• Journal of IKEEE
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• v.24 no.1
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• pp.347-353
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• 2020

In this paper, the durability of an electromagnetic metamaterial absorber is verified in a temperature varying condition mimicking a maritime environment for the purpose of applying it to reduce the radar cross section of an integrated mast of the next-generation destroyer. To validate the durability, the reflectance of the electromagnetic metamaterial absorber was measured after storing it in a chamber that can control the temperature according to Procedure I of Method 501.7 included in MIL-STD-810H. Before and after the environmental test, both of the measured reflectances were retained less than -10 dB over the X band, that can guarantee the stealth functionality.

• Journal of IKEEE
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• v.24 no.1
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• pp.25-32
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• 2020

In this paper, we propose an image generator for OLED panel test that can compensate for color coordinates and luminance by using panel defect inspection and optical measurement while displaying images on OLED panel. The proposed image generator consists of two processes: the image generation process and the process of compensating color coordinates and luminance using optical measurement. In the image generating process, the panel is set to receive the panel information to drive the panel, and the image is output by adjusting the output setting of the image generator according to the panel information. The output form of the image is configured by digital RGB method. The pattern generation algorithm inside the image generator outputs color and gray image data by transmitting color data to a 24-bit data line based on a synchronization signal according to the resolution of the panel. The process of compensating color coordinates and luminance using optical measurement outputs an image to an OLED panel in an image generator, and compensates for a portion where color coordinates and luminance data measured by an optical module differ from reference data. To evaluate the accuracy of the image generator for the OLED panel test proposed in this paper, Xilinx's Spartan 6 series XC6SLX25-FG484 FPGA was used and the design tool was ISE 14.5. The output of the image generation process was confirmed that the target setting value and the simulation result value for the digital RGB output using the oscilloscope matched. Compensating the color coordinates and luminance using optical measurements showed accuracy within the error rate suggested by the panel manufacturer.

• Journal of IKEEE
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• v.24 no.1
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• pp.33-39
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• 2020

In this paper, we propose the design technique of the vehicle's load weight measuring system using tire pressure, which is one of the physical elements of tires. The proposed technique consists of four processes: noise correction by load and vibration, gas flow correction, data mixer and weight conversion. Noise correction by load and vibration eliminates noise that increases the tire's internal pressure due to external shocks and vibrations produced by the vehicle while it is in motion. In the gas flow correction process, the noise of the internal pressure of the tire is increased due to the temperature rise of the ground with respect to the data obtained through the noise correction process due to the load and vibration. In the data mixer process, the load and pressure on the tolerances the empty, median and the full load are classified according to the change in pressure of the tire that is delivered perpendicular to the tire in the event of cargo. In the weight conversion process, weight is expressed by weight through weight conversion algorithms using noise correction results by load and vibration and gas flow correction. The weight conversion algorithm calculates the weight conversion factor, which is the slope of the linear function with respect to the load and pressure change, and converts the weight. In order to evaluate the accuracy of the loading weight measurement system of the vehicle using the tire pneumatic system technique proposed in this paper, we propose the design technique of the vehicle's load weight measuring system using tire pressure, which is one of the physical elements of tires.. Noise correction results by load and vibration and gas flow data correction results showed reliable results. In addition, repeated weight precision test showed better weight accuracy than the standard value of 90% of domestic companies.

• The Korea Journal of Herbology
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• v.30 no.6
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• pp.69-75
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• 2015

Objectives : This study was designed to investigate effects of the combination with Korean Red Ginseng (Panax ginseng C.A. Meyer), Gastrodia Rhizoma (Gastrodia elata Blume) and Polygoni Multiflori Radix (Polygonum multiflorum Thunberg) on metabolic disorders including cholesterol and erectile dysfunction in hyperlipidemia rats.Methods : Animals were divided into six groups; Control with normal diet, high fat/cholesterol-diet (HFCD), fluvastatin, Korean Red Ginseng treated (KRG), and the combination treated (Korean Red Ginseng, Gastrodia Rhizoma and Polygoni Multiflori Radix; 1:1:1 for KGP1 and 2:1:1 for KGP2). The experimental groups initially received HFCD for 10 weeks and then treated orally with fluvastatin, KRG, KGP1 and KGP2 during the final 6 weeks. Erectile function was determined by the measurements of intracavernosal pressure (ICP) and maximal arterial pressure (MAP) after electrical stimulation of the cavernosal nerve.Results : KGP2 decreased the level of total cholesterol and LDL cholesterol in the sera of HFCD rats without no changes of body weights. KRG, KGP1 and KGP2 decreased the level of C-reactive protein (CRP) levels except of fluvastatin, synthetic HMG-CoA reductase inhibitor. KRG, KGP1 and KGP2 significantly increased the ICP, ICP/MAP ratio, area under the curve (AUC) compared with those of normal rat. Morphometric analyses showed that KRG, KGP1 and KGP2 increased the volume of smooth muscle and the regular arrangement of collagen fibers in corpus cavernosum of HFCD rats. The penile expression of eNOS was increased by KRG, KGP1 and KGP2.Conclusions : Based on these results, we suggest that the combination with Korean Red Ginseng, Gastrodia Rhizoma and Polygoni Multiflori may improve hyperlipidemia through regulating the lipid profiles and erectile dysfunction in rats.

• Journal of IKEEE
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• v.19 no.2
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• pp.186-192
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• 2015

This paper proposes an automatic generation technology of test case based on API in source code for software's quality improvement. The proposed technology is comprised of four processes which are analyzing source code by using the Doxygen open source tool, defining API specification by using analyzed results, creating test design, generating a test case by adapting Pairwise test technology. Analyzing source code by using the Doxygen open source tool is the phase in which API information in source code such as the API name, input parameter and return parameter are extracted. Defined API specification by using analyzed results is the phase where API informations, which is needed to generate test case, are defined as a form of database by SQLite database on the basis of extracted API information. Creating test design is the phase in which the scenario is designed in order to be composed as database by defining threshold of input and return parameters and setting limitations based on the defined API. Generating a test case by adapting Pairwise test technique is the phase where real test cases are created and changed into database by adapting Pairwise technique on the base of test design information. To evaluate the efficiency of proposed technology, the research was conducted by begin compared to specification based test case creation. The result shows wider test coverage which means the more cases were created in the similar duration of time. The reduction of manpower and time for developing products is expected by changing the process of quality improving in software developing from man-powered handwork system into automatic test case generation based on API of source code.

• Journal of IKEEE
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• v.19 no.2
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• pp.168-175
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• 2015

In this paper, we propose FPGA design technique for rotating LED display device which is capable of displaying videos with the use of the afterimage effect. The proposed technique is made up of image data correction process based on inverse gamma correction and error diffusion, block interleaving process, and data serial output process. The data correction process based on inverse gamma correction and error diffusion is an image data correction step in which image data received are corrected by inverse gamma correction process to convert the data into linear brightness characteristics, and by error diffusion process to reduce the brightness reduction phenomenon in low-gray-level which is caused by inverse gamma correction. In the block interleaving process, the data of the frames entered transversely are first saved in accordance with entrance order, and then only the longitudinal image data are read. The data serial output process is applied to convert the parallel data in a rotating location into serial data and send them to LED Driver IC, in order to send data which will be displayed on high-speedy rotating LED Bar. To evaluate the accuracy of the proposed FPGA design technique, this paper used XC6SLX45-FG484, a Spartan 6 family of Xilinx, as FPGA, and ISE 14.5 as a design tool. According to the evaluation analysis, it was found that goal values were consistent with simulation values in terms of accurate operation of inverse gamma and error diffusion correction, block interleaving operation, and serialized operation of image data.

• Journal of IKEEE
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• v.19 no.2
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• pp.237-243
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• 2015

Recently, eight out of ten people have smartphone in Korea. Also, many applications of smartphone have increased. So, smartphone addiction has become a social issue. Especially, many people in smartphone addiction can't control themselves. Sometimes they don't realize that they are smartphone addiction. Many studies, mostly surveys, have been conducted to diagnose smartphone addiction, e.g. S-measure. In this paper, we suggest how to detect smartphone addiction based on ECG and Eye Gaze. We measure the signals of ECG from the Shimmer and the signals of Eye Gaze from the smart eye when the subjects see the emotional video. In addition, we extract features from the S-transform of ECG. Using Eye Gaze signals(pupil diameter, Gaze distance, Eye blinking), we extract 12 features. The classifier is trained using Random Forest. The classifiers detect the smartphone addiction using the ECG and Eye Gaze signals. We compared the detection results with S-measure results that surveyed before test. It showed 87.89% accuracy in ECG and 60.25% accuracy in Eye Gaze.

• Journal of IKEEE
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• v.21 no.3
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• pp.268-271
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• 2017

In this paper, we propose the development of high resolution $360^{\circ}$ omnidirectional IP camera with 12 million pixels. The proposed 12-megapixel high-resolution $360^{\circ}$ omnidirectional IP camera consists of a lens unit with $360^{\circ}$ omnidirectional viewing angle and a 12-megapixel high-resolution IP camera unit. The lens section of $360^{\circ}$ omnidirectional viewing angle adopts the isochronous lens design method and the catadioptric facet production method to obtain the image without peripheral distortion which is inevitably generated in the fisheye lens. The 12 megapixel high-resolution IP camera unit consists of a CMOS sensor & ISP unit, a DSP unit, and an I / O unit, and converts the image input to the camera into a digital image to perform image distortion correction, image correction and image compression And then transmits it to the NVR (Network Video Recorder). In order to evaluate the performance of the proposed 12-megapixel high-resolution $360^{\circ}$ omnidirectional IP camera, 12.3 million pixel image efficiency, $360^{\circ}$ omnidirectional lens angle of view, and electromagnetic certification standard were measured.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.58-63
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• 2017

Emergencies and disasters can happen any time without any warning, and things can change and escalate very quickly, and often it is swift and decisive actions that make all the difference. It is a responsibility of the building facility management to ensure that a proven evacuation plan in place to cover various worst scenario to handled automatically inside the facility. To mapping out optimal safe escape routes is a straightforward undertaking, but does not necessarily guarantee residents the highest level of protection. The emergency evacuation navigation approach is a state-of-the-art that designed to evacuate human livings during an emergencies based on real-time decisions using live sensory data with pre-defined optimum path finding algorithm. The poor decision on causalities and guidance may apparently end the evacuation process and cannot then be remedied. This paper propose a cloud connected emergency evacuation system model to react dynamically to changes in the environment in emergency for safest emergency evacuation using IoT based emergency exit sign system. In the previous researches shows that the performance of optimal routing algorithms for evacuation purposes are more sensitive to the initial distribution of evacuees, the occupancy levels, and the type and level of emergency situations. The heuristic-based evacuees routing algorithms have a problem with the choice of certain parameters which causes evacuation process in real-time. Therefore, this paper proposes an evacuee routing algorithm that optimizes evacuation by making using high computational power of cloud servers. The proposed algorithm is evaluated via a cloud-based simulator with different "simulated casualties" are then re-routed using a Dijkstra's algorithm to obtain new safe emergency evacuation paths against guiding evacuees with a predetermined routing algorithm for them to emergency exits. The performance of proposed approach can be iterated as long as corrective action is still possible and give safe evacuation paths and dynamically configure the emergency exit signs to react for real-time instantaneous safe evacuation guidance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.89-103
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• 2020

As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.