• KIPS Transactions on Software and Data Engineering
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• v.8 no.7
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• pp.311-316
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• 2019

Classification problem is to predict the class to which an input data belongs. One of the most popular methods to do this is training a machine learning algorithm using the given dataset. In this case, the dataset should have a well-balanced class distribution for the best performance. However, when the dataset has an imbalanced class distribution, its classification performance could be very poor. To overcome this problem, we propose an over-sampling scheme that balances the number of data by using Conditional Generative Adversarial Networks (CGAN). CGAN is a generative model developed from Generative Adversarial Networks (GAN), which can learn data characteristics and generate data that is similar to real data. Therefore, CGAN can generate data of a class which has a small number of data so that the problem induced by imbalanced class distribution can be mitigated, and classification performance can be improved. Experiments using actual collected data show that the over-sampling technique using CGAN is effective and that it is superior to existing over-sampling techniques.

• The Transactions of the Korea Information Processing Society
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• v.13 no.10
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• pp.545-552
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• 2024

As the 4^th Industrial Revolution progresses, the shipping logistics sector is becoming smarter by utilizing various core technologies such as AI, IoT, and Bigdata. In particular, the collected marine Bigdata plays a significant role in providing various services like vessel operation monitoring analysis and greenhouse gas emission evaluation, and it is also essential in shipping logistics. Although this maritime Bigdata is collected during actual vessel operations, there are instances where data is lost due to temporal and environmental factors. While It is important to identify and address the fundamental cause of such losses, it is also necessary to generate data through the utilization and analysis of the collected data. This paper develops an Emulator that repeatedly generates new location data, speed values, etc., using maritime transport data collected through empirical tests. The location data is generated by calculating the standard deviation from the collected position information, and the speed values are extracted from the generated location data. The generated data is accumulated by being inserted into the database in real-time. To demonstrate the performance of the Emulator, evperiments were conducted using 5 routes, providing its excellence.

• Journal of The Korean Association of Information Education
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• v.21 no.4
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• pp.393-401
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• 2017

The purpose of this study is to develop a deep learning based learning system for improving learner's data analytical thinking ability. The contents of the study are as follows. First, deep learning was applied to the discovery learning model to improve data analytical thinking ability. This is a learning method that can generate a model showing the relationship of given data by using the deep learning method, then apply the model to new data to obtain the result. Second, we developed a deep learning based system for DBD learning model. Specifically, we developed a system to generate a model of data using the deep learning method and to apply this model. The research of deep learning based learning system will be a new approach to improve learner's data analytical thinking ability in future society where data becomes more important.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.49-54
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• 2021

With the recent development of smart healthcare technology, interest in daily diseases is increasing. However, healthcare data has an imbalance between positive and negative data. This is caused by the difficulty of collecting data because there are relatively many people who are not patients compared to patients with certain diseases. Data imbalances need to be adjusted because they affect performance in ongoing learning during disease prediction and analysis. Therefore, in this paper, We replace missing values through multiple imputation in detection models to determine whether they are prevalent or not, and resolve data imbalances through over-sampling. Based on AutoML using preprocessed data, We generate several models and select top 3 models to generate ensemble models.

• Computers and Concrete
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• v.11 no.2
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• pp.149-167
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• 2013

The complete stress-strain behavior of steel fiber reinforced concrete in compression is needed for the analysis and design of structures. An experimental investigation was carried out to generate the complete stress-strain curve of high-performance steel fiber reinforced concrete (HPSFRC) with a strength range of 52-80 MPa. The variation in concrete strength was achieved by varying the water-to-cementitious materials ratio of 0.40-0.25 and steel fiber content (Vf = 0.5, 1.0 and 1.5% with l/d = 80 and 55) in terms of fiber reinforcing parameter, at 10% silica fume replacement. The effects of these parameters on the shape of stress-strain curves are presented. Based on the test data, a simple model is proposed to generate the complete stress-strain relationship for HPSFRC. The proposed model has been found to give good correlation with the stress-strain curves generated experimentally. Inclusion of fibers into HPC improved the ductility considerably. Equations to quantify the effect of fibers on compressive strength, strain at peak stress and toughness of concrete in terms of fiber reinforcing index are also proposed, which predicted the test data quite accurately. Compressive strength prediction model was validated with the strength data of earlier researchers with an absolute variation of 2.1%.

• Korean Journal of Computational Design and Engineering
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• v.18 no.1
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• pp.21-27
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• 2013

Presented in the paper is a log data based modeling method for effective construction of a virtual plant model which can be used for the virtual PLC (Programmable Logic Controller) simulation. For the PLC simulation, the corresponding virtual plant, consisting of virtual devices, is required to interact with the input and output symbols of a PLC. In other words, the behavior of a virtual device should be the same as that of the real device. Conventionally, the DEVS (Discrete Event Systems Specifications) formalism has been used to represent the behavior a virtual device. The modeling using DEVS formalism, however, requires in-depth knowledge in the simulation area, as well as the significant amount of time and efforts. One of the key ideas of the proposed method is to generate a plant model based on the log data obtained from the production system. The proposed method is very intuitive, and it can be used to generate the full behavior model of a virtual device. The proposed approach was applied to an AGV (Automated Guided Vehicle).

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.97-102
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• 2006

Generally, a software development process is composed with requirements analysis, design, coding, test and maintenance. However, some changes of the design step are difficult to complicate the next step in the development process. It always causes the disagreement between design and implementation step. In this paper, we have developed a tool which can generate an application program. The tool can reduce the disagreement between system design and implementation and recognize the business logic to develop the software rapidly and flexibly In addition, we proposed a non-program-based application program system approach was proposed, In. We can generate and modify an application program with this method which can edit the meta data of a system design by the dynamic method for the execution time.

• Progress in Superconductivity
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• v.4 no.2
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• pp.127-131
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• 2003

We have designed and measured an SFQ(Single Flux Quantum) OR gate for a superconducting ALU (Arithmetic Logic Unit). To optimize the circuit, we used WRspice, XIC and Lmeter for simulations and layouts. The OR gate was consisted of a Confluence Buffer and a D Flip-Flop. When a pulse enters into the OR gate, the pulse does not propagate to the other input port because of the Confluence Buffer. A role of D Flip-Flip is expelling the data when the clock is entered into D Flip-Flop. For the measurement of the OR gate operation, we attached three DC/SFQs, three SFQ/DCs and one RS Flip -Flop to the OR gate. DC/SFQ circuits were used to generate the data pulses and clock pulses. Input frequency of 10kHz and 1MHzwere used to generate the SFQ pulses from DC/SFQ circuits. Output data from OR gate moved to RS flip -Flop to display the output on the oscilloscope. We obtained bias margins of the D Flip -Flop and the Confluence Buffer from the measurements. The measured bias margins $\pm$38.6% and $\pm$23.2% for D Flip-Flop and Confluence Buffer, respectively The circuit was measured at the liquid helium temperature.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1634-1637
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• 2003

Any given object on the motor-driven turntable is pictured from 8 to 72 different views with a digital camera. 3D shape reconstruction is performed with the integrated software called by Scanware from these multiple digital photographs. There are several steps such as configuration, calibration, capturing, segmentation, shape creation, texturing and merging process during the shape reconstruction process. 3D geometry data can be exported to cad data such as Autocad input file. Also 3D image model is generated from 3D geometry and texture data, and is used to advertise the model in the internet environment. Consumers can see the object realistically from wanted views by rotating or zooming in the internet browsers with Scanbull spx plug-in. The spx format allows a compact saving of 3D objects to handle or download. There are many types of scan equipments such as laser scanners and photogrammetric scanners. Line or point scan methods by laser can generate precise 3D geometry but cannot obtain color textures in general. Reversely, 3D image modeling with photogrammetry can generate not only geometries but also textures from associated polygons. We got various 3D image models and introduced the process of getting 3D image model of an internet-connected watchdog robot.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.11-20
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• 1998

Although aerial photogrammetry has been used to generate or update digital maps. It is difficult to make the spatial and attribute data for all kinds of objects on the ground with only aerial photogrammetry. Therefore, we are getting informations of the object on the ground through an on-the-spot survey In order to improve accuracy and reliability of on-the-spot survey in this study, we obtained stereo images from high resolution digital camera (1152*864 pixels) and developed the video photogrammetry which was able to determine the three dimensional coordinates from stereo images by applying DLT(Direct Linear Transformation). Also, the developed video photogrammetry could generate and update the spatial and attribute data in digital maps by using a function that could connect three dimensional coordinates with the attribute data.