• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.666-667
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• 2019

우리 주위에는 많은 '평화의 소녀상'이 있지만, 소녀상의 위치나 역사적 의미 같은, 보다 자세한 정보를 얻기는 직접 찾아보지 않으면 얻기 어려운 것이 현실이다. 이에 본 연구에서는 증강현실(Augmented Reality)을 이용하여, 주변 소녀상의 위치 및 시각적 경로 안내뿐 아니라 웹을 이용한 각 소녀상 별 피드(Feed)를 통해 다양한 역사적 정보를 제공 및 공유하고자 한다.

• Nuclear Engineering and Technology
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• v.37 no.1
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• pp.109-117
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• 2005

Limiting conditions for operations (LCOs) are evaluated dynamically using the tool of system dynamics. The LCOs de-fine the allowed outage times (AOTs) and the actions to be taken if the repair cannot be completed within the AOT. System dynamics has been developed to analyze the dynamic reliability of a complicated system. System dynamics using Vensim software have been applied to LCOs assessment for an example system, the auxiliary feed water system of a reference nuclear power plant. Analysis results of both full power operation and shutdown operation have been compared for a measure of core damage frequency. The framework developed in this study has been shown to be very flexible in that it can be applied to assess LCOs quantitatively under any operational context of the TS in FSAR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1234-1257
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• 2023

In this paper, we propose a framework for multi-focus image fusion called PATN. In our approach, by aggregating deep features extracted based on the U-type Transformer mechanism and shallow features extracted using the PSA module, we make PATN feed both long-range image texture information and focus on local detail information of the image. Meanwhile, the edge-preserving information value of the fused image is enhanced using a dense residual block containing the Sobel gradient operator, and three loss functions are introduced to retain more source image texture information. PATN is compared with 17 more advanced MFIF methods on three datasets to verify the effectiveness and robustness of PATN.

• Journal of the Ergonomics Society of Korea
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• v.35 no.6
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• pp.535-550
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• 2016

Objective: To enhance user experience of the product by using "wow" materials and parts, a framework for participatory emotional design and evaluation was proposed and validated through a case study in this paper. Background: Customers in recent days value a product which provides new feeling and images they want to get while interacting with it beyond its function, quality, and usability. Since the product consists of various parts and materials, "wow" materials and parts which can affect the customer's feeling and emotions are the essential components for changing the user experience. Method: A framework for participatory and human sensibility ergonomic design was considered and applied on developing the aesthetically and emotionally affecting glass panels of changing colors. Design experts defined a target market for this multicolor glass panels and modified the existing designing goal. Constraints for this design modification were identified by market trend research and consulting with the company which owns the technology for checking out its feasibility. The company developed and provided prototype samples as well as their competing materials. Quantitative and qualitative evaluation of the emotional quality was conducted to validate whether the design goal was achieved successfully. Results: The target market for the developing materials was defined as finishing for the buildings. The designing goal was set as to feed new visual sensation of clean and colorful images. The emotional quality of two different types of multicolor glass panels and an ordinary unicolor panel were evaluated quantitatively with semantic differential method. Results showed that the emotion of the subjects for the multicolor glass panels can be abstracted into two dimensions; named 'colorfulness' and 'harmony'. It was found that the developed samples got higher scores in emotional quality for both dimensions compared to the ordinary one. Age was found to be a significant factor for evaluating the emotional quality of colorfulness. Conclusion and Applications: The proposed framework is a valid approach for enhancing the user experience of the product by participatory design of emotional materials and parts. This framework can be applied easily on the emotional design and evaluation of different materials and components.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.1
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• pp.84-92
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• 1999

The rumen microbial ecosystem is coming to be recognized as a rich alternative source of genes for industrially useful enzymes. Recent advances in biotechnology are enabling development of novel strategies for effective delivery and enhancement of these gene products. One particularly promising avenue for industrial application of rumen enzymes is as feed supplements for nonruminant and ruminant animal diets. Increasing competition in the livestock industry has forced producers to cut costs by adopting new technologies aimed at increasing production efficiency. Cellulases, xylanases, ${\beta}$-glucanases, pectinases, and phytases have been shown to increase the efficiency of feedstuff utilization (e.g., degradation of cellulose, xylan and ${\beta}$-glucan) and to decrease pollutants (e.g., phytic acid). These enzymes enhance the availability of feed components to the animal and eliminate some of their naturally occurring antinutritional effects. In the past, the cost and inconvenience of enzyme production and delivery has hampered widespread application of this promising technology. Over the last decade, however, advances in recombinant DNA technology have significantly improved microbial production systems. Novel strategies for delivery and enhancement of genes and gene products from the rumen include expression of seed proteins, oleosin proteins in canola and transgenic animals secreting digestive enzymes from the pancreas. Thus, the biotechnological framework is in place to achieve substantial improvements in animal production through enzyme supplementation. On the other hand, the rumen ecosystem provides ongoing enrichment and natural selection of microbes adapted to specific conditions, and represents a virtually untapped resource of novel products such as enzymes, detoxificants and antibiotics.

• Korean Membrane Journal
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• v.7 no.1
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• pp.1-18
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• 2005

The permeate flux decline due to membrane fouling can be addressed using a variety of theoretical stand-points. Judicious selection of an appropriate theory is a key toward successful prediction of the permeate flux. The essential criterion f3r such a decision appears to be a detailed characterization of the feed solution and membrane properties. Modem theories are capable of accurately predicting several properties of colloidal systems that are important in membrane separation processes from fundamental information pertaining to the particle size, charge, and solution ionic strength. Based on such information, it is relatively straight-forward to determine the properties of the concentrated colloidal dispersion in a polarized layer or the cake layer properties. Incorporation of such information in the framework of the standard theories of membrane filtration, namely, the convective diffusion equation coupled with an appropriate permeate transport model, can lead to reasonably accurate prediction of the permeate flux due to colloidal fouling. The schematic of the essential approach has been delineated in Figure 5. The modern approaches based on appropriate cell models appear to predict the permeate flux behavior in crossflow membrane filtration processes quite accurately without invoking novel theoretical descriptions of particle back transport mechanisms or depending on adjust-able parameters. Such agreements have been observed for a wide range of particle size ranging from small proteins like BSA (diameter ${\~}$6 nm) to latex suspensions (diameter ${\~}1\;{\mu}m$). There we, however, several areas that need further exploration. Some of these include: 1) A clear mechanistic description of the cake formation mechanisms that clearly identifies the disorder to order transition point in different colloidal systems. 2) Determining the structure of a cake layer based on the interparticle and hydrodynamic interactions instead of assuming a fixed geometrical structure on the basis of cell models. 3) Performing well controlled experiments where the cake deposition mechanism can be observed for small colloidal particles (< $1\;{\mu}m$). 4) A clear mechanistic description of the critical operating conditions (for instance, critical pressure) which can minimize the propensity of colloidal membrane fluting. 5) Developing theoretical approaches to account for polydisperse systems that can render the models capable of handing realistic feed solutions typically encountered in diverse applications of membrane filtration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.113.1-113.1
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• 2010

IGCC(Integrated Coal Gasification and Combined Cycle) plants can be among the most advanced and environmental systems for electric energy generation from various feed stocks and is becoming more and more popular in new power generation fields. In this work, the performance of IGCC plants employing Shell gasification technology and a GE 7FB gas turbine engine was simulated using IPSEpro open-equation modeling environment for different operating conditions. Performance analyses and comparisons of all operating cases were performed based on the design cases. Discussions were focused on gas composition, syngas production rate and overall performance. The validation of key steady-state performance values calculated from the process models were compared with values from the provided heat and material balances for Shell coal gasification technology. The key values included in the validation included the inlet coal flow rate; the mass flow rate, heating value, and composition of major gas species (CO, H2, CH4, H2O, CO2, H2S, N2, Ar) for the syngas exiting the gasifier island; and the HP and MP steam flows exiting the gasifier island.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1705-1720
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• 2013

Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.

• Proceedings of the KAIS Fall Conference
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• 2011.12b
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• pp.529-532
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• 2011

Recently research efforts for ubiquitous technology that includes RFID(Radio Frequency Deification and sensor networks are conducted very actively The architectural framework of the USN sensor network discovery service. The survey of the USN technology is conducted on four technological visions that contain USN system technology USN networking technology and USN middleware along with the service platform, With respect to each technological division domestic and worldwide leading research projects are primarily explored with their technical features and research projects are primarily explored with their technical features and research outputs. Boasted on the result of the survey we establish a USN software model that includes data sensing, sensor data storage sensor data storage sensor data naming and sensor feed name service. This main objective of this model is to provide a reference model for the facilitation of USN application developments.