• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.578-589
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• 2014

Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.

• Journal of Navigation and Port Research
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• v.38 no.4
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• pp.373-378
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• 2014

In order to prepare for recapitalization of differential GNSS (DGNSS) reference station and integrity monitor (RSIM) due to GNSS diversification, this paper focuses on differential correction algorithm using GPS/Galileo pesudorange. The technical standards on operation and broadcast of DGNSS RSIM are described as operation of differential GPS (DGPS) RSIM for conversion of DGNSS RSIM. Usually, in order to get the differential corrections of GNSS pesudorange, the system must know the real positions of satellites and user. Therefore, for calculating the position of Galileo satellites correctly, using the equation for calculating the SV position in Galileo ICD (Interface Control Document), it estimates the SV position based on Ephemeris data obtained from user receiver, and calculates the clock offset of satellite and user receiver, system time offset between GPS and Galileo, then determines the pseudorange corrections of GPS/Galileo. Based on a platform for performance verification connected with GPS/Galileo integrated signal simulator, it compared the PRC (pseudorange correction) errors of GPS and Galileo, analyzed the position errors of DGPS, DGalileo, and DGPS/DGalileo respectively. The proposed method was evaluated according to PRC errors and position accuracy at the simulation platform. When using the DGPS/DGalileo corrections, this paper could confirm that the results met the performance requirements of the RTCM.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.1
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• pp.1-9
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• 2015

To satisfy stricter $NO_X$ emission regulations for light- and heavy-duty diesel vehicles, a control algorithm needs to be developed based on a selective catalytic reaction (SCR) dynamics model for chemical reactions. This paper presents the development and validation of a SCR dynamics model through test rig experiments and MATLAB simulations. A nonlinear state space model is proposed based on the mass conservation law of chemical reactions in the SCR dynamics model. Experiments were performed on a test rig to evaluate the effects of the $NO_X$ and $NH_3$ concentrations, gas temperature, and space velocity on the $NO_X$ conversion efficiency for the urea-SCR system. The parameter values of the proposed SCR model were identified using the experimental datasets. Finally, a control-oriented model for an SCR system was developed and validated from the experimental data in a MATLAB simulation. The results of this study should contribute toward developing a closed-loop control strategy for $NO_X$ and $NH_3$ slip reduction in the urea-SCR system for an actual engine test bench.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.586-596
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• 2011

In the IT industry, processing units of IT applications are getting smaller and high efficient. Furthermore, the realization of various smart functions is highly feasible now due to advances in sensing technology. The service infrastructures on high efficient and compact mobile devices are applied to various areas. These also could be possessed by users and is built into the devices. Currently, studies on the UX(User Experience) field to attempt an analysis and prediction of user's information are continuing with reference to the UI(User Interface). However, research on the common framework of classification and storing the user-information, and standardization of form has not been attempted yet. In this study, we proposed the AUX(Associative user Experience) model and process structure to store various empirical data by users. The AUX model expressed a diversity of user's empirical data using extended E-TCPN model. And also, we expressed the data structure using XML with reference to the application of AUX model. This expressed model and separation of process structure guarantee its specialty, productivity and flexibility through the humanistic characteristics of users and the independence of technical process structure. The AUX model maps out the AUX information process architecture and expressed the process with the improved MPP algorithm, to analyze of its performance. The simulation of movements applying to MPP traffic allocation of VOD is used to analyze of its performance. The playback deviation of MPP Graphic Allocation Algorism where the AUX model was applied was improved by 10.41% more than the one where it was not applied. As a result of that, playback performance has improved due to the conversion of AUX with accessing media, content of users and dynamic traffic allocation such as MPI and CPI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.493-503
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• 2018

Recently, as living standards have improved, many people are becoming more interested in health, and self-training is increasing through exercise to prevent and manage pre-illness. In general, an imbalance of muscles causes asymmetry of posture, which can cause various diseases by accompanying an adjustment force, circulation action, displacement of internal organs, etc.. In this study, the development of fitness software that can be self - training among smart wears has attracted considerable attention in recent years. In this study, a technology was proposed for the commercialization of self - trainer fitness wear by a simulation through Android - based applications. Self - trainer fitness software was developed by combining a conductive polymer, fashion design, sewing, and electric and electronic technology to monitor the unbalance of the muscles during exercise and make smart wear that can calibrate the asymmetry by oneself. In particular, a polymer sensor was fabricated by deriving the optimal MWCNT concentration, and the electrode signal was collected by attaching the electrode to the optimal position, where the electrode signal line using the conductive fiber was designed and attached to collect the signal. A signal module that converts the bio-signals collected through electrical signal conversion and transmits them using Bluetooth communication was designed and manufactured. Self-trainer fitness software that can be commercialized was developed by combining noise cancellation with Android-based self-training application using a software algorithm method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1028-1036
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• 2008

In the OFDM system, IQ imbalance problem happens at the RF front-end of transceiver, which degrades the BER(bit error rate) performance because it affects the constellation in the received signal. Also, phase noise is generated in the local oscillator of transceivers and it destroys the orthogonality between the subcarriers. Conventional PNS algorithm is effective for phase noise suppression, but it is not useful anymore when there are jointly IQ(In-phase and Quadrature) imbalance and phase noise. Therefore, in this paper, we analyze the effect of IQ imbalance and phase noise generated in the down-conversion of the receiver. Then, we estimate and compensate the IQ imbalance and phase noise at the same time. Compared with the conventional method that IQ imbalance after IFFT is estimated and compensated in front of FFT via the feedback, this proposed method extracts and compensates effect of IQ imbalance after FFT stage. In case IQ imbalance and phase noise exist at the same time, we can decrease complexity because it is needless to use elimination of IQ imbalance in time domain and training sequences and preambles. Also, this method shows that it reduces the ICI and CPE component using adaptive forgetting factor of MMSE after FFT.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.55-61
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• 2017

The V-world, korean type spatial information open platform, provides various services to easily utilize 2D, 3D map and administrative information of the country. Among them, V-world 3D map service, modeled in individual building unit, require requests for each building model file and the draw calls for drawing models on the screen by the request. This causes a large number of model requests and draw calls to occur that increase the latency occurring during the transmission and conversion process between the central processing unit(CPU) and the graphic processing unit(GPU), which lead to the performance degradation of the 3D map service. In this paper, we propose a performance improvement plan to reduce the performance degradation of 3D map service caused by multiple model requests and draw calls. Therefore, we tried to reduce the number of requests and draw calls for the model file by applying a 3D tile model that combined multiple building models to single tile. In addition, we applied the quadtree algorithm to reduce the time required to load the model file by shortening the retrieval time of the model. This is expected to contribute to improving the performance of 3D map service of V-world.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.9
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• pp.31-39
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• 2011

In this paper, we propose a signal readout system with small area and low power consumption for CNT sensor arrays. The proposed system consists of signal readout circuitry, a digital controller, and UART I/O. The key components of the signal readout circuitry are 64 transimpedance amplifiers (TIA) and SAR-ADC with 11-bit resolution. The TIA adopts an active input current mirror (AICM) for voltage biasing and current amplification of a sensor. The proposed architecture can reduce area and power without sampling rate degradation because the 64 TIAs share a variable gain amplifier (VGA) which needs large area and high power due to resistive feedback. In addition, the SAR-ADC is designed for low power with modified algorithm where the operation of the lower bits can be skipped according to an input voltage level. The operation of ADC is controlled by a digital controller based on UART protocol. The data of ADC can be monitored on a computer terminal. The signal readout circuitry was designed with 0.13${\mu}m$ CMOS technology. It occupies the area of 0.173 $mm^2$ and consumes 77.06${\mu}W$ at the conversion rate of 640 samples/s. According to measurement, the linearity error is under 5.3% in the input sensing current range of 10nA - 10${\mu}A$. The UART I/O and the digital controller were designed with 0.18${\mu}m$ CMOS technology and their area is 0.251 $mm^2$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.246-252
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• 2020

Safety accidents have been reported due to falling accumulated snow from cables of cable-supported bridges. In addition to the direct damage caused by falling snow, secondary damage, such as traffic accidents, can occur. Various methods have been proposed to prevent these accidents, but there are still problems in safety and practicality. In this study, a cable robot type was selected as one of the active methods for removing accumulated snow on cables. An attempt was made to increase the climbing ability of the robot to improve the efficiency of snow removal. In addition, the available range of cable diameter for the robot can be adjusted flexibly to be applied to cables used in the field. A high-resolution camera was also installed to check the surface condition of the cable in real time to increase the utility, and be used as a cable inspection robot. A three-axis accelerometer and a tension conversion algorithm were added to measure the tension force of cables. To verify the performance, indoor and field experiments were conducted, and future improvements for the inspection robot were proposed.

• Journal of the Korean association of regional geographers
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• v.23 no.2
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• pp.376-387
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• 2017

This paper attempts to analyze the geographical characters of Twitter data and presents analysis potentials for social network analysis in geography. First, this paper suggests a methodology for a topic modeling-based approach in order to identify the geographical characteristics of tweets, including an analysis flow of Twitter data sets, tweet data collection and conversion, textural pre-processing and structural analysis, topic discovery, and interpretation of tweets' topics. GPS coordinates referencing tweets(geotweets) were extracted among sampled Twitter data sets because it contains the tweet place where it was created. This paper identifies a correlated relationship between some specific topics and local places in Jeju. This correlation is closely associated with some place names and local sites in Jeju Island. We assume it is the intention of tweeters to record their tweet places and to share and retweet with other tweeters in some cases. A surface density map shows the hotspots of tweets, detecting around some specific places and sites such as Jeju airport, sightseeing sites, and local places in Jeju Island. The hotspots show similar patterns of the floating population of Jeju, especially the thirty-year age group. In addition, a topic modeling algorithm is applied for the geographical topic discovery and comparison of the spatial patterns of tweets. Finally, this empirical analysis presents that Twitter data, as social network data, provide geographical significance, with topic modeling approach being useful in analyzing the textural features reflecting the geographical characteristics in large data sets of tweets.