• Nuclear Engineering and Technology
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• v.37 no.1
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• pp.101-108
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• 2005

The neutron induced nuclear cross-section data for Pd-105, Ag-109, Xe-131, and Cs-133 were calculated and evaluated from an unresolved energy to 20 MeV. The energy dependent optical model potential parameters were extracted based on recent experimental data and applied up to 20 MeV. A spherical optical model and a statistical model for the equilibrium energy, and a multistep direct and a multistep compound model for the pre-equilibrium energy were used in the calculation. The direct capture model was recently introduced for fast neutron capture. The theoretically calculated cross-sections were compared with the experimental data and the evaluated files. The total and capture cross-sections calculated using the model were in good agreement with the reference experimental data. The evaluated cross-section results were compiled in ENDF-6 format and merged with the resonance component, already adopted in the ENDF/B-VI release 8. New data library files covering from thermal to 20 MeV were created. They are at the preliminary stage of an ENDF/B- VII release.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.348-354
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• 2018

This study proposes MF (Model Filter)-based M-BDL (MF-based BIM Data Linkage), which is a model filter-based data mapping method for BIM (Building Information Modeling)-BEMS linkage. Recently, BEMS (Building Energy Management System) is actively utilizing 3D spatial information. This allows the user to intuitively manage the facility energy linked to spatial information. To use BIM data in energy management systems, it is essential to link BEMS with BIM data only in terms of the user requirements. On the other hand, if the BIM is a rich dataset and is linked as it is, the user will need to manage the unnecessary information. By mapping only the data required for BEMS in heavy BIM data through M-BDL, the BIM data can be lightened and the amount of data required for maintenance can be reduced. This technology proposes a mapping method that can link the BIM data with the filtered BIM data.

• 건축구조
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• v.19 no.4
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• pp.51-60
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• 2012

In recent years, BIM has been applied to many building projects. However, IFC, which is the core technology of data exchange in BIM, has not been used widely. In particular, IFC has almost never been used to represent rebars in RC structures. This is because the lack of understanding and utilization strategy for data model of IFC on rebars. The purpose of this study is to store and manage the data on rebars using IFC at the schematic design stage. For this, we investigated the data to represent rebars for RC members, such as beam, column, wall, and slab at the schematic design stage. And, we analyzed the data model of IFC on rebars at the schematic design stage. Based on these investigation and analysis on data, we proposed the strategy for utilization of the data model of IFC on rebars. Finally, for verification, we generated a sample IFC file to represent the rebars of a simple RC structure according to the proposed strategy and imported the sample IFC file into the software, which we developed for this study. Based on the results of the import, we concluded that the data on rebars can be stored and managed using the proposed strategy for utilization of the data model of IFC on rebars.

• Journal of KIBIM
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• v.8 no.3
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• pp.12-19
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• 2018

The research aims to find implications of machine learning and urban big data as a way to construct the flexible transportation network system of smart city by responding the urban context changes. This research deals with a problem that existing a bus headway model is difficult to respond urban situations in real-time. Therefore, utilizing the urban big data and machine learning prototyping tool in weathers, traffics, and bus statues, this research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data is gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is implemented by the machine learning tool (RapidMiner Studio) and conducted several tests for bus delays prediction according to specific circumstances. As a result, possibilities of transportation system are discussed for promoting the urban efficiency and the citizens' convenience by responding to urban conditions.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.3
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• pp.235-257
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• 2011

In this study, we proposed the FRAD concept model of authority data schema for author, organization and journal titles included in the academic papers. Academic information includes author names, affiliations, publishers, journals and conferences. They are used as access points, and there are multiple relationships among these entities. It is expected that the use of authority data for academic information based on FRAD conceptual model could improve more accurate retrieval of information, systematic management of academic information, and various forms of knowledge representation. In this study, our entity-relationship authority data will be linked to the document, and included the several properties and relationship to identify the object.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.41-50
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• 2021

The purpose of this study is to analyze various energy platforms using data in the US and to suggest directions and implications. Some of the leading energy platforms are selected and analyzed based on the opening platform model. We focus on the case analysis of the US utility companies. In case of the horizontal open platform, Green Button sponsor's 'Connect My Data (CMD)' driven by the government invites the utility companies to jointly develop the sponsor's data solution. In case of the vertical open platform, the certification program 'Share My Data (SMD)' allows backward compatibility, because the technical improvement is minimal. The utility companies benchmark Amazon's three-sided market mediation and prefer platform and category exclusivity. For the former, they have data analytics companies like Enervee, Opower and for the latter, they have electronics manufactures and energy service providers (ESPs) like Distributed Energy Resources (DERs). Based on this US case study, we suggest the energy platforms to open their platform for renewable energy supply, energy conservation, high-efficiency products, and residential DER dissemination. To successfully implement the government's energy transition policy, the US platforms should be benchmarked as a business model. Especially, it is needed for them to coordinate a platform ecosystem. To ensure trust in the products and services offered on the marketplace platform, platform's certification program is helpful.

• Architectural research
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• v.8 no.1
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• pp.77-84
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• 2006

In spite of enormous increase in data generation, its practical usage in the construction sector has not been prevalent enough compared to those of other industries. The author would explore the obstacles against efficient data application in the arena of expenditure forecasting, and suggest a forecasting method by applying Case-based Reasoning (CBR). The newly suggested method in the research, enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. Among 99 projects collected, the cost data from 88 projects were processed to establish a new forecasting model. The remaining 10 projects were utilized for the validation of the model. From the comprehensive study, the choice of the numbers of referring projects was investigated in detail. It is concluded that selecting similar projects at 12~19 % out of the whole database will produce a more precise forecasting. The new forecasting model, which suggests the predicted values based on previous projects, is more than just a forecasting methodology; it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the knowledge derived from invaluable experience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3328-3349
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• 2020

With rapid development of ubiquitous computing and location-based services (LBSs), human trajectory data and associated activities are increasingly easily recorded. Inappropriately publishing trajectory data may leak users' privacy. Therefore, we study publishing trajectory data while preserving privacy, denoted privacy-preserving activity trajectories publishing (PPATP). We propose S-PPATP to solve this problem. S-PPATP comprises three steps: modeling, algorithm design and algorithm adjustment. During modeling, two user models describe users' behaviors: one based on a Markov chain and the other based on the hidden Markov model. We assume a potential adversary who intends to infer users' privacy, defined as a set of sensitive information. An adversary model is then proposed to define the adversary's background knowledge and inference method. Additionally, privacy requirements and a data quality metric are defined for assessment. During algorithm design, we propose two publishing algorithms corresponding to the user models and prove that both algorithms satisfy the privacy requirement. Then, we perform a comparative analysis on utility, efficiency and speedup techniques. Finally, we evaluate our algorithms through experiments on several datasets. The experiment results verify that our proposed algorithms preserve users' privay. We also test utility and discuss the privacy-utility tradeoff that real-world data publishers may face.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.5
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• pp.400-407
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• 2011

The suggested method of previous Son's study dichotomized subjective response data to modeling noise exposure-response. The method used maximum liklihood estimation instead of least square estimation and the noise exposure-response curve of the study was logistic regression analysis result. The method was originated to modeling community response rate such as %HA or %A. It can be useful when the subjective response was investigated based on predicted noise level. It is difficult to measure the single source emitting noise such as railway because various traffic noise sources combined in our life. The suggested method was adopted to model in this study and railway noise-exposure response curves were modeled because the noise level of this area was predicted data. The data of this study was used by previous Ko's paper but he dealt the area as combined noise area and divided the data by dominant noise source. But this study used all data of this area because the annoyance response to railway noise was higher than other noise according to the result of correlation analysis. The trend of the %HA and %A prediction model to train noise of this study is almost same as the model based on measured noise of previous Lim's study although the investigated areas and methods were different.