range.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.873-882
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• 2011

In this paper, we propose an efficient deinterlacing algorithm which interpolates the missing scan lines by weighted summing of the intra and the inter interpolation pixels according to the spatio-temporal variation. In the spatial interpolation, we adopt a new edge based spatial interpolation method which includes edge directional refinement. The conventional edge dependent interpolation algorithms are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method first finds the edge directions around the pixel to be interpolated and then refines edge direction of the pixel using weighted maximun frequent filter. Futhermore, we improve the accuracy of motion detection by reducing the possibility of motion detection error using 3 tab median filter. In the final interpolation step, we adopt weighted sum of intra and inter interpolation pixels according to spatio-temporal variation ratio, thereby improving the quality in slow moving area. Simulation results show the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Biomedical Science Letters
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• v.10 no.4
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• pp.515-521
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• 2004

To measure regional cerebral blood volume (rCBV) with perfusion MR imaging of cerebral fat embolism by neutral fat and free fatty acids in cats. Triolein (group 1, n=15), oleic acid (group 2, n=9) and linoleic acid (group 3, n=11) were infused into unilateral internal carotid artery using microcatheter through the transfemoral approach. PVA particle was used as a non-fat embolic material in a control group (group 4, n=9). Perfusion-weighted MR image was obtained at 30 minutes and 2 hours postembolization, based on T2-and diffusion-weighted images. The data of lesion and contralateral normal area were transferred to personal computer, time-to-signal intensity curve was drawn and trans for used to △R2/sup */ curve in regular order. The process in the personal computer was done by using the author's developmental image processing program and interactive data language (IDL) softwares. Statistical significance was approved by paired t-test and ANOVA. rCBV of the lesion was decreased comparing to the normal area in all groups. The ratios of rCBV were as follows (group No, at 30 minutes, at 2 hours); group 1,32％, 51％; group 2, 30％, 44％; group 3, 39％, 61％; group 4, 21％, 36％. rCBVs of 2 hours was significantly increased compared to those of 30 minutes in all groups (P<0.005). rCBV was decreased at 30 minutes in cerebral fat embolism and recovered a little, but significantly at 2 hours. Perfusion-weighted images was useful method in offering hemodynamic information in cerebral fat embolism.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.619-622
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• 2015

Recently, there are growing fluctuations of productivity and price caused by severe weather conditions in the agriculture. Yield forecasting methods have been studied to solve the problems. This paper predicted yield per area, production area, and elements of weather based on the linear equation. A yield is calculated by multiplying the production area times the yield per area that is compensated using the weighted sum of the elements of weather. In experiments, proposed method shows that a forecasting precision is the more than 90%.