• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.129-142
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• 2011

Traditionally research in Service Oriented Architecture(SOA) security has focused primarily on exploiting standards and solutions separately. There exists no unified methodology for SOA security to manage risks at the enterprise level. It needs to analyze preliminarily security threats and to manage enterprise risks by identifying vulnerabilities of SOA. In this paper, we propose a metric-based vulnerability assessment method using dynamic properties of services in SOA. The method is to assess vulnerability at the architecture level as well as the service level by measuring run-time dependency between services. The run-time dependency between services is an important characteristic to understand which services are affected by a vulnerable service. All services which directly or indirectly depend on the vulnerable service are exposed to the risk. Thus run-time dependency is a good indicator of vulnerability of SOA.

• The korean journal of orthodontics
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• v.50 no.2
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• pp.86-97
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• 2020

Objective: To propose a three-dimensional (3D) method for evaluating temporomandibular joint (TMJ) changes during Twin-block treatment. Methods: Seventeen patients with Class II division 1 malocclusion treated using Twin-block and nine untreated patients with a similar malocclusion were included in this research. We collected their cone beam computed tomography (CBCT) data from before and 8 months after treatment. Segmentations were constructed using ITK-SNAP. Condylar volume and superficial area were measured using 3D Slicer. The 3D landmarks were identified on CBCT images by using Dolphin software to assess the condylar positional relationship. 3D models of the mandible and glenoid fossa of the patients were constructed and registered via voxel-based superimposition using 3D Slicer. Thereafter, skeletal changes could be visualized using 3DMeshMetric in any direction of the superimposition on a color-coded map. All the superimpositions were measured using the same scale on the distance color-coded map, in which red color represents overgrowth and blue color represents resorption. Results: Significant differences were observed in condylar volume, superficial area, and condylar position in both groups after 8 months. Compared with the control group (CG), the Twin-block group exhibited more obvious condyle-fossa modifications and joint positional changes. Moreover, on the color-coded map, more obvious condyle-fossa modifications could be observed in the posterior and superior directions in the Twin-block group than in the CG. Conclusions: We successfully established a 3D method for measuring and evaluating TMJ changes caused by Twin-block treatment. The treatment produced a larger condylar size and caused condylar positional changes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.4072-4089
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• 2018

This paper introduces a scheme for optimizing the material properties of mass-spring systems of different resolutions to provide coherent behavior for reduced level-of-detail in MSS(Mass-Spring System) meshes. The global optimal material coefficients are derived to match the behavior of provided reference mesh. The proposed method also gives us insight into levels of reduction that we can achieve in the systematic behavioral coherency among the different resolution of MSS meshes. We obtain visually acceptable coherent behaviors for cloth models based on our proposed error metric and identify that this method can significantly reduce the resolution levels of simulated objects. In addition, we have confirmed coherent behaviors with different resolutions through various experimental validation tests. We analyzed spring force estimations through triangular Barycentric coordinates based from the reference MSS that uses a Gaussian kernel based distribution. Experimental results show that the displacement difference ratio of the node positions is less than 10% even if the number of nodes of $MSS^{sim}$ decreases by more than 50% compared with $MSS^{ref}$. Therefore, we believe that it can be applied to various fields that are requiring the real-time simulation technology such as VR, AR, surgical simulation, mobile game, and numerous other application domains.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.139-148
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• 2006

This study is intended to propose quality criteria and Web metrics for usability quality evaluation of multimedia Web sites. Recently, applications of the Web sites are not limited to the area of industry and operating as it integrates the new technology. Also as information super highway becomes common with development or network technology, multimedia Web site is on the rise due to various use of multimedia attributes. Therefore this study expands to apply HTML based Web site quality evaluation studied in Software engineering, HCI, Hypermedia to multimedia Web site, and suggests new metrics by integrating flash usability which is expanding its portion in multimedia Web site lately. The Web metrics proposed in this study are verified by heuristic evaluation from a group of expert. It analyses the results of quantitative and qualitative qualify evaluation on Web Award Korea by comparing the award-winning, high-quality Web site with non-winning Web sites. This study can be used to establish guideline for high-quality multimedia Web site development in the future.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.225-234
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• 2016

The emergence of diverse medical Internet of Things (IoT) devices has facilitated the collection and analysis of medical contexts to assess health conditions. However, the complexity of IoT-based systems for health assessment is quiet high and it requires high development cost, since the designs of the systems highly depend on the heath aspects to be evaluated. In this paper, we propose a design of the platform that provides generic functionalities to various health evaluation applications. We first define a metric for computing a health index, which is a generic health assessment model. And, based on the proposed generic health index, we propose a design of the platform to evaluate diverse aspects of the health including its hardware architecture, software architecture and database design. We describe the result of developing Rainbow Toilet System based on the proposed platform, and assess the practical applicability.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1243-1258
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• 2017

A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.1-8
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• 2010

The key challenge in HW/SW co-design is how to choose the appropriate HW/SW partitioning from the vast array of possible options in the mapping set. In this paper we present a unique and efficient approach for addressing this problem known as Customized Heuristic Algorithm for Reducing Mapping Sets(CHARMS). CHARMS uses sensitivity to individual task computational complexity as well the computed weighted values of system performance influencing metrics to streamline the mapping sets and extract the most optimal cases. Using H.263 encoder, we show that CHARMS sieves out 95.17% of the sub-optimal mapping sets, leaving the designer with 4.83% of the best cases to select from for run-time implementation.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.159-168
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• 2022

The purpose of this study is to look at the precise direction and magnitude of cultural elements such as education, gender, power distance, and risk-taking proclivity on ethical decision-making. Data was collected from 194 interviewees in three groups: general business students, accounting major students, and professional auditors in Vietnam. The path analysis is used to test the impact of cultural factors on ethical awareness, ethical judgment, and ethical intention in different dubious scenarios at the personal level as independent variables, intermediate variables, and moderating variables. The metric is the percentage of respondents who believe a particular behavior is unethical based on a set of ethical principles. The researchers used SPSS AMOS software to conduct a confirmatory factor survey to evaluate the convergent and discriminant validity of latent variables. The results show differences between the two groups of students and professionals on these measures, suggesting that all of the four factors have an effect on ethical decision-making. Based on research results, some recommendations are proposed related to the four factors to improve the ethics of future generations of auditors in Vietnam. This study also contributes to the theory of culture in particular and cultural interference in general in the field of accounting-auditing in Vietnam in the process of international integration.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.41-49
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• 2024

Speech recognition technology is continuously advancing and widely used in various fields. In this study, we aimed to investigate the impact of speech data quality on speech recognition models by dividing the dataset into the entire dataset and the top 70% based on Signal-to-Noise Ratio (SNR). Utilizing Seamless M4T and Google Cloud Speech-to-Text, we examined the text transformation results for each model and evaluated them using the Levenshtein Distance. Experimental results revealed that Seamless M4T scored 13.6 in models using data with high SNR, which is lower than the score of 16.6 for the entire dataset. However, Google Cloud Speech-to-Text scored 8.3 on the entire dataset, indicating lower performance than data with high SNR. This suggests that using data with high SNR during the training of a new speech recognition model can have an impact, and Levenshtein Distance can serve as a metric for evaluating speech recognition models.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.27-33
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• 2024

The environment of academic research is continuously changing due to the increase of information, which raises the need for an effective way to analyze and organize large amounts of documents. In this paper, we propose Performance Improvement of Topic Modeling using BART(Bidirectional and Auto-Regressive Transformers) based Document Summarization. The proposed method uses BART-based document summary model to extract the core content and improve topic modeling performance using LDA(Latent Dirichlet Allocation) algorithm. We suggest an approach to improve the performance and efficiency of LDA topic modeling through document summarization and validate it through experiments. The experimental results show that the BART-based model for summarizing article data captures the important information of the original articles with F1-Scores of 0.5819, 0.4384, and 0.5038 in Rouge-1, Rouge-2, and Rouge-L performance evaluations, respectively. In addition, topic modeling using summarized documents performs about 8.08% better than topic modeling using full text in the performance comparison using the Perplexity metric. This contributes to the reduction of data throughput and improvement of efficiency in the topic modeling process.