• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.7-14
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• 2008

In this paper, we designed the HVIC(High Voltage Gate Driver IC) which has improved noise immunity characteristics and high driving capability. Operating frequency and input voltage range of the designed HVIC is up to 500kHz and 650V, respectively. Noise protection and schmitt trigger circuit is included in the high-side level shifter of designed IC which has very high dv/dt noise immunity characteristic(up to 50V/ns). And also, rower dissipation of high-side level shifter with designed short-pulse generation circuit decreased more that 40% compare with conventional circuit. In addition, designed HVIC includes protection and UVLO circuit to prevent cross-conduction of power switch and sense power supply voltage of driving section, respectively. Protection and UVLO circuit can improve the stability of the designed HVIC. Spectre and Pspice circuit simulator were used to verify the operating characteristics of the designed HVIC.

• Composites Research
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• v.13 no.5
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• pp.50-59
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• 2000

In this paper, two methods to suppress flutter of the composite panel are examined. First, in the active control method, a controller based on the linear optimal control theory is designed and control input voltage is applied on the actuators and a PZT is used as actuator. Second, a new technique, passive suppression scheme, is suggested for suppression of the nonlinear panel flutter. In the passive suppression scheme, a shunt circuit which consists of inductor-resistor is used to increase damping of the system and as a result the flutter can be attenuated. A passive damping technology, which is believed to be more robust suppression system in practical operation, requires very little or no electrical power and additional apparatuses such as sensor system and controller are not needed. To achieve the great actuating force/damping effect, the optimal shape and location of the actuators are determined by using genetic algorithms. The governing equations are derived by using extended Hamilton's principle. They are based on the nonlinear von Karman strain-displacement relationship for the panel structure and quasi-steady first-order piston theory for the supersonic airflow. The discretized finite element equations are obtained by using 4-node conforming plate element. A modal reduction is performed to the finite element equations in order to suppress the panel flutter effectively and nonlinear-coupled modal equations are obtained. Numerical suppression results, which are based on the reduced nonlinear modal equations, are presented in time domain by using Newmark nonlinear time integration method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.864-870
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• 2017

This paper describes a Dual Buck Converter with mode control using variable Frequency to Voltage for portable devices requiring wide load current. The inherent problems of PLL compensation and efficiency degradation in light load current that the conventional hysteretic buck converter has faced have been resolved by using the proposed Dual buck converter which include improved PFM Mode not to require compensation. The proposed mode controller can also improve the difficulty of detecting the load change of the mode controller, which is the main circuit of the conventional dual mode buck converter, and the slow mode switching speed. the proposed mode controller has mode switching time of at least 1.5us. The proposed DC-DC buck converter was implemented by using $0.18{\mu}m$ CMOS process and die size was $1.38mm{\times}1.37mm$. The post simulation results with inductor and capacitor including parasitic elements showed that the proposed circuit received the input of 2.7~3.3V and generated output of 1.2V with the output ripple voltage had the PFM mode of 65mV and 16mV at the fixed switching frequency of 2MHz in hysteretic mode under load currents of 1~500mA. The maximum efficiency of the proposed dual-mode buck converter is 95% at 80mA and is more than 85% efficient under load currents of 1~500mA.

• Journal of the Korean Magnetics Society
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• v.16 no.3
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• pp.157-162
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• 2006

In this study, a high sensitive giant magnetoresistance-spin valve (GMR-SV) bio-sensing device with high linearity and very low hysteresis was fabricated by photolithography and ion beam deposition sputtering system. Detection of the Fe-hemoglobin inside in a red blood and magnetic nanoparticles using the GMR-SV bio-sensing device was investigated. Here a human's red blood includes hemoglobin, and the nanoparticles are the Co-ferrite magnetic particles coated with a shell of amorphous silica which the average size of the water-soluble bare cobalt nanoparticles was about 9 nm with total size of about 50 nm. When 1 mA sensing current was applied to the current electrode in the patterned active GMR-SV devices with areas of $5x10{\mu}m^2 $ and $2x6{\mu}m^2 $, the output signals of the GMRSV sensor were about 100 mV and 14 mV, respectively. In addition, the maximum sensitivity of the fabricated GMR-SV sensor was about $0.1{\sim}0.8%/Oe$. The magnitude of output voltage signals was obtained from four-probe magnetoresistive measured system, and the picture of real-time motion images was monitored by an optical microscope. Even one drop of human blood and nanopartices in distilled water were found to be enough for detecting and analyzing their signals clearly.

• Journal of the Korean Magnetics Society
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• v.25 no.3
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• pp.83-86
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• 2015

Nowadays the weapon systems are employed air bursting munition (ABM) as smart programmable 40 mm shells which have been developed in order to hit the target with programmed munition that can be air burst after a set distance in the battlefield. In order to improve the accuracy of such a bursting time, by measuring the speed of the munition from the barrel, weapon systems calculate the exact time of flight to the target and then the time information must be inputted to the munition. In this study, we introduce a device capable of detecting a shot at K4 40 mm automatic grenade. The shot is composed of a rotating copper band to convert linear motion into rotary motion when it passes through the barrel, the steel section is exert the effect of fragment and aluminum section to give fuze information. The aluminum section was used to detect munition using eddy current method. To measure muzzle velocity by means of non-contact method, two eddy current probes separated 10 cm was employed. Time interval between two eddy current probe detection times was used as muzzle velocity. The eddy current probe was fabricated U-shape Mn-Zn ferrite core with enamelled copper wire, and 200 kHz alternating current was used to detect inductance change. Measured muzzle velocity using the developed sensor was compared to the Doppler radar system. The difference was smaller than 1%.

• Progress in Medical Physics
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• v.26 no.2
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• pp.112-117
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• 2015

In order to establish the quality control on patient safety following the guideline presented by American Association of Physicists in Medicine (AAPM) TG-100 committee, we aim to analyze the modes based on errors occurred during treatment of patients at the radiation oncology department at Yeungnam University Hospital and establish a quality control guideline for patient safety when patient-centered radiation treatment is conducted. We aim to analyze the errors that can occur during radiation treatment at the radiation department, and assess the frequency of error, the severity of error affecting patients, and probability of proceeding without noticing error, with scores. The places where errors can take place were divided into CT simulation treatment room, treatment planning room, and treatment room for the analysis. In CT simulation treatment room, an error from using the immobilization device showed the highest Risk Priority Number (RPN) value of 60, and an error from simulation treatment information input showed the lowest of 6. In treatment planning room, an error from selecting the radiation dose calculation model showed the highest RPN value of 168, and an error of patient treatment start date showed the lowest of 36. In treatment room, a Table Bar error showed the highest RPN value of 252, a weight change error showed 190, and a Pillow error showed the lowest of 24.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.197-204
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• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.127-133
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• 2021

In industrial IoT environments, sensors generate data for their detection targets and deliver the data to IoT gateways. Therefore, managing large amounts of real-time sensor data is an essential feature for IoT gateways, and key-value storage engines are widely used to manage these sensor data. However, key-value storage engines used in IoT gateways do not take into account the characteristics of sensor data generated in industrial IoT environments, and this limits the performance of key-value storage engines. In this paper, we optimize the key-value storage engine by utilizing the features of sensor data in industrial IoT environments. The proposed optimization technique is to analyze the key, which is the input of a key-value storage engine, for further indexing. This reduces excessive write amplification and improves performance. We implement our optimization scheme in LevelDB and use the workload of the TPCx-IoT benchmark to evaluate our proposed scheme. From experimental results we show that our proposed technique achieves up to 21 times better than the existing scheme, and this shows that the proposed technique can perform high-speed data ingestion in industrial IoT environments.