• The Journal of the Korean dental association
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• v.17 no.2 s.117
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• pp.119-128
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• 1979

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.28-39
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• 2007

The issue of customer-centric enterprise focusing on realizing customer needs has recently received considerable attention in the corporate world. However, little research has yet been reported on developing Information Systems (IS) supporting the customer-centric enterprises. This research proposes an integrated approach of IS development that supports organizations aiming to become customer-centric enterprises using various customer profiles. In this paper, we propose an integrated approach unifying goal modeling, business process modeling, and information systems modeling. The approach is expected to be seamlessly linked with the object-oriented systems development approach. Finally, we apply this approach to the real case of a securities company in Japan.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.446-465
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• 2015

In this modern era of technology and information, e-learning approach has become an integral part of teaching and learning using modern technologies. There are different variations or classification of e-learning approaches. One of notable approaches is Personal Learning Environment (PLE). In a PLE system, the contents are presented to the user in a personalized manner (according to the user's needs and wants). The problem arises when a new user enters the system, and due to the lack of information about the new user's needs and wants, the system fails to recommend him/her the personalized e-learning contents accurately. This phenomenon is known as cold-start problem. In order to address this issue, existing researches propose different approaches for recommendation such as preference profile, user ratings and tagging recommendations. In this research paper, the implementation of a novel interaction-based approach is presented. The interaction-based approach improves the recommendation accuracy for the new-user cold-start problem by integrating preferences profile and tagging recommendation and utilizing the interaction among users and system. This research work takes leverage of the interaction of a new user with the PLE system and generates recommendation for the new user, both implicitly and explicitly, thus solving new-user cold-start problem. The result shows the improvement of 31.57% in Precision, 18.29% in Recall and 8.8% in F1-measure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.103-114
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• 2003

This paper aims to propose a method that helps maintenance engineers to evaluate the damage states of bridge structure systems by using a Fuzzy Fault Tree Analysis. It may be stated that Fuzzy Fault Tree Analysis may be very useful for the systematic and rational fuzzy reliability assessment for real bridge structure systems problems because the approach is able to effectively deal with all the related bridge structural element damages in terms of the linguistic variables that incorporate systematically experts experiences and subjective judgement. This paper considers these uncertainties by providing a fuzzy reliability-based framework and shows that the identification of the optimum maintenance scenario is a straightforward process. This is achieved by using a computer program for LIFETIME. This program can consider the effects of various types of actions on the fuzzy reliability index profile of a deteriorating structures. Only the effect of maintenance interventions is considered in this study. However. any environmental or mechanical action affecting the fuzzy reliability index profile can be considered in LIFETIME. Numerical examples of deteriorating bridges are presented to illustrate the capability of the proposed approach. Further development and implementation of this approach are recommended for future research.

• Journal of Korean Dental Science
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• v.16 no.1
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• pp.35-46
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• 2023

Purpose: Culture-based methods for microbiological diagnosis and antibiotic susceptibility tests have limitations in the management of orofacial infections. We aimed to profile pus microbiota and identify antibiotic resistance genes (ARGs) using a culture-independent approach. Materials and Methods: Genomic DNA samples extracted from the pus specimens of two patients with orofacial abscesses were subjected to shotgun sequencing on the NovaSeq system. Taxonomic profiling and prediction of ARGs were performed directly from the metagenomic raw reads. Result: Taxonomic profiling revealed obligate anaerobic polymicrobial communities associated with infections of odontogenic origins: the microbial community of Patient 1 consisted of one predominant species (Prevotella oris 74.6%) with 27 minor species, while the sample from Patient 2 contained 3 abundant species (Porphyromonas endodontalis 33.0%; P. oris 31.6%; and Prevotella koreensis 13.4%) with five minor species. A total of 150 and 136 putative ARGs were predicted in the metagenome of each pus sample. The coverage of most predicted ARGs was less than 10%, and only the CfxA2 gene identified in Patient 1 was covered 100%. ARG analysis of the seven assembled genome/metagenome datasets of P. oris revealed that strain C735 carried the CfxA2 gene. Conclusion: A metagenomics-based approach is useful to profile predominantly anaerobic polymicrobial communities but needs further verification for reliable ARG detection.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.245-269
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• 2007

The standard metadata systems are very popular for the description of structures and semantics of information resources to realize sharing and exchanging information in global ubiquitous environment. In real application domain, various metadata elements are reused together with mix-and-match manner. An application system using diverse metadata systems is compelled with refinement and interoperability of metadata elements. Application profile is the general approach to resolve the various problems occurred in metadata application systems. This paper proposes Application Profile Core Ontology (APO) that can achieve the goals and functions of application profile, and describes metadata application system based on APO.

• The korean journal of orthodontics
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• v.4 no.1
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• pp.21-29
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• 1974

The purpose of the present study is to evaluate changes of the soft tissue relative to underlying skeletal elements during orthodontic treatment, and the influence of orthodontic treatment quantitatively on various regions of the facial profile. 59 Korean young women were selected, whose Hellman dental age was IV A, IV C and V A. Lateral cephalometric head films were taken before and after orthodontic treatment. From tracings, landmarks on skeletal and soft tissue profile were located, and then their linear and angular measurements were made directly. The results were obtained as follow: 1) Soft tissues of the facial profile were closely related and dependent on the underlying dentoskeletal frameworks. Orthodontic treament resulted in the reduction of dentofacial protrusion with both upper and lower lips becoming less procumbent during treament. 2) Thickness of the upper lip increased considerably during orthodontic treatment, and this change was related to maxillary incisor retraction. The ratio between the amount of maxillary incisor retraction and that of increment of upper lip thickness was approximately 5:3. 3) Soft tissue thickness overlying Downs' point A, point B and pogonion was not modified by orthodontic treatment. 4) Holdaway's H line, relating facial profile to the underlying dentoskeletal framework, seemed to be the most practical approach to soft tissue analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1929-1939
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• 1999

This paper presents a neural network approach, which was named PRONET, to 3D object recognition and pose calculation. 3D objects are represented using a set of centroidal profile patterns that describe the boundary of the 2D views taken from evenly distributed view points. PRONET consists of the training stage and the execution stage. In the training stage, a three-layer feed-forward neural network is trained with the centroidal profile patterns using an error back-propagation method. In the execution stage, by matching a centroidal profile pattern of the given image with the best fitting centroidal profile pattern using the neural network, the identity and approximate orientation of the real object, such as a workpiece in arbitrary pose, are obtained. In the matching procedure, line-to-line correspondence between image features and 3D CAD features are also obtained. An iterative model posing method then calculates the more exact pose of the object based on initial orientation and correspondence.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.68.3-69
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• 2021

We present a novel profile stacking technique based on optimal profile decomposition of a 3D spectral line data cube, and its performance test using the HI data cubes of sample galaxies from HI galaxy surveys, THINGS and LITTLE THINGS. Compared to the previous approach which aligns all the spectra of a cube using their central velocities derived from either moment analysis, single Gaussian or hermite h3 polynomial fitting, the new method makes a profile decomposition of the profiles from which an optimal number of single Gaussian components is derived for each profile. The so-called superprofile which is derived by co-adding all the aligned profiles from which the other Gaussian models are subtracted is found to have weaker wings compared to the ones constructed in a typical manner. This could be due to the reduced number of asymmetric profiles in the new method. A practical test made on the HI data cubes of the THINGS and LITTLE THINGS galaxies shows that our new method can extract more mass of kinematically cold HI components in the galaxies than the previous results. Additionally, we fit a double Gaussian model to the superprofiles whose S/N is boosted, and quantify not only their profile shapes but derive the ratio of the Gaussian model parameters, such as the intensity ratio and velocity dispersion ratio of the narrower and broader Gaussian components. We discuss how the superprofile properties of the sample galaxies are correlated with their other physical properties, including star formation rate, stellar mass, metallicity, and gas mass.

• Korean Medical Education Review
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• v.23 no.2
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• pp.118-127
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• 2021

Due to the coronavirus disease 2019 pandemic, the new norm of online learning has been recognized as core to medical institutions for academic continuity, and students are expected to be motivated and engaged in learning while maintaining distance from other peers and educators. To facilitate students' and educators' newly defined roles in online medical education settings, it is crucial to understand how students are actively motivated and engaged in learning. Hence, this study explored medical students' motivational regulation profiles and examined the effects of motivational regulation strategies (MRS) on cognitive learning and learning engagement for online learning. Data were collected after the end of the first semester in 2020 from a sample of 334 medical students enrolled at a public university school of medicine. Latent profile analysis indicated three subgroups with different motivational regulation profiles: the low-profile, medium-profile, and high-profile groups. Regarding different MRS patterns in the high-profile group, mastery self-talk, performance approach self-talk, and the self-consequating strategy appeared to be most applicable for regulating learners' motivation. Analysis of variance showed that the profile groups with higher levels of MRS use were connected to a higher willingness to use cognitive learning strategies and a higher degree of engagement in online learning. The findings of this study emphasize the use of specific sets of MRS to support learning motivation and the need to design effective self-regulated learning environments in online medical education settings.