• Journal of the Korean Society for Precision Engineering
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• v.9 no.1
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• pp.53-65
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• 1992

For improving the performance of maglev systems with a combined lift and guidance, it is suggested that the multivariable control systems and a secondary suspension should be added. The former is required to reject both track irregularities in vertical disturbances and wind gusts in lateral disturbances, and the latter to guarantee passengers against an unsatisfied criteria in ride quality. In this paper, bond graph model for the study of nonlinear dynamics of maglev systems with a combined lift and guidance is presented briefly. And, the secondary suspension is analyzed to understand the role of stiffness and damping factors in passive devices. Finally, LQG/LTR mulitivariable control systems are designed for the overall maglev systems with and without secondary suspension, and then the system performances in these two cases are evaluated.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.27-30
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• 2001

일반적인 운영체제의 보안과 마찬가지로 데이터베이스에서도 보안의 중요성은 강조되고 있다. 다중등급을 가지고 있는 데이터베이스에서 상위등급의 사용자가 사용하는 상위등급 데이터가 하위등급의 사용자가 사용하는 하위등급 데이터로 유입된다면 데이터의 무결성(integrity)이 깨지게 되어 데이터베이스뿐만 아니라 시스템 전체의 보안도 위협받게 된다. 본 연구에서는 대량의 데이터베이스 환경에서 다양한 보안등급을 가지고 있는 사용자가 다양한 등급을 가지고 있는 데이터베이스에 접근할 때 이를 강제적 접근제어(MAC:Mandatory Access Control)와 역할기반 접근제어(RBAC:Role-Based Access Control) 그래프를 이용해 사용자 보안등급에 따른 접근과 상위등급의 데이터가 하위등급으로 유출되지 않도록 이를 효율적으로 관리하고 제어할 수 있는 보안 모델을 제시하는데 중점을 두었다.

• ETRI Journal
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• v.41 no.4
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• pp.437-451
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• 2019

Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed. Unfortunately, most of these techniques still have some potential limitations, that is, (a) high rate of false positives, (b) high time complexity, and (c) failure to detect outliers online. Moreover, these approaches mainly focus on either temporal outliers or spatial outliers. Therefore, this paper aims to introduce novel algorithms that successfully detect both temporal outliers and spatial outliers. Our contributions are twofold: (i) modifying the Hampel Identifier (HI) algorithm to achieve high accuracy identification rate in temporal outlier detection, (ii) combining the Gaussian process (GP) model and graph-based outlier detection technique to improve the performance of the algorithm in spatial outlier detection. The results demonstrate that our techniques outperform the state-of-the-art methods in terms of accuracy and work well with various data types.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.197-212
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• 2022

The study uses the audited financial statements of 26 Vietnamese commercial banks listed on the Ho Chi Minh City Stock Exchange (HOSE) and Hanoi Stock Exchange (HOSE) during the 2008-2018 period to estimate the system GMM model, which provides empirical evidence on the effect of the variables of customer deposit to total assets (DEPO) ratio, loan to assets (LTA) ratio, liquidity of commercial banks (LIQ), credit development (CRD) ratio, external funding (EFD) ratio, and credit loss provision (LLP) ratio on liquidity risk. The study confirms that commercial banks' internal factors play the most important role, and there is no empirical evidence on macro variables that affect liquidity risk. Finally, in accordance with the theoretical framework, the study uses an estimation method with the R language and the bootstrap methodology to give empirical proof of the nonlinear correlation and U-shaped graph between commercial bank size and liquidity risk. The importance of commercial bank size in absorbing and moderating the effects of liquidity shocks is demonstrated, however, excessive growth in commercial bank size would increase liquidity risk in commercial bank operations.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.310-322
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• 2023

Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.81-92
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• 2003

Generalized LR parsing is one of the enhanced LR parsing methods so that it overcome the limit of one-way linear stack of the traditional LR parser using graph-structured stack, and it has been playing an important role of a firm starting point to generate other variations for NL parsing equipped with various mechanisms. In this paper, we propose a conditional Action Model that can solve the problems of conventional probabilistic GLR methods. Previous probabilistic GLR parsers have used relatively limited contextual information for disambiguation due to the high complexity of internal GLR stack. Our proposed model uses Surface Phrasal Types representing the structural characteristics of the parse for its additional contextual information, so that more specified structural preferences can be reflected into the parser. Experimental results show that our GLR parser with the proposed Conditional Action Model outperforms the previous methods by about 6-7% without any lexical information, and our model can utilize the rich stack information for syntactic disambiguation of probabilistic LR parser.

• Information Systems Review
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• v.19 no.1
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• pp.49-74
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• 2017

The development of smart devices has affected employees' working environments and their lives. However, using smart devices is causing employees to experience technostress. This study aims to investigate the effects of technostress in using smart devices on usage intention in an organization. Moreover, the study investigates the effect of employees' stress-coping methods on the intention to use smart devices. This study posits familiarity, use innovativeness, role ambiguity, system vulnerability, technological limitation, and ubiquity as the antecedents of technostress. Data collected from 317 users who have experience in using smart devices in organizations are empirically tested against a research model using the PLS graph. Analysis results show that role ambiguity, system vulnerability, and technological limitation significantly influence technostress. Moreover, users take up emotion-focused coping behaviors because of technostress. Emotion-focused coping behaviors affect usage intention in organizations. However, technostress and problem-focused coping behaviors do not directly affect usage intention in organizations.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.615-623
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• 2006

A non-functional requirement is a property or quality that the proposed systems have to support the functional requirements. A non-functional requirement is reflected by quality attribute These non-functional requirements playa crucial role during system development, serving as selection criteria for choosing among decisions. It should be continuously considered through the software development process. In spite of the importance of the non-functional requirements, it received little attention because of ambiguousness and invisibility of non-functional requirements. Therefore non-functional model which is a process to analyze the non-functional requirement is proposed for improving the management efficiency of non-functional requirements. Also, this paper presents the trace among the UML diagrams to the conceptual model. According to the non-functional requirement development process, this paper achieved performance-based case study. After then, non-functional requirement should be traced using the UML diagrams.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.24-34
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• 2021

The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

• Journal of Astronomy and Space Sciences
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• v.39 no.1
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• pp.1-10
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• 2022

The universe is thought to be filled with not only Standard Model (SM) matters but also dark matters. Dark matter is thought to play a major role in its construction. However, the identity of dark matter is as yet unknown, with various search methods from astrophysical observartion to particle collider experiments. Because of the cross-section that is a thousand times smaller than SM particles, dark matter research requires a large amount of data processing. Therefore, optimization and parallelization in High Performance Computing is required. Dark matter in hypothetical hidden sector is though to be connected to dark photons which carries forces similar to photons in electromagnetism. In the recent analysis, it was studied using the decays of a dark photon at collider experiments. Based on this, we studies double dark photon decays at lepton colliders. The signal channels are e⁺e^- → A'A' and e⁺e^- → A'A'γ where dark photon A' decays dimuon. These signal channels are based on the theory that dark photons only decay into heavily charged leptons, which can explain the muon magnetic momentum anomaly. We scanned the cross-section according to the dark photon mass in experiments. MadGraph5 was used to generate events based on a simplified model. Additionally, to get the maximum expected number of events for the double dark photon channel, the detector efficiency for several center of mass (CM) energy were studied using Delphes and MadAnalysis5 for performance comparison. The results of this study will contribute to the search for double dark photon channels at lepton colliders.