• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.155-160
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• 2014

There are many image processing based algorithms and applications that fail when illumination change occurs. Therefore, the illumination change has to be detected then the illumination change occurred images need to be enhanced in order to keep the appropriate algorithm processing in a reality. In this paper, a new method for detecting illumination changes efficiently in a real time by using local region information and fuzzy logic is introduced. The effective way for detecting illumination changes in lighting area and the edge of the area was selected to analyze the mean and variance of the histogram of each area and to reflect the changing trends on previous frame's mean and variance for each area of the histogram. The ways are used as an input. The changes of mean and variance make different patterns w hen illumination change occurs. Fuzzy rules were defined based on the patterns of the input for detecting illumination changes. Proposed method was tested with different dataset through the evaluation metrics; in particular, the specificity, recall and precision showed high rates. An automatic parameter selection method was proposed for contrast limited adaptive histogram equalization method by using entropy of image through adaptive neural fuzzy inference system. The results showed that the contrast of images could be enhanced. The proposed algorithm is robust to detect global illumination change, and it is also computationally efficient in real applications.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.120-134
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• 2000

In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

• Journal of the Korean Society of Radiology
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• v.9 no.2
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• pp.67-72
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• 2015

In diagnostic radiology, the use of automatic exposure control device is internationally recommended for diagnosis and optimization. However, if exposed to prolonged radiation is a complicated manufacturing process, there is a problem that occurs decrease of various performance overall brightness sensor, which is commercially available conventional. Therefore, in this study, absorption of X-ray is high, and I want to evaluate the AEC applicability of the sensor of the photoconductor-based production has an easy advantage. Experimental results confirms the possibility of fabrication of the sensor through an increase in the SNR, with the detection efficiency superior, accurate turn-off. In addition, it is confirmed that the experimental results of the transmittance and the latent image, Ghost effect by the light conductor does not appear, in the case of a photoconductor with the exception of the PbO, 80% - and it was confirmed good transmittance of 90%. Therefore, excellent mechanical stability and poor performance due to a change of the doping concentration than the existing products that have been put to practical use, the sensor easy photoconductor based, fabrication and can be applied as AEC sensor is expected.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.417-424
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• 2006

Despite of many researches related to create 3D digital maps, it is still time-consuming and costly because a large part of 3D digital mapping is conducted manually. To circumvent this limitation, we proposed methodologies to create 3D digital maps with 3D symbols automatically. For this purpose, firstly, the 3D symbol library to represent 3D objects as 3D symbols was constructed. In this library, we stored the attribute and geometry information of 3D objects which define types and shapes of symbols respectively. These information were used to match 3D objects with 3D symbols and extracted from 2D digital maps and LiDAR(Light Detection and Ranging) data. Then, to locate 3D symbols into a base map automatically, we used predefined parameters such as the size, the height, the rotation angle and the center of gravity of 3D objects which are extracted from LiDAR data. Finally, the 3D digital map in urban area was constructed and the results were tested. Through this research, we can identify that the developed algorithms can be used as effective techniques for 3D digital mapping.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.369-374
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• 2015

In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some brain hemorrhage patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of brain hemorrhage. As the results of examining over 40 example CT images of brain hemorrhage, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including average gray level, average contrast, smoothness, and Skewness while others showed a little low disease recognition rate: 95% for uniformity and 87.5% for entropy. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of brain hemorrhage and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.

• Journal of KIISE
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• v.42 no.12
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• pp.1522-1534
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• 2015

This work presents a new method that can predict, without the use of training data, whether an input essay is written on a given topic. ConceptNet is a common-sense knowledge base that is generated automatically from sentences that are extracted from a variety of document types. An essay prompt is the topic that an essay should be written about. The method that is proposed in this paper uses ConceptNet and an essay prompt to decide whether or not an input essay is off-topic. We introduce a way to find the shortest path between two nodes on ConceptNet, as well as a way to calculate the semantic similarity between two nodes. Not only an essay prompt but also a student's essay can be represented by concept nodes in ConceptNet. The semantic similarity between the concepts that represent an essay prompt and the other concepts that represent a student's essay can be used for a calculation to rank "on-topicness" ; if a low ranking is derived, an essay is regarded as off-topic. We used eight different essay prompts and a student-essay collection for the performance evaluation, whereby our proposed method shows a performance that is better than those of the previous studies. As ConceptNet enables the conduction of a simple text inference, our new method looks very promising with respect to the design of an essay prompt for which a simple inference is required.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.32-40
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• 2008

Fuzzy rules are very useful and efficient to describe classification rules especially when the attribute values are continuous and fuzzy in nature. However, it is generally difficult to determine membership functions for generating efficient fuzzy classification rules. In this paper, we propose a method of automatic generation of efficient fuzzy classification rules using evolutionary algorithm. In our method we generate a set of initial membership functions for evolutionary algorithm by supervised clustering the training data set and we evolve the set of initial membership functions in order to generate fuzzy classification rules taking into consideration both classification accuracy and rule comprehensibility. To reduce time to evaluate an individual we also propose an evolutionary algorithm with data partition evaluation in which the training data set is partitioned into a number of subsets and individuals are evaluated using a randomly selected subset of data at a time instead of the whole training data set. We experimented our algorithm with the UCI learning data sets, the experiment results showed that our method was more efficient at average compared with the existing algorithms. For the evolutionary algorithm with data partition evaluation, we experimented with our method over the intrusion detection data of KDD'99 Cup, and confirmed that evaluation time was reduced by about 70%. Compared with the KDD'99 Cup winner, the accuracy was increased by 1.54% while the cost was reduced by 20.8%.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.380-389
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• 2007

In Korea, undoubtedly, the cancer is one of the most common reasons of death, and hepatoma is the second highest fatal cancer regardless of the gender only next to the stomach cancer In the middle and prime-aged between 40 and 60 years, the incidence of hepatoma is the highest in the world, and the death rate due to hepatoma is the highest among OECD countries. In this paper, we propose a novel method for automatic identification of hepatoma from a contrast enhanced CT images, which is used in an expert system that helps medical specialists. First, consecutive $40{\sim}50$ contrail enhanced CT images are photographed by every 5mm from the upper part of the chest, and using position information on the rib, we classify the internal area including only internal organs and the external one that consists of the rib, subcutaneous fat layers, and the background from the CT images. Then, the region of the liver is extracted from the classified internal area by using information on the intensity, the distribution of brightness, and using the regions extracted from consecutive images, we restore information on the 5 mm space occurred between the consecutive two slides tty applying a shape-based interpolation method. Lastly, using the characteristics such as the brightness and the morphology, we are able to extract the regions of hepatoma. The expert system based on our method is sufficiently competitive when it is compared with the diagnoses by specialists in the diagnostic radiology.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.4
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• pp.11-17
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• 2001

In this paper, we propose a polarity decision carrier recovery algorithm for high order QAM(Quadrature Amplitude Modulation), which has robust and large frequency acquisition performance in the high order QAM modem. The proposed polarity decision PD(Phase Detector) output and its variance characteristic are mathematically derived and the simulation results are compared with conventional DD(Decision-Directed) method. While the conventional DD algorithm has linear range of $3.5^{\circ}{\sim}3.5^{\circ}$, the proposed polarity decision PD algorithm has linear range as large as $-36^{\circ}{\sim}36^{\circ}$ at ${\gamma}-17.9$. The conventional DD algorithm can only acquire offsets less than ${\pm}10\;KHz$ in the case of the 256 QAM while an analog front-end circuit generally can reduce the carrier-frequency offset down to only ${\pm}100\;KHz$. Thus, in this case additional AFC or phase detection circuit for carrier recovery is required. But by adopting the proposed polarity decision algorithm, we can find the system can acquire up to ${\pm}300\;KHz$at SNR = 30dB without aided circuit.

• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.39-48
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• 2014

The speed of aging society is increasingly getting faster in Korea. Currently, there are over one million elderly living alone, which represents more than 19% of the total elderly in Korea. Although various policies and research have been implemented for caring the elderly living alone, there have been obvious limitations in realization of the caring system due to inconvenience, privacy violation, difficult operation and maintenance. Therefore, the objective of this study is to develop a method and a prototype system to monitor safety of elderly living alone by using energy usage information of automatic meter reading device. The proposed system is expected to improve or resolve the existing limitations and to provide 24 hour monitoring and early detection of death for the elderly living alone without adding staffs for operation and maintenance in a more effective and economic way.