• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.17-24
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• 2018

Military camera equipment has a problem that observability is inferior due to various shaking factors. In this paper, we propose an image stabilization algorithm considering performance and execution time to solve this problem and implemented it in Zynq SoC. We stabilized both the simple shaking in the fixed observation position and the sudden shaking in the moving observation position. The feature of the input image is extracted by the Sobel edge algorithm, the subblock with the large edge data is selected, and the motion vector, which is the compensation reference, is calculated through template matching using the 3-step search algorithm of the region of interest. In addition, the proposed algorithm can distinguish the shaking caused by the simple shaking and the movement by using the Kalman filter, and the stabilized image can be obtained by minimizing the loss of image information. To demonstrate the effectiveness of the proposed algorithm, experiments on various images were performed. In comparison, PSNR is improved in the range of 2.6725~3.1629 (dB) and image loss is reduced from 41% to 15%. On the other hand, we implemented the hardware-software integrated design using HLS of Xilinx SDSoC tool and confirmed that it operates at 32 fps on the Zynq board, and realized SoC that operates with real-time processing.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.875-881
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• 2014

The redundancy resolution of the seven DOF (Degree of Freedom) upper limb exoskeleton is key to the synchronous motion between a robot and a human user. According to the seven DOF human arm model, positioning and orientating the wrist can be completed by multiple arm configurations that results in the non-unique solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and its effect on the redundancy resolution of the seven DOF human arm model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing two cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid of the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each of two consecutive points along the task space trajectory. The contribution of each criterion on the redundancy was verified by the post processing of experimental data collected with a motion capture system. Results indicate that the bimodal redundancy resolution approach improved the accuracy of the predicted swivel angle. Statistical testing of the dynamic constraint contribution shows that under moderate speeds and no load, the dynamic component of the human arm is not dominant, and it is enough to resolve the redundancy without dynamic constraint for the realtime application.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.43-48
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• 2014

Usually, image deconvolution is applied as a preprocessing step in surveillance systems to reduce the effect of motion or out-of-focus blur problem. In this paper, we propose a blind-image deconvolution filtering approach based on genetic programming (GP). A numerical expression is developed using GP process for image restoration which optimally combines and exploits dependencies among features of the blurred image. In order to develop such function, first, a set of feature vectors is formed by considering a small neighborhood around each pixel. At second stage, the estimator is trained and developed through GP process that automatically selects and combines the useful feature information under a fitness criterion. The developed function is then applied to estimate the image pixel intensity of the degraded image. The performance of developed function is estimated using various degraded image sequences. Our comparative analysis highlights the effectiveness of the proposed filter.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.129-136
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• 2020

Recognizing finger movements have been used as a intuitive way of human-computer interaction. In this study, we implement an wearable device for finger motion recognition and evaluate the accuracy of several ML (Machine learning) techniques. Not only HMM (Hidden markov model) and DTW (Dynamic time warping) techniques that have been traditionally used as time series data analysis, but also NN (Neural network) technique are applied to compare and analyze the accuracy of each technique. In order to minimize the computational requirement, we also apply the pre-processing to each ML techniques. Our extensive evaluations demonstrate that the NN-based gesture recognition system achieves 99.1% recognition accuracy while the HMM and DTW achieve 96.6% and 95.9% recognition accuracy, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.19-28
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• 2021

Recently, in the field of education, various attempts have been made to apply virtual reality technology to an educational field and use it as an educational medium. Accordingly, in the science subject area, it is necessary to simulate science experiments that can make various and active experiments out of various limitations such as space and situation by using virtual reality environment construction technology. In this study, after selecting a physics course from a science subject, an experimental simulation using a parabolic motion formula, one of physical phenomena, is implemented in a virtual space, and then used in actual physics education based on the learning standards of the STEAM theory. Prove this is possible. Through this, it was confirmed that a specific educational model using virtual reality space can be designed, and it shows that education can be conducted with more effective educational methods in various subjects of education through the combination of traditional educational model and modern technology. Regarding the results of the research, it suggests the possibility of future research plans and practical use in the educational field.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.595-602
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• 2021

The robot is developing into a software-oriented shape that recognizes the surrounding situation and is given a task. Cloud Robotics Platform is a method to support Service Oriented Architecture shape for robots, and it is a cloud-based method to provide necessary tasks and motion controllers depending on the situation. As it evolves into a humanoid robot, the robot will be used to help humans in generalized daily life according to the three robot principles. Therefore, in addition to robots for specific individuals, robots as public goods that can help all humans depending on the situation will be universal. Therefore, the importance of information security in the Cloud Robotics Computing environment is analyzed to be composed of people, robots, service applications on the cloud that give intelligence to robots, and a cloud bridge that connects robots and clouds. It will become an indispensable element for In this paper, we propose a Security Scheme that can provide security for communication between people, robots, cloud bridges, and cloud systems in the Cloud Robotics Computing environment for intelligent robots, enabling robot services that are safe from hacking and protect personal information.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.38-43
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• 2017

Sensor Networks (WSNs) can be defined as a self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or base-station where the data can be observed and analyzed. Typically a wireless sensor network contains hundreds of thousands of sensor nodes. The sensor nodes can communicate among themselves using radio signals. A wireless sensor node is equipped with sensing and computing devices, radio transceivers and power components. The individual nodes in a wireless sensor network (WSN) are inherently resource constrained: they have limited processing speed, storage capacity, communication bandwidth and limited-battery power. At present time, most of the research on WSNs has concentrated on the design of energy- and computationally efficient algorithms and protocols In order to extend the network life-time, in this paper we are looking into a routing protocol, especially LEACH and LEACH-related protocol. LEACH protocol is a representative routing protocol and improves overall network energy efficiency by allowing all nodes to be selected to the cluster head evenly once in a periodic manner. In LEACH, in case of movement of sensor nodes, there is a problem that the data transmission success rate decreases. In order to overcome LEACH's nodes movements, LEACH-Mobile protocol had proposed. But energy consumption increased because it consumes more energy to recognize which nodes moves and re-transfer data. In this paper we propose the new routing protocol considering nodes' mobility. In order to simulate the proposed protocol, we make a scenario, nodes' movements randomly and compared with the LEACH-Mobile protocol.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.55-61
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• 2006

In modern society, development of medical technology has extended the human life span. However, it has also caused some side-effects. Mostly old people who live alone are not available the medical service quickly when they are in emergency situations. Moreover heart related diseases as well are rapidly increasing with aging. This study proposes the emergency medical alarm system. This system measures the physiological signals such as ECG(electrocardiogram), temperature, and motion data, analyzes those data automatically, and sends the urgent message to the Emergency Medical Center and to their family. There are two main parts in the system. In the first part, physiological data acquisition part, the troublesome addition and deletion of body signals on existing proposed systems have been supplemented, which led to the modulized production by means of ECG sensor module, temperature sensor module, acceleration sensor module. The other part is mobile unit, which includes signal processing and transmission functions. And bluetooth allows two parts to communicate with each other. Data that are processed in the mobile unit are stored in the PC database through the WLAN using TCP/IP protocol.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.175-182
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• 2006

Radars are used to detect the motion of the low flying enemy planes in the military. Radar-detected raw data are first processed and then inserted into the ground tactical C4I system. Next, these data we analyzed and broadcasted to the Shooter system in real time. But the accuracy of information and time spent on the displaying and graphical computation are dependent on the operator's capability. In this paper, we propose the Flying Object Tracking Management System that allows the displaying of the objects' trails in real time by using data received from the radars. We apply the coordinate system translation algorithm, existing communication protocol improvements with communication equipment, and signal and information computation process. Especially, radar signal duplication computation and synchronization algorithm is developed to display the objects' coordinates and thus we can improve the Tactical Air control system's reliability, efficiency, and easy-of-usage.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.