• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.284-284
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• 2016

Topological insulator (TI) is a bulk-insulating material with topologically protected Dirac surface states in the band gap. In particular, $Bi_2Se_3$ attracted great attention as a model three-dimensional TI due to its simple electronic structure of the surface states in a relatively large band gap (~0.3 eV). However, experimental efforts using $Bi_2Se_3$ have been difficult due to the abundance of structural defects, which frequently results in the bulk conduction being dominant over the surface conduction in transport due to the bulk doping effects of the defect sites. One promising approach in avoiding this problem is to reduce the structural defects by heteroepitaxially grow $Bi_2Se_3$ on a substrate with a compatible lattice structure, while also preventing surface degradation by encapsulating the pristine interface between $Bi_2Se_3$ and the substrate in a clean growth environment. A particularly promising choice of substrate for the heteroepitaxial growth is hexagonal boron nitride (h-BN), which has the same two-dimensional (2D) van der Waals (vdW) layered structure and hexagonal lattice symmetry as $Bi_2Se_3$. Moreover, since h-BN is a dielectric insulator with a large bandgap energy of 5.97 eV and chemically inert surfaces, it is well suited as a substrate for high mobility electronic transport studies of vdW material systems. Here we report the heteroepitaxial growth and characterization of high quality topological insulator $Bi_2Se_3$ thin films prepared on h-BN layers. Especially, we used molecular beam epitaxy to achieve high quality TI thin films with extremely low defect concentrations and an ideal interface between the films and substrates. To optimize the morphology and microstructural quality of the films, a two-step growth was performed on h-BN layers transferred on transmission electron microscopy (TEM) compatible substrates. The resulting $Bi_2Se_3$ thin films were highly crystalline with atomically smooth terraces over a large area, and the $Bi_2Se_3$ and h-BN exhibited a clear heteroepitaxial relationship with an atomically abrupt and clean interface, as examined by high-resolution TEM. Magnetotransport characterizations revealed that this interface supports a high quality topological surface state devoid of bulk contribution, as evidenced by Hall, Shubnikov-de Haas, and weak anti-localization measurements. We believe that the experimental scheme demonstrated in this talk can serve as a promising method for the preparation of high quality TI thin films as well as many other heterostructures based on 2D vdW layered materials.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.1-16
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• 2015

Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

• The Journal of Engineering Geology
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• v.16 no.1 s.47
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• pp.69-83
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• 2006

This study aims to evaluate a complex groundwater flow system around the underground oil storage caverns using the concept of hydraulic compartment. For the hydrogeological analysis, the hydraulic testing data, the evolution of groundwater levels in 28 surface monitoring boreholes and pressure variation of 95 horizontal and 63 vertical water curtain holes in the caverns were utilized. At the cavern level, the Hydraulic Conductor Domains(fracture zones) are characterized one local major fracture zone(NE-1)and two local fracture zones between the FZ-1 and FZ-2 fracture zones. The Hydraulic Rock Domain(rock mass) is divided into four compartments by the above local fracture zones. Two Hydraulic Rock Domains(A, B) around the FZ-2 zone have a relatively high initial groundwater pressures up to $15kg/cm^2$ and the differences between the upper and lower groundwater levels, measured from the monitoring holes equipped with double completion, are in the range of 10 and 40 m throughout the construction stage, indicating relatively good hydraulic connection between the near surface and bedrock groundwater systems. On the other hand, two Hydraulic Rock Domains(C, D) adjacent to the FZ-1, the groundwater levels in the upper and lower zones are shown a great difference in the maximum of 120 m and the high water levels in the upper groundwater system were not varied during the construction stage. This might be resulted from the very low hydraulic conductivity$(7.2X10^{-10}m/sec)$ in the zone, six times lower than that of Domain C, D. Groundwater recharge rates obtained from the numerical modeling are 2% of the annual mean precipitation(1,356mm/year) for 20 years.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.59-68
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• 1998

Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

• Korean Journal of Construction Engineering and Management
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• v.1 no.3 s.3
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• pp.124-134
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• 2000

In construction projects, the design information, which should contain accurate product information in a systematic way, needs to be applicable through the life-cycle of projects. However, paper-based 2D drawings and relevant documents has difficulties in communicating and sharing the owner's and architect's intention and requirement effectively and building a corporate knowledge base through on-going projects due to Tack of interoperability between specific task or function-oriented software and handling massive information. Meanwhile, computer and information technologies are being developed so rapidly that the practitioners are even hard to adapt them into the industry efficiently. 3D modeling capabilities in CAD systems are enormously developed and enables users to associate 3D models with other relevant information. However, this still requires a great deal of efforts and costs to have all the design information represented in CAD system, and the sophisticated system is difficult to manage. This research focuses on the transition period from 2D-based design Information management to 3D-based, which means co-existence of 2D and 3D-based management. This research proposes a model of a compound system of 2D and 3D-based CAD system which presents the general design information using 3D model integrating with 2D CAD drawings for detailed design information. This research developed an integrated information management system for design and specification by associating 2D drawings and 3D models, where 2D drawings represents detailed design and parts that are hard to express in 3D objects. To do this, related management processes was analyzed to build an information model which in turn became the basis of the integrated information management system.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.35-42
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• 2016

Recently many researches have been focused on the use of the markerless augmented reality system using face, foot, and hand of user's body to alleviate many disadvantages of the marker based augmented reality system. In addition, most existing augmented reality systems have been utilized rigid objects since they just desire to insert and to basic interaction with virtual object in the augmented reality system. In this paper, unlike restricted marker based augmented reality system with rigid objects that is based in display, we designed and implemented the markerless augmented reality system using deformable objects to apply various fields for interactive situations with a user. Generally, deformable objects can be implemented with mass-spring modeling and the finite element modeling. Mass-spring model can provide a real time simulation and finite element model can achieve more accurate simulation result in physical and mathematical view. In this paper, the proposed markerless augmented reality system utilize the mass-spring model using tetraheadron structure to provide real-time simulation result. To provide plausible simulated interaction result with deformable objects, the proposed method detects and tracks users hand with Kinect SDK and calculates the external force which is applied to the object on hand based on the position change of hand. Based on these force, 4th order Runge-Kutta Integration is applied to compute the next position of the deformable object. In addition, to prevent the generation of excessive external force by hand movement that can provide the natural behavior of deformable object, we set up the threshold value and applied this value when the hand movement is over this threshold. Each experimental test has been repeated 5 times and we analyzed the experimental result based on the computational cost of simulation. We believe that the proposed markerless augmented reality system with deformable objects can overcome the weakness of traditional marker based augmented reality system with rigid object that are not suitable to apply to other various fields including healthcare and education area.

• Journal of Food Hygiene and Safety
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• v.29 no.3
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• pp.217-222
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• 2014

This study was performed to evaluate the sporicidal efficacy of a fumigation disinfectant containing 20% ortho-phenylphenol against Clostridium perfringens (C. perfringens) spores. In this research, efficacy test of fumigant against C. perfringens spores was carried out according to French standard NF T 72-281. C. perfringens spores working culture suspension number (N value), all the spore numbers on the carriers exposed with the fumigant (n1, n2, and n3), the number of bacterial spore suspensions by pour plate method (N1), the number of bacterial spore suspensions by filter membrane method (N2) and the mean number of bacterial spore recovered on the control-carriers (T value) were obtained from the preliminary test. In addition, the reduction number of C. perfringens spores exposed with the fumigant (d value) was calculated using T value, the mean number of bacterial spore in recovery solution (n'1) and the mean number of bacterial spore on carriers plated in agar (n'2). N value was $4.3{\times}10^7spores/mL$, and n1, n2, and n3 were higher than 0.5N1, 0.5N2 and 0.5N1, respectively. Additionally, T value was $4.9{\times}10^5spores/carrier$. In the sporicidal effect of the fumigant, the d value was 4.52log reduction. According to the French standard for the fumigant, the d value for the effective sporicidal fumigant should be over than 3log reduction. The results indicated that Fumagari $OPP^{(R)}$ had an efficient sporicidal activity against spores of C. perfringens, then the fumigant can be applied to disinfect food materials and kitchen appliances contaminated with bacterial spores.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.115-122
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• 2002

There is various points that should be improved in Fairness such as our contract practice to propose construction projects, project managing and the stakeholders' way of thinking and culture. We consider that the revision of construction related provisions and systems is required but even more, an overall change in business management through the implementation of Integrated Construction Information Management System that will enable the owner, which drives the project, and contractor sharing construction information is required. To mange construction related information in an integrated manner, designing information should be smoothly transferred to purchasing information, and changes are required in order to move ahead to process-oriented work system. Finally information created from various construction organizations should be delivered in an aligned and standardized manner as well. The domestic Nuclear Power Plant Construction has been accepting various technology transfers from U.S, France, Canada and UK, which enabled us to self-support technology and recently even proceeded to the phase exporting our technology to others. However, continuous effort is required to improve internal business efficiency and to respond to external environmental change such aselectricity market deregulation. Recently, in accordance with the result in number of CEO's intention to make progress in IT and improve business efficiency, the number of enterprises introducing Enterprise Resource Planning is increasing. ERP is an innovative tool which changes the way of performing work from organization and department orientation to process-orientation in order to optimize the resources, such as human and material resources, through out the Enterprise by performing BPR which will maximize overall business efficiency of the enterprise, such includes not only construction management, but also business management. KHNP continued to performing large scaled construction projects such as nuclear power plant construction for past 30 years and took the initiatives of large scale project management and Quality management ability in domestic industry by having independent capability of over all construction planning, purchasing and, construction and start up management etc. To maintain our leading position of improving construction management technology based on our accumulated project management experience and technology, KHNP included construction into our ERP project in purpose of innovating construction business. We would like to discuss the characteristics of nuclear construction business, project management system, information system infrastructure and information sharing system among construction related entities, and implementation practices for information system, and consider how to resolve our practice that should be improved in this thesis.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.1-15
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• 2006

In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.