• Journal of Agricultural Extension & Community Development
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• v.29 no.4
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• pp.251-264
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• 2022

This study aimed to identify the factors that influence young entrepreneurs' desire to start a smart farm business. Young entrepreneurs' entrepreneurial self-efficacy, entrepreneurial intention, entrepreneurship, and Entrepreneurial opportunity recognition were modeled structurally, and the mediating effect of entrepreneurship and entrepreneurial opportunity recognition was investigated. Data were conducted from 159 usable questionnaires. The following are the findings of this study. Entrepreneurial self-efficacy did not have a significant effect on entrepreneurial intention, but entrepreneurship and entrepreneurial opportunity recognition were found to have a mediating effect on entrepreneurial intention. Therefore, the preparation of training programs to encourage entrepreneurship or the dissemination of pertinent information to identify opportunities should take precedence over immediate startup.

• Journal of KIISE
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• v.42 no.8
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• pp.1031-1038
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• 2015

The recent emergence of smart phones, wearable devices, and even the IoT concept made it possible for various objects to interact one another anytime and anywhere. Among many of such smart services, a smart home service typically requires a large number of sensors to recognize the residents' activities. For this reason, the ideas on activity recognition using the data obtained from those sensors are actively discussed and studied these days. Furthermore, plenty of sensors are installed in order to recognize activities and analyze their patterns via data mining techniques. However, if many of these sensors should be installed for IoT smart home service, it raises the issue of cost and energy consumption. In this paper, we proposed a new method for reducing the number of sensors for activity recognition in a smart environment, which utilizes the principal component analysis and clustering techniques, and also show the effect of improvement in terms of the activity recognition by the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1122-1129
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• 2009

Recently taping robot with smart recognition function have been studied in the coil manufacturing field. Due to the difficulty of 3D surface processing from the complicated working environment, it is not easy to accomplish smart tape attachment motion with non-contact sensor. To solve these problems the applicable surface recognition algorithm and a flexible sensing device has been recommended. In this research, the fusion method between 1D displacement and 3D laser scanner is applied for robust tape attachment about cold rolled coil. With these sensors we develop a two-step exploration and the smart algorithm for the awareness of non-aligned coil's information. In the proposed robot system for tape attachment, the problem is reduced to coil's radius searching with laser displacement sensor at first, and then position and orientation detection with 3D laser scanner. To get the movement at the robot's base frame, the hand-eye compensation between robot's end effector and sensing device should be also carried out respectively. In this paper, we examine the auto-coordinate transformation method in the calibration step for the real environment usage. From the experimental results, it was shown that the taping motion of robot had a robust under the non-aligned cold rolled coil.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.143-150
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• 2017

In this paper, we propose a novel motion recognition platform using smart-phone tracking and color communication. The interface requires only a camera and a personal smart-phone to provide a motion control interface rather than expensive equipment. The platform recognizes the user's gestures by the tracking 3D distance and the rotation angle of the smart-phone, which acts essentially as a motion controller in the user's hand. Also, a color coded communication method using RGB color combinations is included within the interface. Users can conveniently send or receive any text data through this function, and the data can be transferred continuously even while the user is performing gestures. We present the result that implementation of viable contents based on the proposed motion recognition platform.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.85-95
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• 2011

Smart phones, greatly expanding in the recent mobile market, are equipped with various features compared to existing feature phones and provide the conveniences to in several ways. The camera, one of the features of a smartphone, creates the digital contents, such photos and videos, and plays a role for the media which transmits information, such as video calls and bar code reader. QR-Code recognition is also one of the camera features. It contains a variety of information in two-dimensional bar code type in matrix format, and makes it possible to obtain the information by using smart phones. This paper analyzes the method of QR-Code recognition, password method-the existing user-authentication technique, smart card, biometrics and voice recognition and so on and thenn designs a new user-authentication technique. The proposed user-authentication technique is the technique in which QR-Code, which can be simply granted is read by smart phones and transmitted to a server, for authentication. It has the advantages in view that it will simply the process of authentication and conteract the disadvantages, such as brute force attack, man-inthe-middle attack, and keyboard hacking, which may occur in other authentication techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.393-396
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• 1995

In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

• Journal of Drive and Control
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• v.17 no.3
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• pp.9-14
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• 2020

A special purpose machine with two manipulators and quadruped crawler system is being developed to work at disaster sites where it is intended to quickly respond in the initial stages after the event. In this study, a terrain recognition module is developed so that the above special purpose machine can quickly obtain ground information to help choose its path while recognizing objects in its way, this is intended to enhance the remote driver's limited situational awareness. Terrain recognition modules were developed for two tasks (real-time path guidance, precision terrain measurements). The real-time path guidance analyzes terrain and obstacles while moving, while the precision terrain measurement feature provides more accurate terrain information by precisely measuring the ground in front of the vehicle while stationary. In this study, an air-cooled sensor protection module was developed so that the terrain recognition module can continue its vital tasks in the event of exposure to foreign substances, including scattered dust, mist and rainfall, as well as high temperatures.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.48-55
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• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.260-267
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• 2015

In the past, we implemented a web-based smart education platform, but this is not efficient in a smart or mobile education environment. Therefore, in this paper, we propose an Android-based e-board smart platform for a smart or mobile education system. Here, we use Anoto digital pen- and dot pattern-based technologies. This Android-based smart education platform is efficient for a smart education environment. Further, we implement the hardware and software parts of the technologies, an Anoto-based trajectory recognition algorithm, and a probabilistic neural network for handwritten digit and hand gesture recognition.

• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.278-286
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• 2008

Reliable functionalities for autonomous navigation and object recognition/handling are key technologies to service robots for executing useful services in human environments. A considerable amount of research has been conducted to make the service robot perform these operations with its own sensors, actuators and a knowledge database. With all heavy sensors, actuators and a database, the robot could have performed the given tasks in a limited environment or showed the limited capabilities in a natural environment. With the new paradigms on robot technologies, we attempted to apply smart environments technologies-such as RFID, sensor network and wireless network- to robot functionalities for executing reliable services. In this paper, we introduce concepts of proposed smart environments based robot navigation and object recognition/handling method and present results on robot services. Even though our methods are different from existing robot technologies, successful implementation result on real applications shows the effectiveness of our approaches.