• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.137-140
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• 1996

Finding line segments in an intensity image has been one of the most fundamental issues in computer vision. In complex scenes, it is hard to detect the locations of point features. Line features are more robust in providing greater positional accuracy. In this paper we present a robust "line features extraction" algorithm which extracts line feature in a single pass without using any assumptions and constraints. Our algorithm consists of five steps: (1) edge scanning, (2) edge normalization, (3) line-blob extraction, (4) line-feature computation, and (5) line linking. By using edge scanning, the computational complexity due to too many edge pixels is drastically reduced. Edge normalization improves the local quantization error induced from the gradient space partitioning and minimizes perturbations on edge orientation. We also analyze the effects of edge processing, and the least squares-based method and the principal axis-based method on the computation of line orientation. We show its efficiency with some real images.al images.

• Phonetics and Speech Sciences
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• v.6 no.1
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• pp.71-76
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• 2014

In this paper voice quality of normal speech is qualitatively classified by five components of breathy, creaky, rough, nasal, and thin/thick voice. To determine whether a correlation exists between a subjective measure of voice and an objective measure of voice, each voice is perceptually evaluated using the 1/2/3 scale by speech processing specialists and acoustically analyzed using speech analysis tools such as the Praat, MDVP, and VoiceSauce. The speech parameters include features related to speech source and vocal tract filter. Statistical analysis uses a two-independent-samples non-parametric test. Experimental results show that statistical analysis identified a significant correlation between the speech feature parameters and the components of voice quality.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.1
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• pp.99-112
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• 1994

This paper describe the development of a systematic method of slicing solid parts based on a data structure called Sliced Profile Data Structure(SPDS). SPDS is an augmented polygon data structure that allows multiple layers of sliced profiles to be connected together. The method consists of five steps: (1) Selection of slicing directions, (2) Determination of slicing levels, (3) Creation of sliced profiles, (4) Connection of sliced profiles, and (5) Refinement. The presented method is aimed at enhancing the applicability of CSG for manufacturing by overcoming the problem of non-uniqueness and global nature. The SPDS-based method of feature extraction is suitable for recognizing broad scope of features with detailed information. The method is also suitable for identifying the global relationships among features and is capable of incorporating the context dependency of feature extraction.

• The Journal of Information Systems
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• v.20 no.2
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• pp.21-36
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• 2011

The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. This paper focuses on online customer reviews of products. It makes some contributions. Especially it proposes minimalism and chunking framework for analyzing and comparing consumer opinions of competing products. Users are able to clearly see the strengths and weaknesses of each product in the minds of consumers in terms of various product features. This comparison is useful to both potential customers and product manufacturers. For a product manufacturer, the comparison enables it to easily gather marketing intelligence and product benchmarking information. In this paper, we only focus on mining opinion/product features that the reviewers have commented on. Five types of online review presentations are presented to mine such features. Our experimental results show that these techniques are useful to identify customers' opinions and trends.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.59-65
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• 2004

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.32.2-32.2
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• 2018

We present the structural parameters of ~ 910 dwarf elliptical-like galaxies in the local universe ($z{\lesssim}0.01$) derived from the r-band images of the Sloan Digital SKy Survey (SDSS). We examine the dependence of structural parameters on the morphological types (dS0, dE, dEbc, dSph, and dEblue) and the environment. There is not much difference in the structural parameters among the five subtypes but the mean surface brightness within the effective radius (<${\mu}e$>) of dSph galaxies is clearly different from that of other subtypes. The frequency of disk features such as spiral arm, bar, lens, and rings strongly depends on the morphology of dwarf elliptical-like galaxies with no disk features in dSph galaxies. The absence of disk features and the low surface brightness of dSph galaxies are thought to be closely related to their low mass which leads to different evolution from other subtypes of dwarf elliptical-like galaxies. Density Environments Using IMSNG.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.2
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• pp.59-66
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• 2016

Dynamic changes in the field of labor relations have become a general trend in the world practice. These changes are due the impact of globalization and technological innovation above all. Concept of "precarization of employment" appeared due the new emerging labor relations. This term has been used for more than thirty-five years, but there is still no generally accepted definition of it. A wide range of authors' viewpoints on problem of precarization makes it vague and impossible to strictly to identify its borders. Features of its manifestations in different countries also complicate the problem. Kazakhstan is a country with export-oriented economy of raw materials. At the same time government try to solve the problem for the industrial-innovative development of the economy. These two factors bring additional specific features in the manifestation of the precarization of employment in the country. The aim of the paper is to identify the features of "precarization of employment" concept in Kazakhstan's practice, based on the proposed definition.

• English Language & Literature Teaching
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• v.18 no.3
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• pp.53-75
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• 2012

The present study examined the role of language proficiency in dyadic discourse in the organization of repairs and the distribution of linguistic features contained in repairs. One native speaker of English and five non-native speakers participated and formed three dyads: one same-proficiency NNS-NNS (non-native speaker), one different-proficiency NNS-NNS, and one NS (native speaker)-NNS dyads. Results showed that overall repair patterns in this type of interaction were more conversational than didactic, and that the degree of difference in proficiency between the participants in the dyad influenced repair patterns and the distribution of linguistic features in relation to repair patterns. Also, discussed in the present paper are some implications of the results and other issues related to language learning.

• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.244-253
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• 2001

For more complete process planning, machining sequence determination is critical to attain machining economics. Although many studies have been conducted in recent years, most of them suggests the non-unique machining sequences. When the tool approach directions(TAD) are considered fur a feature, both machining time and number of setups can be reduced. Then, the unique machining sequence can be extracted from alternate(non-unique) sequences by minimizing the idle time between operations within a sequence. This study develops an algorithm to generate the best machining sequence for composite prismatic features in a vertical milling operation. The algorithm contains five steps to produce an unique sequence: a precedence relation matrix(PRM) development, tool approach direction determination, machining time calculation, alternate machining sequence generation, and finally, best machining sequence generation with idle times. As a result, the study shows that the algorithm is effective for a given composite feature and can be applicable fur other prismatic parts.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.1-11
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• 2017

In this paper, we design and implement PADIL(Prediction And Detection of Information Leakage) system that predicts and detect information leakage behavior of insider by analyzing network traffic and applying a variety of machine learning methods. we defined the five-level information leakage model(Reconnaissance, Scanning, Access and Escalation, Exfiltration, Obfuscation) by referring to the cyber kill-chain model. In order to perform the machine learning for detecting information leakage, PADIL system extracts various features by analyzing the network traffic and extracts the behavioral features by comparing it with the personal profile information and extracts information leakage level features. We tested various machine learning methods and as a result, the DecisionTree algorithm showed excellent performance in information leakage detection and we showed that performance can be further improved by fine feature selection.