• Korean journal of communication and information
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• v.71
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• pp.52-74
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• 2015

The May 18 Democratic Movement has been considered to be specific case of the big deviation in social memory among the events that occurred after the Korea War. Compared with other events associated with the democratization movement, the May 18 Democratic Movement is special in that can be achieved various changed meaning. In this study, primary focus will be on the background and logics to show what changed the meaning of the May 18 Democratic Movement from the perspectives of the memorial project. And to investigate influences of change of meaning on perspectives and forms of memorial projects. Recognition and forms of memorial projects on the May 18 Democratic Movement had been largely changed around 2000s. Memorial projects were the aspects that are the logics of the social movements absorbed into the logics of the institutionalization before 2000s. During this period, it was done primarily the discourse of a holy ground for democracy and sanctuarization, had characterized the nature of the struggle of memory. After 2000s, the May 18 Democratic Movement has been interpreted historical resources to create a cultural city and a human rights city. Sometimes the May 18 Democratic Movement was appropriated by local development discourse, and sometimes was adopted as the material of differentiation strategy in the city. Form of memorial projects has also been changed type of struggle of memory to type of heritage industry.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.2
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• pp.69-74
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• 2013

In this paper, we propose the pattern classification algorithm of recognizing wrist movements based on electromyogram(EMG) to raise the recognition rate. We consider 30 characteristics of EMG signals wirh the root mean square(RMS) and the difference absolute standard deviation value(DASDV) for the extraction of precise features from EMG signals. To get the groups of each wrist movement, we estimated 2-dimension features. On this basis, we divide each group into two parts with mean to compare and promote the recognition rate of pattern classification effectively. For the motion classification based on EMG, the k-nearest neighbor(k-NN) is used. In this paper, the recognition rate is 92.59% and 0.84% higher than the study before.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.982-990
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• 2018

In recent years, many wearable devices and mobile apps related to life care have been developed, and a service for measuring the movement during walking and showing the amount of exercise has been provided. However, they do not measure walking in detail, so there may be errors in the total calorie consumption. If the user's behavior is measured by a multi-axis sensor and learned by a machine learning algorithm to recognize the kind of behavior, the detailed operation of walking can be autonomously distinguished and the total calorie consumption can be calculated more than the conventional method. In order to verify this, we measured activities and created a model using a machine learning algorithm. As a result of the comparison experiment, it was confirmed that the average accuracy was 12.5% or more higher than that of the conventional method. Also, in the measurement of the momentum, the calorie consumption accuracy is more than 49.53% than that of the conventional method. If the activity recognition is performed using the wearable device and the machine learning algorithm, the accuracy can be improved and the energy consumption calculation accuracy can be improved.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.473-480
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• 2014

As the use of computer has been popularized these days, an active research is in progress to make much more convenient and natural interface compared to the existing user interfaces such as keyboard or mouse. For this reason, there is an increasing interest toward Microsoft's motion sensing module called Kinect, which can perform hand motions and speech recognition system in order to realize communication between people. Kinect uses its built-in sensor to recognize the main joint movements and depth of the body. It can also provide a simple speech recognition through the built-in microphone. In this paper, the goal is to use Kinect's depth value data, skeleton tracking and labeling algorithm to recognize information about the extraction and movement of hand, and replace the role of existing peripherals using a virtual mouse, a virtual keyboard, and a speech recognition.

• Ocean Systems Engineering
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• v.4 no.1
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• pp.53-62
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• 2014

The detection of ship wakes image can demonstrate substantial information regarding on a ship, such as its tonnage, type, direction, and speed of movement. Consequently, the wake target recognition is a favorable way for ship identification. This paper proposes a Local Binary Pattern (LBP) approach to extract image features (wakes) for training an Improved Back Propagation Artificial Neural Network (IBPANN) to identify ship speed. This method is applied to sort and recognize the ship wakes of five different speeds images, the result shows that the detection accuracy is satisfied as expected, the average correctness rates of wakes target recognition at the five speeds may be achieved over 80%. Specifically, the lower ship's speed, the better accurate rate, sometimes it's accuracy could be close to 100%. In addition, one significant feature of this method is that it can receive a higher recognition rate than the nearest neighbor classification method.

• Women's Health Nursing
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• v.4 no.2
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• pp.245-257
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• 1998

The characteristics of health behavior related pregnancy and childbirth have reflected on the cultural belief and value in the society. The efforts for women's health promotion through the current illumination of the traditional health care are the prompting assignment to be in nursing. The process of motherhood already progress before the motherhood actually. The functional state as the expectant mother can be the important predicting factor of the postpartum state, the quality of a married life. Motherhood was analyzed by Walker and Avant's method to clarify the concept 'to be a mother' using the various concepts like Koreans' Taekyo, transition to motherhood, maternal identity, maternal role attainment, maternal fetal attachment, and maternal fetal interaction. Upon the concept analysis, naturalness, responsibility, attachment, readiness, controllability were identified as the defining characteristics of motherhood. The antecedents of motherhood were consist of maternal affection, positive self esteem, pregnancy acceptance, fetus recognition and the consequences of motherhood were consist of positive maternal identity, maternal fetal attachment, confidence about the maternal role, the healthy mother and the healthy baby. The empirical referents of motherhood were consists of recognition of motherhood, expectation about motherhood, fetal recognition with ultrasonography and fetal movement, experience of unification between mother and fetus, expression of affection to the fetus, concern about fetal health, concern and practice about Taekyo, adaptation behavior about physical change and discomfort due to pregnancy. Therefore it is necessary to develop the instruction program of motherhood including the defining attributes identified in this study.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.1
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• pp.76-83
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• 2012

In a real-time indoor place recognition system using image features detection, specific markers included in input image should be detected exactly and quickly. However because the same markers in image are shown up differently depending to movement, direction and angle of camera, it is required a method to solve such problems. This paper proposes a technique to extract the features of object without regard to change of the object scale. To support real-time operation, it adopts SURF(Speeded up Robust Features) which enables fast feature detection. Another feature of this system is the user mark designation which makes possible for user to designate marks from input image for location detection in advance. Unlike to use hardware marks, the feature above has an advantage that the designated marks can be used without any manipulation to recognize location in input image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1751-1767
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• 2016

Home security has become the prime concern for everyone in present scenario. In this work an attempt has been made to develop a home security system which is accessible, affordable and yet effective.The proposed system is based on 'Remote Embedded Control System' (RECS) which works both on the web and gsm platform for authentication and monitoring. This system is therefore cost effective as it relies on existing network infrastructure. As PCA is most popular and efficient algorithm for face recognition, it has been usedin this work. Next to it an interface has been developed for communication purpose in the embedded security system through the ZigBee module. Based on this embedded system, automated control of door movement has been implemented through electromagnetic door lock technology. This helps the users to monitor the real-time activities through web services/SMS. The web service consists of either web browser command or e-mail provision. The system establishes the communication between the system and authenticated user. The e-mail received by the system from the authorized person will monitor and control the real-time operation and door lock. The entire control system is reinforced using ARM1176JZF-S microcontroller and tested for actual use in the home environment. The result shows the experimental verification of the proposed system.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.35-44
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• 2020

In this study, we propose a reliable command placement recognition algorithm using tangible commands blocks developed for our coding puzzle platform, and present its performance measurement results on an Augmented Reality testbed environment. As a result, it can recognize up to 30 tangible blocks simultaneously and their placements within 5 seconds reliably. It is successfully ported to an existing coding puzzle mobile app and can operate an IoT attached robot via bluetooth connected mobile app.

• Smart Media Journal
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• v.5 no.3
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• pp.25-29
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• 2016

This paper presents research for non-contact gesture recognition system using EPS(Electronic Potential Sensor) for measuring the human body of electromagnetic fields. It implemented a signal acquisition and signal processing system for designing a system suitable for motion recognition using the data coming from the sensors. we transform AC-type data into DC-type data by applying a 10Hz LPF considering H/W sampling rate. in addition, we extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensor.