• 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.

• Corrosion Science and Technology
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• v.16 no.1
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• pp.1-7
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• 2017

When aiming for an increased and more sustainable use of metals a thorough knowledge of the corrosion phenomenon as function of the local metal microstructure is of crucial importance. In this work, we summarize the information presented in our previous publications[1-3] and present an overview of the different local (electrochemical) techniques that have been proven to be effective in studying the relation between different microstructural variables and their different electrochemical behavior. Atomic force microscopy (AFM)[1], scanning electrochemical microscopy (SECM)[2], and electrochemical scanning tunneling microscopy (EC-STM)[3] were used in combination with electron backscatter diffraction (EBSD). Consequently, correlations could be identified between the grain orientation and grain boundary characteristics, on the one hand, and the electrochemical behavior on the other hand. The grain orientation itself has an influence on the corrosion, and the orientation of the neighboring grains also seems to play a decisive role in the dissolution rate. With respect to intergranular corrosion, only coherent twin boundaries seem to be resistant.

• Safety and Health at Work
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• v.11 no.1
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• pp.61-70
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• 2020

Background: This study aims to assess whether the TSI PortaCount (Model 8020) is a measuring instrument comparable with the flame photometer. This would provide an indication for the suitability of the PortaCount for determining the workplace protection factor for particulate filtering facepiece respirators. Methods: The PortaCount (with and without the N95-Companion^TM) was compared with a stationary flame photometer from Moores (Wallisdown) Ltd (Type 1100), which is a measuring instrument used in the procedure for determining the total inward leakage of the particulate filtering facepiece respirator in the European Standard. Penetration levels of sodium chloride aerosol through sample respirators of two brands (A and B) were determined by the two measuring systems under laboratory conditions. For each brand, thirty-six measurements were conducted. The samples were split into groups according to their protection level, conditioning before testing, and aerosol concentration. The relationship between the gauged data from two measuring systems was determined. In addition, the particle size distribution inside the respirator and outside the respirator was documented. Linear regression analysis was used to calculate the association between the PortaCount (with and without the N95-Companion^TM) and the flame photometer. Results: A linear relationship was found between the raw data scaled with the PortaCount (without N95-Companion^TM) and the data detected by the flame photometer (R² = 0.9704) under all test conditions. The distribution of particle size was found to be the same inside and outside the respirator in almost all cases. Conclusion: Based on the obtained data, the PortaCount may be applicable for the determination of workplace protection factor.

• The Journal of Korean Obstetrics and Gynecology
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• v.15 no.4
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• pp.136-148
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• 2002

This study was performed to investigate the relation between Iridological constitution and Gynecological disease. Iris is one of the most complicated part of our bodies. It reflects perfectly organ's status, toxic accumulation, person's characteristics and healing effects. Many signs of Iridology were closely researched to examine the relation between Iridology and disease. After studying these matters, we could find that lacuna and auto-nerve wreath are intimately related. Especially the portions of auto-nerve wreath loss are accorded with the organ's present illness. Most of patients have scurf ring and vessel congestion sign. Large Intestine's structure also shows us the meaningful result that ballooned is the most common, spasticity and stricture are next. Connective tissue weakness constitution is 39.22%, complex 35.29% and blood-originated 25.49%. According to the three-step constitution by the Genetic facter, average type is 52.94%, weak type 35.29% and strong type 11.76%. Above these results, we can reach a conclusion that Iridological constitution are intimately related with Gynecological disease. And further study are requested to get a objectivity in a Gynecological diagnose. Iridology is a bright prospective study and interesting diagnostic method. If we deeply investigate this science, before long we can have a great outcome and more objective diagnostic skill.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.1-8
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• 2007

The images, which were acquired from various systems such as CCTV and Robot, include many human faces. Because of a rapid increase in visual data, we cannot process these manually; rather we need to do these automatically. Furthermore, companies require automatic security systems to protect their new technology. There are various options available to us, including face recognition, iris recognition and fingerprint recognition. Face recognition is preferable since it does not require direct contact. However, the standard 2-Dimensional method is limited, so Morphable Models may be recommended as an alternative. The original morphable model, made by MPI, contains a large quantity of data such as texture and geometry data. This paper presents a Geometrix-based morphable model designed to reduce this data capacity.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.692-702
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• 2006

In this study, a weighted fuzzy min-max (WFMM) neural network model for pattern classification is proposed. The model has a modified structure of FMM neural network in which the weight concept is added to represent the frequency factor of feature values in a learning data set. First we present in this paper a new activation function of the network which is defined as a hyperbox membership function. Then we introduce a new learning algorithm for the model that consists of three kinds of processes: hyperbox creation/expansion, hyperbox overlap test, and hyperbox contraction. A weight adaptation rule considering the frequency factors is defined for the learning process. Finally we describe a feature analysis technique using the proposed model. Four kinds of relevance factors among feature values, feature types, hyperboxes and patterns classes are proposed to analyze relative importance of each feature in a given problem. Two types of practical applications, Fisher's Iris data and Cleveland medical data, have been used for the experiments. Through the experimental results, the effectiveness of the proposed method is discussed.

• Korean Journal of Plant Taxonomy
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• v.41 no.4
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• pp.370-382
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• 2011

We investigated the area around four moors from May 2009 to June 2010 for plant diversity in Moojechineup, officially designated as the Ramsar wetland. The vascular plants of Moojechineup at Mt. Jeongjok were recorded as total 149 taxa, 55 families, 105 genera, 128 species, 1 subspecies, 16 varieties, and 4 forms. Rare plants were observed 7 taxa (Eriophorum gracile Koch, Drosera rotundifolia L., Iris ensata var. spontanea (Makino) Nakai, Kobresia bellardii (All.) Degl, Utricularia bifida L., Utricularia racemosa Wall., Utricularia yakusimensis Masam.). Korean endemic plants were 1 taxon, floristics special plants were 19 taxa, and naturalized plants were 3 taxa. Phytogeographical and evolutionarily, Eriophorum gracile is an important species; hence, further studies are needed to conserve it. Moojechineup is similar to the Shinbulsan wetland in terms of wetland plants (hydrophytes). Moojechineup's flora changes are in process slowly compared to earlier work; thus, continuing interest and appropriate measures should be encouraged.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.563-571
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• 2017

The purpose of this paper is to establish an emotional expression factors of digital eye contents that can be applied to digital environments. The emotion which can be applied to the smart doll is derived and we suggest guidelines for expressive factors of each emotion. For this paper, first, we research the concepts and characteristics of emotional expression are shown in eyes by the publications, animation and actual video. Second, we identified six emotions -Happy, Angry, Sad, Relaxed, Sexy, Pure- and extracted the emotional expression factors. Third, we analyzed the extracted factors to establish guideline for emotional expression of digital eyes. As a result, this study found that the factors to distinguish and represent each emotion are classified four categories as eye shape, gaze, iris size and effect. These can be used as a way to enhance emotional communication effects such as digital contents including animations, robots and smart toys.

• Korean Journal of Environment and Ecology
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• v.18 no.2
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• pp.107-123
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• 2004

The vascular plants of Mt. Deog-yu area in the Baekdudaegan were recorded as 411 taxa; 91 families, 243 genera, 353 species, 53 varieties and 5 forma. From the floristic point of view, the Baekdudaegan, a main mountain range of the Korean peninsula, in the region of Mt. Deog-yu, belongs to the southern province in Korea, as the species like Cephalotaxus koreana, Lindera obtusiloba, Ilex macropoda and Stewartia koreana. are ranged in this region. But the species of the Northern element such as Betula costata, Betula ermani, Heloniopsis orientalis and Disporum ovale are also recorded in the region. Above the sea level from 1,000m, many sub alpine plant species are recorded. Rare and endangered plant species which are categorized by the Office of Forestry were 10 species such as Lilium cernum, Paeonia obovata, Abies koreana, Disporum ovale, Lilium distichum, Tricyrtis dilatata, Clematis chiisanensis, Bupleurum euphorbioides, Rhododendron schonoskii and Iris ensata var. spontanea. The protected plant species which are categorized by the Ministry of Environment were recorded only Lilium cernum. The Korean endemic plant species were recorded as 22 taxa; 12 families, 21 genera, 20 species 1 varieties, and 1 forma. Among them the plant species such as Cephalotaxus koreana, Abies koreana, Hosta capitata, Polygonatum lasianthum var. coreanum and Tricyrtis dilatata are representative ones in the region.

• 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.