• Bulletin of the Society of Naval Architects of Korea
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• v.26 no.2
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• pp.32-40
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• 1989

Dynamic ship positioning(DP) system is used to keep the position and heading of a ship, or a floating platform, above a pre-selected site on the seabed by using thrusters. This paper presents a control system based on filtering technique and optimal control theory. The planar motions of a vessel are assumed to consist of low frequency(LF) component and high frequency(HF) one. The former is mainly due to thrusters, current, wind and second order wave forces, while the latter is mainly due to first order oscillatory component of the wave force. Furthermore position measurement signals include the noise. By means of self-tuning filter and Kalman filter techniques, LF motion estimates and HF ones are seperately achieved from the position measurements of the vessel. The estimated LF motions are used as input to the feedback loops. The total thruster power is minimized using the Linear Quadratic Gaussian control theory. The performance of the vessel with the DP system is investigated by computer simulation.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.122-135
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• 2011

Mobile spam message is a harmful factor which makes receivers to be annoyed and leads to unnecessary social cost. Unwanted junk messages flowing to a smart phone ruin main purpose of the smart work system to enhance the productivity, so we need to study on this area. In this paper, we proposed a novel spam filter on the smartphone in order to reduce computing process and improve the accuracy rate by feedback of error results to a training sample set. As the spam classifier operates on the smartphone independently with training on only user's received data, it could reflect user preference. The authorized personal computer takes on heavy works, such as preprocessing, feature selecting and training process, and the smartphone takes on light works to block junk messages. Experimental results showed reasonable accuracy rate of over 95%, and we found that the application occupied constant computing resources while running on the phone.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.133-145
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• 1996

This paper presents an indirect cutting force measuring system, which uses the current signals from the AC servo drive units of the horizontal machining center, with its applications to the adaptive regulation of the cutting forces in various milling processes and to the on-line monitoring of tool breakage. A typical model for the feed-drive control system of a horizontal machining center is developed to analyze cutting force measurement from the drive motor. The pulsating milling forces can be measured indirectly within the bandwidth of the current feedback control loop of the feed-drive system. It is shown that the indirectly measured cutting force signals can be used in the adaptive controller for cutting force regulation. The whole scheme has been embedded in the commercial machining center and a series of cutting experiments on the face cutting processes are performed. The adaptive controller reveals reliable cutting force regulating capability against the various cutting conditions. It is also shown that the tool breakage in milling can be detected within one spindle revolution by adaptively filtering the current signals. The effect of the cutter run-out has been considered for the reliable on-line detection of tool breakage.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.109-116
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• 2005

Wind power and photovoltaic(PV) systems are getting into the spotlight as substitute energy. But problem is happened stability by speed change of wind and the power output of the sun's ray. The power output amount according to velocity of wind power system. System breakdown can happen at change of sudden velocity, typhoon and night. This paper shows a automatic tail safety brake controller based on feedback control using wind velocity. The operation of automatic tail safety controller verified by manual test. PV system is a energy change system by temperature of sun's ray and cell. Maximum power point tracking(MPPT) is used in PV systems to maximize the photovoltaic array output power. In existed PV system is low output and changeable DC voltage for boost and filtering the buck-boost converter use. But, this paper established deformed DC-DC converter. Changed Buck-boost converter's unlined output current to line output current using DC-DC converter. This is effect that reduce ripple of output current. Proved through an output waveform comparison experiment. Finally, tail safety brake controller is established to wind turbine system for stability elevation and DC-DC converter is established on PV system for stability output.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.1049-1061
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• 2018

As mobile devices such as smartphones and tablet PCs become more popular, users are becoming accustomed to consuming a massive amount of multimedia content every day without time or space limitations. From the industry, the need for user satisfaction investigation has consequently emerged. Conventional methods to investigate user satisfaction usually employ user feedback surveys or interviews, which are considered manual, subjective, and inefficient. Therefore, the authors focus on a more objective method of investigating users' brainwaves to measure how much they enjoy their content. Particularly for multimedia content, it is natural that users will be immersed in the played content if they are satisfied with it. In this paper, the authors propose a method of using a portable and dry electroencephalogram (EEG) sensor device to overcome the limitations of the existing conventional methods and to further advance existing EEG-based studies. The proposed method uses a portable EEG sensor device that has a small, dry (i.e., not wet or adhesive), and simple sensor using a single channel, because the authors assume mobile device environments where users consider the features of portability and usability to be important. This paper presents how to measure attention, gauge and compute a score of user's content immersion level after addressing some technical details related to adopting the portable EEG sensor device. Lastly, via an experiment, the authors verified a meaningful correlation between the computed scores and the actual user satisfaction scores.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.

• Journal of KIISE:Software and Applications
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• v.33 no.2
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• pp.201-219
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• 2006

The key to developing software with the lowest cost and highest quality is to implement or fit the software development process into a given environment. Generally, applying commercial or standard software development processes on a specific project can cause too much overhead if there is no effort to customize the given generic processes. Even though the customizing activities are done before starting the project, these activities are thoroughly dependent on the process engineers who have abundant experience and knowledge with tailoring processes. Owing to this dependence on human knowledge, it has been very difficult to explain the rationale for the results of process tailoring and it takes a long time to get the customized process that is applicable. Hence, we suggest a process tailoring method which adopts the artificial neural network based teaming theory to reduce the time consumed by process tailoring. Furthermore, we suggest the feedback loop mechanism to get higher accuracy in the neural network designed for the process tailoring. It can be done by reusing the process tailoring data results and determining its appropriateness level as sample data to the neural network. We proved the effectiveness of our process tailoring method through case studies using real historical data, which yielded abundant process tailoring results as sample data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.538-542
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• 2018

Echo generated in digital hearing aid vent give rise to user's discomfort. For cancelling feedback echo in vent, it is required to estimate vent impulse response exactly. The vent impulse response has time varying and sparse characteristics. The IPNLMS has been known a useful adaptive algorithm to estimate vent impulse response with these characteristics. In this paper, subband sparse adaptive filter which applying IPNLMS to subband hearing aid structure is proposed to cancel echo of vent by estimating sparse vent impulse response. In the propose method, the decomposition of input signal to subband can pre-whiten each subband signal, so adaptive filter convergence speed can be improved. And the poly phase component decomposition of adaptive filter increases sparsity of each components, and the better echo cancellation can be possible without additional computation. To derive coefficients update equation of the adaptive filter, by defining the cost function based weight NLMS is defined, and the coefficient update equation of each subband is derived. For verifying performances of the adaptive filter, convergence speed, and steady state error by white signal input, and echo cancelling results by real speech input are evaluated by comparing conventional adaptive filters.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.5-9
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• 2004

In this paper, we studied the OCT(Optical Coherence Tomography) system which it has been extensively studied because of having some advantages such as high resolution cross-sectional images, low cost, and small size configuration. A basic principle of OCT system is Michelson interferometer. The characteristics of light source determine the resolution and the transmission depth. As a results, the light source have a commercial SLD with a central wavelength of 1,285 nm and FWHM(Full Width at Half Maximum) of 35.3 nm. The optical delay line part is necessary to equal of the optical path length with scattered light or reflected light from sample. In order to equal the optical path length, the stage which is attached to reference mirror is moved linearly by step motor And the interferometer is configured with the Michelson interferometer using single mod fiber, the scanner can be focused of the sample by using the reference arm. Also, the 2-dimensional cross-sectional images were measured with scanning the transverse direction of the sample by using step motor. After detecting the internal signal of lateral direction at a paint of sample, scanner is moved to obtain the cross-sectional image of 2-demensional by using step motor. Photodiode has been used which has high detection sensitivity, excellent noise characteristic, and dynamic range from 800 nm to 1,700 nm. It is detected mixed small signal between noise and interference signal with high frequency After filtering and amplifying this signal, only envelope curve of interference signal is detected. And then, cross-sectional image is shown through converting this signal into digitalized signal using A／D converter. The resolution of the OCT system is about 30$\mu\textrm{m}$ which corresponds to the theoretical resolution. Also, the cross-sectional image of ping-pong ball is measured. The OCT system is configured with Michelson interferometer which has a low contrast because of reducing the power of feedback interference light. Such a problem is overcomed by using the improved inteferometer. Also, in order to obtain the cross-sectional image within a short time, it is necessary to reduce the measurement time for improving the optical delay line.