• Journal of Dental Rehabilitation and Applied Science
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• v.36 no.2
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• pp.61-69
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• 2020

Purpose: Zirconia fixed partial dentures with mandibular 2^nd premolar and 2^nd molar as abutments are fabricated and then the effects of inter-abutment distance on fracture resistance of zirconia fixed partial dentures is studied. Materials and Methods: The materials used in this study are Cameleon S zirconia block and S2 zirconia block, which are divided into CS Group and S2 Group applying different inter-abutment distance for each material, and the sintered zirconia fixed partial denture was luted to the epoxy resin die using a temporary luting cement, and then the fracture resistance was measured by placing a 6 mm diameter hardened steel ball on the occlusal surfaces of the pontics and applying pressure at a cross head speed of 1.0 mm/min on a universal testing machine with a load cell of 5.0 kN. Results: The fracture resistance of zirconia fixed partial dentures is not significantly affected by inter-abutment distance The fracture resistance of zirconia fixed partial dentures in CS Group was significantly higher in 15 mm of inter-abutment distance than in 13 mm and 17 mm of inter-abutment distance (P < 0.05). The fracture resistance of zirconia fixed partial dentures in S2 Group was not significantly different between the three groups (P > 0.05). Conclusion: The fracture resistance of zirconia fixed partial dentures with mandibular 2^nd premolar and 2^nd molar as abutments does not significantly affected by the inter-abutment distance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.164-170
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• 2017

The CNC machine tool field is showing a growing trend with the recent rapid development of manufacturing industries such as semiconductors, automobiles, medical devices, various inspection and test equipment, mechanical metal processing equipment, aircraft, shipbuilding and electronic equipment. However, small and medium-sized machining companies that use CNC machine tools are experiencing difficulties in increasingly intense competition. Especially, small companies which are receiving orders from 3rd or 4th venders are very difficult in business management. In recent years, company S experienced difficulty to make product quality and delivery time due to the ignorance of the processing method when manufacturing cooling plate jig made of SUS304 material used for cell phone liquid crystal glass processing. In order to solve these problems, we redesigned the process according to the size of our company and tried to manage all processes with quantified data. In the meantime, we have found that there is a need to improve the cutter process, which accounts for most of the machining process. Therefore, we have investigated the correlation between RPM and FEED of three cutters that have been used in the past. As a result, we found that it is the most urgent problem to solve the roughing process during the cutter operation which occupies more than 70% of the total machining. In order to shorten the machining time and improve the quality in machining of SUS304 cooling plate jig, we select the main factors such as price, tool life, maintenance cost, productivity, quality, RPM, and FEED and use AHP to find the most suitable milling cutter. We also tried to solve the problem of delivery, quality and production capacity which was a big problem of S company through experiment operation with selected cutter tool. As a result, the following conclusions were drawn. First, the most efficient of the three cutters currently available in the machining center has proven to be an M-cutter. Second, although one additional facility was required, it was possible to produce the existing facilities without additional investment by supplementing the lack of production capacity due to productivity improvement. Third, the Company's difficulties in delivery and capacity shortfalls have been resolved. Fourth, annual sales increased by KRW 109 million and profits increased by KRW 32 million annually. Fifth, it can confirm the usefulness of AHP method in corporate decision making and it can be utilized in various facility investment and process improvement in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Korean Journal of Materials Research
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• v.20 no.11
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• pp.617-622
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• 2010

We have studied methods to save Si source during the fabrication process of crystalline Si solar cells. One way is to use a thin silicon wafer substrate. As the thickness of the wafers is reduced, mechanical fractures of the substrate increase with the mechanical handling of the thin wafers. It is expected that the mechanical fractures lead to a dropping of yield in the solar cell process. In this study, the mechanical properties of 220-micrometer-solar grade Cz p-type monocrystalline Si wafers were investigated by varying saw-damage etching conditions in order to improve the flexural strength of ultra-thin monocrystalline Si solar cells. Potassium hydroxide (KOH) solution and tetramethyl ammonium hydroxide (TMAH) solution were used as etching solutions. Etching processes were operated with a varying of the ratio of KOH and TMAH solutions in different temperature conditions. After saw-damage etching, wafers were cleaned with a modified RCA cleaning method for ten minutes. Each sample was divided into 42 pieces using an automatic dicing saw machine. The surface morphologies were investigated by scanning electron microscopy and 3D optical microscopy. The thickness distribution was measured by micrometer. The strength distribution was measured with a 4-point-bending tester. As a result, TMAH solution at $90^{\circ}C$ showed the best performance for flexural strength.

• Journal of Astronomy and Space Sciences
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• v.27 no.2
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• pp.153-160
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• 2010

We modified the optical system of 500 mm wide-field telescope of which point spread function showed an irregularity. The telescope has been operated for Near Earth Space Survey (NESS) located at Siding Spring Observatory (SSO) in Australia, and the optical system was brought back to Korea in January 2008. After performing a numerical simulation with the tested value of surface figure error of the primary mirror using optical design program, we found that the surface figure error of the mirror should be fabricated less than root mean square (RMS) $\lambda$/10 in order to obtain a stellar full width at half maximum (FWHM) below $28\;{\mu}m$. However, we started to figure the mirror for the target value of RMS $\lambda$/20, because system surface figure error would be increased by the error induced by the optical axis adjustment, mirror cell installation, and others. The radius of curvature of the primary mirror was 1,946 mm after the correction. Its measured surface figure error was less than RMS $\lambda$/20 on the table of polishing machine, and RMS $\lambda$/15 after installation in the primary mirror cell. A test observation performed at Daeduk Observatory at Korea Astronomy and Space Science Institute by utilizing the exiting mount, and resulted in $39.8\;{\mu}m$ of stellar FWHM. It was larger than the value from numerical simulation, and showed wing-shaped stellar image. It turned out that the measured-curvature of the secondary mirror, 1,820 mm, was not the same as the designed one, 1,795.977 mm. We fabricated the secondary mirror to the designed value, and finally obtained a stellar FWHM of $27\;{\mu}m$ after re-installation of the optical system into SSO NESS Observatory in Australia.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.6
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• pp.493-498
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• 2016

In the present study, graphene oxide based polyurethane foams were manufactured as a part of the development process of mechanically strengthened polyurethane foam insulation material. This material is used in a liquefied natural gas carrier cargo containment system. The temperature of the containment system is $-163^{\circ}C$. First, graphene oxide was synthesized using the Hummers' method, and it was supplemented into polyol-isocyanate reagent by considering a different amount of graphene oxide weight percent. Then, a bulk form of graphene-oxide-polyurethane foam was manufactured. In order to investigate the cell stability of the graphene-oxide-polyurethane foam, its microstructural morphology was observed, and the effect of graphene oxide on microstructure of the polyurethane foam was investigated. In addition, the compressive strength of graphene-oxide-polyurethane foam was measured at ambient and cryogenic temperatures. The cryogenic tests were conducted in a cryogenic chamber equipped with universal testing machine to investigate mechanical and failure characteristics of the graphene-oxide-polyurethane foam. The results revealed that the additions of graphene oxide enhanced the mechanical characteristics of polyurethane foam. However, cell stability and mechanical strength of graphene-oxide-polyurethane foam decreased as the weight percent of graphene oxide was increased.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.197-207
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• 2010

Using a variety of data-mining methods on high-throughput cDNA microarray data, the level of gene expression in two different tissues can be compared, and DEG(Differentially Expressed Gene) genes in between normal cell and tumor cell can be detected. Diagnosis can be made with these genes, and also treatment strategy can be determined according to the cancer stages. Existing cancer classification methods using machine learning select the marker genes which are differential expressed in normal and tumor samples, and build a classifier using those marker genes. However, in addition to the differences in gene expression levels, the difference in gene-gene correlations between two conditions could be a good marker in disease diagnosis. In this study, we identify gene pairs with a big correlation difference in two sets of samples, build gene classification modules using these gene pairs. This cancer classification method using gene modules achieves higher accuracy than current methods. The implementing clinical kit can be considered since the number of genes in classification module is small. For future study, Authors plan to identify novel cancer-related genes with functionality analysis on the genes in a classification module through GO(Gene Ontology) enrichment validation, and to extend the classification module into gene regulatory networks.

• Archives of Plastic Surgery
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• v.38 no.4
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• pp.438-444
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• 2011

Purpose: Adipose-derived stromal cells (ASCs) are readily harvested from lipoaspirated tissue or subcutaneous adipose tissue fragments. The stromal vascular fraction (SVF) is a heterogeneous set of cell populations that surround and support adipose tissue, which includes the stromal cells, ASCs, that have the ability to differentiate into cells of several lineages and contains cells from the microvasculature. The mechanisms that drive the ASCs into the osteoblast lineage are still not clear, but the process has been more extensively studied in bone marrow stromal cells. The purpose of this study was to investigate the osteogenic capacity of adipose derived SVF cells and evaluate bone formation following implantation of SVF cells into the bone defect of human phalanx. Methods: Case 1 a 43-year-old male was wounded while using a press machine. After first operation, segmental bone defects of the left 3rd and 4th middle phalanx occurred. At first we injected the SVF cells combined with demineralized bone matrix (DBM) to defected 4th middle phalangeal bone lesion. We used P (L/DL)LA [Poly (70L-lactide-co-30DL-lactide) Co Polymer P (L/DL)LA] as a scaffold. Next, we implanted the SVF cells combined with DBM to repair left 3rd middle phalangeal bone defect in sequence. Case 2 was a 25-year-old man with crushing hand injury. Three months after the previous surgery, we implanted the SVF cells combined with DBM to restore right 3rd middle phalangeal bone defect by syringe injection. Radiographic images were taken at follow-up hospital visits and evaluated radiographically by means of computerized analysis of digital images. Results: The phalangeal bone defect was treated with autologous SVF cells isolated and applied in a single operative procedure in combination with DBM. The SVF cells were supported in place with mechanical fixation with a resorbable macroporous sheets acting as a soft tissue barrier. The radiographic appearance of the defect revealed a restoration to average bone density and stable position of pharyngeal bone. Densitometric evaluations for digital X-ray revealed improved bone densities in two cases with pharyngeal bone defects, that is, 65.2% for 4th finger of the case 1, 60.5% for 3rd finger of the case 1 and 60.1% for the case 2. Conclusion: This study demonstrated that adipose derived stromal vascular fraction cells have osteogenic potential in two clinical case studies. Thus, these reports show that cells from the SVF cells have potential in many areas of clinical cell therapy and regenerative medicine, albeit a lot of work is yet to be done.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1273-1281
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• 2014

Tissue engineering is an emerging research field that has the potential to restore, regenerate and repair damaged bone tissue and organs. Tricalcium phosphate and hydroxyapatite biomaterials-based calcium phosphate are excellent materials that have both osteoconduction and biocompatibility for bone tissue regeneration. In this study, solution structures were successfully fabricated using a fused deposition modeling system based on deposition and heating devices. The morphology characteristics of the bioceramic scaffolds sintered at a temperature of $1,300^{\circ}C$ were analyzed by scanning electron microscopy. The effects of various blended TCP/HA ratio on the microstructure and shrinkage were studied. The mechanical properties of the scaffolds were measured using a compression testing machine from stress-strain curves on the crosshead velocity of 1 mm/min. The fabricated scaffolds were evaluated by cell proliferation tests of MG-63 cells. The results of this study suggest that the blended TCP(75 wt%)/HA(25 wt%) scaffold is an appropriate scaffold for bone tissue regeneration.