• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• 조명전기설비학회논문지
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• 제28권12호
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• pp.30-37
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• 2014

Recently, Concerns of imbalance for power supply has been raised by the increase of electric power consumption, but the interest of electric safety is still lacking due to the incompleteness of regulations. Particularly, Arcing fault, direct cause of electric fire accidents, is difficult to detect, interrupt due to unformal signal behaviour in previous research and apply to real system. In this paper, Arcing fault simulator device was fabricated to investigate the characteristics of series arcing fault and simulated the faults in various real load. Also, this study are analysed arcing fault signal by using the harmonic analysis of the acquired data from the current of the power supply and proposed the methods to prevent the series arcing fault accidents in advance.

• 대한안전경영과학회지
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• 제9권5호
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• pp.157-165
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• 2007

Currently, there are two major problems in professional engineer(PE) licensure system in Korea to be accredited internationally. One is a incompleteness of system connecting the licensure and the accredited engineering education program and the other one is a insufficient working experience condition required for achieving PE license. Therefore, these two problems are setbacks hindering Korea's PE license accredited internationally. In this study, international tendency stream on mutual accreditation of PE license are reviewed first, and the PE licensure system of the major countries are compared and analyzed. Based on the results, requirements improvement plan are suggested and the gradual implementation method are suggested also.

• 전기학회논문지
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• 제60권3호
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• pp.486-491
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• 2011

Since Korea has high accident rate for the electrical shock than other advanced countries, it causes very serious problems. In this paper, a new classification method for analyzing electricity accidents is proposed, which is based on the microscopic view while existing methods have been based at the macroscopic view point. Electrical accidents cases can be mainly divided by three cases, which are from live works, incompleteness of the grounding system and imperfectness of the safety education and public relations. New data format of electrical shocks are proposed in the environment of smart grids.

• Nuclear Engineering and Technology
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• 제48권2호
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• pp.404-418
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• 2016

This paper presents a documentation and development method to facilitate the certification of scientific computing software used in the safety analysis of nuclear facilities. To study the problems faced during quality assurance and certification activities, a case study was performed on legacy software used for thermal analysis of a fuelpin in a nuclear reactor. Although no errors were uncovered in the code, 27 issues of incompleteness and inconsistency were found with the documentation. This work proposes that software documentation follow a rational process, which includes a software requirements specification following a template that is reusable, maintainable, and understandable. To develop the design and implementation, this paper suggests literate programming as an alternative to traditional structured programming. Literate programming allows for documenting of numerical algorithms and code together in what is termed the literate programmer's manual. This manual is developed with explicit traceability to the software requirements specification. The traceability between the theory, numerical algorithms, and implementation facilitates achieving completeness and consistency, as well as simplifies the process of verification and the associated certification.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.655-669
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• 2019

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

• 제어로봇시스템학회논문지
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• 제21권4호
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• pp.378-384
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• 2015

Indoor localization is becoming one of the most important technologies for smart mobile applications with different requirements from conventional outdoor location estimation algorithms. Fingerprinting location estimation techniques based on neural networks have gained increasing attention from academia due to their good generalization properties. In this paper, we propose a novel location estimation algorithm based on an ensemble of multiple neural networks. The neural network ensemble has drawn much attention in various areas where one neural network fails to resolve and classify the given data due to its' inaccuracy, incompleteness, and ambiguity. To the best of our knowledge, this work is the first to enhance the location estimation accuracy in indoor wireless environments based on a neural network ensemble using fingerprinting training data. To evaluate the effectiveness of our proposed location estimation method, we conduct the numerical experiments using the TGn channel model that was developed by the 802.11n task group for evaluating high capacity WLAN technologies in indoor environments with multiple transmit and multiple receive antennas. The numerical results show that the proposed method based on the NNE technique outperforms the conventional methods and achieves very accurate estimation results even in environments with a low number of APs.

• 천문학회지
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• 제50권2호
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• pp.21-27
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• 2017

The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

• Genomics & Informatics
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• 제7권3호
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• pp.159-162
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• 2009

Human personal genome sequencing can be done with high efficiency by aligning a huge number of short reads derived from various next generation sequencing (NGS) technologies to the reference genome sequence. One of the major obstacles is the incompleteness of human reference genome. We tried to analyze the effect of hidden gene duplication on the NGS data using the known example of hydin gene. Hydin2, a duplicated copy of hydin on chromosome 16q22, has been recently found to be localized to chromosome 1q21, and is not included in the current version of standard human genome reference. We found that all of eight personal genome data published so far do not contain hydin2, and there is large number of nsSNPs in hydin. The heterozygosity of those nsSNPs was significantly higher than expected. The sequence coverage depth in hydin gene was about two fold of average depth. We believe that these unique finding of hydin can be used as useful indicators to discover new hidden multiplication in human genome.

• 인터넷정보학회논문지
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• 제18권3호
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• pp.49-61
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• 2017

Wikipedia infoboxes have emerged as an important structured information source on the web. To compose infobox for an article, considerable amount of manual effort is required from an author. Due to this manual involvement, infobox suffers from inconsistency, data heterogeneity, incompleteness, schema drift etc. Prior works attempted to solve those problems by generating infobox automatically based on the corresponding article text. However, there are many articles in Wikipedia that do not have enough text content to generate infobox. In this paper, we present an automated approach to generate infobox for movie domain of Wikipedia by extracting information from several sources of the web instead of relying on article text only. The proposed methodology has been developed using semantic relations of article content and available semi-structured information of the web. It processes the article text through some classification processes to identify the template from the large pool of template list. Finally, it extracts the information for the corresponding template attributes from web and thus generates infobox. Through a comprehensive experimental evaluation the proposed scheme was demonstrated as an effective and efficient approach to generate Wikipedia infobox.