• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2008.06a
• /
• pp.241-241
• /
• 2008

Macrofore formation in silicon and other semiconductors using electrochemical etching processes has been, in the last years, a subject of great attention of both theory and practice. Its first reason of concern is new areas of macropore silicone applications arising from microelectromechanical systems processing (MEMS), membrane techniques, solar cells, sensors, photonic crystals, and new technologies like a silicon-on-nothing (SON) technology. Its formation mechanism with a rich variety of controllable microstructures and their many potential applications have been studied extensively recently. Porous silicon is formed by anodic etching of crystalline silicon in hydrofluoric acid. During the etching process holes are required to enable the dissolution of the silicon anode. For p-type silicon, holes are the majority charge carriers, therefore porous silicon can be formed under the action of a positive bias on the silicon anode. For n-type silicon, holes to dissolve silicon is supplied by illuminating n-type silicon with above-band-gap light which allows sufficient generation of holes. To make a desired three-dimensional nano- or micro-structures, pre-structuring the masked surface in KOH solution to form a periodic array of etch pits before electrochemical etching. Due to enhanced electric field, the holes are efficiently collected at the pore tips for etching. The depletion of holes in the space charge region prevents silicon dissolution at the sidewalls, enabling anisotropic etching for the trenches. This is correct theoretical explanation for n-type Si etching. However, there are a few experimental repors in p-type silicon, while a number of theoretical models have been worked out to explain experimental dependence observed. To perform ordered macrofore formaion for p-type silicon, various kinds of mask patterns to make initial KOH etch pits were used. In order to understand the roles played by the kinds of etching solution in the formation of pillar arrays, we have undertaken a systematic study of the solvent effects in mixtures of HF, N-dimethylformamide (DMF), iso-propanol, and mixtures of HF with water on the macrofore structure formation on monocrystalline p-type silicon with a resistivity varying between 10 ~ 0.01 $\Omega$ cm. The etching solution including the iso-propanol produced a best three dimensional pillar structures. The experimental results are discussed on the base of Lehmann's comprehensive model based on SCR width.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.1
• /
• pp.19-30
• /
• 2014

For the expansion of the Semantic Web, studies in converting the data stored in the relational database into the ontology are actively in process. Such studies mainly use an RDB to RDF mapping model, the model to map relational database components to RDF components. However, pre-proposed mapping models have got different expression modes and these damage the accessibility and reusability of the users. As a consequence, the necessity of the standardized mapping language was raised and the W3C suggested the R2RML as the standard mapping language for the RDB to RDF model. The R2RML has a characteristic that converts only the relational database schema data to RDF. For the same reasons above, the ontology about the relation data between table name and column name of the relational database cannot be added. In this paper, we propose an RDB to RDF mapping system considering semantic relations of RDB components in order to solve the above issue. The proposed system generates the mapping data by adding the RDFS attribute data into the schema data defined by the R2RML in the relational database. This mapping data converts the data stored in the relational database into RDF which includes the RDFS attribute data. In this paper, we implement the proposed system as a Java-based prototype, perform the experiment which converts the data stored in the relational database into RDF for the comparison evaluation purpose and compare the results against D2RQ, RDBToOnto and Morph. The proposed system expresses semantic relations which has richer converted ontology than any other studies and shows the best performance in data conversion time.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.8
• /
• pp.507-516
• /
• 2013

Mobile devices have limited computing power and resources. Since mobile devices are equipped with rich network connectivity, an approach to subscribe cloud services can effectively remedy the problem, which is called Mobile Cloud Computing (MCC). Most works on MCC depend on a method to offload functional components at runtime. However, these works only consider the limited verion of offloading to a pre-defined, designated node. Moveover, there is the limitation of managing services subscribed by applications. To provide a comprehensive and practical solution for MCC, in this paper, we propose a self-stabilizing process and its management-related methods. The proposed process is based on an autonomic computing paradigm and works with diverse quality remedy actions such as migration or replicating services. And, we devise a pratical offloading mechanism which is still in an initial stage of the study. The proposed offloading mechanism is based on our proposed MCC meta-model. By adopting the self-stabilization process for MCC, many of the technical issues are effectively resolved, and mobile cloud environments can maintain consistent levels of quality in autonomous manner.

• Journal of Digital Contents Society
• /
• v.18 no.8
• /
• pp.1593-1601
• /
• 2017

In a big data platform, association rule mining applications could bring some benefits. For instance, in a agricultural big data platform, the association rule mining application could recommend specific products for farmers to grow, which could increase income. The key process of the association rule mining is the frequent itemsets mining, which finds sets of products accompanying together frequently. Former researches about this issue, e.g. Apriori, are not satisfying enough because huge possible sets can cause memory to be overloaded. In order to deal with it, SON algorithm has been proposed, which divides the considered set into many smaller ones and handles them sequently. But in a single machine, SON algorithm cause heavy time consuming. In this paper, we present a method to find association rules in our Hadoop based big data platform, by parallelling SON algorithm. The entire process of association rule mining including pre-processing, SON algorithm based frequent itemset mining, and association rule finding is implemented on Hadoop based big data platform. Through the experiment with real dataset, it is conformed that the proposed method outperforms a brute force method.

• Spatial Information Research
• /
• v.9 no.2
• /
• pp.291-307
• /
• 2001

In today's environmental engineering practice, many technologies such as GIS have been adopted to analyze chemical and biological process in water bodies and pollutants movements on the land surface. However, the linkage between spatially represented land surface pollutants and the in-stream processes has been relatively weak. This lack of continuity needs to develop a method in order to link the spatially-based pollutant source characterization with the water quality modeling. The objective of this thesis was to develop a two-way(forward and backward) link between ArcView GIS software and the USEPA water quality model, WASP5. This thesis includes a literature review, the determination of the point source and non-point source loadings from WASP5 modeling, and the linkage of a GIS with WASP5 model. The GIS and model linkage includes pre-processing of the input data within a GIS to provide necessary information for running a model in the forms of external input files. The model results has been post-processed and stored in the GIS database to be reviewed in a user defined form such as a chart, or a table. The interface developed from this study would provide efficient environment to support the easier decision making form water quality management.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.11
• /
• pp.66-72
• /
• 2014

Histogram of oriented gradient (HOG) feature is widely used in vision-based pedestrian detection. The interpolation is the most important technique in HOG feature calculation to provide high detection rate. In interpolation technique of HOG feature calculation, two nearest orientation bins to gradient orientation for each pixel and the corresponding weights are required. In this paper, therefore, an efficient gradient orientation bin and weight calculation circuit for HOG feature is proposed. In the proposed circuit, pre-calculated values are defined in tables to avoid the operations of tangent function and division, and the size of tables is minimized by utilizing the characteristics of tangent function and weights for each gradient orientation. Pipeline architecture is adopted to the proposed circuit to accelerate the processing speed, and orientation bins and the corresponding weights for each pixel are calculated in two clock cycles by applying efficient coarse and fine search schemes. Since the proposed circuit calculates gradient orientation for each pixel with the interval of $1^{\circ}$ and determines both orientation bins and weights required in interpolation technique, it can be utilized in HOG feature calculation to support interpolation technique to provide high detection rate.

• Korean Journal of Childcare and Education
• /
• v.10 no.6
• /
• pp.243-264
• /
• 2014

The present study examined the effects of science activities motivated through children's songs on young children's science-related attitudes, and understanding of science processing. skills. The subjects of the present study were 40 children aged five, among them 20 children being assigned into an experimental group, and 20 children into a control group. An Hyun-Jeong's(2011). 'The Test of Science-Related Attitudes' and science process skills measurement questions from 'The Science Learning Assessment' by Samarapungavan, Mantzicopoulos, Patrick, and French (2009) were used after adapting them as research tools. The experimental group performed science activities motivated through children's songs 21 times, 3 times a week for 7 weeks; learning children's songs and asking science questions at the first stage, performing science activities at the second stage, and adapting children's songs based on the findings of science activities. The control group performed the learning of children's songs, science activities, and rhythmic activities in the same period. The pre- and post-test data were analyzed as at-test using SPSS program. The study results indicated that science activities motivated through children's songs were effective in improving young children's science-related attitudes and their understanding of science process skills.

• Journal of Korea Water Resources Association
• /
• v.41 no.3
• /
• pp.293-303
• /
• 2008

Reservoir turbidity flows degrade the efficiency and sustainability of water supply system in many countries located in monsoon climate region. A decision support system called RTMMS aimed to assist reservoir operations was developed for the real time monitoring, modeling, and management of turbidity flows induced by flood runoffs in Daecheong reservoir. RTMMS consists of a real time data acquisition module that collects and stores field monitoring data, a data assimilation module that assists pre-processing of model input data, a two dimensional numerical model for the simulation of reservoir hydrodynamics and turbidity, and a post-processor that aids the analysis of simulation results and alternative management scenarios. RTMMS was calibrated using field data obtained during the flood season of 2004, and applied to real-time simulations of flood events occurred on July of 2006 for assessing its predictive capability. The system showed fairly satisfactory performance in reproducing the density flow regimes and fate of turbidity plumes in the reservoir with efficient computation time that is a vital requirement for a real time application. The configurations of RTMMS suggested in this study can be adopted in many reservoirs that have similar turbidity issues for better management of water supply utilities and downstream aquatic ecosystem.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.12C
• /
• pp.1029-1038
• /
• 2008

In this paper, we propose a method for an arbitrary-view image generation in multi-view video and methods for pre- and post-processing to compensate unattended regions in the generated image. To generate an arbitrary-view image, camera geometry is used. Three dimensional coordinates of image pixels can be obtained by using depth information of multi-view video and parameter information of multi-view cameras, and by replacing three dimensional coordinates on a two dimensional image plane of other view, arbitrary-view image can be reconstructed. However, the generated arbitrary-view image contains many unattended regions. In this paper, we also proposed a method for compensating these regions considering temporal redundancy and spatial direction of an image and an error of acquired multi-view image and depth information. Test results show that we could obtain a reliably synthesized view-image with objective measurement of PSNR more than 30dB and subjective estimation of DSCQS(double stimulus continuous quality scale method) more than 3.5 point.

• Journal of KIISE:Databases
• /
• v.30 no.5
• /
• pp.438-450
• /
• 2003

Spatial joins find pairs of objects that overlap with each other. In spatial joins using indexes, original-space indexes such as the R-tree are widely used. An original-space index is the one that indexes objects as represented in the original space. Since original-space indexes deal with sizes of objects, it is difficult to develop a formal algorithm without relying on heuristics. On the other hand, transform-space indexes, which transform objects in the original space into points in the transform space and index them, deal only with points but no sites. Thus, spatial join algorithms using these indexes are relatively simple and can be formally developed. However, the disadvantage of transform-space join algorithms is that they cannot be applied to original-space indexes such as the R-tree containing original-space objects. In this paper, we present a novel mechanism for achieving the best of these two types of algorithms. Specifically, we propose a new notion of the transform-space view and present the transform-space view join algorithm(TSVJ). A transform-space view is a virtual transform-space index based on an original-space index. It allows us to interpret on-the-fly a pre-built original-space index as a transform-space index without incurring any overhead and without actually modifying the structure of the original-space index or changing object representation. The experimental result shows that, compared to existing spatial join algorithms that use R-trees in the original space, the TSVJ improves the number of disk accesses by up to 43.1% The most important contribution of this paper is to show that we can use original-space indexes, such as the R-tree, in the transform space by interpreting them through the notion of the transform-space view. We believe that this new notion provides a framework for developing various new spatial query processing algorithms in the transform space.