• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.565-572
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• 2020

This study developed a software platform using machine learning of artificial intelligence to optimize the distillation column system. The distillation column is representative and core process in the petrochemical industry. Process stabilization is difficult due to various operating conditions and continuous process characteristics, and differences in process efficiency occur depending on operator skill. The process control based on the theoretical simulation was used to overcome this problem, but it has a limitation which it can't apply to complex processes and real-time systems. This study aims to develop an empirical simulation model based on machine learning and to suggest an optimal process operation method. The development of empirical simulations involves collecting big data from the actual process, feature extraction through data mining, and representative algorithm for the chemical process. Finally, the platform for the distillation column was developed with verification through a developed model and field tests. Through the developed platform, it is possible to predict the operating parameters and provided optimal operating conditions to achieve efficient process control. This study is the basic study applying the artificial intelligence machine learning technique for the chemical process. After application on a wide variety of processes and it can be utilized to the cornerstone of the smart factory of the industry 4.0.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5B
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• pp.465-475
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• 2004

Transport Control Protocol (TCP) has been implemented in software running on CPU in end systems, and the protocol processing has appeared as a new bottleneck due to advanced link technology. TCP processing is a critical issue in Storage Area Network (SAN) such as iSCSL, and the overall performance of the Storage Area Network heavily depends on speed of TCP processing. TCP Engine implemented in hardware reduces the load of CPU in end systems as well as accelerates the protocol processing, and hence high speed data processing is achieved. In this paper, we have proposed a hardware engine for TCP processing. TCP engine consists of three major block, TCP Connection block Rx TCP block and Tx TCP block TCP Connection block is responsible for managing TCP connection states. Rx TCP block is responsible for receive flow which receives packets from network and sends to CPU. Rx TCP performs header and data processing and sends header information to TCP connection block and Tx TCP block It also assembles out-of-ordered data to in-ordered before it transfers data to CPU. Tx TCP block is responsible for transmit flow which transfers data from CPU to network. Tx TCP performs retransmission for reliable data transfer and management of transmit window and sequence number. Various test-cases are used to verify the TCP functions. The TCP Engine is synthesized using 0.18 micron technology and results in 51K gates not including buffers for temporal data storage.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.236-243
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• 2009

With advances in topic detection and tracking(TDT), automatic trend analysis from a collection of time-stamped documents, like patents, news papers, and blog pages, is a challenging research problem. Past research in this area has mainly focused on showing a trend line over time of a given concept by measuring the strength of trend-associated term frequency information. for detection of emerging trends, either a simple criterion such as frequency change was used, or an overall comparison was made against a training data. We note that in order to show most salient trends detected among many possibilities, it is critical to devise a ranking function. To this end, we define four properties(change, persistency, stability and volume) of trend lines drawn from frequency information, to quantify various aspects of trends, and propose a method by which trend lines can be ranked. The properties are examined individually and in combination in a series of experiments for their validity using the ranking algorithm. The results show that a judicious combination of the four properties is a better indicator for salient trends than any single criterion used in the past for ranking or detecting emerging trends.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.261-272
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• 2009

The EJB 3.0 specifications, which were improved in terms of performance and ease of development, were recently announced. Accordingly, for the EJB 3.0 application environment, developers generally prefer the gradual transformation of components whose performance must be improved to the complete transformation of all the EJB 2.1 components into EJB 3.0 components. Previous studies, however, did not consider the service of the application and did not ensure the compatibility and reusability of the components in the full replacement of EJB 3.0 due to the transformation using different specifications. This study proposed three transformation techniques that consider the service supported in the existing application, wherein the compatibility and reusability of the components are ensured in the case of the full replacement of EJB 3.0. The proposed transformation techniques are techniques for gradual transformation, such as direct transformation that directly connects components, indirect transformation that uses the EJB connector, and indirect template transformation wherein the template pattern is applied to the indirect transformation. The proposed transformation techniques were verified by comparing the reusability and processing capability of the components per second, and the standards for selecting a technique were provided based on the characteristics of the transformation into EJB 3.0 that were found in this study.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.177-186
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• 2012

In this paper, we propose a real-time approach for detecting and tracking a hand region by analyzing depth images. We build a hand model in advance. The model has the shape information of a hand. The detecting process extracts out moving areas in an image, which are possibly caused by moving a hand in front of a camera. The moving areas can be identified by analyzing accumulated difference images and applying the region growing technique. The extracted moving areas are compared against a hand model to get justified as a hand region. The tracking process keeps the track of center points of hand regions of successive frames. For this purpose, it involves three steps. The first step is to determine a seed point that is the closest point to the center point of a previous frame. The second step is to perform region growing to form a candidate region of a hand. The third step is to determine the center point of a hand to be tracked. This point is searched by the mean-shift algorithm within a confined area whose size varies adaptively according to the depth information. To verify the effectiveness of our approach, we have evaluated the performance of our approach while changing the shape and position of a hand as well as the velocity of hand movement.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.187-194
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• 2012

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease, transrectal ultrasound(TRUS) images are being used because the cost is low. But, accurate detection of prostate boundaries is a challenging and difficult task due to weak prostate boundaries, speckle noises and the short range of gray levels. This paper proposes a method for automatic prostate segmentation in TRUS images using its average shape model and invariant features. This approach consists of 4 steps. First, it detects the probe position and the two straight lines connected to the probe using edge distribution. Next, it acquires 3 prostate patches which are in the middle of average model. The patches will be used to compare the features of prostate and nonprostate. Next, it compares and classifies which blocks are similar to 3 representative patches. Last, the boundaries from prior classification and the rough boundaries from first step are used to determine the segmentation. A number of experiments are conducted to validate this method and results showed that this new approach extracted the prostate boundary with less than 7.78% relative to boundary provided manually by experts.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.387-396
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• 2018

Stock price prediction has been a difficult problem to solve. There have been many studies to predict stock price scientifically, but it is still impossible to predict the exact price. Recently, a variety of types of cryptocurrency has been developed, beginning with Bitcoin, which is technically implemented as the concept of distributed ledger. Various approaches have been attempted to predict the price of cryptocurrency. Especially, it is various from attempts to stock prediction techniques in traditional stock market, to attempts to apply deep learning and reinforcement learning. Since the market for cryptocurrency has many new features that are not present in the existing traditional stock market, there is a growing demand for new analytical techniques suitable for the cryptocurrency market. In this study, we first collect and process seven cryptocurrency price data through Bithumb's API. Then, we use the gradient boosting model, which is a data-driven learning based machine learning model, and let the model learn the price data change of cryptocurrency. We also find the most optimal model parameters in the verification step, and finally evaluate the prediction performance of the cryptocurrency price trends.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.208-214
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• 2020

In this study, we have developed a drone magnetic exploration system (proto-type) using a fluxgate magnetic sensor. Hardware of the system consists of a fluxgate magnetometer, an inertial measurement unit (IMU), a GPS, and a communication module. And we have developed monitoring software, which enables it to transmit the measured data to the ground control system (GCS) in real time. The measured magnetic data are finally saved as 1 Hz data after passing through a notch filter and a band-pass filter. For verification of this system, a preliminary test was conducted to check the magnetic responses of a magnetic object first, then the field test was carried out in two iron mines. We tested the developed system on the field test in Pocheon, Gyeonggi and Jeongseon, Gangwon. The magnetic data from the developed drone system was very similar to those from unmanned airship system developed by Korea Institute of Geoscience and Mineral Resources (KIGAM). As a result, preliminary experiment and field test have demonstrated that this system is applicable for outdoor aeromagnetic exploration. It requires more studies to improve filter function and instrument performance to minimize noise in the future.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.5
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• pp.11-24
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• 2011

A real-time hybrid test of a 3 story-3 bay reinforced concrete frame which is divided into numerical and physical substructure models under uniaxial earthquake excitation was run using a fixed iteration implicit HHT time integration method. The first story inner non-ductile column was selected as the physical substructure model, and uniaxial earthquake excitation was applied to the numerical model until the specimen failed due to severe damage. A finite-element analysis program, Mercury, was newly developed and optimized for a real-time hybrid test. The drift ratio based on the top horizontal displacement of the physical substructure model was compared with the result of a numerical simulation by OpenSees and the result of a shaking table test. The experiment in this paper is one of the most complex real-time hybrid tests, and the description of the hardware, algorithm and models is presented in detail. If there is an improvement in the numerical model, the evaluation of the tangent stiffness matrix of the physical substructure model in the finite element analysis program and better software to reduce the computational time of the element state determination for the force-based beam-column element, then the comparison with the results of the real-time hybrid test and the shaking table test deserves to make a recommendation. In addition, for the goal of a "Numerical simulation of the complex structures under dynamic loading", the real time hybrid test has enough merit as an alternative to dynamic experiments of large and complex structures.

• Korean journal of communication and information
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• v.45
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• pp.220-254
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• 2009

Presidential TV debates serve as an important instrument for the general viewers to evaluate the candidates’ character, to examine their policy, and finally to make an important political decisions to cast ballots. Every words candidates utter in the course of entire election campaign exert influence of a certain significance by delivering their ideas and by creating clashes with their respective opponents. This study focuses on the conceptual venue, coined as ‘stasis’ by ancient rhetoricians, in which the clashes take place, and examines the words selection made by each candidates, the manners in which they form stasis, call for evidence, educate the public, and finally create a legitimate form of political argumentation. The study applied computer based content analysis using KrKwic and UCINET software to analyze semantic networks among the candidates. The results showed three major candidates, namely Lee Myung Bak, Jung Dong Young, and Lee Hoi Chang, displayed separate patterns in their use of language, by selecting the words that are often neglected by their opponents. Apparently, the absence of stasis and the lack of speaking mutual language significantly undermined the effects of debates. Central questions regarding issues of North Korea failed to meet basic requirements, and the respondents failed to engage in effective argumentation process.