• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.176-183
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• 1995

Mean opinion score (MOS) method has been used in many areas to quantify opinions of respondents not only in survey research but in evaluating the parameters of population that are not measurable of are technically hard to be measured. Histogram is an important graphical technique because of the role it plays in describing categorical data as well as quantitative. In MOS method, subjective opinions of respondents are quantified by opinion scores and the arithmetic means of opinion scores have been used to describe the interesting population. Since opinion scores are polytomous, the values of arithmetic means have little meanings. In this paper, cumulative percentage curves as a function of the means of opinion scores are derived by combining means of opinion scores and histograms. It is proposed for better interpretation to opinion scores in MOS method, one of subjective evaluation methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• Restorative Dentistry and Endodontics
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• v.2 no.1
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• pp.15-19
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• 1976

The author studied on the transfer of radioactive fluorine ($^{18}F$) to dental hard tissue through animal experiments which was divided into two groups. First group of rats were sacrified 1, 2, 5, 10 and 20 minutes after intraperitoneal injection. Second group were sacrified 1 and 3 minutes after topical application on anterior teeth. The teeth were removed and sectioned by means of abrasive wheel and polished on india stone as thick as about 50 microns. Autoradiograph picture was made by close contact of high-speed dental X-ray film on prepared specimen for 2 hours. The results of this study were as follows; 1) There was no evidence of transfer of $^{18}F$ on dental hard tissue on the cases of 1, 2 and 5 minutes survival after intraperitoneal injection. 2) Radioactive sodium fluorine incorporated to dental hard tissue was slight and diffuse at 10 minutes cases and significant incorporated picture was noticed at 20 minutes cases in intraperitoneal injection. 3) On topical application groups incorporated $^{18}F$ to enamel was traced clearly only on enamel surface at 1 minute cases and significant transfer into whole enamel was found at 3 minutes cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.203-210
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• 2017

Data clustering is one of the most difficult and challenging problems and can be formally considered as a particular kind of NP-hard grouping problems. The K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, it has high possibility to trap in local optimum and high variation of solutions with different initials for the large data set. Therefore, we need study efficient computational intelligence method to find the global optimal solution in data clustering problem within limited computational time. The objective of this paper is to propose a combined artificial bee colony (CABC) with K-means for initialization and finalization to find optimal solution that is effective on data clustering optimization problem. The artificial bee colony (ABC) is an algorithm motivated by the intelligent behavior exhibited by honeybees when searching for food. The performance of ABC is better than or similar to other population-based algorithms with the added advantage of employing fewer control parameters. Our proposed CABC method is able to provide near optimal solution within reasonable time to balance the converged and diversified searches. In this paper, the experiment and analysis of clustering problems demonstrate that CABC is a competitive approach comparing to previous partitioning approaches in satisfactory results with respect to solution quality. We validate the performance of CABC using Iris, Wine, Glass, Vowel, and Cloud UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KABCK (K-means+ABC+K-means) is better than ABCK (ABC+K-means), KABC (K-means+ABC), ABC, and K-means in our simulations.

• The korean journal of orthodontics
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• v.35 no.3 s.110
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• pp.163-173
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• 2005

The purpose of this study was to compare the asymmetric degree between maxillofacial hard and soft tissues in individuals with facial asymmetry. Computerized tomographies (CT) of 34 adults (17 male, 17 female) who had facial asymmetry were taken. The CT images were transmitted to personal computers and then reconstructed into three-dimensional (3D) images through the use of computer software. In order to evaluate the degree of facial asymmetry, 6 measurements were constructed as the hard tissue measurements while 6 counterpart measurements were taken as the soft tissue measurements. The means and standard deviations were obtained for each measurement using 3D measure, then t-test was used to investigate the differences between each hard tissue measurement and the corresponding soft tissue measurement All measurements used in the present study showed statistically significant differences between the hard and soft tissues. The degree of soft tissue asymmetry was smaller than that of corresponding hard tissue asymmetry in case of chin deviation, frontal ramal inclination difference, and frontal corpus inclination difference. On the other hand, the degree of soft tissue asymmetry was greater than that of underlying hard tissue asymmetry in the measurement of lip canting and lip cheilion height difference The present study suggests that asymmetric differences of hard and soft tissue is observed nu facial asymmetric subjects and thus soft tissue analysis is needed in addition to hard tissue analysis when making an evaluation of facial asymmetry.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1183-1192
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• 2000

This paper relates to the flexural vibration analysis of the hard disk drive (HDD) spindle systems by means of the finite element method. In contrast to previous researches, every system componebt is here analytically modeled taking into account its flexibility and also the centrifugal effect particularly for the disk. To prove the effectiveness and accuracy of the proposed method, commercial HDD spindle systems with two and three identical disks are chosen as examples. Then, their major flexural natural modes are computed employing only a small number of element meshes as the shaft rotaional speed is varied, and compared with the bumerical or experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.3
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• pp.107-114
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• 2001

The durability of head/disk interface is an important issue for hard disk drives. Currently, there are several means of assessing the performance and integrity of the head/disk interface. In this work Track Average Amplitude(TAA) signal was used to analyzed the head/disk interface with respect to variations in disk velocity, slider pre-load and preformed scratch on the disk. Particularly, TAA variation due to disk defect in the form of a scratch was investigated.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.549-556
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• 2005

A hard-type centroids in the conventional clustering algorithm such as k-modes algorithm cannot keep the uncertainty inherently in data sets as long as possible before actual clustering(decision) are made. Therefore, we propose the k-populations algorithm to extend clustering ability and to heed the data characteristics. This k-population algorithm as found to give markedly better clustering results through various experiments.

• The Journal of Korean Academy of Prosthodontics
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• v.41 no.4
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• pp.493-502
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• 2003

Statement of problem : Removable partial denture and complete denture often require denture base relines to improve the fittness against tissue-bearing mucosa because of the gradual change in edentulous ridge contour and resorption of underlyng bony structure. Self-curing hard reline resins offers the immediate and relatively inexpensive means to be recondition the surface of denture base directly However weak bond between denture base resin and reline material can harbor bacteria, promote staining, or result in complete separation of the two materials. Purpose : The purpose of this study was to evaluate the effect of denture cleansers on bond strength and surface hardness of reline resin to denture base resin Denture base resin beams($60.0{\times}15.0{\times}3.0mm$) were made with Lucitone 199. Material and methods : 10mm section was removed from the center of each specimen. The samples were replaced in the molds and the space of l0mm sections were packed with Tokuso Rebase reline material. The specimens were immersed in denture cleansers (Polident, Cleadent) and were evaluated after 1 week, 2 weeks, and 4 weeks. The bond strength and surface hardness of self-curing hard reline materials to heat-curing denture base resin were measured using an UTM (universal testing machine). Results and conclusion : 1) There was no significant difference of usage, kind, and denture cleaner by application time on the bonding strength of self-curing hard reline resin to denture base resin. 2) There was no significant difference of usage, kind, and denture cleaner by application time on the surface hardness, but the surface hardness showed decreasing tendency, as the time of immersion was extended. 3) The failure modes of the specimens was initially adhesive failure and finally cohesive failure of self-curing hard reline resin.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2885-2887
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• 2005

We introduce a hybrid identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of HCM clustering help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the GAs and the least square method. Numerical example is included to evaluate the performance of the proposed model.