• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.812-824
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• 2016

Morning grooming is a ritual daily held for transition from private to public life of an individual. Based on the previous literature's definition of the ritual characteristics, this study aims to identify the meaning of grooming rituals that are repeatedly performed every morning. Although many studies have conducted ritualistic analysis of the behaviors that are closely related to daily life, few studies analyze grooming from a ritualistic perspective. Establishing the ritual - that is, a person's distinct behavioral pattern-as the core concept, this study reveals the relationship between ritual performers and the ritual's composition to identify the meaning of the grooming ritual. The study conducts qualitative research with ten participants to identify the ritual characteristics of every-morning grooming and the factors that influence this ritual. Considering everyday grooming as a behavioral pattern that possesses mostly ritualistic elements, the study examines both the external characteristics that are shown through the methods of grooming and the internal characteristics that reflect the inherent symbolic meaning. This study contributes to extending the scope of the field. By understanding the factors that influence grooming rituals, companies can communicate their marketing messages regarding the step-by-step approach to grooming, thereby supporting consumers to effectively use various grooming products.

• Journal of ILASS-Korea
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• v.21 no.3
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• pp.155-161
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• 2016

Injected fuel pressure waves of a common rail injector with various current profiles supplied to the injecor were measured using Bosch method. In order to drive the common rail injector, the current in the solenoid should be controlled using what is known as a peak and hold pattern, which consists of a high current level with a short time duration (peak) in the first step and a low current level with a long time duration (hold) in the subsequent step. The current profile can be shaped by swithcing an injector driving power source with the peak and hold waves. The capture, compare and PWM (CCP) pin in the microprocessor was used to generate the combined peak and hold waves. The PWM square wave generated from the CCP pin has a duty ratio of 100% for the peak current and 10% or 30% for the hold pattern. Five patterns of the current profile were generated by combining the peak and hold wave. The common rail pressure is controlled at 75, 100, and 130 MPa. As the fuel rail pressure increases, the variations of the measured fuel injection pressure wave according to the current profiles decrease.

• Journal of the Korean Institute of Gas
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• v.2 no.1
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• pp.53-58
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• 1998

By knowledge-based approach, the SDG(Signed Directed Graph) is automatically synthesized, which is commonly used to represent the causal effects between process variables. Automatic synthesis of SDG is progressed by two steps : (1)inference step uses knowledge base and (2)verification step uses Loop-Verifier. First, Topology and Knowledge Base are constructed by using the information on equipment. And then, Primary-SDG is synthesized by Character Pattern Matching between Variable-Relation-Representation generated by using Topology and Variable-Tendency-Data contained in Knowledge Base. Finally, a modified SDG is made after the Primary-SDG is verified by Loop-Verifier.

• The Journal of the Society of Stroke on Korean Medicine
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• v.14 no.1
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• pp.8-14
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• 2013

■ Objectives The goal of this study is to find the correlation between the motor function and gait pattern of stroke patients. ■ Methods We measured Manual muscle test(MMT), Motricity index(MI) and Spatiotemporal gait parameters of admitted hemiplegic patients with stroke. The gait parameters were measured using a Treadmill gait system. ■ Results There is a significant correlation between motor function and spatiotemporal parameters such as step length, stride length, step time, stride time, total double support or cadence, in stroke patients. ■ Conclusion The better motor function of stroke was, the more gait improved.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.83-84
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• 2006

In this paper, we examine discharge characteristics of cross-linked polyethylene (since then; XLPE) according to thickness. Voltage was applied to power frequency by step method, and calibration of discharge was set to 50[pC] (slope=8.333). After the voltage was applied, for 10 [sec] (600 [cycle]), occurring discharge and number were detected. Determine of input pattern is difficult because discharge pattern is irregular. Therefore we investigated pattern using the K-means Analysis and Weibull function. Also we investigated variation of centroid and cluster.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2368-2375
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• 2015

To accommodate various navigational commands, a humanoid should be able to change its walking motion in real time. Using the modifiable walking pattern generation (MWPG) algorithm, a humanoid can handle dynamic walking commands by changing its walking period, step length, and direction independently. If the humanoid is given a command to perform an infeasible movement, the algorithm substitutes the infeasible command with a feasible one using binary search. The feasible navigational command is subsequently translated into the desired center-of-mass (CM) state. Every sample time CM reference is generated using a zero-moment-point (ZMP) variation scheme. Based on this algorithm, various complex walking patterns can be generated, including backward and sideways walking, without detailed consideration of the feasibility of the navigational commands. In a previous study, the effectiveness of the MWPG algorithm was verified by dynamic simulation. This paper presents experimental results obtained using the small-sized humanoid robot platform DARwIn-OP.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.714-717
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• 1996

This paper presents a fault detection and diagnosis methodologies based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. At the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model(WSM) is used to generate those candidates. The weight is determined from dynamic simulation. Using WSMs, the methodology can generate the cause candidates and rank them according to the probability. Secondly, the fault propagation trends identified from the partial or complete sequence of measurements are compared to the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies and showed satisfactory diagnostic resolution.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.143-145
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• 2005

In this paper, an empirical study result on pattern estimation method is devoted to reveal underlying data patterns with a relatively reduced computational cost. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). Conventional SAHN based clustering requires large computation time in the initial step of algorithm. To deal with this concern, we modified overall process with a partial approach. In the beginning of this method, we divide given data set to several sub groups with uniform sampling and then each divided sub data group is applied to SAHN based method. The advantage of this method reduces computation time of original process and gives similar results. Proposed is applied to several test data set and simulation result with conceptual analysis is presented.