• Bulletin of the Korean Chemical Society
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• v.33 no.10
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• pp.3368-3372
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• 2012

The $Bi_2O_3$ nanowires are highly sensitive to low concentrations of $NO_2$ in ambient air and are almost insensitive to most other common gases. However, it still remains a challenge to enhance their sensing performance and detection limit. This study examined the influence of the encapsulation of ${\beta}-Bi_2O_3$ nanorods with $In_2O_3$ on the $NO_2$ gas sensing properties. ${\beta}-Bi_2O_3-core/In_2O_3-shell$ nanorods were fabricated by a two-step process comprising the thermal evaporation of $Bi_2O_3$ powders and sputter-deposition of $In_2O_3$. Multiple networked ${\beta}-Bi_2O_3-core/In_2O_3-shell$ nanorod sensors showed the responses of 12-156% at 1-5 ppm $NO_2$ at $300^{\circ}C$. These response values were 1.3-2.7 times larger than those of bare ${\beta}-Bi_2O_3$ nanorod sensors at 1-5 ppm $NO_2$. The enhancement in the response of ${\beta}-Bi_2O_3$ nanorods to $NO_2$ gas by the encapsulation by $In_2O_3$ can be accounted for based on the space-charge model.

• Korean journal of communication and information
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• v.54
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• pp.98-117
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• 2011

This paper is a theoretical inquiry of the changing roles of digital technologies in the representation of risk. Critically examining existing perspectives on risk society and risk communication, this paper argues that digital technologies and images in risk communication have been relatively understudied. Having said that, this paper suggests that Actor-network Theory provide useful theoretical tools for current studies on how digital technologies affect contemporary risk communication practices. Furthermore, this paper examines varied recent studies investigating how digital technologies of visualization are at play in risk communication practices. In doing so, this paper demonstrates how digital images and technologies interrupt the processes that scientific evidence is presented and facts are constructed in varied contemporary scientific reasoning. It will focus on the emerging mode of seeing and visual regime made possible by the increased usage of digital image and technologies, which are characterized by networked connection, sensor, computerized algorithm, and increased storage space. Finally this paper will discuss on the implications on future studies on the roles of digital images and technologies in risk communication practices in Korean context.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.91-98
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• 2010

In order to control moving facilities on a remote place effectively, it are required to acquire a environment informations such as images where the moving facilities are placed. However, since there is no tools to acquire such informations to the central control system based on the non-networked sensor environments, it is difficult to control the moving facilities remotely. Therefore, we design and implement the Zigbee based image transmission system and communication protocol to control the moving target remotely. The wireless control utilizing the Zigbee protocol is that electrically consumption is more small than the Bluetooth and reliability of data transmission is better. The implemented Zigbee based control systems and communication protocol have the normal and replay function for a realtime control of the moving target under the server PC and the mobile FDA with the WiFi protocol. The functional operability and performance are analyzed by a designed prototype under the wireless home network environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.384-389
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• 2005

The objective on this project is to develop a cooperative Field Robot (FR), by using a customize Open Control Platform (OCP) as design and development process. An OCP is a CORBA-based solution for networked control system, which facilitates the transitioning of control designs to embedded targets. In order to achieve the cooperation surveillance system, two FRs are distributed by navigation messages (GPS and sensor data) using CORBA event-channel communication, while graphical information from IR night vision camera is distributed using CORBA Asynchronous Method Invocation (AMI). The QoS features of AMI in the network are to provide the additional delivery method for distributing an IR camera Images will be evaluate in this experiment. In this paper also presents an empirical performance evaluation from the variable chunk sizes were compared with the number of clients and message latency, some of the measurement data's are summarized in the following paragraph. In the AMI buffers size measurement, when the chuck sizes were change, the message latency is significantly change according to it frame size. The smaller frame size between 256 bytes to 512 bytes is more efficient fur the message size below 2Mbytes, but it average performance in the large of message size a bigger frame size is more efficient. For the several destination, the same experiment using 512 bytes to 2 Mbytes frame with 2 to 5 destinations are presented. For the message size bigger than 2Mbytes, the AMI are still able to meet requirement far more than 5 clients simultaneously.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1204-1212
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• 2008

The vehicle simulation (flight simulator) in 1920's was the first in the virtual reality. With the development of precise optical and electromagnetic equipment, the virtual reality widened its application for other purposes than military one. Based on the realistic display technology, it is more and more common in the various areas such as entertainment, medical profession, learning, film, architectural design, tourism and etc. In 1989, Jaron Ranier was the first to use the terminology 'Virtual Reality'. With this term, all virtual projects could be classified in a single item. But even before the term was used, the virtual reality has been studied up to now. As a part of virtual reality, the human thirst for the impossible thing has led to the development of ride film. The ride film consists of the special technical elements as well as the psychological analysis of human being. The ultimate purpose of virtual reality is engrossment through interaction. Even though the real interaction requires interface, input sensor and reaction ability, the ride film is not an element of the typical interaction. The virtual reality is mostly defined in technical terms now. But in this study, we will analyze the concepts worked out by Professor Michael Haim who is called a philosopher in the cyberspace in aspect of experience-oriented definition. We will analyze the adaptability of virtual reality based on his concepts such as artificial reality/ interaction/ engrossment/ networked world/ remote display/ simulation/ onmon engrossment. And also, we aim to suggest the directions of developing the ride films for perfect engrossment and to draw optimized conclusion thereon. In this viewpoint, we consider that the study of ride film on which there were few case studies will contribute to level up the basic frameworks of IT technology and the digital image.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.