• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.366-370
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• 2003

This paper is on weighted model reduction using structurally balanced truncation. For a given weighted(single or double-sided) transfer function, a state space realization with the linear fractional transformation form is obtained. Then we prove that two block diagonal LMI(linear matrix inequality) solutions always exist, and it is possible to get a reduced order model with guaranteed stability and a priori error bound. Finally, two examples are used to show the validity of proposed weighted reduction method, and the method is compared with other existing methods.

• 대한건축학회논문집:계획계
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• 제35권1호
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• pp.47-54
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• 2019

This study proposes a new ERAM model with building population weighting. Previous studies of applying weightings on ERAM model on the scale of urban space were focused on the relationship between the street and the human behavior. However, this study focuses on the influences that buildings give to human behavior and develops a building population weighted ERAM model. This research starts by analyzing ERAM model to its basic compositions, which are adjacency matrix and row vector. It applies building population weighting to the row vector, while previous studies put weightings in the adjacency matrix. Building population weighted ERAM model calculates the building population weighting based on GIS data, which provides objective and massive data of buildings in the urban scale. For the verification of the model, Insa-dong and Myeong-dong were analyzed with both ERAM model and building population weighted ERAM model. The results were analyzed through the correlation test with actual pedestrian population data of the two districts. As a result, the explanation ability of building population weighted ERAM model for the pedestrian population turned out to be higher than the ERAM model. Since building population weighted ERAM model has the structure that can be combined with other weighted ERAM models, it is expected to develop a multi-weighted ERAM model with better explanation ability as a further study.

• 한국음향학회지
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• 제18권5호
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• pp.78-82
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• 1999

본 연구는 잡음에 강한 음성 파라미터로써 널리 사용하는 가중 켑스트럼에 관한 연구이다. 특히 청각 모델인 PLP(Perceptual Linear Predictive)에서 켑스트럼을 추출 후 비대칭형 성문 펄스 파형 형태를 가중치 함수로 사용하는 방법을 제안한다. 또한 이러한 가중 켑스트럼을 성도 모델에서의 성도파형과 켑스트럼과 연관하여 분석하였다. 그리고 청각 모델인 PLP의 켑스트럼에 가중시켜 청각 모델과 성도 모델을 모두 적용한 음성 파라미터를 얻었다. 이러한 방법의 성능 평가를 위해 차량내 잡음과 길거리에서의 잡음 환경에서의 고립 단어 인식 실험을 하였다. 그리고 기존의 LP(Linear Prediction)에 의한 가중된 윈도우 켑스트럼 및 PLP에 의한 가중된 Liftering 켑스트럼 등과 비교하였다. 모의 실험 결과는 기존의 가중된 cepstrum 보다 제안하는 성문 가중 켑스트럼이 보다 높은 인식율을 보여준다.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• 산경연구논집
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• 제9권11호
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• pp.39-54
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• 2018

Purpose - To success, in spite of deficient resources, a start-up company has to check various circumstances. Many researchers proposed different appraisal methods for technology commercialization. But everybody agrees Merrifield is the first one, who is a pioneer of an appraisal model of technology commercialization. After he proposed it, many researchers and field workers developed a more complicated model, which called a BMO model. In this research, considering the circumstances of start-ups that lack available resources, it proposes a new appraisal method for technology commercialization, which is named a weighted-BMO model. Research design, data, and methology - For the new BMO-model, it studied the preceding studies. And it found that the success factors for start-ups were correlated with technology commercialization. After comparing the success factors for technology commercialization of start-ups with BMO appraisal factor, it withdraws the net BMO appraisal model: which we are calling the weighted-BMO model. Results - This study found a few things. First, actually, the BMO appraisal factors related with the success factors of technology commercialization. Second, the weighted-BMO model, which included the entrepreneur ability factor, was more accurately estimated the success of technology-based start-ups than the BMO model. Third, it overcame the weakness of the BMO-model, which did not include quantitative factors. In addition to evaluating the feasibility of the BMO model, we also presented a strategy for the future direction. But, still, it included a few shortcomings, which we are calling the arbitrage of weighted value. Sometimes, the intentional weighted value can deliberate the different valuation. Conclusitons - Due to this study, the weighted-BMO model included appraisal factors related with the success factors of technology commercialization and the entrepreneur ability factor, and quantitative factors. When evaluating the combined score of the existing Merrified BMO components, 35 points of the first pass criterion accounted for 29.17% of the total score, and 80 points of the merit score of the second rank criterion were 66.67% Considering that the weighted sum is taken into account, the baseline score of the weighted summing method for each component of the modified BMO model is 2.92 points, which is 29.17% of the weighted sum total of 10 points. The evaluation score was 6.67 points, 66.67% of the weighted total score of 10 points.

• 대한의용생체공학회:의공학회지
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• 제15권3호
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• pp.325-332
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• 1994

본 논문에서는 2D 심초음파영상으로 부터 가중모델을 검출하고 이 모델로써 Hough변환을 수행하여 좌심실의 심내벽윤곽을 검출하는 방법을 제안하였다. 제안된 방법의 수행은 다음과 같이 크게 두단계로 나누어진다. 첫번째 단계에서는 근사적인 심내벽 모델과 모델의 중심을 검출하기 위하여 근사모델 검출 알고리듬이 수행되고 그런다음, 검출된 모델로써 가중모델을 구성한다. 두번째 단계에서는 가중모델과 에지영상을 이용한 Hough변환을 수행하므로써 좌심실 동공의 중심을 자동적으로 찾은 다음, 가중모델, 에지영상 및 동공의 중심과 같은 지식을 이용하여 심내벽 윤곽을 검출하였다.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.177-182
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• 2022

Technology is progressing with every passing day and the enormous usage of electricity is becoming a necessity. One of the techniques to enjoy the assistances in a smart home is the efficiency to manage the electric energy. When electric energy is managed in an appropriate way, it drastically saves sufficient power even to be spent during hard time as when hit by natural calamities. To accomplish this, prediction of energy consumption plays a very important role. This proposed prediction model Coherent Weighted K-Means Clustering ARIMA (CWKMCA) enhances the weighted k-means clustering technique by adding weights to the cluster points. Forecasting is done using the ARIMA model based on the centroid of the clusters produced. The dataset for this proposed work is taken from the Pecan Project in Texas, USA. The level of accuracy of this model is compared with the traditional ARIMA model and the Weighted K-Means Clustering ARIMA Model. When predicting,errors such as RMSE, MAPE, AIC and AICC are analysed, the results of this suggested work reveal lower values than the ARIMA and Weighted K-Means Clustering ARIMA models. This model also has a greater loglikelihood, demonstrating that this model outperforms the ARIMA model for time series forecasting.

• 수산경영론집
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• 제47권1호
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• pp.87-100
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• 2016

Suhyup Bank became to be subject to regulation of capital ratio by Basel III which was introduced in order to enhance stability of the financial institution. Accordingly, Suhyup Bank will require recapitalization. It is important to estimate the risk-weighted assets in calculating of Suhyup Bank's recapitalization scale. Therefor, this study aimed to present a scientific model as estimated the risk-weighted assets. Risk-weighted assets are calculated by applying different risk weights for loans, may have a certain relationship with the loans. Results show that the risk-weighted assets is affected by the previous year's risk-weighted assets and influenced the increase in loans during the year. Since the required basic capital adequacy ratio was specified, the risk-weighted assets should be predicted reasonably. Accordingly, on this study it was tried to derive the accounting equation to predict the risk-weighted assets based on management data of a bank since introduction of Basel III. As the risk-weighted assets were weighted differently according to the type of loans, if the accounting equation is derived by using the type of loans, then it would be helpful for the risk management of banks in the long-term. According to this, the increase of loan would be predicted on the basis of past management performance of Suhyup Bank, and for this reason, the future risk-weighted assets of Suhyup Bank were predicted. The result of this study was showed that 98.3% of risk-weighted assets of the previous year, 62.4% of the secured loan changes and 95.1% of the credit loan changes affected risk-weighted assets.

• 산업공학
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• 제18권2호
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• pp.158-166
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• 2005

Human-error and mental stress caused by psychophysiological dissonance between people and artificial environments have become a social problem. And it is a common knowledge that comfort environment reduces human-error and mental stress. Comfort sensibility is related to complex interactions between fabric, climatic, physiological and psychological variables. Currently, comfort sensibility has been evaluated by many sensory tests. However, it is difficult to evaluate comfort sensibility because a concrete concept of comfort sensibility is hard to define. In this paper, we propose a model to evaluate the comfort sensibility using Fuzzy-weighted score on an individual's subjective state for the stimulus. To represent the degree of comfort sensibility level for the stimulus, we represent comfort sensibility using 2 dimensional sensibility vector model. And we use the fuzzy-weighted score that is a fuzzy version of the weighted checklist technique computerized for evaluating the subjects. As an example, this model is applied to 1/f fluctuation sound evaluation. The results show that this model can be effectively used to the quantitative evaluation of comfort sensibility for the stimulus.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.227-235
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• 2017

When the spatial information of each location is given specifically as coordinates it is popular to use the geographically weighted regression to incorporate the spatial information by assuming that the regression parameters vary spatially across locations. In this paper, we relax the linearity assumption of geographically weighted regression and propose a geographically weighted least squares-support vector machine for estimating geographically weighted mean by using the basic concept of kernel machines. Generalized cross validation function is induced for the model selection. Numerical studies with real datasets have been conducted to compare the performance of proposed method with other methods for predicting geographically weighted mean.