• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.77-88
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• 2017

Recently, with the advent of knowledge based society where information and knowledge make values, patents which are the representative form of intellectual property have become important, and the number of the patents follows growing trends. Thus, it needs to classify the patents depending on the technological topic of the invention appropriately in order to use a vast amount of the patent information effectively. IPC (International Patent Classification) is widely used for this situation. Researches about IPC automatic classification have been studied using data mining and machine learning algorithms to improve current IPC classification task which categorizes patent documents by hand. However, most of the previous researches have focused on applying various existing machine learning methods to the patent documents rather than considering on the characteristics of the data or the structure of patent documents. In this paper, therefore, we propose to use two structural fields, technical field and background, considered as having impacts on the patent classification, where the two field are selected by applying of the characteristics of patent documents and the role of the structural fields. We also construct multi-label classification model to reflect what a patent document could have multiple IPCs. Furthermore, we propose a method to classify patent documents at the IPC subclass level comprised of 630 categories so that we investigate the possibility of applying the IPC multi-label classification model into the real field. The effect of structural fields of patent documents are examined using 564,793 registered patents in Korea, and 87.2% precision is obtained in the case of using title, abstract, claims, technical field and background. From this sequence, we verify that the technical field and background have an important role in improving the precision of IPC multi-label classification in IPC subclass level.

• The Journal of Korean Academy of Prosthodontics
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• v.48 no.4
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• pp.294-300
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• 2010

Purpose: The template-guided implant surgery offers several advantages over the traditional approach. The purpose of this study was to evaluate the accuracy of coordinate synchronization procedure with 5-axis milling machine for surgical template fabrication by means of reverse engineering through universal CAD software. Materials and methods: The study was performed on ten edentulous models with imbedded gutta percha stoppings which were hidden under silicon gingival form. The platform for synchordination was formed on the bottom side of models and these casts were imaged in Cone beam CT. Vectors of stoppings were extracted and transferred to those of planned implant on virtual planning software. Depth of milling process was set to the level of one half of stoppings and the coordinate of the data was synchronized to the model image. Synchronization of milling coordinate was done by the conversion process for the platform for the synchordination located on the bottom of the model. The models were fixed on the synchordination plate of 5-axis milling machine and drilling was done as the planned vector and depth based on the synchronized data with twist drill of the same diameter as GP stopping. For the 3D rendering and image merging, the impression tray was set on the conbeam CT and pre- and post- CT acquiring was done with the model fixed on the impression body. The accuracy analysis was done with Solidworks (Dassault systems, Concord, USA) by measuring vector of stopping’s top and bottom centers of experimental model through merging and reverse engineering the planned and post-drilling CT image. Correlations among the parameters were tested by means of Pearson correlation coefficient and calculated with SPSS (release 14.0, SPSS Inc. Chicago, USA) ($\alpha$ = 0.05). Results: Due to the declination, GP remnant on upper half of stoppings was observed for every drilled bores. The deviation between planned image and drilled bore that was reverse engineered was 0.31 (0.15 - 0.42) mm at the entrance, 0.36 (0.24 - 0.51) mm at the apex, and angular deviation was 1.62 (0.54 - 2.27)$^{\circ}$. There was positive correlation between the deviation at the entrance and that at the apex (Pearson Correlation Coefficient = 0.904, P = .013). Conclusion: The coordinate synchronization 5-axis milling procedure has adequate accuracy for the production of the guided surgical template.

• Korean Journal of Agricultural Science
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• v.8 no.1
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• pp.90-96
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• 1981

To design more efficient agricultural machinery, the accurately measuring system among many other factors is essential. A light-beam oscillographic recorder is generally used in measuring dynamic strain but it is not compatible with the extremely high speed measuring system such as 1,000 m/s, also is susceptable to damage due to vibration while using the system in field. The recorder used light sensitive paper for strip chart recording. The reading and analysis of data from the strip charts is very cumbersome, errorneous and time consuming. A microcomputer was interfaced with A/D converter, microcomputer program was developed for measuring, system calibration was done and the strain generated from a cantilever beam vibrator was measured. The results are summarized as follows. 1. Microcomputer program was developed to perform strain measuring of agricultural machine elements and could be controled freely the measuring intervals, no. of channels and no. of data. The maximum measuring speed was $62{\mu}s$. 2. Calibration the system was performed with triangle wave generated from a function generator and checked by an oscilloscope. The sampled data were processed using HP 3000 minicomputer of Chungnam National University computer center the graphical results were triangle same as input wave and so the system have been out of phase distorsion and amplitude distorsion. 3. The strain generated from a cantilever beam vibrator which has free vibration period of 0.019 second were measured by the system controlled to have l.0 ms of time interval and its computer output showing vibration curve which is well filted to theoretical value. 4. Using microcomputer on measuring the strain of agricultural machine elements could not only save analyzing time and recording papers but also get excellent adaptation to field experiment, especially in measurement requiring high speed and good precision.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• 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.

• Journal of Service Research and Studies
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• v.6 no.2
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• pp.23-35
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• 2016

Firms should seek greater profits and corporate growth through new businesses. New businesses contribute realizing creative economy that creates good jobs, and expanding the company by securing new markets and creating new profits and growth. However, new business is risky management decision-making to have a high failure rate because it involves the adaptation of new business environment and the burden of new investments, including the uncertainty of success in business. Therefore, innovation strategies play important roles for the new business entry, using product innovation, process innovation, business model innovation, disruptive innovation, and strategic innovation, etc. and company will get huge economic results by pushing them into successful business. It is essential that innovation strategy and IT development strategy along with business strategy of a firm are linked, and their strategic alignment is considered to be a critical success factor for new business success. Hyundai Heavy Industries(HHI) pursued marine engine business for the development of precision machinery industry and shipbuilding industry of Korea, and the company recognized the importance of new business strategy, innovation strategy, and IT strategy inter-linked, and pushed strategic alignment boldly. As a result, HHI won the competition in European and Japanese engine manufacturers and climbed into the world's largest engine manufacturer. This study suggests investigating and analyzing a case that HHI succeeded in marine engine business expansion using strategic innovation strategy as a way of the introduction of CNC machine tools and the development of HEMAPT system.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.5
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• pp.442-448
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• 1999

We introduce the systematization design method using similarity theory which is profitable in the c compatability and standardization of the developed products and the reduction of construction time and price to d develop and design a machine equipment. Systematization design method is to select the standard model for d designing and developing from the large machinery to the super precision one and then to induce the c characteristic of machines step by step in advance in case of miniaturizing and making largelongleftarrowscale. With this m method, we extract the peculiar characteristics through the close analysis on the physical and ttx:hnical part a and predict the characteristic experiment for the magnitude we desire by an머ogical mathematical analysis. At l last, we will get the design sample the users demand with the verification of the data on optimum design p previously. In this paper, we could predict the characteristic of the product the users rC'Quire in advance with the d design method applying similarity theor${\gamma}$ and suggested the design method which could meet the various r requirements the users want. Also, it is shown that the standardization design by the similarity theory is a available as comparing the characteristic values expc'Cted through the experiment of the actual actuator with t the theoretical character data of similarity theoη after selecting the linear actuator as a model.

• Journal of Technologic Dentistry
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• v.31 no.1
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• pp.55-61
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• 2009

Passive fitting of meso-structure and super-structures is a predominant requirement for the longevity and clinical success of osseointegrated dental implants. However, precision and passive fitting has been unpredictable with conventional methods of casting as well as for corrective techniques. Alternative to conventional techniques, electro discharge machining(EDM) is an advanced method introduced to dental technology to improve the passive fitting of implant prosthesis. In this technique material is removed by melting and vaporization in electric sparks. Regarding the efficacy of EDM, the application of this technique induces severe surface morphological and elemental alterations due to the high temperatures developed during machining, which vary between $10,000{\sim}20,000^{\circ}C$. The aim of this study was to investigate the morphological and elemental alterations induced by EDM process of casting dental gold alloy and non-precious alloy used for the production of implant-supported prosthesis. A conventional clinical dental casting alloys were used for experimental specimens patterns, which were divided in three groups, high fineness gold alloy(Au 75%, HG group), low fineness gold alloy(Au 55%, LG group) and nonprecious metal alloy(Ni-Cr, NP group). The UCLA type plastic abutment patterns were invested with conventional investment material and were cast in a centrifugal casting machine. Castings were sandblasted with $50{\mu}m\;Al_2O_3$. One casting specimen of each group was polished by conventional finishing(HGCON, LGCON, NPCON) and one specimen of each group was subjected to EDM in a system using Cu electrodes, kerosene as dielectric fluid in 10 min for gold alloy and 20 min for Ni-Cr alloy(HGEDM. LGEDM, NOEDM). The surface morphology of all specimens was studied under an energy dispersive X-ray spectrometer (EDS). The quantitative results from EDS analysis are presented on the HGEDM and LGEDM specimens a significant increase in C and Cu concentrations was found after EDM finishing. The different result was documented for C on the NPEDM with a significant uptake of O after EDM finishing, whereas Al, Si showed a significant decrease in their concentrations. EDS analysis showed a serious uptake of C and Cu after the EDM procedure in the alloys studied. The C uptake after the EDM process is a common finding and it is attributed to the decomposition of the dielectric fluid in the plasma column, probably due to the development of extremely high temperatures. The Cu uptake is readily explained from the decomposition of Cu electrodes, something which is also a common finding after the EDM procedure. However, all the aforementioned mechanisms require further research. The clinical implication of these findings is related with the biological and corrosion resistance of surfaces prepared by the EDM process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.63-71
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• 2018

A flower support was developed for real flower decoration automation production system using an ultrasonic wave sealer to automatically produce a system. Because a flower support for real flower decoration that was produced manually could not meet the needs of the consumers, this study developed an automated manufacturing system to increase productivity. A flower support for real flower decoration was constructed using a cap consisting of plastic and plate made from non-woven fabric. The guide was designed to transport the cap to the ultrasonic wave sealer and optimal guide was developed from the test according to the material and shape. To produce the entire system, the guides and accessories were weighed and appropriate motors and pulleys were calculated. Control of the automation production system was based on a PCB board, which increased the reliability and security, and a remote controller with manual and automatic modes was prepared. After development, tests of the transfer precision and repetition accuracy revealed an X-axis of 2.7mm, a Y-axis of 1 mm, and a repetition of 0 mm. The productivity was also checked. The automated machine worked 8 hours/day to make 35 supports and 70 Therefore, the automatic system produces 200% more output than manual work

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.334-341
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• 2016

In this paper, the study of a waveguide aperture-coupled feed-structured antenna has been conducted for the purpose of applying it to a wireless back-haul system sufficient for high-capacity gigabits-per-second data rates. For this study, a $32{\times}32$ waveguide slot sub-array antenna with a corporate-feed structure was designed and produced. Also, this antenna is used at 57 GHz to 66 GHz in the V-band. The construction of the antenna is a laminated form with radiating parts (outer groove and slot, cavity), a coupled aperture, and feeds in each. The antenna was designed with HFSS, which is based on 3D-FEM, produced with aluminum processed by a precision-controlled milling machine, and assembled after a silver-plating process. The measurement result from analysis of the characteristics of the antenna shows that return loss is less than -12 dB, VSWR < 2.0, and a wide bandwidth ranges up to 16%. An overall first side lobe level is less than -12.3 dB, and a 3 dB beam width is narrow at about $1.85^{\circ}$. Also, antenna gain is 38.5 dBi, offering high efficiency exceeding 90%.