• Journal of Industrial Technology
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• v.27 no.B
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• pp.97-101
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• 2007

We have developed a Edge Position Controller (EPC) using a ultrasonic sensor and applied to a fabric machine as a web guide system. Hardware devices composed of a ultrasonic transmitter-receiver sensor module and microprocessor-based sensor signal processing system are developed to realize the proposed system. We evaluated the control characteristics of the EPC and the performance of the system was good enough to apply the actual system.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.303-308
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• 2012

One dimensional line edge detection sensor was investigated for the application to detect line or edge of wide sheet winding to cylindrical roller. Line edge detection sensor was realized using align-free 1:1 optical system having 1 convex lens and by processing sum or difference of signals from two photo-diodes in a bi-cell photodetector. Line width up to 0.1mm on object having various materials and colors was detectable, and the deviation of wound sheet was found to be under 0.2mm.

• Journal of Sensor Science and Technology
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• v.27 no.3
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• pp.143-149
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• 2018

In this paper, we introduce an edge-spike modulation method for visible light communication (VLC). This method is effective in preventing LED flicker and 120 Hz noise interference in base-band VLC. In the VLC transmitter, edge-spikes are generated by passing the digital data through a simple RC-high pass filter (HPF). The LED modulation of the edge-spikes does not change the average power of the LED light; thus it prevents LED flicker. In the VLC receiver, the 120 Hz noise from other lighting lamps is easily eliminated by RC-HPF, while the edge-spike signal is detected normally. In our experiment, the message of an air-quality sensor was successfully transmitted using edge-spike modulation. This structure is useful in constructing, e.g., wireless gas monitoring sensor systems to warn and prevent harmful gas leakage accidents in buildings using LED light.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.88-93
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• 2010

In this paper, an edge detecting sensor using ultrasonic detection module is developed which will be used for areas of industrial applications such as plastic film winding system, cloth winding system, paper roll industry, etc. The developed sensor have properties that more exactly detect the edge line, that less affected by environmental noise, and that it produced more stable measurement output. The mass of the winding object is dominantly affect the dynamics of the system and it could produce undesirable result of the system such as stability of the closed-loop system and accuracy of edge-line-following-control(ELFC) objective. Also, there exist sensor noise due to the mechanical vibration or other environmental effect. These noise also degrade the efficiency of control system. In order to compensate these problems, this paper present a fuzzy PI/PID edge-line-controller, and which is designed and implemented.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.308-311
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• 1998

Some nondestructive diagnostic methods including various types of corrosion sensors have been investigated. Under these conditions, a new structure of sensor that has a pair of electrode and magneto-supply was proposed. In order to detect the edge of the iron rust part, three-poles touch-type corrosion sensor is now proposed. The iron rust pattern where the sensor touches is estimated by means of the impedance of the sensor, and the edge of the iron rust is recognized by comparing the three measured impedances. As the result, our proposed sensor is useful to detect the initial state of iron rust.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.9-15
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• 2021

In this paper, the Embedded MEMS system to the power apparatus used Edge Impulse machine learning tools and therefore an improved predictive system design is implemented. The proposed MEMS embedded system is developed based on nRF52840 system and the sensor with 3-Axis Digital Magnetometer, I2C interface and magnetic measurable range ±120 uT, BM1422AGMV which incorporates magneto impedance elements to detect magnetic field and the ARM M4 32-bit processor controller circuit in a small package. The MEMS embedded platform is consisted with Edge Impulse Machine Learning and system driver implementation between hardware and software drivers using SensorQ which is special queue including user application temporary sensor data. In this paper by experimenting, TensorFlow machine learning training output is applied to the power apparatus for analyzing the status such as "Normal, Warning, Hazard" and predicting the performance at level of 99.6% accuracy and 0.01 loss.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.26-34
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• 1998

In this paper, a force control algorithm for edge following task is suggested. Through the contact state modeling between rigid part and end-effector of robot, contact force and contact angle that are essencial parameters to build the control strategies for following movement of end-effector are derived. From these two parameters, we discriminate the every contact state into 8 cases and calculate the new moving position and direction simply. For the experiment. RX90 robot from Staubli with robot language V$^{+}$ is applied and F/T sensor is attached to the wrist of robot with RCC. Finally, 3 edge following experiments including the following of corner point are executed with successful results.s.

• Journal of Power Electronics
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• v.10 no.3
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• pp.300-305
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• 2010

This paper presents a two Hall sensor method for rotor angle detection in permanent magnet synchronous motors (PMSM). To minimize the implementation complexity, the system is designed to measure the edge field of permanent magnet pieces. However, there are nonlinearities in the measured values of the edge field. In this work, an angle correction algorithm is proposed, and the improvements in accuracy are verified through experiments. Finally, a field orientation controller is constructed with the proposed angle detection algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.1-8
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• 2002

The color interpolation scheme can play an important role in overcoming the physical limitation of the CCD image sensor and in increasing the resolution of color signals, while most conventional approaches result in blurred edges and false color artifacts. In this paper, we have proposed an improved edge-adaptive color interpolation scheme for a progressive scan CCD image sensor with RGB color filter array The edge indicator function proposed utilizes not only the within-channel correlation but also the cross-channel correlation, and reflects the edge characteristics of an image adaptively. The color components unavailable for at each channel are interpolated along the edge direction, not across the edges, so that aliasing artifacts are supressed. Furthermore, we eliminated false color artifacts resulting from the color image formation model in the edge-adaptive color interpolation scheme by adopting the switching algorithm based on the color edge detection. Simulation results of the proposed algorithm indicate that the improved edge-adaptive color interpolation scheme produces quantitatively better and visually more pleasing results than conventional approaches.