• International conference on construction engineering and project management
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• 2015.10a
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• pp.559-563
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• 2015

Identification of energy use patterns in buildings has a great opportunity for energy saving. To find what energy use patterns exist, clustering analysis has been commonly used such as K-means and hierarchical clustering method. In case of high dimensional data such as energy use time-series, data reduction should be considered to avoid the curse of dimensionality. Principle Component Analysis, Autocorrelation Function, Discrete Fourier Transform and Discrete Wavelet Transform have been widely used to map the original data into the lower dimensional spaces. However, there still remains an ongoing issue since the performance of clustering analysis is dependent on data type, purpose and application. Therefore, we need to understand which data reduction techniques are suitable for energy use management. This research aims find the best clustering method using energy use data obtained from Seoul National University campus. The results of this research show that most experiments with data reduction techniques have a better performance. Also, the results obtained helps facility managers optimally control energy systems such as HVAC to reduce energy use in buildings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1959-1968
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• 2016

The recent automobiles, a number of ECU inside the vehicle has been used. Also, each ECU is connected to different types of networks in accordance with the characteristics. Therefore, efficient data exchange between discrete network has emerged as a very important element. The gateway is responsible for the ability to exchange data between discrete network. In this study, we propose the new gateway algorithm to provide the structure of the mapping table to improve the efficiency of data exchange between discrete network. Also it provides a structure of a new gateway algorithm with a function of adjusting the priority of the data to be transmitted to another network arbitrarily. Moreover, the proposed gateway structure may simultaneously convert the transmission data input from a particular network to multiple networks. Another advantage is easy to change the entire data structure only if we change the table structure in the gateway.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.309-320
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• 2020

Bayesian networks, also known as directed acyclic graphs (DAG), are used in many areas of medicine, meteorology, and genetics because relationships between variables can be modeled with graphs and probabilities. In particular, Bayesian network classifiers, which are used to predict discrete data, have recently become a new method of data mining. Bayesian networks can be grouped into different models that depend on structured learning methods. In this study, Bayesian network models are learned with various properties of structure learning. The models are compared to the simplest method, the naïve Bayes model. Classification results are compared by applying learned models to various real data. This study also compares the relationships between variables in the data through graphs that appear in each model.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.201-208
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• 2016

Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.1-11
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• 2023

Smart factory environments and digital twin environments are established, and today's factories accumulate vast amounts of production data and are managed in real time as visualized results suitable for user convenience. Production simulation techniques are in the spotlight as a way to prevent delays in delivery and predict factory volatility in situations where production schedule planning becomes difficult due to the diversification of production products. With the development of the digital twin environment, new packages are developed and functions of existing packages are updated, making it difficult for users to make decisions on which packages to use to develop simulations. Therefore, in this study, the concept of Discrete Event Simulation (DES) performed based on discrete events is defined, and the characteristics of various simulation packages were compared and analyzed. To this end, studies that solved real problems using discrete event simulation software for 10 years were analyzed, and three types of software used by the majority were identified. In addition, each package was classified by simulation technique, type of industry, subject of simulation, country of use, etc., and analysis results on the characteristics and usage of DES software were provided. The results of this study provide a basis for selection to companies and users who have difficulty in selecting discrete event simulation package in the future, and it is judged that they will be used as basic data.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.2
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• pp.276-286
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• 1995

In this study, pressure drop and heat transfer coefficients were measured in tubes with three dimensional roughness. Dimples were made by rotating the saw-tooth shaped finning disc on the outer tube surface. Resultant dimple shape was oval. Friction and heat transfer tests were performed with a range of roughness variables-roughness height 'e', axial roughness pitch 'p', circumferential roughness pitch 'z'. Within the test range, tube with e=0.5mm, z=5mm, p=3mm performed best. The efficiency ratio(rati of the heat transfer improvement and the pressure drop increase) of the tube approached 1.0 at low Reynolds number, and it was higher than that of the two-dimensional roughess tube of the same roughness height. Test data were predicted by 'discrete element method'. Results show that discrete element method underpredicts the friction data by 2% to 32%, and overpredicts the heat transfer data by-12% to 113%.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2399-2410
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• 2017

In this paper, a linear matrix inequality-based sampled-data fuzzy observer design method is proposed based on the exact discretization approach. In the proposed design technique, a numerically relaxed observer design condition is obtained by using the discrete-time fuzzy Lyapunov function. Unlike the existing studies, the designed observer is robust to the uncertain premise variable because the fuzzy observer is designed under the imperfect premise matching condition, in which the membership functions of the system and observer are mismatched. In addition, we apply the proposed method to the state estimation problem of the attitude and heading reference system (AHRS). To do this, we derive a Takagi-Sugeno fuzzy model for the AHRS system, and validate the proposed method through the hardware experiment.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.281-283
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• 2005

Processing Plasmas are very sensitive to a variation in process parameters, To maintain process quality and device field, plasma malfunction should be tightly monitored with high sensitivity. A new monitoring method is presented and this was accomplished by applying discrete wavelet transformation to X-ray photoelectron spectroscopy. XPS data were collected during a plasma etching of silicon carbide. Various effects of DWT factor on fault sensitivity were optimized experimentally. Compared to raw data, total percent sensitivity for DWT data demonstrated a significantly improved sensitivity to plasma faults induced by bias power.

• The Journal of the Acoustical Society of Korea
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• v.16 no.1E
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• pp.29-34
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• 1997

Numerical prediction of aerodynamic noise radiated by subsonic rotors are carried out. A computer program has been developed which incorporates both the discrete frequency noise as well as the broadband noise arising from the ingestion of turbulence. Acoustic analogy is used in conjunction with Homicz's formulation of turbulence ingestion noise. Formulation 1A of Farassat is used to enhance the numerical analysis performance of Ffowcs-Williams Hawkings equation by eliminating the numericla time differentiation. Homicz's trubulence ingestion noise prediction technique is used to understand the characteristics of broadband noise radiated by isotropic trubulence in gestion. Numerical predictions are carried out for a number of rotor configurations and compared with experimental data. Monopole consideration of transonic rotor agrees well with both the experimental data and the linear theory. Noise radiation characteristics of rotor at lifting hover are investigated utilizing simple blade loading obtained by thin wing section theory. By incorporating discrete noise prediction of steady loading with broadband spectrum, much better agreement with experimental data is obtained in the low frequency region. The contributions from different noise mechanisms can also be analyzed through this method.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.294-301
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• 2016

In this paper, we present methods to efficiently parallelize iterative 3D image reconstruction by exploiting trigeneous devices (three different types of device) at the same time: a CPU, an integrated GPU, and a discrete GPU. We first present a technique that exploits single instruction multiple data (SIMD) architectures in GPUs. Then, we propose a performance estimation model, based on which we can easily find the optimal data partitioning on trigeneous devices. We found that the performance significantly varies by up to 6.23 times, depending on how SIMD units in GPUs are accessed. Then, by using trigeneous devices and the proposed estimation models, we achieve optimal partitioning and throughput, which corresponds to a 9.4% further improvement, compared to discrete GPU-only execution.