• The Korea Journal of Herbology
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• v.26 no.1
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• pp.1-6
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• 2011

Objectives : Due to morphological similarity, many substitutes and counterfeits have been used as Moktong for thousands of years. This study was designed to determine discriminative criteria for identifying medicinal herbs used as Moktong. Methods : Akebia quinata, A. trifoliata, Clematis armandii, and Aristolochia manshuriensis were collected in various regions. Samples were authenticated and examined by observation and microscopy with paraffin embedding and triple staining using the modified Ju staining method. Results : Three different types of features to establish discriminative criteria for four kinds of Moktong were identified. Botanical features include differences in phyllotaxy, leaf shape, and caulescent. External morphological features were arrangement and size of fine holes(xylem), and overall shape of the section. Internal morphological features include the number of medullary rays, shape of the pitch, type of tissues rounding pitch, appearance of annual rings, shape and amount of crystals(calcium-oxalate), and the appearance of cork cambium. Further details(e.g. identification keys) are in the article. Conclusions : These criteria could provide an effective method for identifying numerous kinds of Moktong distributed in markets throughout northeast Asian nations.

• Journal of Oral Medicine and Pain
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• v.47 no.2
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• pp.87-94
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• 2022

Purpose: This study aimed to evaluate the differences between clinical and quantitative sensory testing (QST) results among persistent idiopathic dentoalveolar pain (PIDP), inflammatory dental pain, and control group subjects to identify discriminative clinical features for differential diagnosis. Methods: Thirty-three patients (5 PIDP-a without surgical procedures 10 PIDP-b with surgical procedures, 8 dental pain patients, and 10 controls) were evaluated for clinical features and QST results. Cold pain threshold, heat pain threshold, mechanical pain threshold (MPT), mechanical pain sensitivity, and pressure pain threshold (PPT) were performed. Psychological factors were assessed using Symptom Checklist-90-Revision (SCL-90-R) and a chart review was conducted to evaluate additional discriminative clinical features such as pain quality and treatment prognosis. Results: The dental pain group had lower PPT than the PIDP-b and the control group. The PIDP-a group showed higher MPT and PPT than the PIDP-b and dental pain group but the difference was not statistically significant. Differences in SCL-90-R SOM (Somatization), O-C (obsessive-compulsive), ANX (anxiety), and PSY (Psychoticism) values were statistically significant among groups. PIDP-a and PIDP-b groups showed remaining symptoms after treatment and the pain tended to spread widely, whereas, in toothache patients, symptoms disappeared after treatment. However, factors that confound the diagnosis, such as an increase in pain during chewing and a decrease in the pain threshold at the affected site, could also be identified. Conclusions: PIDP and dental pain groups have distinct clinical symptoms, but there are also factors that cause confusing in diagnosis. Therefore, various clinical examination results should be carefully reviewed and comprehensively evaluated in the differential diagnosis process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.794-814
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• 2012

We propose a novel method for improving Wi-Fi positioning accuracy while reducing the energy consumption of mobile devices. Our method presents three contributions. First, we jointly and intelligently select the optimal subset of access points for positioning via maximum mutual information criterion. Second, we further propose local discriminant embedding algorithm for nonlinear discriminative feature extraction, a process that cannot be effectively handled by existing linear techniques. Third, to reduce complexity and make input signal space more compact, we incorporate clustering analysis to localize the positioning model. Experiments in realistic environments demonstrate that the proposed method can lower energy consumption while achieving higher accuracy compared with previous methods. The improvement can be attributed to the capability of our method to extract the most discriminative features for positioning as well as require smaller computation cost and shorter sensing time.

• Journal of Multimedia Information System
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• v.1 no.2
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• pp.119-126
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• 2014

We propose a bicycle detection system riding on people based on modified projected local binary pattern(PLBP) for vision based intelligent vehicles. Projection method has robustness for rotation invariant and reducing dimensionality for original image. The features of Local binary pattern(LBP) are fast to compute and simple to implement for object recognition and texture classification area. Moreover, We use uniform pattern to remove the noise. This paper suggests that modified LBP method and projection vector having different weighting values according to the local shape and area in the image. Also our system maintains the simplicity of evaluation of traditional formulation while being more discriminative. Our experimental results show that a bicycle and motorcycle riding on people detection system based on proposed PLBP features achieve higher detection accuracy rate than traditional features.

• ETRI Journal
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• v.41 no.6
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• pp.750-759
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• 2019

Presently, the extraction of hand-crafted features is still the dominant method in radar emitter recognition. To solve the complicated problems of selection and updation of empirical features, we present a novel automatic feature extraction structure based on deep learning. In particular, a convolutional neural network (CNN) is adopted to extract high-level abstract representations from the time-frequency images of emitter signals. Thus, the redundant process of designing discriminative features can be avoided. Furthermore, to address the performance degradation of a single platform, we propose the construction of an ensemble learning-based architecture for multi-platform fusion recognition. Experimental results indicate that the proposed algorithms are feasible and effective, and they outperform other typical feature extraction and fusion recognition methods in terms of accuracy. Moreover, the proposed structure could be extended to other prevalent ensemble learning alternatives.

• ETRI Journal
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• v.33 no.2
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• pp.210-218
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• 2011

Battiti's mutual information feature selector (MIFS) and its variant algorithms are used for many classification applications. Since they ignore feature synergy, MIFS and its variants may cause a big bias when features are combined to cooperate together. Besides, MIFS and its variants estimate feature redundancy regardless of the corresponding classification task. In this paper, we propose an automated greedy feature selection algorithm called conditional mutual information-based feature selection (CMIFS). Based on the link between interaction information and conditional mutual information, CMIFS takes account of both redundancy and synergy interactions of features and identifies discriminative features. In addition, CMIFS combines feature redundancy evaluation with classification tasks. It can decrease the probability of mistaking important features as redundant features in searching process. The experimental results show that CMIFS can achieve higher best-classification-accuracy than MIFS and its variants, with the same or less (nearly 50%) number of features.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.141-149
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• 2007

Associating the shoulder line with head location of the human body is useful in verifying, localizing and tracking persons in an image. Since the head line and the shoulder line, what we call ${\Omega}$-shape, move together in a consistent way within a limited range of deformation, we can build a statistical shape model using Active Shape Model (ASM). However, when the conventional ASM is applied to ${\Omega}$-shape fitting, it is very sensitive to background edges and clutter because it relies only on the local edge or gradient. Even though appearance is a good alternative feature for matching the target object to image, it is difficult to learn the appearance of the ${\Omega}$-shape because of the significant difference between people's skin, hair and clothes, and because appearance does not remain the same throughout the entire video. Therefore, instead of teaming appearance or updating appearance as it changes, we model the discriminative appearance where each pixel is classified into head, torso and background classes, and update the classifier to obtain the appropriate discriminative appearance in the current frame. Accordingly, we make use of two features in fitting ${\Omega}$-shape, edge gradient which is used for localization, and discriminative appearance which contributes to stability of the tracker. The simulation results show that the proposed method is very robust to pose change, occlusion, and illumination change in tracking the head and shoulder line of people. Another advantage is that the proposed method operates in real time.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.231-233
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• 2003

Agricultural land use generally shows specific temporal characteristics of NDVI obtained from satellite data. In terms of winter wheat, a higher value compared with other land use types in May and a considerably low value in June could be discriminative features of temporal change of NDVI. In this study, the author examined methods for estimating winter wheat sown area in sub-pixel level of coarse resolution satellite data using temporal characteristics of NDVI. Application of the methods to the major grain production area in China exhibited properly a spatial distribution pattern of winter wheat sown area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1595-1613
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• 2017

The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.387-396
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• 2005

The purpose of this research was to find differences of children's behavioral pattern between players and non players of the online game "Lineage" in on-line and off line space. As a result, social behaviors of children who play online games were less active than who don't. Based on their motive and behavior pattern in online world, four behavior patterns in online world were identified; "Single-Oriented", "Community-Oriented", "Off-Real World" and "Discriminative." Off-Real World and Discriminative players were more sociable than Single-Oriented and Community-Oriented players. And Discriminative player has more self assertive attitude than others. This study may serve as a model to understand how players will respond to the various game features and how they adopt the virtual world for their interpersonal relationships.