• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2484-2490
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• 2012

This study reports on the development and performance verification of cell simulation boards of simulator and the embedded program for board control of the battery management system (BMS) of electric vehicle (EV) cars, which manages the next-generation automotive lithium-ion battery pack. Here, we have improved the speed of the simulator by using operational (OP) amplifier and transistors that were connected in series. In addition, using a digital analog converter (DAC) in each channel, we have improved the performance by channel-to-channel isolation (isolation) as compared to the traditional methods. Furthermore, by constructing a current-limiting protection circuit, one can be protected from disturbance and, by utilizing a precision shunt resistor for the current sensor, we have increased the precision of the current control. In order to verify the performance of the developed simulator, we have performed the experiment 10 times, with values ranging from 0.5 V to 5 V, and a voltage drop step of 0.5 V. Significance analysis of experimental data, and repeatability tests were performed, showing an average standard deviation of 0.001~0.004 V, indicating high repeatability and high statistical significance of the current method and system.

• Korean Journal of Materials Research
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• v.19 no.11
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• pp.576-580
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• 2009

$BaTiO_3$/epoxy composites have been widely investigated as promising materials for embedded capacitors in printed circuit boards. It is generally known that the dielectric constant (K) of the $BaTiO_3$/epoxy composites increases with improvement of the dispersion of $BaTiO_3$ particles in the epoxy matrix that comes from adding surfactant. The influences of surfactant addition on the dielectric properties of the $BaTiO_3$/epoxy composites are reported in the present study. The dielectric constant of the $BaTiO_3$/epoxy composites is not significantly affected by the surfactant addition. However, the temperature coefficient of capacitance increases and the peel strength decreases as the amount of added surfactant increases. The influences of surfactant addition on the dielectric properties of the neat epoxy are also very similar to those of the $BaTiO_3$/epoxy composites. The residual surfactant in the $BaTiO_3$/epoxy composites affects the temperature coefficient of capacitance and the peel strength of the epoxy matrix, which in turn affects the temperature coefficient of capacitance and the peel strength of the $BaTiO_3$/epoxy composites.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.11-23
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• 2016

Recent days, touch interaction interface is the most widely used interaction interface to communicate with digital devices. Because of its usability, touch technology is applied almost everywhere from watch to advertising boards and it is growing much bigger. However, this technology has a critical weakness. Normally, touch input device needs a contact surface with touch sensors embedded in it. Thus, touch interaction through general objects like books or documents are still unavailable. In this paper, a human-object interaction framework based on RGB-D camera is proposed to overcome those limitation. The proposed framework can deal with occluded situations like hovering the hand on top of the object and also moving objects by hand. In such situations object recognition algorithm and hand gesture algorithm may fail to recognize. However, our framework makes it possible to handle complicated circumstances without performance loss. The framework calculates the status of the object with fast and robust object recognition algorithm to determine whether it is an object or a human hand. Then, the hand gesture recognition algorithm controls the context of each object by gestures almost simultaneously.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.81-101
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• 2003

The financial statements purpose to provide useful information to decision-making process of business managers. The value-relevant information, however, embedded in the financial statement has been often overlooked in Korea. In fact, the financial statements in Korea have been utilized for nothing but account reports to Security Supervision Boards (SSB). The objective of this study is to develop earnings forecasting models through financial statement analysis using artificial intelligence (AI). AI methods are employed in forecasting earnings: artificial neural networks (ANN) for manufacturing industry and case~based reasoning (CBR) for banking industry. The experimental results using such AI methods are as follows. Using ANN for manufacturing industry records 63.2% of hit ratio for out-of-sample, which outperforms the logistic regression by around 4%. The experiment through CBR for banking industry shows 65.0% of hit ratio that beats the statistical method by 13.2% in holdout sample. Finally, the prediction results for manufacturing industry are validated through monitoring the shift in cumulative returns of portfolios based on the earning prediction. The portfolio with the firms whose earnings are predicted to increase is designated as best portfolio and the portfolio with the earnings-decreasing firms as worst portfolio. The difference between two portfolios is about 3% of cumulative abnormal return on average. Consequently, this result showed that the financial statements in Korea contain the value-relevant information that is not reflected in stock prices.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.24-30
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• 2009

In this paper, the FPGA modem platform complying with 3GPP Release 7 eHSPA specifications and its regularized verification flow are proposed. The FFGA platform consists of modem board supporting physical layer requirements, MCU and DSP core embedded control board to drive the modem board, and peripheral boards for RF interfacing and various equipment interfaces. On the other hand, the proposed verification flow has been regularized into three categories according to the correlation degrees of hardware-software inter-operation, such as simple function test, scenario test call processing and system-level performance test. When it comes to real implementations, the emulation verification strategy for low power mobile SoC is also introduced.

• Journal of IKEEE
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• v.23 no.3
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• pp.844-851
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• 2019

As wearable technology is becoming more common and a part of our lives, there have been many efforts to offer various smart services with wearable devices, such as motion recognition, safety of driving, and so on. In this paper, we present a method that exploits the 9-axis inertial sensors embedded in a smartwatch to identify whether the user is a vehicle driver or not and to estimate the steering wheel turning direction in the vehicle. The system consists of three components: (i) position recognition, (ii) driver recognition, and (iii) steering-wheel turning detection components. We have developed a prototype system for detecting user's motion with Arduino boards and IMU sensors. Our experiments show high accuracy in recognizing the driver and in estimating the wheel rotation angle. The average experimental error was $11.77^{\circ}$ which is small enough to perceiver the turning direction of steering-wheel.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.75-80
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• 2009

Bum-in test is one for eliminating semiconductor devices that are subject to early failures and other operational problems; it is usually carried out on the devices by imposing severe test conditions such as elevated voltages, temperatures, and time. In order for such a test to be performed, each burn-in board having devices to be tested, needs to be inserted into a corresponding slot. A set of such slots is called a zone. The slots comprising a zone can only have the burn-in boards with the devices of the same type. In order to test many different types of semiconductor devices, it is desirable to build a burn-in test system to have as many zones as possible. A zone controller controlling a zone, is a device that performs a burn-in test and collects test results. In case of existing systems, each zone controller takes care of a zone that consists of a fixed number of slots. Since a zone controller is, in most cases, embedded into a workstation that controls the overall testing process, adding new zone controllers is restricted by the spaces for them. As a way to solve or alleviate these problems, a dynamic zone system in which the number of slots in a zone can be dynamically allocated, is presented. This system maximizes the efficiency of system utilization, by altering the number of slots and hence minimizing the idle slots of a zone. In addition, all the test operations being performed must be aborted for maintenance in existing systems. In dynamic zone systems, however, a separate and independent maintenance is allowed for each slot, as long as the main power supply system has no problem.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.