• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.253-261
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• 2002

A spatially adaptive falter was formulated to imrove PET image qualify and the Performance of the filter was evaluated using simulation and phantom and human PET studies. In the proposed filter. if a pixel was identified as the edge Pixel, the Pixel value was Preserved. Otherwise a Pixel was replaced by the mean of the pixel values weighted by 2:7: 2. A Pixel was identified as the edge Pixel. if it satisfies the following conditions : the number of ADs (absolute difference between center and neighborhood pixels) which is smaller than THl (($pix_max{\times}0.1/log_2(NPM)$, NPM : mean of 6 neighborhood pixels excluding minimum and maximum) is 8-k and the number of ADs which is lager than TH2 ($NPM{\times}0.1$) is k. where k : 2, 3, …, 6. The results of this study demonstrate the superior performance of the Proposed titter compared to Gaussian fitter, weight median filter and subset averaged median filter. The proposed tittering method is simple but effective in increasing uniformity and contrast with minimal degradation of spatial resolution of PET images and thus. is expected to Provide improved diagnositc quality PET images .

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Korean Journal of Environmental Agriculture
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• v.30 no.2
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• pp.153-159
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• 2011

BACKGROUND: This experiment was conducted to investigate the distribution and burden characteristics of heavy metal in the rainwater sampled at Taean area, in the middle part of Korea, from April 2002 to October 2003. METHODS AND RESULTS: The relationship between concentration of heavy metal and other chemical properties in the rainwaters was also evaluated. Chemical properties in the rainwater were various differences with raining periods and years. It appeared that a weighted average pH values of rainwater was ranged from 5.0 to 5.1. Heavy metal concentrations in the rainwater were ranked as Pb > Zn > Cu > Ni > As > Cr > Cd. As compared with heavy metal concentrations of rainwater in 2002, Cu, Pb, and Zn were higher than other elements in 2003. There were positive correlation between major ionic components, such as ${NH_4}^+$, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $Na^+$, ${SO_4}^{2-}$ and ${NO_3}^-$, and As, Cd, Zn, Cr, and Ni concentrations in rainwater. For heavy metal distribution of rainwater, the order of average enrichment factor was Cd > Pb > As > Cu > Zn > Ni > Cr, and these were relatively higher than the natural components such as Fe, Mg and Ca. The monthly enrichment factor were relatively high, from August to October at Taean. The monthly amount of heavy metal precipitation was high in the rainy season from July to August because of great influence of rainfall. CONCLUSION(s): The results of this study suggest that the heavy metals(Cd, Pb, As, Cu, and Zn) of rainwater is strongly influenced by anthropogenic sources rather than natural sources.

• Progress in Medical Physics
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• v.17 no.2
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• pp.89-95
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• 2006

The purpose of this study was to evaluate the radiation doses during CT transmission scan by changing tube voltage and tube current, and to estimate the radiation dose during our clinical whole body $^{137}Cs$ transmission scan and high quality CT scan. Radiation doses were evaluated for Philips GEMINI 16 slices PET/CT system. Radiation dose was measured with standard CTDI head and body phantoms in a variety of CT tube voltage and tube current. A pencil ionization chamber with an active length of 100 mm and electrometer were used for radiation dose measurement. The measurement is carried out at the free-in-air, at the center, and at the periphery. The averaged absorbed dose was calculated by the weighted CTDI ($CTDI_w=1/3CTDI_{100,c}+2/3CTDI_{100,p}$) and then equivalent dose were calculated with $CTDI_w$. Specific organ dose was measured with our clinical whole body $^{137}Cs$ transmission scan and high quality CT scan using Alderson phantom and TLDs. The TLDs used for measurements were selected for an accuracy of ${\pm}5%$ and calibrated in 10 MeV X-ray radiation field. The organ or tissue was selected by the recommendations of ICRP 60. The radiation dose during CT scan is affected by the tube voltage and the tube current. The effective dose for $^{137}Cs$ transmission scan and high qualify CT scan are 0.14 mSv and 29.49 mSv, respectively. Radiation dose during transmission scan in the PET/CT system can measure using CTDI phantom with ionization chamber and anthropomorphic phantom with TLDs. further study need to be peformed to find optimal PET/CT acquisition protocols for reducing the patient exposure with same image qualify.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.215-224
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• 1994

In this paper, the rotation and size invariant fingerprint recognition using the neural network EART (Extended Adaptive Resonance Theory) is studied ($515{\times}512$) gray level fingerprint images are converted into the binary thinned images based on the adaptive threshold and a thinning algorithm. From these binary thinned images, we extract the ending points and the bifurcation points, which are the most useful critical feature points in the fingerprint images, using the $3{\times}3$ MASK. And we convert the number of these critical points and the interior angles of convex polygon composed of the bifurcation points into the 40*10 critical using the weighted code which is invariant of rotation and size as the input of EART. This system produces very good and efficient results for the rotation and size variations without the restoration of the binary thinned fingerprints.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.388-396
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• 2016

The metropolitan subway network of Seoul has gone through many evolutionary processes in past decades to disperse the floating population and improve the traffic flow. In this study, we analyzed how the structural characteristics and the efficiency of the subway network have changed according to the dynamic evolutionary processes of the metropolitan subway network of Seoul. We have also proposed new measures that can be used to characterize the structural properties of the subway network more practically. It is shown that the global efficiency is about 74%, which is higher than those of subway networks of foreign countries. It should also be considered that passenger flow between stations is even higher, at about 85%. Since the private lines, including line 9, the New Bundang line, the Uijeongbu line, and the Ever line do not release their traffic data since September, 2013, only 5 years of data from September, 2008 to September, 2013 is available. So, in this study we limit the analysis period to these 5 years.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.147-155
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• 2015

In this paper, we consider a mobile sensor network for monitoring a polluted area where human beings cannot access. Due to the limited sensing range of individual unmanned vehicles, they need to cooperate to achieve an effective sensing coverage and move to a more polluted region. In order to address the limitations of sensing and communication ranges, we propose a hazardous substance monitoring network based on virtual force algorithms, and develop a testbed. In the considered monitoring network, each unmanned vehicle achieves an optimal coverage and move to the highest interest area based on neighboring nodes sensing values and locations. By using experiments based on the developed testbed, we show that the proposed monitoring network can autonomously move toward a more polluted area and obtain a high weighted coverage.

• Information Systems Review
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• v.11 no.3
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• pp.39-62
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• 2009

The previous literature on the field of performance management mainly focuses on the research regarding the critical success factors, the intention of use, and the output of the BSC system. This paper is to develop and analyze the influencing factors of the acceptance on the BSC performance indicators in the public sector. The result from the analysis of the data collected from this research shows that these influencing factors include the education about BSC, the specificity of the indicators, the connection between strategy and mission, and the participation and support during the development of the indicators. Further, the result reveals that the CEO's concern is nothing to do with the employees acceptance of the BSC performance indicators in the public sector, unlike the consistent result from the previous literature. The reason is because the employees often tend to refuse the performance indicators of the CEO's concern that increase their workload due to the establishment of the excessive target of the indicators and their periodic reports.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.224-236
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• 1997

In order to control the flow of traffic in ATM networks and optimize the usage of network resources, an appropriate control mechanism is necessary to cope with congestion or prevent degradation of network performance caused by congestion. While the conventional UPC algorithm provides only unstable preventive function unrelated with the state of networks and is unable to recover congestion, the proposed adaptive UPC algorithm supervises the situation of ATM networks using the information from OAM cell. Then the monitor of the proposed adaptive UPC algorithm controls leaky rate and buffer threshold value according to QOS. Therefore, the proposed algorithm can cope with congestion as well as prevent and react sensitively to buffer delay. In proportion to the diversity of traffic and the increase of transmission rate in networks, the adaptive UPC-BT algorithm proposed in this paper can be effectively used in ATM networks with wide applications. This paper shows that the proposed algorithm efficiently uses in ATM networks with application. This paper shows that the proposed algorithm efficiently use network resources and provides QOS to users for various kinds of traffics by comparing with conventional UPC algorithms.

• Journal of the Korea Concrete Institute
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• v.26 no.4
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• pp.465-474
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• 2014

This is a comparative study that shows the overall environmental impacts from concrete structures when different compressive strength of concrete applied to structural systems having the same reference flow with different durability. A total of 24 MPa, 40 MPa and 60 MPa cases is analyzed to define the characteristic using end-point perspective LCA methodology including the stages of production, construction, maintenance and disposal. As results, global warming, non-renewable energy and respiratory inorganics problems are the major issues for assessing environmental impacts of concrete products.