• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1499-1507
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• 2009

With the abundance of digital contents, the necessity of precise indexing technology is consistently required. To meet these requirements, the intelligent software entity needs to be the subject of information retrieval and the interoperability among intelligent entities including human must be supported. In this paper, we analyze the unifying framework for multi-modality indexing that Snoek and Worring proposed. Our work investigates the method of improving the authenticity of indexing information in contents-based automated indexing techniques. It supports the creation and control of abstracted high-level indexing information through ontological concepts of Semantic Web skills. Moreover, it attempts to present the fundamental model that allows interoperability between human and machine and between machine and machine. The memory-residence model of processing ontology is inappropriate in order to take-in an enormous amount of indexing information. The use of ontology repository and inference engine is required for consistent retrieval and reasoning of logically expressed knowledge. Our work presents an experiment for storing and retrieving the designed knowledge by using the Minerva ontology repository, which demonstrates satisfied techniques and efficient requirements. At last, the efficient indexing possibility with related research is also considered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.72-77
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• 2017

This paper focuses on the development of a supporting S/W tool for the automated design of an automotive press trim die. To define the die design process based on automation, we analyze the press die design process of the current industry and group repetitive works in the 3D modeling process. The proposed system consists of two modules, namely the template models of the trim steel parts and UI function for their auto-positioning. Four kinds of template models are developed to adapt to various situations and the rules of the interaction formula which are used for checking and correcting the directions of the datum point, datum curve, datum plane are implemented to eliminate errors. The system was developed using CATIA Knowledgeware, CAA(CATIA SDK) and Visual C++, in order for it to function as a plug-in module of CATIA V5, which is one of the major 3D CAD systems in the manufacturing industry. The developed system was tested by applying it to various panels of current automobiles and the results showed that it reduces the time-cost by 74% compared to the traditional method.

• Imaging Science in Dentistry
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• v.45 no.1
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• pp.23-29
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• 2015

Purpose: This study aimed to assess the reliability of measurements performed on three-dimensional (3D) virtual models of maxillary defects obtained using cone-beam computed tomography (CBCT) and 3D optical scanning. Materials and Methods: Mechanical cavities simulating maxillary defects were prepared on the hard palate of nine cadavers. Images were obtained using a CBCT unit at three different fields-of-views (FOVs) and voxel sizes: 1) $60{\times}60mm$ FOV, $0.125mm^3$ ($FOV_{60}$); 2) $80{\times}80mm$ FOV, $0.160mm^3$ ($FOV_{80}$); and 3) $100{\times}100mm$ FOV, $0.250mm^3$ ($FOV_{100}$). Superimposition of the images was performed using software called VRMesh Design. Automated volume measurements were conducted, and differences between surfaces were demonstrated. Silicon impressions obtained from the defects were also scanned with a 3D optical scanner. Virtual models obtained using VRMesh Design were compared with impressions obtained by scanning silicon models. Gold standard volumes of the impression models were then compared with CBCT and 3D scanner measurements. Further, the general linear model was used, and the significance was set to p=0.05. Results: A comparison of the results obtained by the observers and methods revealed the p values to be smaller than 0.05, suggesting that the measurement variations were caused by both methods and observers along with the different cadaver specimens used. Further, the 3D scanner measurements were closer to the gold standard measurements when compared to the CBCT measurements. Conclusion: In the assessment of artificially created maxillary defects, the 3D scanner measurements were more accurate than the CBCT measurements.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.115-119
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• 1996

odel). One of important tasks for hydrological analysis is the division of watershed. It can be an essential factor amThe main objective of this study is to extract of the geometric characteristics of the Pyongchang River basin, headwaters of the South Ran River. A GIS is capable of extracting various hydrological factors from DEM(digital elevation mong various geometric characteristics of watershed. In this study, watershed itself and other geometric factors of watershed are extracted from DEM by using a GIS technique. The manual process of tasks to obtain geometric characteristics of watershed is automated. by using the function of ARC/INFO software as a GIS package. Scanned data is used for this study and it is converted to DEM data Various forms of representation of spatial data are handled in main modules and a GRID module of ARC/INFO. A GRID module is used on a stream in order to define watershed boundary, so it would be possible to obtain the watersheds. Also, a flowdirection, stream networks and others are generated. The results show that GIS can aid watershed management and research and surveillance. Also the geometric characteristics as parameters of watershed can be quantified by a using GIS technique. Resonable results can be obtained as compared with conventional graphic methods.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.5
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• pp.418-428
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• 2016

In this study, a Vessel Shore Report Management System (VSRMS) is developed for the International Maritime Organization (IMO), Maritime Service Portfolio (MSP) Number 8, which comprises vessel shore reporting. Several documents have to be completed before the arrival/departure of a vessel at a port, as each national port has its own reporting format and data. The present vessel reporting system is inefficient, time-consuming, and involves excessive paperwork, which results in duplications and errors. To solve this problem, in this study, the vessel reporting formats and data contents of various national ports are investigated, as at present, the reporting documents required by the current IMO standard includes insufficient information which is requested by national ports. Initially, the vessel reporting information of various national ports are collected and analyzed. Subsequently, a database structure for managing vessel reporting data for ports worldwide is devised. To make the transfer of data and the exchange of information of vessel reports much more reliable, efficient, and paper-free, VSRMS, which is a software application for the simplification and facilitation of vessel report formalities, is developed. This application is developed using the latest Microsoft C#.Net Programming Language in the Microsoft Visual Studio framework 4.5. It provides a user interface and a backend MySQL server used for database management. SAP Crystal Reports 2013 is used for designing and generating vessel reports in the original report formats. The VSRMS can facilitate vessel reporting and improve data accuracy through the reduction of input data, efficient data exchange, and reduction of the cost of communication. Adoption of the VSRMS will allow the vessel shore reporting system to be automated, resulting in enhanced work efficiency for shipping companies. Based on this information system and architecture, the consensus of various international organizations, such as the IMO, the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA), the Federation of National Associations of Ship Brokers and Agents (FONASBA), and the Baltic and International Maritime Council (BIMCO), is required so that vessel reporting is standardized internationally.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.42.1-42.1
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• 2018

Deep Ecliptic Patrol of the Southern Sky (DEEP-South) observation is being made during the off-season for exoplanet survey, using Korea Microlensing Telescope Network (KMTNet). An optimal combination of its prime focus optics and the 0.3 billion pixel CCD provides a four square degrees field of view with 0.4 arcsec/pixel plate scale which is also best suited for small body studies. Normal operation of KMTNet started in October 2015, and a significant portion of the allocated telescope time for DEEP-South is dedicated to targeted observation, Opposition Census (OC), of near-Earth asteroids for physical and taxonomic characterization. This is effectively achieved through multiband, time series photometry using Johnson-Cousins BVRI filters. Uninterrupted monitoring of the southern sky with KMTNet is optimized for spin characterization of a broad spectrum of asteroids ranging from the near-Earth space to the main-belt, including binaries, asteroids with satellites, slow/fast- and non-principal axis-rotators, and thus is expected to facilitate the debiasing of previously reported lightcurve observations. Our software subsystem consists of an automated observation scheduler, a pipelined data processing system for differential photometry, and an easy-to-use lightcurve analysis toolkit. Lightcurves, spin periods and provisional determination of class of asteroids to which the lightcurve belongs will be presented, using the dataset from first year operation of KMTNet. Our new taxonomic classification scheme for asteroids will also be summarized.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.560-570
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• 2009

RFID, Radio Frequency Identification, is a technology of automated identification replacing bar-code. RFID technology has advantages that it recognizes fast and it is strong to contamination using wireless communication. However, there are difficult problems that should be solved for popularization of RFID. Among of these, tag anti-collision problem is dealed in this paper. It affected the performance of RFID system directly. This paper analyzes conventional algorithms and proposes new algorithms of tag anti-collision. The algorithm proposed was composed of appropriate properties to each phase of distribution and recognition as hybrid between ALOHA-based algorithm and QT-based algorithm. At phase of distribution, the number of tags recognizing at a frame was reduced using ALOHA-based algorithm. It addressed the delay problem because of deep depth of tree. At phase of recognition, it solved ALOHA-based chronic problem that couldn't recognize all the tags sometimes. Moreover, QTR algorithm that recognize by reversed tag IDs was adopted for the performance. The FQTR algorithm proposed in this paper showed brilliant performance as compared with convention algorithms by simulation.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.213-219
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• 2018

In this paper, we propose a design method and process for hardware and software of hybrid V2X communication module that supports both C-ITS communication protocol designed for vehicle environment and Legacy LTE communication technology. C-ITS is suitable for safety service applications due to its low latency characteristics, and Legacy LTE is a technology suitable for non-safety applications such as traffic information and infotainment due to high latency and high capacity. The hybrid V2X communication module supports multiple communication technologies of WAVE and LTE, in which WAVE supports multiple channels, so that it is designed to transmit road information such as LDM and positioning correction information to an autonomous vehicle in real time. The main design results presented in this paper will be applied to the implementation of future hybrid V2X communication terminals for vehicles.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.53-60
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• 2020

Sentiment analysis is the automated process of understanding attitudes and opinions about a given topic from written or spoken text. One of the sentiment analysis approaches is a dictionary-based approach, in which a sentiment dictionary plays an much important role. In this paper, we propose a method to automatically generate Korean sentiment lexicon from the well-known English sentiment lexicon called VADER (Valence Aware Dictionary and sEntiment Reasoner). The proposed method consists of three steps. The first step is to build a Korean-English bilingual lexicon using a Korean-English parallel corpus. The bilingual lexicon is a set of pairs between VADER sentiment words and Korean morphemes as candidates of Korean sentiment words. The second step is to construct a bilingual words graph using the bilingual lexicon. The third step is to run the label propagation algorithm throughout the bilingual graph. Finally a new Korean sentiment lexicon is generated by repeatedly applying the propagation algorithm until the values of all vertices converge. Empirically, the dictionary-based sentiment classifier using the Korean sentiment lexicon outperforms machine learning-based approaches on the KMU sentiment corpus and the Naver sentiment corpus. In the future, we will apply the proposed approach to generate multilingual sentiment lexica.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.145-152
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• 2020

MRC (Machine reading comprehension) is the AI NLP task that predict the answer for user's query by understanding of the relevant document and which can be used in automated consult services such as chatbots. Recently, the BERT (Pre-training of Deep Bidirectional Transformers for Language Understanding) model, which shows high performance in various fields of natural language processing, have two phases. First phase is Pre-training the big data of each domain. And second phase is fine-tuning the model for solving each NLP tasks as a prediction. In this paper, we have made the Patent MRC dataset and shown that how to build the patent consultation training data for MRC task. And we propose the method to improve the performance of the MRC task using the Pre-trained Patent-BERT model by the patent consultation corpus and the language processing algorithm suitable for the machine learning of the patent counseling data. As a result of experiment, we show that the performance of the method proposed in this paper is improved to answer the patent counseling query.