• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.179-185
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• 2010

In this paper, we present a performance evaluation for face recognition algorithm using feature feedback according to the Feature mask. In the face recognition method using feature feedback, important region is extracted from original data set by using the reverse mapping from the extracted features to the original space. In this paper, we evaluate the performance of feature feedback according to shape of Feature Mask for Yale data. Comparing the result using Important part and unimportant part, we show the validity and applicability of the pattern recognition method based on feature feedback.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.360-365
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• 2013

The paper introduces dynamic generation technique of foot trajectories using CPG(Central Pattern Generator). In this approach, the generated foot trajectories can be changeable according to variable outputs of CPG in various environments, because they are given as mapping functions of the output signals of the CPG oscillators. It enables to provide an adaptable foot trajectory for environmental change. To demonstrate the effectiveness of the proposed approach, experiments on humanoid robot Nao is executed in the Webot simulation. The performance and motion features of CPG based approach is analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1899-1904
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• 2017

This paper presents a new one-time password approach generated based on $4{\times}4$ pattern schedule. It demonstrates generation of passkey from initial seed of random codes and mapping out in table pattern schedule which will produce a new form of OTP scheme in protecting information or data. The OTP-2FA has been recognized by many organizations as a landmark to authentication techniques. OTP is the solution to the shortcomings of the traditional user name/password authentication. With the application of OTP, some have benefited already while others have had second thoughts because of some considerations like cryptographic issue. This paper presents a new method of algorithmic approach based on table schedule (grid authentication). The generation of OTP will be based on the random parameters that will be mapped out in rows and columns allowing the user to form the XY values to get the appropriate values. The algorithm will capture the values and extract the predefined characters that produce the OTP codes. This scheme can work in any information verification system to enhance the security, trust and confidence of the user.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.618-622
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• 2008

In this paper, we suggest new music composition algorithm based on fractal theory. User can define and control fractal shape by setting an initial state and production rules in L-System. We generate an asymmetric fractal tree based on L-System and probability. Then a music is generated by the fractal tree image using sonification techniques. We introduce two composition algorithm using the fractal tree. First, monophonic music can be generated by mapping x and y axis to velocity and pitch, respectively Second, harmonic music also can be generated by mapping x and y axis to time and pitch, respectively Using our composition algorithm, user can easily generate a music which has repeated pattern created by recursive feature of fractal, and a music which has structure similar to fractal tree image.

• Journal of Environmental Science International
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• v.22 no.10
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• pp.1305-1316
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• 2013

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was $0.041{\pm}0.001$, indicating steady variability.

• Journal of Korea Game Society
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• v.8 no.2
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• pp.57-68
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• 2008

Texture Mapping is a technique for adding realism to an image in 3D graphics Chip. Bilinear filtering mode of this technique needs accesses of 4 texels to process one pixel. In this paper we analyzed the access pattern of texture, and proposed the high performance texture cache which can access 4 texels simultaneously. We evaluated using simulation results of 3D game(Quake 3, Unreal Tournament 2004). Simulation results show that proposed texture cache has high performance on the case where physical size is less then or equal 8KBytes.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.3
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• pp.93-100
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• 2008

Laser interferometry is widely used as a measuring system in many fields because of its high resolution and ability to measure a broad area in real-time all at once. In conventional LASER interferometry, for example Out-of-plane ESPI(Electronic Speckle Pattern Interferometry), In plane ESPI, Shearography and Holography, it uses PZT or other components as a phase shift instrumentation to extract 3D deformation data, vibration mode and others. However, in most cases PZT has some disadvantages, which include nonlinear errors and limited time of use. In the present study, a new type of LASER interferometry using a laser diode is proposed. Using LASER Diode Sinusoidal Phase Modulating (LD-SPM) interferometry, the phase modulation can be directly modulated by controlling the LASER Diode injection current thereby eliminating the need for PZT and its components. This makes the interferometry more compact. This paper reports on a new approach to the LD Modulating interferometry that involves four-buckets phase shift method. This study proposes a four-bucket phase mapping algorithm, which was developed to have a guaranteed application, to stabilize the system in the field and to be a user-friendly GUI. In this paper, the theory for LD wavelength modulation and sinusoidal phase modulation of LD modulating interferometry is shown. Four-bucket phase mapping algorithm is then introduced.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.35-44
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• 2017

PURPOSES: This study suggests a specific methodology for the prediction of road surface temperature using vehicular ambient temperature sensors. In addition, four kind of models is developed based on machine learning algorithms. METHODS : Thermal Mapping System is employed to collect road surface and vehicular ambient temperature data on the defined survey route in 2015 and 2016 year, respectively. For modelling, all types of collected temperature data should be classified into response and predictor before applying a machine learning tool such as MATLAB. In this study, collected road surface temperature are considered as response while vehicular ambient temperatures defied as predictor. Through data learning using machine learning tool, models were developed and finally compared predicted and actual temperature based on average absolute error. RESULTS : According to comparison results, model enables to estimate actual road surface temperature variation pattern along the roads very well. Model III is slightly better than the rest of models in terms of estimation performance. CONCLUSIONS : When correlation between response and predictor is high, when plenty of historical data exists, and when a lot of predictors are available, estimation performance of would be much better.