• Journal of Korea Technology Innovation Society
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• v.16 no.2
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• pp.391-407
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• 2013

The paper tests the embodiment hypothesis by measuring the technological obsolescence of a specific year (1990)'s technology and investigating the relationship between labor productivity and technological obsolescence. This approach is based on Salter (1969) that emphasizes the economic aspect of technology. We use the rate of economic surplus as the proxy of technological obsolescence for 10 main industries, including food processing, textiles, chemicals, non-steel metals, steels, metal products, machinery, electronics, precision machinery, and transportation equipments. The result shows that the embodiment hypothesis is not accepted for the overall manufacturing sector. However, we found the vintage effect - a positive relationship between technological obsolescence and labor productivity over time - in textiles, chemicals, non-steel metals, metal products, electronics, and transportation equipments. Therefore, the government should support R&D investment as well as capital equipments investment for the industries with large vintage effect.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.764-776
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• 1999

In this paper, a tracking algorithm for a maneuvering single target in the presence of multiple data from multiple sensors is investigated. Allowing individual sensors to function by themselves, the estimates from individual sensors on the same target are fused for the purpose of improving the state estimate. The filtering method adopted in the local sensors is the variable dimensional filter with input estimatio technique, which consists of a constant velocity model and a constant acceleration model. A posteriori probability for the maneuvering hypothesis is newly derived. It is shown that the relation function of the a posteriori probability is a function of only the covariance of the fused estimates. Simulation results are provided.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.433-441
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• 1992

This paper describes an algorithm that can efficiently analyze the ECG signal using frame knowledge representation technique. Input to the analysis process is a set of significant points which have been extracted from an original sampled signal(lead II) by the syntactic peak recognition algorithm. The hierarchical property of ECG signal is represented by hierarchical AND/OR graph. The semantic information and constraints of the ECG signal are desctibed by frame. As the control mechanism for labeling points, the search mechanism with the mixed paradigms of data-driven and model driven hypothesis formation, scoring function, hypothesis modification network and instance inheritance are used. We used the CSE database in order to evaluate the performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.575-579
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• 1990

This paper describes an algorithm that can efficiently analyze the multichannel ECG signal using the frame. The input is a set of significant features (points) which have been extracted from an original sampled signal by using the split-and-merge algorithm. A signal from each channel can be hierarchical ADN/OR graph on the basis of the priori knowledge for ECG signal. The search mechanisms with some heuristics and the mixed paradigms of data-driven hypothesis formation are used as the major control mechanisms. The mutual relations among features are also considered by evaluating a score based on the relational spectrum. For recognition of morphologies corresponding to OR nodes, an hypothesis modification strategy is used. Other techniques such as instance, priority update of prototypes, and template matching facility are also used. This algorithm exactly recognized the primary points and supporting points from the multichannel ECG signals.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.75-81
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• 2014

This study is analyzed using the Shanghai stock market and Shenzhen stock market data in order to analyze the usefulness of accounting information to appear from the introduction of international accounting standards in China. Summarized the relevant previous researches for objective study approach, studied the hypothesis based on the empirical analysis and set a hypothesis as adjusting the stuffs to fix in this research model. In this study, Analyzed the hypothesis to input of detailed variables for analyzing the value relevance between periods before fair value and after fair value. Also, in this hypothesis study, analyzed and estimated to affect the quality of information the acceptant period when compare with acceptant periods and before periods of fair value. These results suggested that impact the net asset value per share and earnings per share of the company because the value of the relationship had statistically significant at the level of relevance. Therefore, in the future studies about fair value assessment, will be expected that usefulness of the enterprise value evaluation method enable to discuss it such as critical sucess factors.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.63-73
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• 2009

This paper presents a vehicle detection method that uses convolution matching method based on a simple color information. An input image is expressed as 8 oriented color expression(Red, Green, Blue, White, Black, Cyan, Yellow, Magenta) considering an orientation of a pixel color vector. It makes the image very reliable and strong against changes of illumination condition or environment. This paper divides the vehicle detection into a hypothesis generation step and a hypothesis verification step. In the hypothesis generation step, the vehicle candidate region is found by vertical edge and shadow. In the hypothesis verification step, the convolution matching and the complexity of image edge are used to detect real vehicles. It is proved that the proposed method has the fast and high detection rate on various experiments where the illumination source and environment are changed.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1387-1395
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• 2006

This paper considers testing for the ratio of two exponential means. We propose a solution based on a Bayesian decision rule to this problem in which no subjective input is considered. The criterion for testing is the Bayesian reference criterion (Bernardo, 1999). We derive the Bayesian reference criterion for testing the ratio of two exponential means. Simulation study and a real data example are provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2178-2198
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• 2024

Graph-based document models have good capabilities to reveal inter-dependencies among unstructured text data. Natural language processing (NLP) systems that use such models as an intermediate representation have shown good performance. This paper proposes a novel fuzzy graph-based document model and to demonstrate its effectiveness by applying fuzzy logic tools for text summarization. The proposed system accepts a text document as input and identifies some of its sentence level features, namely sentence position, sentence length, numerical data, thematic word, proper noun, title feature, upper case feature, and sentence similarity. The fuzzy membership value of each feature is computed from the sentences. We also propose a novel algorithm to construct the fuzzy graph as an intermediate representation of the input document. The Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metric is used to evaluate the model. The evaluation based on different quality metrics was also performed to verify the effectiveness of the model. The ANOVA test confirms the hypothesis that the proposed model improves the summarizer performance by 10% when compared with the state-of-the-art summarizers employing alternate intermediate representations for the input text.

• The Journal of the Acoustical Society of Korea
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• v.19 no.2
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• pp.90-94
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• 2000

In this paper, we propose an efficient method of estimating a critical threshold which is used to reject unreliable patterns in a HMM based recognition system. The rejection methods based on the anti-models which are formulated as the statistical hypothesis determine whether or not to accept an input pattern by comparing the likelihood ratio of HMM and anti-models to a critical threshold. It is quite difficult to fix a threshold for the probability of a HMM because the range of such probabilities varies severely depending on the chosen class model. We estimate the critical threshold, which is very class-dependent, using the likelihood scores for the training database. In our experiments, we applied the proposed estimating method of the threshold to the HMM based 3D hand gesture recognition system. We found that this method can be used successfully for rejecting unreliable input gestures regardless of the types of anti-models.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1003-1013
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• 2016

This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.