• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.463-474
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• 2015

Future Ground Control Stations (GCSs) for Unmanned Aerial Vehicles (UAVs) teleoperation targets better situational awareness by providing extra motion cues to stimulate the vestibular system. This paper proposes a new virtual environment for long range Unmanned Aerial Vehicle (UAV) control via Non-Line-of-Sight (NLoS) communications, which is based on motion platforms. It generates motion cues for the teleoperator for extra sensory stimulation to enhance the guidance performance. The proposed environment employs the distributed component simulation over GSM network as a simulation platform. GSM communications are utilized as a multi-hop communication network, which is similar to global satellite communications. It considers a UAV mathematical model and wind turbulence effects to simulate a realistic UAV dynamics. Moreover, the proposed virtual environment simulates a Multiple Axis Rotating Device (MARD) as Human Machine Interface (HMI) device to provide a complete delay analysis. The demonstrated measurements cover Graphical User Interface (GUI) capabilities, NLoS GSM communications delay, MARD performance, and different software workload. The proposed virtual environment succeeded to provide visual and vestibular feedbacks for teleoperators via GSM networks. The overall system performance is acceptable relative to other Line-of-Sight (LoS) systems, which promises a good potential for future long range, medium altitude UAV teleoperation researches.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.64-72
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• 2013

This paper proposes a dynamic gesture recognition algorithm using SVM(Support Vector Machine) which is suitable for multi-dimension classification. First of all, the proposed algorithm locates the beginning and end of the gestures on the video frames at the Kinect camera, spots meaningful gesture frames, and normalizes the number of frames. Then, for gesture recognition, the algorithm extracts gesture features using body parts' positions and relations among the parts based on the human model from the normalized frames. C-SVM for each dynamic gesture is trained using training data which consists of positive data and negative data. The final gesture is chosen with the largest value of C-SVM values. The proposed gesture recognition algorithm can be applied to the interactive storybook as gesture interface.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.238-245
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• 2013

Gesture recognition has been widely one of the research areas for natural user interface. This paper presents a novel gesture recognition method using tree classification and multiclass SVM(Support Vector Machine). In the learning step, 3D trajectory of human gesture obtained by a Kinect sensor is classified into the tree nodes according to their distributions. The gestures are resampled and we obtain the histogram of the chain code from the normalized data. Then multiclass SVM is applied to the classified gestures in the node. The input gesture classified using the constructed tree is recognized with multiclass SVM.

• Archives of design research
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• v.16 no.2
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• pp.49-56
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• 2003

In order to design a product for old people, it is important to identify usability problems through usability test and solve such problems in design process. So, we performed a study on design evaluation and improvement focusing on washing machine, that is one of the most useful electric home appliances in old people's daily life. Also, we studied the method that the goniometer can be used in usability evaluation for a specific part of product and the result can be used in product design. And, methods for the decision of design concept and direction, the development of design alternatives, design evaluation, model making, and comparison test through human factors theory and experiment were studied. The result can be used as an important data in the development of washing machine for old people and the proposed methodology can be used in other products for old people as well as washing machine.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.90-95
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• 2014

The researchs using brain-computer interface, the new interface system which connect human to macine, have been maded to implement the user-assistance devices for control of wheelchairs or input the characters. In recent researches, there are several trials to implement the speech recognitions system based on the brain wave and attempt to silent communication. In this paper, we studied how to extract features of vowel based on international phonetic alphabet (IPA), as a foundation step for implementing of speech recognition system based on electroencephalogram (EEG). We conducted the 2 step experiments with three healthy male subjects, and first step was speaking imagery with single vowel and second step was imagery with successive two vowels. We selected 32 channels, which include frontal lobe related to thinking and temporal lobe related to speech function, among acquired 64 channels. Eigen value of the signal was used for feature vector and support vector machine (SVM) was used for classification. As a result of first step, we should use over than 10th order of feature vector to analyze the EEG signal of speech and if we used 11th order feature vector, the highest average classification rate was 95.63 % in classification between /a/ and /o/, the lowest average classification rate was 86.85 % with /a/ and /u/. In the second step of the experiments, we studied the difference of speech imaginary signals between single and successive two vowels.

• Journal of Internet Computing and Services
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• v.6 no.5
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• pp.73-83
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• 2005

This paper proposes both a novel tactile human-computer interface method and an improved algorithm for the wearable PC. Under the condition of Ubiquitous computing, the next generation PC aims at effective representation and integration of colors, brightness of light. sound, odor, taste and feelings. Also, it aims at human being centered man-machine interface. In spite of various functions of the wearable PC, for the convenience of possessing, hardware platform for the wearable PC should be small-sized and light weighted one. The main problems of making small sized PC are user interfaces, like keyboard, monitor and so on. The traditional user interfaces have critical limitations for reducing their size. In this paper, we propose a novel user input method and improved algorithm to constructing small sized, light weighted and wearable PC. And, we verify the effectiveness of suggested method and algorithm compared to the traditional algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.55-61
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• 2014

Recently, the manufacturing system is being changed in a mass customization and small quantity batch production. MES is a powerful production management tool supporting production optimization from the process initiation to the final shipment. It is a production management system which plans and executes based on the production data in the shop floor. This study deployed the utilization of production data and web HMI system to process real-time production data through the collection with the shop floor. The developed system was applied to the equipment operating time and other production data could be processed with the real-time. The proposed system and web HMI can be applied for various production systems by using different logic.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.8
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• pp.37-44
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• 2008

Nowadays, the increasing global competition forces manufacturer to reduce the cost and time for implementation of manufacturing system. The AR(augmented reality) technology as a new human-machine interface introduces a noteworthy perspective for a new manufacturing system design. Using AR technology, a physically existing production environment can be superimposed with virtual planning objects. Therefore, the planning tasks can be validated without modeling the surrounding environment of the production domain during short process planning time. In this paper, we introduce the construction of AR browser and determine the optimal environment parameters for field application of AR system through lots of tests. And, many methods such as multi-marker coordinate system, division of virtual objects and so on, are proposed in order to solve the problems suggested from initial field test. Based on these tests and results, the test-bed of C/Pad assembly system is configured and robot program for C/Pad assembly is generated based on AR system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.835-838
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• 2003

Computer vision and natural-language dialogue play an important role in friendly human-machine interfaces for service robots. In this paper we describe an integrated face detection and face recognition system for a welfare robot, which has also been combined with the robot's speech interface. Our approach to face detection is to combine neural network (NN) and genetic algorithm (GA): ANN serves as a face filter while GA is used to search the image efficiently. When the face is detected, embedded Hidden Markov Model (EMM) is used to determine its identity. A real-time system has been created by combining the face detection and recognition techniques. When motivated by the speaker's voice commands, it takes an image from the camera, finds the face inside the image and recognizes it. Experiments on an indoor environment with complex backgrounds showed that a recognition rate of more than 88% can be achieved.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.411-414
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• 2003

Particle swarm optimization (PSO) is employed to train fuzzy-neural networks (FNN), which can be employed as an important building block in real life robot systems, controlled by voice-based commands. The FNN is also trained to capture the user spoken directive in the context of the present performance of the robot system. The system has been successfully employed in a real life situation for navigation of a mobile robot.