• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.409-413
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• 2005

The logical analysis of data(LAD) is an effective Boolean-logic based data mining tool. A critical step in analyzing data by LAD is the pattern generation stage where useful knowledge and hidden structural information in data is discovered in the form of patterns. A conventional method for pattern generation in LAD is based on term enumeration that renders the generation of higher degree patterns practically impossible. In this paper, we present a new optimization-based pattern generation methodology and propose two mathematical programming medels, a mixed 0-1 integer and linear programming(MILP) formulation and a well-studied set covering problem(SCP) formulation for the generation of optimal and heuristic patterns, respectively. With benchmark datasets, we demonstrate the effectiveness of our models by automatically generating with much ease patterns of high complexity that cannot be generated with the conventional approach.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.309-315
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• 2012

Active data are the input data which are changed its membership as Vector Quantization codebook generation algorithm is processed. In the process of VQ codebook generation algorithm performed, the actual active data out of the entire input data will be less presented as the process is performed. Therefore, if we can accurately find the active data and only if we are going to do VQ codebook generation on the active data, then we can significantly reduce the overall generation time. In this paper, we presented the triangle inequality based algorithm to select the active data. Experimental results show that our algorithm is superior to other methods in terms of the VQ codebook generation time.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.3
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• pp.108-114
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• 2014

On a large scale of data center, heat generation rates from sever computers occupy almost the entire cooling load of the building, and it is gradually increasing. The efficiency of air distribution system in data centers can be affected by heat generation rates of server computers. In this study, the distributions of airflow and temperature in a data center have been investigated by CFD simulations under various conditions of heat generation rates for server computers. From the results, air around the cold aisle which has high temperature flows tremendously into the cold aisle according to the increase of heat generation rates for server computers and the air temperature in the cold aisle becomes higher. The SHI (supply heat index) and RHI (return temperature index) show almost similar values to the cases study because the air inflow rates to server computers increase with the heat generation rates of server computers.

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.62-69
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• 2013

In this paper, Korea Institute of Energy Research, building integrated renewable energy monitoring system that utilizes solar power generation forecast data forecast model is proposed. Renewable energy integration of real-time monitoring system based on monitoring data were building a database and the database of the weather conditions and to study the correlation structure was tailoring. The weather forecast cloud cover data, generation data, and solar radiation data, a data mining and time series analysis using the method developed models to forecast solar power. The development of solar power in order to forecast model of weather forecast data it is important to secure. To this end, in three hours, including a three-day forecast today Meteorological data were used from the KMA(korea Meteorological Administration) site offers. In order to verify the accuracy of the predicted solar circle for each prediction and the actual environment can be applied to generation and were analyzed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.498-504
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• 2006

This paper describes the simple payback period analysis of small co-generation system based on the existing apartment and building data. First, We investigate apartment and building data more than $2000[m^2]$ using Ministry of Construction & Transportation's computer system. And then we calculate the latent amount of small co-generation system considering gas company and CHP. Second, we classify the latent amount of small co-generation system into office, hospital, hotel, department store, complex building and apartment. Finally, we perform the simple payback period analysis for small co-generation system. The results show the simple payback period of small co-generation system is less then 10 years.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.11-18
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• 2006

The logical analysis of data(LAD) is a Boolean-logic based data mining tool. A critical step in analyzing data by LAD is the pattern generation stage where useful knowledge and hidden structural information in data is discovered in the form of patterns. A conventional method for pattern generation in LAD is based on term enumeration that renders the generation of higher degree patterns practically impossible. In this paper, we present a novel optimization-based pattern generation methodology and propose two mathematical programming models, a mixed 0-1 integer and linear programming (MILP) formulation and a well-studied set covering problem (SCP) formulation for the generation of optimal and heuristic patterns, respectively. With benchmark datasets, we demonstrate the effectiveness of our models by automatically generating with ease patterns of high complexity that cannot be generated with the conventional approach.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.3-12
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• 2020

Nowadays, as-is BIM generation has been popularly adopted in the architecture, engineering, construction and facility management (AEC/FM) industries. In order to generate a 3D as-is BIM of a structural component, current methods require a registration process that merges different sets of point cloud data obtained from multiple locations, which is time-consuming and registration error-prone. To tackle this limitation, this study proposes a registration-free 3D point cloud data acquisition technique for as-is BIM generation. In this study, small-size mirrors that rotate in both horizontal and vertical direction are used to enable the registration-free data acquisition technique. First, a geometric model that defines the relationship among the mirrors, the laser scanner and the target component is developed. Second, determinations of optimal laser scanner location and mirror location are performed based on the developed geometrical model. To validate the proposed registration-free as-is BIM generation technique, simulation tests are conducted on key construction components including a PC slab and a structural wall. The result demonstrates that the registration-free point cloud data acquisition technique can be applicable in various construction elements including PC elements and structural components for as-is BIM generation.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.753-756
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• 2024

This study integrates Rivet and Retrieved Augmented Generation (RAG) technologies to enhance automated report generation, addressing the challenges of large-scale data management. We introduce novel algorithms, such as Dynamic Data Synchronization and Contextual Compression, expected to improve report generation speed by 40% and accuracy by 25%. The application, demonstrated through a model corporate entity, "Company L," shows how such integrations can enhance business intelligence. Empirical validations planned will utilize metrics like precision, recall, and BLEU to substantiate the improvements, setting new benchmarks for the industry. This research highlights the potential of advanced technologies in transforming corporate data processes.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.79-84
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• 2023

Image generation models have been applied in various fields to overcome data sparsity, time and cost issues. However, it has limitations in generating images from regular pattern images and detecting defects in such data. In this paper, we verified the feasibility of the image generation model to generate pattern images and applied it to data augmentation for defect detection of OLED panels. The data required to train an OLED defect detection model is difficult to obtain due to the high cost of OLED panels. Therefore, even if the data set is obtained, it is necessary to define and classify various defect types. This paper introduces an OLED panel defect data acquisition system that acquires a hypothetical data set and augments the data with an image generation model. In addition, the difficulty of generating pattern images in the diffusion model is identified and a possibility is proposed, and the limitations of data augmentation and defect detection data augmentation using the image generation model are improved.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.5
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• pp.496-510
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• 2016

Simulation technology is a type of shipbuilding product lifecycle management solution used to support production planning or decision-making. Normally, most shipbuilding processes are consisted of job shop production, and the modeling and simulation require professional skills and experience on shipbuilding. For these reasons, many shipbuilding companies have difficulties adapting simulation systems, regardless of the necessity for the technology. In this paper, the data model for shipyard production simulation model generation was defined by analyzing the iterative simulation modeling procedure. The shipyard production simulation data model defined in this study contains the information necessary for the conventional simulation modeling procedure and can serve as a basis for simulation model generation. The efficacy of the developed system was validated by applying it to the simulation model generation of the panel block production line. By implementing the initial simulation model generation process, which was performed in the past with a simulation modeler, the proposed system substantially reduced the modeling time. In addition, by reducing the difficulties posed by different modeler-dependent generation methods, the proposed system makes the standardization of the simulation model quality possible.