Millimeter wave (mmWave) has attracted great interest recently and the necessity of Millimeter Mobile Broadband (MMB) system has appeared based on the 4 Generation Long Term Evolution-Advanced (LTE-A) Specification. Currently, there are many studies about the mmWave communication channel. And it is subject of interest to analyze the performance in MMB channel environments. In this paper, we design the MMB system for 5th Generation mobile communication and propose channel models through the analysis of the mmWave propagation characteristics. Also, we have analyzed the performance of the MMB system of 28 GHz band in MMB channel environments.

In recent SONAR (sound navigation and ranging) systems, wideband active SONAR systems has received more attention than narrowband SONAR systems due to the remarkable detection performance in terms of range resolution. However, the wideband SONAR systems usually requires a huge amount of computational burden in order to achieve their own superiority. To cope with this drawback of the wideband SONAR systems, this paper proposes a fast target detection and velocity estimation method using an extended replica in wideband hyperbolic frequency modulation active SONAR system. Computer simulation shows that the proposed method can be implemented by a highly reduced computational complexity with a little performance degradation in target detection and velocity estimation compared to the conventional filter bank method.

We have studied on ozonate water cleaning mechanisms to apply in manufacturing process of 156 mm silicon wafer which is used in the solar cell fabrication. We have analyzed contamination sources on wafer surface which causes poor quality and performance of products in fabrication process, and examined cleaning process using ozonate water to eliminate it. Contamination sources consist of remaining material like organic matter in slurry and detergent and particles in sawing wire. Using this novel technology it is possible for the solar cell wafer to clean with low cost, high performance, and eco-friendly.

In this paper, the compact model for FinFET gate resistance is developed. Based on the FinFET geometry and material, the value of the gate resistance is extracted by Y-parameter analysis using 3D device simulator, Sentaurus. By dividing the gate resistance into horizontal and vertical components, the proposed gate resistance model captures the non-linear characteristics. The proposed compact model reflects the realistic gate structure which has two different materials (Tungsten, TiN) stacked. Using the proposed model, the number of fins for the minimum gate resistance can be proposed based on the variation of gate geometrical parameters. The proposed gate resistance model is implemented in BSIM-CMG. A ring-oscillator is designed, and its delay performance is compared with and without gate resistance.

In this paper, a design of Signal Processing Analog Front-End IC for Automotive Piezo-Resistive Type Pressure Sensor is presented. In modern society, as the car turns to go from mechanical to electronic technology, the accuracy and reliability of electronic parts required importantly. In order to improve these points, Programmable Gain Amplifier (PGA) amplifies the received signal in accordance with gain for increasing the accuracy after PRT Sensor is operated to change physical pressure signals to electrical signals. The signal amplified from PGA is processed by Digital blocks like ADC, CMC and DAC. After going through this process, it is possible to determine the electrical signal to physical pressure signal. As processing analog signal to digital signal, reliability and accuracy in Analog Front-End IC is increased. The current consumption of IC is 5.32mA. The die area of the fabricated IC is .

In this paper, we propose a novel method to effectively eliminate flickering artifacts caused by dehazing in video sequences. When applying a dehazing technique directly to each image in a video sequence, flicker artifacts may occur because atmospheric values are calculated without considering the relation of adjacent frames. Although some existing methods reduce flickering artifacts by calculating highly correlated transmission values between adjacent frames, flickering artifacts may still occur. Therefore, in order to effectively reduce flickering artifacts, we propose a novel approach considering temporal averages of atmospheric light values calculated from adjacent frames. Experimental results have shown that the proposed method achieves better performance of video dehazing with less flickering artifact than existing methods.

A recent issued Internet of Things (IoT) is based on the service that everything around us is exchanging the information and reacting upon these information. These IoT services are mainly dealing with the information that was generated by the information nodes of IoT networks such as sensors, where the way how the information from information nodes should be dealt with is very important in terms of service reliability in IoT networks. This paper introduces a new scheme for service reliability and energy efficiency that is reducing the energy consumption of actuator node reacting upon the request messages from the information nodes in IoT networks.

Recently a variety of study of Korean parsing system is carried out by many software engineers and linguists. The parsing system mainly uses the method of machine learning or symbol processing paradigm. But the parsing system using machine learning has long training time because the data of Korean sentence is very big. And the system shows the limited recognition rate because the data has self error. In this thesis we design system using feature module which can reduce training time and analyze the recognized rate each the number of training sentences and repetition times. The designed system uses the separated modules and sorted table for binary search. We use the refined 36,090 sentences which is extracted by Sejong Corpus. The training time is decreased about three hours and the comparison of recognized rate is the highest as 84.54% when 10,000 sentences is trained 50 times. When all training sentence(32,481) is trained 10 times, the recognition rate is 82.99%. As a result it is more efficient that the system is used the refined data and is repeated the training until it became the steady state.

Mobile devices are generally using app images which are artificially designed. Accordingly, this paper presents adjusting device brightness based on app image categorization for enhancing the visibility under various light condition. First, the proposed method performed two prior subjective tests under various lighting conditions for selecting features of app images concerning visibility and for selecting satisfactory range of device brightness for each app image. Then, the relationship between selected features of app image and satisfactory range of device brightness is analyzed. Next, app images are categorized by using two features of average brightness of app image and distribution ratio of advanced colors that are related to satisfaction range of device brightness. Then, optimal device brightness for each category is selected by having the maximum frequency of satisfaction device brightness. Experimental results show that the categorized app images with optimal device brightness have high satisfaction ratio under various light conditions.

In this paper, we propose a directionally adaptive aliasing and noise removal using dictionary learning based on space-frequency analysis. The proposed aliasing and noise removal algorithm consists of two modules; i) aliasing and noise detection using dictionary learning and analysis of frequency characteristics from the combined wavelet-Fourier transform and ii) aliasing removal with suppressing noise based on the directional shrinkage in the detected regions. The proposed method can preserve the high-frequency details because aliasing and noise region is detected. Experimental results show that the proposed algorithm can efficiently reduce aliasing and noise while minimizing losses of high-frequency details and generation of artifacts comparing with the conventional methods. The proposed algorithm is suitable for various applications such as image resampling, super-resolution image, and robot vision.

Signal processing technique of linear frequency modulation-frequency shift keying (LFM-FSK) waveform has been introduced for rear view radars of an automobile. LFM-FSK waveform consists of two sequential stepped frequency waveforms with some frequency offset, and thus, can be used to generate inverse synthetic aperture radar (ISAR) images of rear view target of an automobile. However, ISAR images can often be blurred due to inter-pulse phase errors. To resolve this problem, one-dimensional (1-D) entropies of high resolution range profiles (HRRP) are minimized with the help of particle swarm optimization (PSO). The searching space used in PSO is adaptively adjusted by the use of information on the target`s velocity obtained from LFM-FSK waveforms. Simulation results show that the proposed method can generate well-focused ISAR images.

The existing rough mode decision (RMD) algorithm, used in HEVC standard loses the coding efficiency and wastes encoding time when encoding using transform skip mode (TSM) because the RMD algorithm in HEVC uses a selection method that is designed for DCT, not for TSM. This paper proposes a new RMD algorithm for TSM in HEVC. Our proposed RMD algorithm enhances the coding efficiency by employing a new cost function to increase the probability of selecting the best intra prediction mode for TSM. In addition, it reduces the encoding time by skipping the encoding process of least feasible TSM based on a newly proposed threshold value. The experiment results show that the proposed method achieves coding gains of -0.3% for screen contents with a 10% reduction in encoding time compared to those of the HEVC standard.

In a conventional sonar system, which uses LFM signal for detecting targets with varying speed, the results of multiple LFM Doppler correlators are aligned and the maximum alined result are selected as a test cell for detecting targets. As the number of the LFM Doppler correlators are increased for accurate target detection, as the required computational complexity and the memory are also increased. This fact makes it difficult to implement the accurate LFM target detector. In this paper, we propose a new fast target detection which is robust for the variation of target speed. Because the proposed method uses the summation of alined results of large numbers of LFM Doppler correlators, the proposed method increase SNR and provide robust SNR for the variation of target speed. And the proposed method can provide very fast target detection by implementing the process, the summation of alined results of large numbers of LFM Doppler correlators, as one summation filter.

The Euclidean distance between error probability density functions (EDEP) has been used as a performance criterion for supervised adaptive signal processing in impulsive noise environments. One of the drawbacks of the EDEP algorithm is a heavy computational complexity due to the double summation operations at each iteration time. In this paper, a recursive method to reduce its computational burden in the estimation of the EDEP and its gradient is proposed. For the data block size N, the computational complexity for the estimation of the EDEP and its gradient can be reduced to O(N) by the proposed method, while the conventional estimation method has . In the performance test, the proposed EDEP and its gradient estimation yield the same estimation results in the steady state as the conventional block-processing method. The simulation results indicates that the proposed method can be effective in practical adaptive signal processing.

We address the problem of corrective control for two asynchronous sequential machines in parallel connection. Each asynchronous machine receives the same external input and shows independent state transition characteristics. We propose a novel control scheme in which only one corrective controller is employed so as to make the closed-loop system of each machine match the behavior of the corresponding reference model. Compared with the former method utilizing two corrective controllers, our scheme can reduce the controller size and computational load in controller design. We present the existence condition and design procedure for a state-feedback corrective controller under the assumption that the controlled machines are of input/state type. The design procedure for the proposed controller is described in an illustrative example.

In this research a signal processing system is designed for detecting the ultrasonic signal envelope using Xilinx`s Zynq SoC(system on chip). As a design tool, Vivado IDE(integrated design environment) is used to hierarchically design the whole signal processing system. The proposed system consists of a Zynq-internal ADC, an FIR(finite impulse response) BPF(band pass filter), an absolute value calculator, an FIR LPF(lpw pass filter), and the Kalman filter. Under this configuration, two design schemes, HW design scheme with LPF as a final stage and HW/SW co-design scheme with a Kalman filter as a final stage, are compared in terms of the performance and efficiency. As a result, envelope detecting performances of the two schemes are proved to be almost same, but the HW/SW co-design is verified to be much more efficient than the HW design considering the much smaller time consumption during system design.

In a delay line type of a time-to-digital converter implemented in Field Programmable Gate Array, the timing accuracy decreases for a longer carry chain. In this paper, we propose a structure that has a multi-phase clock and a state machine to check metastability; this would reduce the required length of the carry chain with the same time resolution. To reduce the errors caused by the time difference in the four delay lines associated with a four-phase clock, the proposed TDC generates a single input pulse from four phase clocks and uses a single delay line. Moreover, the state machine is designed to find the phase clock that is used to generate the single input pulse and determine the metastable state without a synchronizer. With the measurement range of 1 ms, the measured resolution was 22 ps, and the non-linearity was 25 ps.

While the development of a portable plate panel display, thinning, high color reproduction, high brightness studies have been actively performed. LED, OLED is used as a light source. The research on quantum dot is much accomplished by the material of light source. Such quantum dot is the next generation semiconductor nano fluorescent substance because quantum dot has the high color reproduction and flexible display characteristic. In this study, we presented to method of using the quantum dot for implementation of the plate panel display. Quantum Dot (CdSe/ZnS), having a 100um thickness, is spread in PET barrier film. A Blue LED having a wavelength of 455nm as a light source irradiating light to the optical characteristic of the devices produced and evaluated. Also we presented the possibility for application with the color change film of the LCD.

We present on a threshold switching device based on AsGeTeSi material which is significantly improved by two processes: reactive during deposition, and plasma hardening. The introduction of N2 in the two-step processing enables a stackable and thermally stable device structure, is allowing integration of switch and memory devices for application in nano scale array circuits. Despite of its good threshold switching characteristics, AsTeGeSi-based switches have had key issues with reliability at a high temperature to apply resistive memory. This is usually due to a change in a Te concentration. However, our chalconitride switches(AsTeGeSiN) show high temperature stability as well as high current density over at celll. A cycling performance of the switch was over times. In addition, we demonstrated a memory cell consisted of 1 switch-1 resistor (1S-1R) stack structure using a TaOx resistance memory with the AsTeGeSiN select device.

In this study, we develop liquid density sensor by measuring of balanced position between gravity and bouyancy, corresponding to liquid density, using distance measuring by magnetostriction technology. For improvement of accuracy of liquid density sensor system. And we derive the related equation between liquid density and moving distance of density sensor, and make the calibration method for liquid density sensor by magnetostriction technology. Using fabricated liquid density sensing system and derived equation, have measured the density of several liquids. And compare it to measuring results using Oscillating U-tube type high accuracy density meter, having 0.000001 g/cc resolution. The deviation of results between two density measuring systems was less than 0.001 g/cc.

In this paper, we proposed the clothing management system using the smart hanger. Proposed system consists of smart hanger, base module, and server, and the smart hanger consists of MCU, LED, RFID reader, RF chip, ring sensor, and battery. The smart hanger reads the RFID tag attached to the clothes and wirelessly transmitted to the server. The server associated base module communicates with the smart hanger and transmits information to the server. The server manages clothing through the DB, and can display various information through the web page and the smart phone. In order to verify the usefulness of the proposed system, we did experiment with the management system for clothing store and laundry where using a lot of hangers. Performance tests of the smart hanger are applied to check the current consumption and can be predicted the battery life with the proposed low power algorithm. The clothing store management system can be increased sales and convenience of the consumer. The laundry management system can be increased the efficiency of laundry category and convenience of the consumer.

In this paper, we developed a LGP(Light Guide Panel) dry cleaning system for particle cleaning using corona discharge and dry adhesive roll. Therefore, we design a cleaning mechanism that can be applied dry adhesive dust removal roll and ESD(electrostatic discharge) by using corona discharge. Also, we design and implementation of equipment, which can loading, unloading and transfer LGP automatically. The developed equipment is dust and particle cleaning experimental results to demonstrate its stability.