• Journal of Surface Science and Engineering
• /
• v.40 no.4
• /
• pp.185-189
• /
• 2007

A scanning electron microscope (SEM) is a complex system, consisting of many sophisticated components. For a systematic characterization, a $2^4$ full factorial experiment was conducted. The SEM components examined include condenser lens 1 and 2 (denoted as A and B, respectively), and Objective lens (coarse and fine-denoted as C and D respectively). A statistical analysis was conduced to investigate factor effects and variations In response surfaces. Among four factors, main effect analysis revealed that A and D were Identified as the dominant factor. Moreover, B showed conflicting effect against C. The $R^2$ of statistical regression model constructed was about 69.6%. The model generated 3D response surface plots facilitated understanding of complex tactor effects.

• Health Policy and Management
• /
• v.9 no.1
• /
• pp.110-138
• /
• 1999

This study intended to understand the factors influencing the utilization of charged retirement home services for the elderly by stage of discision making. At the same time the purpose of the study is also to present the results of this study as data for the expectation of the demand. The subject of this study was non-utilizer (635 persons) and utilizer (62 persons) of charged retirement home services over the age of sixty. Non-utilizer was selected by random sampling in urban and rural area, and utilizer was investigated by census survey in the three charged retirement home. The research method was interview survey by questionaire. The questionaire was composed of 59 items, 25 variables, 5 components. The research model was to add Andersen's Prediction Model. The components were predisposing component, enabling component, need component, actualizing component, psychologic component. The results of this study were as follows. 1)In the stage of recognizing the residence problem, the recognizer were 76.7% (487 persons) of all the non-utilizer. The factors of influencing were property (B=-4.1E-05), solidarity with children (B=-.1070), house satisfaction (B=-.2517), need of charged retirement home (B=.2614). 2)In the stage of selecting an altenative as utilizing of charged retirement home services, the selecter were 41.1% (261 persons) of all the non-utilizer. The factors of influencing were perception of charged retirement home (B=.2790), need of charged retirement home (B=.2971). 3)In the stage of decion-making, the decider were 29.6% (188 persons) of all the non-utilizer. The factor of influencing was need of charged retirement home (B=.3570). 4)In the stage of the actualization, the factors of influencing were charge ability of utilization (B=.1025), significant others (B=.1868). The upper results were implemented by using the statistical methods of frequency, t-test, $$\chi$^{2}$-test, multiple logistic regression ( and P 〈 .05 ).

• Journal of the Korean Society for Nondestructive Testing
• /
• v.35 no.2
• /
• pp.128-133
• /
• 2015

This paper describes the construction of a static 3D ultrasonography image by tracking the radiation beam position during the handy operation of a 1D array probe to enable point-of-care use. The theoretical model of the transformation from the translational and rotational information of the sensor mounted on the probe to the reference Cartesian coordinate system was given. The signal amplification and serial communication interface module was made using a commercially available sensor. A test phantom was also made using silicone putty in a donut shape. During the movement of the hand-held probe, B-mode movie and sensor signals were recorded. B-mode images were periodically selected from the movie, and the gray levels of the pixels for each image were converted to the gray levels of 3D voxels. 3D and 2D images of arbitrary cross-section of the B-mode type were also constructed from the voxel data, and agreed well with the shape of the test phantom.

• The KIPS Transactions:PartB
• /
• v.19B no.3
• /
• pp.195-200
• /
• 2012

In Korean, spelling change in various forms must be recovered into base forms in morphological analysis as well as part-of-speech (POS) tagging is difficult without morphological analysis because Korean is agglutinative. This is one of notorious problems in Korean morphological analysis and has been solved by morpheme recovery rules, which generate morphological ambiguity resolved by POS tagging. In this paper, we propose a morpheme recovery scheme based on machine learning methods like Na$\ddot{i}$ve Bayes models. Input features of the models are the surrounding context of the syllable which the spelling change is occurred and categories of the models are the recovered syllables. The POS tagging system with the proposed model has demonstrated the $F_1$-score of 97.5% for the ETRI tree-tagged corpus. Thus it can be decided that the proposed model is very useful to handle morpheme recovery in Korean.

• Journal of Environmental Impact Assessment
• /
• v.15 no.2
• /
• pp.93-100
• /
• 2006

In general, the verification to prediction formula in a national road and the main street of a town has been used recklessly in Korea. Therefore we investigated the validity of an existing prediction formula (NIER(87, 99), TR-Noise, KLC(2002)) with correction relationship which was based on both the prediction formular from apartment complex in the field and height 1.5m from the surface level. On the results of measuring the noise level form an isolated distance, the noise level showed that it was 4.5~5.5dB(A) by reason of becoming 2 folder far from a source. From the distribution of noise level measured by the apartment floors, the measurement point (1st floor) was 58.7~71.4dB(A) at its lowest level and the middle floors (3, 5, 7 and 10) were the highest distribution of noise level. From the analysis results on the application validity to an existing prediction formular (NIER(87, 99), TR-Noise, KLC(2002)) in the height 1.5m, the correction coefficients were 0.95~0.96 and the measured values were reasonably close to the predicted values, indicating the validity and adequacy of the predicted models. KLC(2002) model was found accurate within 3dB(A) with 36 data out of the total 42 data, showing the most accuracy among the predict models. However, the developed models have to improve the accuracy with a various of factors.

• The Journal of Society for e-Business Studies
• /
• v.15 no.3
• /
• pp.163-181
• /
• 2010

As a part of efforts to reduce the global emissions of greenhouse gases, the Kyoto Protocol was signed by major developed countries ("Annex I" countries). According to the Kyoto protocol, the Emission Trading Scheme that derives a trading market of the $CO_2$ emission rights is appeared. It causes that business institutions give lots of efforts to reduce $CO_2$ by using new environmentally sound technologies or increasing efficiency in production. On the while there have been several studies trying to develop a methodology to measure the effect of $CO_2$ reduction and its monetary value. In this research we suggest ECRE (Evaluation of $CO_2$ Reduction in E-transformation) model which can measure the $CO_2$ reduction effect through the introduction of G2B system. ECRC model was developed based on the IPCC methodology. ECRC model measures the two major effects of the $CO_2$ reduction which are '$CO_2$ reduction effect from transportation' and '$CO_2$ reduction effect from the decrease of paper use'. In this paper, we calculate the economic effect of $CO_2$ reduction with the case of the G2B system in Korea. This research suggests a basic methodology to measure the $CO_2$ reduction performance for the e-transformed institution.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.12
• /
• pp.11-19
• /
• 2013

This paper proposes an algorithm using vibration signals and texture analysis for mechanical fault diagnosis of an induction motor. We analyze characteristics of contrast and pattern of an image converted from vibration signal and extract three texture features using gray-level co-occurrence model(GLCM). Then, the extracted features are used as inputs of a multi-level support vector machine(MLSVM) which utilizes the radial basis function(RBF) kernel function to classify each fault type. In addition, we evaluate the classification performance with varying the parameter from 0.3 to 1.0 for the RBF kernel function of MLSVM, and the proposed algorithm achieved 100% classification accuracy with the parameter of the RBF from 0.3 to 1.0. Moreover, the proposed algorithm achieved about 98% classification accuracy with 15dB and 20dB noise inserted vibration signals.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.2
• /
• pp.385-394
• /
• 2021

In this paper, a new equation of electromagnetic wave transmission matrix was proposed to calculate the reflected power and transmitted power for the multi-layered planar lossy structure. The applied human leg was modeled as a four-layer planar structure of skin, fat, muscle and bone. The complex dielectric constant to consider the loss of each of these layers was calculated using the 4-pole cole-cole model parameter. When electromagnetic waves were incident on the skin surface, total reflected and transmitted power, and human body loss were calculated for a frequency band of 0.1 to 20.0 GHz. And for various muscle thicknesses, the power reflected only from the outermost bone and re-radiated from the skin was calculated. It was confirmed that at the muscle thickness of 3.0 mm and the frequency of 4.6 GHz the return loss was -6.13 dB, which was 3.42 dB lower than the average value.

• Communications for Statistical Applications and Methods
• /
• v.3 no.3
• /
• pp.187-194
• /
• 1996

We treat the problem of estimating reliability R = P[Y < X] in the stress-strength model in which a unit of strength X is subfected to enviromental stress Y./ In this paper several nonparametric approaches to estimation of R are analyzed and compared by simulations.

• The KIPS Transactions:PartB
• /
• v.19B no.3
• /
• pp.177-182
• /
• 2012

We propose effective motion and observation models for the position of a WiFi-equipped smartphone user in large indoor environments. Three component motion models provide better proposal distribution of the pedestrian's motion. Our Gaussian interpolation-based observation model can generate likelihoods at locations for which no calibration data is available. These models being incorporated into the particle filter framework, our WiFi fingerprint-based localization algorithm can track the position of a smartphone user accurately in large indoor environments. Experiments carried with an Android smartphone in a multi-story building illustrate the performance of our WiFi localization algorithm.