• 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.

• Journal of Sensor Science and Technology
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• v.14 no.2
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• pp.69-77
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• 2005

The electronic nose (e-nose) has been used in food industry and quality controls in plastic packaging. Recently it finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. Moreover, the use of portable e-nose enables the on-site measurements and analysis of vapors without extra gas-sampling units. This is expected to widen the application of the e-nose in various fields including point-of-care-test or e-health. In this study, a PDA-based portable e-nose was developed using micro-machined gas sensor array and miniaturized electronic interfaces. The rich capacities of the PDA in its computing power and various interfaces are expected to provide the rapid and application specific development of the diagnostic devices, and easy connection to other facilities through information technology (IT) infra. For performance verification of the developed portable e-nose system, Six different vapors were measured using the system. Seven different carbon-black polymer composites were used for the sensor array. The results showed the reproducibility of the measured data and the distinguishable patterns between the vapor species. Additionally, the application of two typical pattern recognition algorithms verified the possibility of the automatic vapor recognition from the portable measurements. These validated the portable e-nose based on PDA developed in this study.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.15-27
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• 2007

In Korea, hepatoma is the thirdly frequent cause of death from cancer occupying 17.2% among the whole deaths from cancer and the rate of death from hepatoma comes to about 21's persons per one-hundred thousand ones. This paper proposes an automatic method for the extraction of areas being suspicious as hepatoma from a CT scan and evaluates the availability as an auxiliary tool for the diagnosis of hepatoma. For detecting tumors in the internal of the liver from CT scans, first, an area of the liver is extracted from about $45{\sim}50's$ CT scans obtained by scanning in 2.5-mm intervals starting from the lower part of the chest. In the extraction of an area of the liver, after unconcerned areas outside of the ribs being removed, areas of the internal organs are separated and enlarged by using intensity information of the CT scan. The area of the liver is extracted among separated areas by using information on position and morphology of the liver. Since hepatoma is a hypervascular turner, the area corresponding to hepatoma appears more brightly than the surroundings in contrast-enhancement CT scans, and when hepatoma shows expansile growth, the area has a spherical shape. So, for the extraction of areas of hepatoma, areas being brighter than the surroundings and globe-shaped are selected as candidate ones in an area of the liver, and then, areas appearing at the same position in successive CT scans among the candidates are discriminated as hepatoma. For the performance evaluation of the proposed method, experiment results obtained by applying the proposed method to CT scans were compared with the diagnoses by radiologists. The evaluation results showed that all areas of the liver and liver tumors were extracted exactly and the proposed method has a high availability as an auxiliary diagnosis tools for the discrimination of liver tumors.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.177-183
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• 2002

Current state-of-the-art of VMS control is based upon simple knowledge-based inference engine with message set and each message's priority. And R&Ds of the VMS control are focused on the accurate detection and estimation of traffic condition of the subject roadways. However VMS display itself cannot achieve a desirable traffic allocation among alternative routes in the network In this context, VMS display strategy is the most crucial part in the VMS control. VMS itself has several limitations in its nature. It is generally known that VMS causes overreaction and concentration problems, which may be more serious in urban network than highway network because diversion should be more easily made in urban network. A feedback control algorithm is proposed in this paper to address the above-mentioned issues. It is generally true that feedback control approach requires low computational effort and is less sensitive to models inaccuracy and disturbance uncertainties. Major features of the proposed algorithm are as follows: Firstly, a regulator is designed to attain system optimal traffic allocation among alternative routes for each VMS in the network. Secondly, strategic messages should be prepared to realize the desirable traffic allocation, that is, output of the above regulator. VMS display strategy module is designed in this context. To evaluate Probable control benefit and to detect logical errors of the Proposed feedback algorithm, a offline simulation test is performed using real network in Daejon, Korea.