• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.6
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• pp.37-45
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• 2011

As vehicles become more intelligent, in-vehicle networking (IVN) systems such as controller area network (CAN) or FlexRay are essential for convenience and safety of drivers. To expand the applicability of IVN systems, attention is currently being focused on the communication between heterogeneous networks such as body networking and chassis networking systems. A gateway based on message mapping method was developed to interconnect FlexRay and CAN networks. However, this type of gateways has the following shortcomings. First, when a message ID was changed, the gateway must be reloaded with a new mapping table reflecting the change. Second, if the number of messages to be transferred between two networks increase, software complexity of gateway increases very rapidly. In order to overcome these disadvantages, this paper presents FlexRay-CAN gateway based on node mapping method. More specifically, this paper presents a node mapping based FlexRay-CAN gateway operation algorithm along with the experimental evaluation for ID change.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.151-169
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• 2014

We propose a new technique for autonomous navigation and travelling of mobile robot based on ultrasonic sensors through the narrow labyrinth that leave only distance of a few centimeters on each side between the guides and the robot. In our current implementation the ultrasonic sensor system fires at a rate of 100 ms, that is, each of the 8 sensors fires once during each 100 ms interval. This is a very good firing rate, implemented here for optimal performance. This paper presents an extensively tested and verified solution to the problem of obstacle avoidance. Our solution is based on the optimal placement of ultrasonic sensors at strategic locations around the robot. Both the sensor location and the associated navigation algorithm are defined in such a way that only the accurate radial sonar data is used for accurate travelling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1171-1187
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• 2012

A depth adjustment method for visual fatigue reduction for depth-image-based rendering (DIBR) system is proposed. One important aspect of the method is that no calibration parameters are needed for adjustment. By analyzing 3D image warping, the perceived depth is expressed as a function of three adjustable parameters: virtual view number, scale factor and depth value of zero parallax setting (ZPS) plane. Adjusting these three parameters according to the proposed parameter modification algorithm when performing 3D image warping can effectively change the perceived depth of stereo pairs generated in DIBR system. As the depth adjustment is performed in simple 3D image warping equations, the proposed method is facilitative for hardware implementation. Experimental results show that the proposed depth adjustment method provides an improvement in visual comfort of stereo pairs as well as generating comfortable stereoscopic images with different perceived depths that people desire.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.113-125
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• 2017

Customers have been affected by others' opinions when they make a purchase. Thanks to the development of technologies, people are sharing their experiences such as reviews or ratings through online or social network services, However, although ratings are intuitive information for others, many reviews include only texts without ratings. Also, because of huge amount of reviews, customers and companies can't read all of them so they are hard to evaluate to a product without ratings. Therefore, in this study, we propose a methodology to predict ratings based on reviews for a product. In a methodology, we first estimate the topic-review matrix using the Latent Dirichlet Allocation technic which is widely used in topic modeling. Next, we predict ratings based on the topic-review matrix using the artificial neural network model which is based on the backpropagation algorithm. Through experiments with actual reviews, we find that our methodology can predict ratings based on customers' reviews. And our methodology performs better with reviews which include certain opinions. As a result, our study can be used for customers and companies that want to know exactly a product with ratings. Moreover, we hope that our study leads to the implementation of future studies that combine machine learning and topic modeling.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.163-170
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• 2007

In this paper, we propose that the polyphase scaler whose performance to that of the bicubic method, has less complexity in hardware structure. In order to get the new information, proposed system is based on the group delay which is one of the digital filter characteristics. The performance of this system is superior to that of bicubic algorithm which is well known. Because the hardware structure is simpler than other image scalers, we can adopt this system for mobile devices easily. The previous polyphase filters make blurring noise which is generated by up-scaling. We replace polyphase filters by boost-up filter to get vivid image. The proposed scaler is verified by Xilinx Virtex2 FPGA and is used as digital Boom in mobile camera phone.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.5
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• pp.57-63
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• 1995

In this paper, 3-Phase PWM AC/DC step up type converter that reduces the harmonics and reactive power of the distribution line is analyzed and the stable control method is proposed as controlling the sinusoidal phase current and phase voltage in phase. In implementation of controller, simple control algorithm is derived as the instantaneous voltage control methods without current sensor. The instantaneous voltage is controled by PWM method and the switching frequency is presented in low range 3 [kHz] for reducing the switching loss. In case of active load, four quadrants operation converter regenerate power from the load to the power source is conducted. Through the computer simulation and experimentation, the proposed control method is justified.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.79-92
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• 2020

As the number of systems increases and the network size increases, automated attack prediction systems are urgently needed to respond to cyber attacks. In this study, we developed four types of information gathering sensors for collecting asset and vulnerability information, and developed technology to automatically generate attack graphs and predict attack targets. To improve performance, the attack graph generation method is divided into the reachability calculation process and the vulnerability assignment process. It always keeps up to date by starting calculations whenever asset and vulnerability information changes. In order to improve the accuracy of the attack target prediction, the degree of asset risk and the degree of asset reference are reflected. We refer to CVSS(Common Vulnerability Scoring System) for asset risk, and Google's PageRank algorithm for asset reference. The results of attack target prediction is displayed on the web screen and CyCOP(Cyber Common Operation Picture) to help both analysts and decision makers.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.62-68
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• 2006

The important arithmetic operations over finite fields include multiplication and exponentiation. An exponentiation operation can be implemented using a series of squaring and multiplication operations over GF($2^m$) using the binary method. Hence, it is important to develop a fast algorithm and efficient hardware for multiplication. This paper presents an efficient bit-serial systolic array for MSB-first multiplication in GF($2^m$) based on the polynomial representation. As compared to the related multipliers, the proposed systolic multiplier gains advantages in terms of input-pin and area-time complexity. Furthermore, it has regularity, modularity, and unidirectional data flow, and thus is well suited to VLSI implementation.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.31-38
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• 2017

With the Development of Information Technology, Security is becoming very Important. Existing Security Systems are Mostly Expensive and Not Easy to Implement, and are Also very Complex when using Biometric Information. In this paper, We try to solve this Problem by Implementing a Low cost Internet based Security Terminal Using Fingerprint and Face Image. To Implement a Low-cost Security System, a Fingerprint Scanner and a Camera are installed in Raspberry pi, and the Scanned Image is encrypted with the AES-256 Algorithm and Transmitted to Cloud. Through This Study, We confirmed the Possibility of the Proposed System in view of Authentication, Cost Reduction, Security and Scalability.